<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>5</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Kanbara, Sakiko</style></author><author><style face="normal" font="default" size="100%">Miyagawa, Shoko</style></author><author><style face="normal" font="default" size="100%">Miyazaki, Hiroyuki</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">Kanbara, Sakiko</style></author><author><style face="normal" font="default" size="100%">Miyagawa, Shoko</style></author><author><style face="normal" font="default" size="100%">Miyazaki, Hiroyuki</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Care for Disaster Risk Reduction and Communication: Lessons Learned and Way to Forward</style></title><secondary-title><style face="normal" font="default" size="100%">Disaster Nursing, Primary Health Care and Communication in Uncertainty</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2022</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://doi.org/10.1007/978-3-030-98297-3_30</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">Springer International Publishing</style></publisher><pub-location><style face="normal" font="default" size="100%">Cham</style></pub-location><pages><style face="normal" font="default" size="100%">337–346</style></pages><isbn><style face="normal" font="default" size="100%">978-3-030-98297-3</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">We have contributed to the mutual support of the community, not within the framework of medical care or disaster prevention to health and well-being directly contributed to SDG 3. Through the care of local nurses who can flexibly respond to any disaster, we have been visualizing the care and communication for disaster risk reduction while using new technologies. The local nurse is a knowledge base that exists continuously in the community and is most concerned with the health, safety, and security of the people in the society. It is expected to play a coordinating role in local health crises from the long-term and holistic perspective forward. ``Target 3.d strengthen the capacity of all countries, in particular developing countries.&#039;&#039; Therefore, it is critical to update the knowledge about ``early warning, risk reduction, and management of national and global health risks.&#039;&#039; Its social context and commitment to a sustainable future need to be revised and updated periodically to keep pace with new technologies and developments. Mutual support involving community-based organizations, private nonprofit organizations, private companies, educational and research institutions, and academic institutions is also essential. Broadening the space for action and allowing for more dialogue were also required to enable each institution to coordinate its response as appropriate. Thinking within a diverse global agenda frameworks allows for a multilateral and multisectoral approach to realizing the SDGs. This book would show a comprehensive ``big blueprint&#039;&#039; for global citizen to understand. ``No one&#039;s health and well-being will be left behind&#039;&#039; through disaster nursing and disaster risk reduction with emerging communication and data.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>5</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Miyazaki, Hiroyuki</style></author><author><style face="normal" font="default" size="100%">Miyagawa, Shoko</style></author><author><style face="normal" font="default" size="100%">Joshi, Archana Shrestha</style></author><author><style face="normal" font="default" size="100%">Kanbara, Sakiko</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">Kanbara, Sakiko</style></author><author><style face="normal" font="default" size="100%">Miyagawa, Shoko</style></author><author><style face="normal" font="default" size="100%">Miyazaki, Hiroyuki</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Case Studies of ICT/GIS Application for DRR</style></title><secondary-title><style face="normal" font="default" size="100%">Disaster Nursing, Primary Health Care and Communication in Uncertainty</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2022</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://doi.org/10.1007/978-3-030-98297-3_28</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">Springer International Publishing</style></publisher><pub-location><style face="normal" font="default" size="100%">Cham</style></pub-location><pages><style face="normal" font="default" size="100%">317–325</style></pages><isbn><style face="normal" font="default" size="100%">978-3-030-98297-3</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">This chapter introduces suitable applications for disaster risk reduction (DRR) using information technologies and geospatial information in primary health care. We assessed the practices in aspects of (1) problems addressed by the solution, (2) stakeholders of the problems, (3) user or beneficiary of the provided information and data, (4) outcomes of the solution, and (5) key technology specifications required for providing the information and data, specifically focusing spatial precision and temporal frequency. The analysis shed light on the current issues and limitations of the implemented systems while paving the way for future development addressing the rules from geospatial services.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>5</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Miyazaki, Hiroyuki</style></author><author><style face="normal" font="default" size="100%">Miyagawa, Shoko</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">Kanbara, Sakiko</style></author><author><style face="normal" font="default" size="100%">Miyagawa, Shoko</style></author><author><style face="normal" font="default" size="100%">Miyazaki, Hiroyuki</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Designing Data for DRR (Disaster Risk Reduction) Services</style></title><secondary-title><style face="normal" font="default" size="100%">Disaster Nursing, Primary Health Care and Communication in Uncertainty</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2022</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://doi.org/10.1007/978-3-030-98297-3_27</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">Springer International Publishing</style></publisher><pub-location><style face="normal" font="default" size="100%">Cham</style></pub-location><pages><style face="normal" font="default" size="100%">309–316</style></pages><isbn><style face="normal" font="default" size="100%">978-3-030-98297-3</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">This chapter provides basic methods of service design, which is a key technique for bringing benefits of ICT and GIS to end users. The methods comprise a series of user-oriented designs including defining and scoping problems, identifying and analyzing stakeholders, designing and defining specification requirements of information and data, and prototyping. These are useful for interdisciplinary fields like disaster nursing and primary health care. The approach is also applied to the framework of analyzing case studies in the next chapter, so it is encouraged to read this chapter before the next chapter. Readers will be equipped with methods of analyzing problems for designing solutions with ICT and GIS after reading this chapter.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Maharjan, Nisha</style></author><author><style face="normal" font="default" size="100%">Miyazaki, Hiroyuki</style></author><author><style face="normal" font="default" size="100%">Pati, Bipun Man</style></author><author><style face="normal" font="default" size="100%">Dailey, Matthew N.</style></author><author><style face="normal" font="default" size="100%">Shrestha, Sangam</style></author><author><style face="normal" font="default" size="100%">Nakamura, Tai</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Detection of River Plastic Using UAV Sensor Data and Deep Learning</style></title><secondary-title><style face="normal" font="default" size="100%">Remote Sensing</style></secondary-title><short-title><style face="normal" font="default" size="100%">Remote Sensing</style></short-title></titles><dates><year><style  face="normal" font="default" size="100%">2022</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Jan-07-2022</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://www.mdpi.com/2072-4292/14/13/3049</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">14</style></volume><pages><style face="normal" font="default" size="100%">3049</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><issue><style face="normal" font="default" size="100%">13</style></issue></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>5</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Sritart, Hiranya</style></author><author><style face="normal" font="default" size="100%">Miyazaki, Hiroyuki</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">Kanbara, Sakiko</style></author><author><style face="normal" font="default" size="100%">Miyagawa, Shoko</style></author><author><style face="normal" font="default" size="100%">Miyazaki, Hiroyuki</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Geographic Information System (GIS) and Data Visualization</style></title><secondary-title><style face="normal" font="default" size="100%">Disaster Nursing, Primary Health Care and Communication in Uncertainty</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2022</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://doi.org/10.1007/978-3-030-98297-3_26</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">Springer International Publishing</style></publisher><pub-location><style face="normal" font="default" size="100%">Cham</style></pub-location><pages><style face="normal" font="default" size="100%">297–307</style></pages><isbn><style face="normal" font="default" size="100%">978-3-030-98297-3</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">This chapter is to understand the functionality of GIS focusing on disaster nursing operations, comprising (1) data acquisition, (2) data analysis, (3) data visualization, and (4) data management and sharing. The reader will understand the conceptual basics of GIS, which is useful for designing GIS-based information management systems and applications. By reading and understanding this chapter, the readers will start GIS applications in finding their projects and activities.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Parven, Afshana</style></author><author><style face="normal" font="default" size="100%">Pal, Indrajit</style></author><author><style face="normal" font="default" size="100%">Witayangkurn, Apichon</style></author><author><style face="normal" font="default" size="100%">Pramanik, Malay</style></author><author><style face="normal" font="default" size="100%">Nagai, Masahiko</style></author><author><style face="normal" font="default" size="100%">Miyazaki, Hiroyuki</style></author><author><style face="normal" font="default" size="100%">Wuthisakkaroon, Chanakan</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Impacts of disaster and land-use change on food security and adaptation: Evidence from the delta community in Bangladesh</style></title><secondary-title><style face="normal" font="default" size="100%">International Journal of Disaster Risk Reduction</style></secondary-title><short-title><style face="normal" font="default" size="100%">International Journal of Disaster Risk Reduction</style></short-title></titles><dates><year><style  face="normal" font="default" size="100%">2022</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Jan-08-2022</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://www.sciencedirect.com/science/article/abs/pii/S2212420922003387</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">78</style></volume><pages><style face="normal" font="default" size="100%">103119</style></pages><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>5</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Estuar, Maria Regina</style></author><author><style face="normal" font="default" size="100%">Miyagawa, Shoko</style></author><author><style face="normal" font="default" size="100%">Pulmano, Christian</style></author><author><style face="normal" font="default" size="100%">Victorino, John Noel</style></author><author><style face="normal" font="default" size="100%">Ohta, Sachiko</style></author><author><style face="normal" font="default" size="100%">Miyazaki, Hiroyuki</style></author><author><style face="normal" font="default" size="100%">Kanbara, Sakiko</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">Kanbara, Sakiko</style></author><author><style face="normal" font="default" size="100%">Miyagawa, Shoko</style></author><author><style face="normal" font="default" size="100%">Miyazaki, Hiroyuki</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Management of Health- and Disaster-Related Data</style></title><secondary-title><style face="normal" font="default" size="100%">Disaster Nursing, Primary Health Care and Communication in Uncertainty</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2022</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://doi.org/10.1007/978-3-030-98297-3_25</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">Springer International Publishing</style></publisher><pub-location><style face="normal" font="default" size="100%">Cham</style></pub-location><pages><style face="normal" font="default" size="100%">285–296</style></pages><isbn><style face="normal" font="default" size="100%">978-3-030-98297-3</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Prolonged health emergencies and disasters greatly affect health and well-being of individuals and communities. Past experiences on extreme emergencies and disasters have taught communities the value of preparedness. Information is key in responding to health crises especially in areas where health capacity is challenged. This chapter explains the necessity of identifying appropriate health and disaster data and proposes its transformation to information needed for decision-making. It presents different examples of systems and datasets that were used for the management of response during disasters and extreme emergencies. By introducing examples from Japan and Philippines, this chapter also points out that aside from medical data, nonmedical data, such as lifestyle and hygiene information, are necessary to protect the health of disaster victims.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Sritart, Hiranya</style></author><author><style face="normal" font="default" size="100%">Taertulakarn, Somchat</style></author><author><style face="normal" font="default" size="100%">Kanbara, Sakiko</style></author><author><style face="normal" font="default" size="100%">Miyazaki, Hiroyuki</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Spatial Equity and Healthcare Access in the COVID-19 Pandemic</style></title><secondary-title><style face="normal" font="default" size="100%">Proceedings of the 6th International Conference on Medical and Health Informatics</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2022</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://doi.org/10.1145/3545729.3545782</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">Association for Computing Machinery</style></publisher><pub-location><style face="normal" font="default" size="100%">New York, NY, USA</style></pub-location><isbn><style face="normal" font="default" size="100%">9781450396301</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Healthcare facilities around the world become overwhelmed by the number of infected coronavirus patients that needed to be treated during the COVID-19 outbreak, resulting in medical staff and healthcare services shortages. Regarding to understand and minimize the inequalities in healthcare services, it is crucial to evaluate the available healthcare resource, particularly the intensive care unit (ICU) beds that are critical for the COVID-19 pandemic. Therefore, this study aims to explore and determine the spatial distribution of the confirmed COVID-19 patients and the healthcare capacities in the province of Ubon Ratchathani, Thailand. Applying the GIS platform with the data analysis of 2SFCA (Two-Step Floating Catchment Area) based approach, we emphasize the spatial distribution of both patients and healthcare resources in the study area. The spatial accessibility index regarding the physicians and ICU beds was determined and highlighted in each district. Additionally, the vulnerable regions were identified by the level of healthcare accessibility. We believe this study offers valuable insight in gaining a better understanding and supporting effective response activities toward pandemic resilience.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>5</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Kanbara, Sakiko</style></author><author><style face="normal" font="default" size="100%">Joshi, Archana Shrestha</style></author><author><style face="normal" font="default" size="100%">Miyagawa, Shoko</style></author><author><style face="normal" font="default" size="100%">Miyazaki, Hiroyuki</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">Kanbara, Sakiko</style></author><author><style face="normal" font="default" size="100%">Miyagawa, Shoko</style></author><author><style face="normal" font="default" size="100%">Miyazaki, Hiroyuki</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Sustainable Development Goals SeriesDisaster Nursing, Primary Health Care and Communication in UncertaintyCare for Disaster Risk Reduction</style></title></titles><dates><year><style  face="normal" font="default" size="100%">2022</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://link.springer.com/chapter/10.1007/978-3-030-98297-3_4</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">Springer International Publishing</style></publisher><pub-location><style face="normal" font="default" size="100%">Cham</style></pub-location><pages><style face="normal" font="default" size="100%">31 - 39</style></pages><isbn><style face="normal" font="default" size="100%">978-3-030-98296-6</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>6</ref-type><contributors><secondary-authors><author><style face="normal" font="default" size="100%">Kanbara, Sakiko</style></author><author><style face="normal" font="default" size="100%">Miyagawa, Shoko</style></author><author><style face="normal" font="default" size="100%">Miyazaki, Hiroyuki</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Sustainable Development Goals SeriesDisaster Nursing, Primary Health Care and Communication in Uncertainty</style></title></titles><dates><year><style  face="normal" font="default" size="100%">2022</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://link.springer.com/10.1007/978-3-030-98297-3https://link.springer.com/content/pdf/10.1007/978-3-030-98297-3https://link.springer.com/content/pdf/10.1007/978-3-030-98297-3.pdf</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">Springer International Publishing</style></publisher><pub-location><style face="normal" font="default" size="100%">Cham</style></pub-location><isbn><style face="normal" font="default" size="100%">978-3-030-98296-6</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Koga, Yohei</style></author><author><style face="normal" font="default" size="100%">Miyazaki, Hiroyuki</style></author><author><style face="normal" font="default" size="100%">Shibasaki, Ryosuke</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Adapting Vehicle Detector to Target Domain by Adversarial Prediction Alignment</style></title><secondary-title><style face="normal" font="default" size="100%">IGARSS 2021 - 2021 IEEE International Geoscience and Remote Sensing Symposium2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2021</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://ieeexplore.ieee.org/document/9554416/http://xplorestaging.ieee.org/ielx7/9553015/9553016/09554416.pdf?arnumber=9554416</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">IEEE</style></publisher><pub-location><style face="normal" font="default" size="100%">Brussels, Belgium</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Kii, Masanobu</style></author><author><style face="normal" font="default" size="100%">Goda, Yuki</style></author><author><style face="normal" font="default" size="100%">Vichiensan, Varameth</style></author><author><style face="normal" font="default" size="100%">Miyazaki, Hiroyuki</style></author><author><style face="normal" font="default" size="100%">Moeckel, Rolf</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Assessment of Spatiotemporal Peak Shift of Intra-Urban Transportation Taking a Case in Bangkok, Thailand</style></title><secondary-title><style face="normal" font="default" size="100%">Sustainability</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2021</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://www.mdpi.com/2071-1050/13/12/6777</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">13</style></volume><pages><style face="normal" font="default" size="100%">6777</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Reducing congestion has been one of the critical targets of transportation policies, particularly in cities in developing countries suffering severe and chronic traffic congestions. Several traditional measures have been in place but seem not very successful. This paper applies the agent-based transportation model MATSim for a transportation analysis in Bangkok to assess the impact of spatiotemporal transportation demand management measures. We collect required data for the simulation from various data sources and apply maximum likelihood estimation with the limited data available. We investigate two demand management scenarios, peak time shift, and decentralization. As a result, we found that these spatiotemporal peak shift measures are effective for road transport to alleviate congestion and reduce travel time. However, the effect of those measures on public transport is not uniform but depends on the users’ circumstances. On average, the simulated results indicate that those measures increase the average travel time and distance. These results suggest that demand management policies require considerations of more detailed conditions to improve usability. The study also confirms that microsimulation can be a tool for transport demand management assessment in developing countries.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Sritart, Hiranya</style></author><author><style face="normal" font="default" size="100%">Tuntiwong, Kuson</style></author><author><style face="normal" font="default" size="100%">Miyazaki, Hiroyuki</style></author><author><style face="normal" font="default" size="100%">Taertulakarn, Somchat</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Disparities in Healthcare Services and Spatial Assessments of Mobile Health Clinics in the Border Regions of Thailand</style></title><secondary-title><style face="normal" font="default" size="100%">International Journal of Environmental Research and Public Health</style></secondary-title><short-title><style face="normal" font="default" size="100%">IJERPH</style></short-title></titles><dates><year><style  face="normal" font="default" size="100%">2021</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Jan-10-2021</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://www.mdpi.com/1660-4601/18/20/10782</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">18</style></volume><pages><style face="normal" font="default" size="100%">10782</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><issue><style face="normal" font="default" size="100%">20</style></issue></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Bencure, Jannet C.</style></author><author><style face="normal" font="default" size="100%">Tripathi, Nitin K.</style></author><author><style face="normal" font="default" size="100%">Miyazaki, Hiroyuki</style></author><author><style face="normal" font="default" size="100%">Ninsawat, Sarawut</style></author><author><style face="normal" font="default" size="100%">Kim, Sohee Minsun</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Factors affecting decision-making in land valuation process using AHP: a case in the Philippines</style></title><secondary-title><style face="normal" font="default" size="100%">International Journal of Housing Markets and Analysis</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2021</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2021</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://doi.org/10.1108/IJHMA-11-2020-0136</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">ahead-of-print</style></volume><isbn><style face="normal" font="default" size="100%">1753-8270</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Purpose The research aims to establish importance scheme of geospatial factors for land valuation activities that may serve as an eye-opener and aid the concerned government agencies in drafting land valuation policies and guidelines to achieve a sound land governance and administration. It specifically identifies and weighs geospatial valuation factors to establish their importance. Design/methodology/approach The research involves discussions and survey questionnaires given to land experts (i.e. appraisers, environmental planners, land economist, geodetic engineers and assessors) who indicated their opinions on influence of geospatial factors on land value. The analytic hierarchy process (AHP) is then used to weigh the factors in terms of its importance. Findings The result was then compared with the multiple regression analysis (MRA) taking into consideration the standardized regression coefficient of the 15 factors. The AHP method found out the major road accessibility and slope direction as the most and least influential factors, respectively, while surprisingly MRA found major road accessibility not significant at p &lt; 0.05 level of significance. Research limitations/implications The research generally reflects the sub-urban type of study area; hence, inclusion of other road types such as express ways and subways and performing sensitivity analysis of AHP are suggested in future studies. Practical implications The findings of the study will provide information of concerned government agencies in improving valuation activities, as well as to update values regularly based on the geospatial factors. Originality/value To the best of the authors’ knowledge, this study is the first effort to rank geospatial factors with analytic hierarchy analytic process that further considered both their negative and positive influences on land value. The approach surmounts the flaw and shortcomings of empirical methods of identifying importance of factors.</style></abstract><issue><style face="normal" font="default" size="100%">ahead-of-print</style></issue></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Sirikanjanaanan, Sirinya</style></author><author><style face="normal" font="default" size="100%">Somwang, Arissara</style></author><author><style face="normal" font="default" size="100%">Jitkuntee, Pornchanok</style></author><author><style face="normal" font="default" size="100%">Miyazaki, Hiroyuki</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Land Cover Change Analysis of Metro Manila, the Philippines using Time-Series Landsat Data for 1989, 2004 and 2019</style></title><secondary-title><style face="normal" font="default" size="100%">宇宙からの地球環境・災害のモニタリングとリスク評価: 生研フォーラム論文集= Monitoring of Global Environment and Disaster Risk Assessment from Space: the IIS Forum proceedings</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2021</style></year></dates><publisher><style face="normal" font="default" size="100%">東京大学生産技術研究所地球環境工学研究グループ</style></publisher><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Ngatu, Nlandu Roger</style></author><author><style face="normal" font="default" size="100%">Muzembo, Basilua Andre</style></author><author><style face="normal" font="default" size="100%">Choomplang, Nattadech</style></author><author><style face="normal" font="default" size="100%">Kanbara, Sakiko</style></author><author><style face="normal" font="default" size="100%">Wumba, Roger</style></author><author><style face="normal" font="default" size="100%">Ikeda, Mitsunori</style></author><author><style face="normal" font="default" size="100%">Mbelambela, Etongola Papy</style></author><author><style face="normal" font="default" size="100%">Muchanga, Sifa Marie-Joelle</style></author><author><style face="normal" font="default" size="100%">Suzuki, Tomoko</style></author><author><style face="normal" font="default" size="100%">Wada, Koji</style></author><author><style face="normal" font="default" size="100%">Al Mahfuz, Hasan</style></author><author><style face="normal" font="default" size="100%">Sugishita, Tomohiko</style></author><author><style face="normal" font="default" size="100%">Miyazaki, Hiroyuki</style></author><author><style face="normal" font="default" size="100%">Ikeda, Shunya</style></author><author><style face="normal" font="default" size="100%">Hirao, Tomohiro</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Malaria rapid diagnostic test (HRP2/pLDH) positivity, incidence, care accessibility and impact of community WASH Action programme in DR Congo: mixed method study involving 625 households</style></title><short-title><style face="normal" font="default" size="100%">Malaria Journal</style></short-title></titles><dates><year><style  face="normal" font="default" size="100%">2021</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2021/02/27</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://doi.org/10.1186/s12936-021-03647-9</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">20</style></volume><pages><style face="normal" font="default" size="100%">117</style></pages><isbn><style face="normal" font="default" size="100%">1475-2875</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Malaria is one of the most prevalent and deadliest illnesses in sub-Saharan Africa. Despite recent gains made towards its control, many African countries still have endemic malaria transmission. This study aimed to assess malaria burden at household level in Kongo central province, Democratic Republic of Congo (DRC), and the impact of community participatory Water, Sanitation and Hygiene (WASH) Action programme.</style></abstract><issue><style face="normal" font="default" size="100%">1</style></issue></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Hiroyuki Miyazaki</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Applications of Earth Observation Data from Small-scale Satellites for Disaster Management by Combinations with Open Geospatial Data</style></title><secondary-title><style face="normal" font="default" size="100%">3rd Human Resource Development and Space Data Utilization for Disaster</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2020</style></year><pub-dates><date><style  face="normal" font="default" size="100%">01/2020</style></date></pub-dates></dates><pub-location><style face="normal" font="default" size="100%">Bali, Indonesia</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>5</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Kanbara, Sakiko</style></author><author><style face="normal" font="default" size="100%">Pandey, Apsara</style></author><author><style face="normal" font="default" size="100%">Estuar, Maria Regina E.</style></author><author><style face="normal" font="default" size="100%">Lee, Hyeon Ju</style></author><author><style face="normal" font="default" size="100%">Miyazaki, Hiroyuki</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">Chan, Emily Ying Yang</style></author><author><style face="normal" font="default" size="100%">Shaw, Rajib</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">EpiNurse, Health Monitoring by Local Nurses on Nepal Earth Quake 2015</style></title><secondary-title><style face="normal" font="default" size="100%">Public Health and Disasters: Health Emergency and Disaster Risk Management in Asia</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2020</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://doi.org/10.1007/978-981-15-0924-7_15</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">Springer Singapore</style></publisher><pub-location><style face="normal" font="default" size="100%">Singapore</style></pub-location><pages><style face="normal" font="default" size="100%">229 - 244</style></pages><isbn><style face="normal" font="default" size="100%">978-981-15-0924-7</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">The name, EpiNurse, refers to local nurses who perform epidemiological surveillance and care to ensure human security in and communicate with health authorities on the health status of communities. They collect and report epidemiological information by using easy-to-use technology in communities in which access to health information of the populace is hindered by catastrophic accidents or other geo-/socio-political reasons. EpiNurse Nepal Project (August 2015–April 2016) carried out epidemiological surveillances at 24 camps in 9 districts after the 2015 Nepal earthquake. By applying ICT and questionnaire, EpiNurse member nurses collected shelter-related data and information, such as location and timestamps, and geo-tagged photos. Identification of typical health behavior patterns and comparative information about differences between community and temporary shelters provided insights into the health security assessment. This initiative experiments how nurse should collect and deliver the health emergency information on their own local culture, lifestyle, and perceptions. The potential of EpiNurse concept lies not only in producing innovative research outcomes by improving or optimizing existing ICT application in health sector, but also in promoting research knowledge and exchange of ideas regarding social issues and challenges in the field of health emergency and community resilience. The most critical challenge in practice relates to collecting and storing data, which later would have been generated into reasonable health security index information to be used for predicting the likelihood of occurrence of health emergency events. It is necessary to apply human behavior modeling using geospatial technology in order to create data transferring modules for first responders and civilian populations regarding DRR and behaviors.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Peungnumsai, Apantri</style></author><author><style face="normal" font="default" size="100%">Miyazaki, Hiroyuki</style></author><author><style face="normal" font="default" size="100%">Witayangkurn, Apichon</style></author><author><style face="normal" font="default" size="100%">Kim, Sohee Minsun</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A Grid-Based Spatial Analysis for Detecting Supply–Demand Gaps of Public Transports: A Case Study of the Bangkok Metropolitan Region</style></title><secondary-title><style face="normal" font="default" size="100%">Sustainability</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2020</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://www.mdpi.com/2071-1050/12/24/10382</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">12</style></volume><pages><style face="normal" font="default" size="100%">10382</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Public transport service has been promoted to reduce the problems of traffic congestion and environmental impacts due to car dependency. Several public transportation modes are available in Bangkok Metropolitan Region (BMR) such as buses, heavy rails, vans, boats, taxis, and trains while in some areas have fewer modes of public transport available. The disparity of public transport service negatively impacts social equity. This study aims to identify the gaps between public transport supply and demand and to demonstrate introduced indicators to assess the public transport performance incorporating transport capacity and equilibrium access aspects. Supply index was used to evaluate the level of service, and the demand index was applied to estimate travel needs. Furthermore, the Lorenz curves and the Gini coefficients were used to measure the equity of public transport. The results highlight that more than half of the BMR population is living in low-supply high-demand areas for public transportation. Moreover, the equitable access analysis has identified that the high-income population has better access to public transport than the low-income population. The results suggest that public transport gaps and equity indicate the inclusiveness of public transportation, as well as to the areas where to improve the public transport service. Thus, the methodology used in this study can be applied to another city or region similar to BMR.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Koga, Yohei</style></author><author><style face="normal" font="default" size="100%">Miyazaki, Hiroyuki</style></author><author><style face="normal" font="default" size="100%">Shibasaki, Ryosuke</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A Method for Vehicle Detection in High-Resolution Satellite Images that Uses a Region-Based Object Detector and Unsupervised Domain Adaptation</style></title><secondary-title><style face="normal" font="default" size="100%">Remote Sensing</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2020</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://www.mdpi.com/2072-4292/12/3/575</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">12</style></volume><pages><style face="normal" font="default" size="100%">575</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Recently, object detectors based on deep learning have become widely used for vehicle detection and contributed to drastic improvement in performance measures. However, deep learning requires much training data, and detection performance notably degrades when the target area of vehicle detection (the target domain) is different from the training data (the source domain). To address this problem, we propose an unsupervised domain adaptation (DA) method that does not require labeled training data, and thus can maintain detection performance in the target domain at a low cost. We applied Correlation alignment (CORAL) DA and adversarial DA to our region-based vehicle detector and improved the detection accuracy by over 10% in the target domain. We further improved adversarial DA by utilizing the reconstruction loss to facilitate learning semantic features. Our proposed method achieved slightly better performance than the accuracy achieved with the labeled training data of the target domain. We demonstrated that our improved DA method could achieve almost the same level of accuracy at a lower cost than non-DA methods with a sufficient amount of labeled training data of the target domain.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Sritart, Hiranya</style></author><author><style face="normal" font="default" size="100%">Miyazaki, Hiroyuki</style></author><author><style face="normal" font="default" size="100%">Kanbara, Sakiko</style></author><author><style face="normal" font="default" size="100%">Hara, Takashi</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Methodology and Application of Spatial Vulnerability Assessment for Evacuation Shelters in Disaster Planning</style></title><secondary-title><style face="normal" font="default" size="100%">Sustainability</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2020</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://www.mdpi.com/2071-1050/12/18/7355</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">12</style></volume><pages><style face="normal" font="default" size="100%">7355</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Evacuation shelters are the most important means for safeguarding people in hazardous areas and situations, and thus minimizing losses, particularly those due to a disaster. Therefore, evacuation shelter assignment and evacuation planning are some of the critical factors for reducing vulnerability and increasing resilience in disaster risk reduction. However, an imbalance of shelter distribution and spatial heterogeneity of a population are the critical issues limiting the accessibility of evacuation shelters in real situations. In this study, we propose a methodology for spatial assessment to reduce vulnerability and evaluate the spatial distribution of both shelter demand and resources, considering spatial accessibility. The method was applied to the case study of Mabi, in the context of a disaster caused by the 2018 flooding. We applied this approach to evaluate the area and identified the vulnerability of the evacuation shelters and the residents. The proposed method revealed that 54.55% of the designated evacuation shelters and 59% of the total population were physically vulnerable to the flood. The results highlight, using GIS maps, that the total shelter capacity was significantly decreased to 43.86%. The outcome assessment addressed specific vulnerable shelters and the imbalance between the demand for and resources of each shelter. Accordingly, this study provides practical information and a valuable reference for supporting local governments and stakeholders to improve future disaster planning, prevention, and preparedness.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>13</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">N. Lakmal Deshapriya</style></author><author><style face="normal" font="default" size="100%">Matthew N. Dailey</style></author><author><style face="normal" font="default" size="100%">Manzul Kumar Hazarika</style></author><author><style face="normal" font="default" size="100%">Hiroyuki Miyazaki</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Vec2Instance: Parameterization for Deep Instance Segmentation</style></title></titles><dates><year><style  face="normal" font="default" size="100%">2020</style></year></dates><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>10</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Dadhich, Gautam</style></author><author><style face="normal" font="default" size="100%">Miyazaki, Hiroyuki</style></author><author><style face="normal" font="default" size="100%">Babel, Mukand</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Applications of SENTINEL-1 Synthetic Aperture Radar Imagery for Floods Damage Assessment: a Case Study of Nakhon SI Thammarat, Thailand</style></title><secondary-title><style face="normal" font="default" size="100%">International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2019</style></year></dates><volume><style face="normal" font="default" size="100%">42</style></volume><language><style face="normal" font="default" size="100%">eng</style></language><issue><style face="normal" font="default" size="100%">2/W13</style></issue></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Hiroyuki Miyazaki</style></author><author><style face="normal" font="default" size="100%">Wataru Ohira</style></author><author><style face="normal" font="default" size="100%">Satoshi Kaneko</style></author><author><style face="normal" font="default" size="100%">Ryosuke Shibasaki</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Development of an Automated Settlement Mapping System using High-Resolution Satellite Images and Deep Learning</style></title><secondary-title><style face="normal" font="default" size="100%">The 60th Annual Meeting for the Japanese Society of Tropical Medicine</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2019</style></year><pub-dates><date><style  face="normal" font="default" size="100%">11/2019</style></date></pub-dates></dates><pub-location><style face="normal" font="default" size="100%">Okinawa, Japan</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">We developed an automated system of building with the use of high-resolution satellite images and deep learning, comprising a geospatial data management system, an image data processing system, and a quality control system. The system development has achieved the component of the geospatial data management and image data processing, and performed building mapping of some large extents, while the development of quality control systems is ongoing. Because we developed the system with open-source and web-based software, anyone can participate in the preparation of training data just only with a computer and the Internet. The system is expected to be a platform for the large-scale mapping of buildings and other ground objects with international collaborations of local partners. The building maps developed by this system are expected to be a basis of analyzing demography with possible risks and impacts of communicable diseases.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Bencure, Jannet C.</style></author><author><style face="normal" font="default" size="100%">Tripathi, Nitin K.</style></author><author><style face="normal" font="default" size="100%">Miyazaki, Hiroyuki</style></author><author><style face="normal" font="default" size="100%">Ninsawat, Sarawut</style></author><author><style face="normal" font="default" size="100%">Kim, Sohee Minsun</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Development of an Innovative Land Valuation Model (iLVM) for Mass Appraisal Application in Sub-Urban Areas Using AHP: An Integration of Theoretical and Practical Approaches</style></title><secondary-title><style face="normal" font="default" size="100%">Sustainability</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2019</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://www.mdpi.com/2071-1050/11/13/3731</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">11</style></volume><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Land development in sub-urban areas is more frequent than in highly urbanized cities, causing land prices to increase abruptly and making it harder for valuers to update land values in timely manner. Apart from this, the non-availability of sufficient reliable market values forces valuers to use alternatives and subjective judgement. Land value is critical not only for private individuals but also for government agencies in their day-to-day land dealings. Thus, mass appraisal is necessary. In other words, despite the importance of reliable land value in all aspects of land administration, valuation remains disorganized, with unregulated undertakings that lack concrete scientific, legal, and practical foundations. A holistic and objective way of weighing geospatial factors through expert consultation, legal reviews, and evidence (i.e., news) will provide more realistic results than a regression-based method that does not comprehend valuation factors (i.e., physical, social, economic, environmental, and legal aspects). The analytic hierarchy process (AHP) enables these factors to be included in the model, hence providing a realistic result. The innovative land valuation model (iLVM), developed in this study, is an inclusive approach wherein experts are involved in the selection and weighing of 15 factors through the AHP. The model was validated using root mean squared error (RMSE) and compared with multiple regression analysis (MRA) through a case study in Baybay City, Philippines. Based on the results, the iLVM (RMSE = 0.526) outperformed MRA (RMSE = 1.953).</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>10</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Yuki Akiyama</style></author><author><style face="normal" font="default" size="100%">Hiroyuki Miyazaki</style></author><author><style face="normal" font="default" size="100%">Sirinya Sirikanjanaanan</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Development of micro population data for each building: Case study in Tokyo and Bangkok</style></title><secondary-title><style face="normal" font="default" size="100%">2019 First International Conference on Smart Technology &amp; Urban Development (STUD)</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">building</style></keyword><keyword><style  face="normal" font="default" size="100%">census</style></keyword><keyword><style  face="normal" font="default" size="100%">disaggregation</style></keyword><keyword><style  face="normal" font="default" size="100%">micro geodata</style></keyword><keyword><style  face="normal" font="default" size="100%">population</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2019</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://ieeexplore.ieee.org/document/9018851</style></url></web-urls></urls><pub-location><style face="normal" font="default" size="100%">Chiang Mai, Thailand</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">In order to carry out sustainable development and management of cities, it is necessary to design and implement appropriate city planning and traffic planning. Indispensable information for designing them is the population distribution. However, population data with high spatial resolution, such as building units, are rarely maintained in cities in developing countries. Therefore, this study examined the development of methods for estimating the number of residents per building in Tokyo and Bangkok using detailed building maps and population census in subdistrict units. In addition, using these methods, we tried to develop micro population data (MPD) across Tokyo and Bangkok. Moreover, the reliability of MPD was verified by comparing it with population census with higher resolution than subdistrict unit in Tokyo. As a result, it has become possible to develop MPDs that are strongly correlated with the population census of various aggregation units and have small errors.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>10</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">B. Devkota</style></author><author><style face="normal" font="default" size="100%">K. Kim</style></author><author><style face="normal" font="default" size="100%">C. Zhuang</style></author><author><style face="normal" font="default" size="100%">H. Miyazaki</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Disaggregate Hotel Evaluation by Using Diverse Aspects from User Reviews</style></title><secondary-title><style face="normal" font="default" size="100%">2019 IEEE International Conference on Big Data and Smart Computing (BigComp)</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Adaptation models</style></keyword><keyword><style  face="normal" font="default" size="100%">aspects</style></keyword><keyword><style  face="normal" font="default" size="100%">Coherence</style></keyword><keyword><style  face="normal" font="default" size="100%">coherent hotel aspects</style></keyword><keyword><style  face="normal" font="default" size="100%">customer satisfaction</style></keyword><keyword><style  face="normal" font="default" size="100%">data mining</style></keyword><keyword><style  face="normal" font="default" size="100%">Data models</style></keyword><keyword><style  face="normal" font="default" size="100%">disaggregate hotel evaluation</style></keyword><keyword><style  face="normal" font="default" size="100%">diverse aspects</style></keyword><keyword><style  face="normal" font="default" size="100%">Estimation</style></keyword><keyword><style  face="normal" font="default" size="100%">Feature extraction</style></keyword><keyword><style  face="normal" font="default" size="100%">fine-grained aspect level opinions</style></keyword><keyword><style  face="normal" font="default" size="100%">frequent noun-adjective co-occurrence statistics</style></keyword><keyword><style  face="normal" font="default" size="100%">hotel industry</style></keyword><keyword><style  face="normal" font="default" size="100%">hotel ranking</style></keyword><keyword><style  face="normal" font="default" size="100%">hotel reviews</style></keyword><keyword><style  face="normal" font="default" size="100%">latent aspects</style></keyword><keyword><style  face="normal" font="default" size="100%">Predictive models</style></keyword><keyword><style  face="normal" font="default" size="100%">purchase decision</style></keyword><keyword><style  face="normal" font="default" size="100%">statistical analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">supervised methods</style></keyword><keyword><style  face="normal" font="default" size="100%">topic modeling</style></keyword><keyword><style  face="normal" font="default" size="100%">unsupervised learning</style></keyword><keyword><style  face="normal" font="default" size="100%">user attention</style></keyword><keyword><style  face="normal" font="default" size="100%">user reviews</style></keyword><keyword><style  face="normal" font="default" size="100%">word co-occurrence statistics</style></keyword><keyword><style  face="normal" font="default" size="100%">word embeddings</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2019</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Feb</style></date></pub-dates></dates><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Experienced opinions about products and services can guide a potential user for a better purchase decision. Fine-grained aspect level opinions embedded within reviews must be explored to discover experienced users&#039; latent opinion about the aspects (i.e. features of products like cost, value for money, etc.) and their relative importance. In this paper, we present an unsupervised approach for discovering coherent hotel aspects based on the user attention. This model effectively integrates techniques like topic modeling and word embeddings along with the frequent noun-adjective co-occurrence statistics to automatically discover coherent hotel aspects. Further supervised methods are used to understand the user&#039;s relative emphasis on the aspects and finally rank the hotels. This method does not assume any predefined seed words and discovers coherent level aspects by directly using user attention and word co-occurrence statistics in addition to topic modeling and word embeddings. The performance evaluation of this method was done by collecting various hotel reviews from multiple travel websites. Results show that the proposed methods improved the baseline performance up to 90%. Hence, the results thus obtained are very promising and indicate that the system is simple, scalable and most of all accurate in ranking hotels based on the latent aspects expressed in the user reviews.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>10</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Masanobu Kii</style></author><author><style face="normal" font="default" size="100%">Apantri Peungnumsai</style></author><author><style face="normal" font="default" size="100%">Varameth Vichiensan</style></author><author><style face="normal" font="default" size="100%">Hiroyuki Miyazaki</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Effect of Public Transport Network on Urban Core and the Future Perspective in Bangkok, Thailand</style></title><secondary-title><style face="normal" font="default" size="100%">2019 First International Conference on Smart Technology &amp; Urban Development (STUD)</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">location probability</style></keyword><keyword><style  face="normal" font="default" size="100%">network  centrality</style></keyword><keyword><style  face="normal" font="default" size="100%">point of interest</style></keyword><keyword><style  face="normal" font="default" size="100%">railway  network</style></keyword><keyword><style  face="normal" font="default" size="100%">urban  core</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2019</style></year><pub-dates><date><style  face="normal" font="default" size="100%">12/2019</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://ieeexplore.ieee.org/document/9018769</style></url></web-urls></urls><pub-location><style face="normal" font="default" size="100%">Chiang Mai, Thailand</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%"> City  center  is  an  essential  components  of  urban  structure   that   rules   urban   activities   including   economy,   transport,  and  social  interactions.  In  Bangkok,  Thailand,  the  railway network is expanding and the expansion is expected to  affect  the  city  center  locations.  In  this  study  we  attempt  to  capture   the   effect   of   public   transport   network   on   the   accumulation of three types of urban core facilities based on the spatial statistical approach, and estimate the future perspective of locations of those facilities. As a result we found that expected number of facilities in current urban core in Bangkok decreases and  the  number  of  facilities  at  stations  on  planned  railways  increases under certain conditions. The results can be utilized to estimate the future travel pattern and residential locations. </style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>10</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Tsuyoshi Takano</style></author><author><style face="normal" font="default" size="100%">Hiroyoshi Morita</style></author><author><style face="normal" font="default" size="100%">Shinichiro Nakamura</style></author><author><style face="normal" font="default" size="100%">Hiroyuki Miyazaki</style></author><author><style face="normal" font="default" size="100%">Wasan Pattara-atikom</style></author><author><style face="normal" font="default" size="100%">Napaporn Piamsa-nga</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Impact of Rainfall on Urban Traffic Flow based on Probe Vehicle Data in Bangkok</style></title><secondary-title><style face="normal" font="default" size="100%">First International Conference on Smart Technology &amp; Urban Development (STUD 2019)</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Climate  change</style></keyword><keyword><style  face="normal" font="default" size="100%">Probe  vehicle  data</style></keyword><keyword><style  face="normal" font="default" size="100%">Rainfall  impact</style></keyword><keyword><style  face="normal" font="default" size="100%">Regression model</style></keyword><keyword><style  face="normal" font="default" size="100%">Travel speed</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2019</style></year><pub-dates><date><style  face="normal" font="default" size="100%">12/2019</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://saki.siit.tu.ac.th/stud2019/uploads_final/111__18076cee1637baa6dafa754962eb2939/FinalFile_stud19_takano_v7_en.pdf</style></url></web-urls></urls><pub-location><style face="normal" font="default" size="100%">Chiang Mai, Thailand</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Adverse  weather  frequently  affects  the  capacities  and  travel  speeds  on  roadways,  which  result  in  worsened  traffic  congestion  and  incurred  productivity  loss.  Further,  with  climate  change   predicted   to   increase   rainfall   in   various   cities   in   Southeast Asia, the risk of flood damage in this region is not only anticipated  to  increase  and  affect  urban  function  but  may  also  significantly  aggravate  daily  traffic  flow.  This  study  highlighted  an analysis of the effect of rainfall on urban traffic flow through the  use  of  probe  vehicle  data  and  rainfall  data  in  the  center  of  Bangkok,  which  is  known  in  Southeast  Asia  for  problems  with  respect to maintenance of pumps and drainage channels and for many   flooded   roads   after   heavy   rainfalls.  The  experimental  results  demonstrated  that  the  average  travel  speed  decreased  by  0.02 km/hour per 1 mm of daily rainfall. In particular, at the time of  peak  traffic  demand,  the  travel  speed  was  notably  reduced  when   passengers   preferred   automobile   traffic.   In   2018,   the   economic loss estimate in central Bangkok due to annual rainfall was  approximately  0.01%  of  the  city’s  GDP.  Future  rainfall  forecast  data  makes  it  possible  to  assess  the  risk  of  climate  change on urban traffic flow.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>5</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Hiroyuki Miyazaki</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Measurement of Inter- and Intra-city Connectivity Using Vehicle Probe Data</style></title><secondary-title><style face="normal" font="default" size="100%">Measuring Connectivity Within and Among Cities in ASEAN</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Connectivity</style></keyword><keyword><style  face="normal" font="default" size="100%">Probe data</style></keyword><keyword><style  face="normal" font="default" size="100%">Urban</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2019</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://www.ide.go.jp/English/Publish/Download/Brc/26.html</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">26</style></number><publisher><style face="normal" font="default" size="100%">JETRO Bangkok/IDE-JETRO</style></publisher><pub-location><style face="normal" font="default" size="100%">Bangkok</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">This chapter analyzes intra- and  inter-city connectivity using the vehicle probe  data  for  selected  48-hour  slots  in  March  and  September  in  2017  and  2018.  I demonstrate the potential analyses by aggregating the probe data of commercial vehicles with  overlay  to  geographical  extents  of  the  majo r  cit ies  ident ified  by  night-time  light  satellite image data.The cit ies  could  be classified  into  more  vehicles  in  the  daytime  or  night time, which were likely associated with drivers’ preference on traffic conditions by the time. Some cities indicated notable changes of driving speeds by the time, possibly owing to traffic condition with  people’s  commuting  as  well  as  transport  infrastructure,  such as highways. More than half of the vehicles were traveling only two cities within the 48-hour periods, which were possibly shuttle trips between two cities. Some cities in the large  industrial  areas  and  inland  cities  indicated  high  proportion  of  vehicles  were  travelling more than two cities, indicating contribution to connectivity among the city.</style></abstract><section><style face="normal" font="default" size="100%">2</style></section></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>10</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Sharma, A</style></author><author><style face="normal" font="default" size="100%">Miyazaki, H</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Multi-Hazard Risk Assessment in Urban Planning and Development Using AHP</style></title><secondary-title><style face="normal" font="default" size="100%">ISPRS-International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2019</style></year></dates><volume><style face="normal" font="default" size="100%">4238</style></volume><pages><style face="normal" font="default" size="100%">363–371</style></pages><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>10</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Apantri Peungnumsai</style></author><author><style face="normal" font="default" size="100%">Hiroyuki Miyazaki</style></author><author><style face="normal" font="default" size="100%">Apichon Witayangkurn</style></author><author><style face="normal" font="default" size="100%">Masanobu Kii</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A Review of MATSim: A Pilot Study of Chatuchak, Bangkok</style></title><secondary-title><style face="normal" font="default" size="100%">First International Conference on Smart Technology &amp; Urban Development (STUD 2019)</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Agent-based modeling</style></keyword><keyword><style  face="normal" font="default" size="100%">Road transportation</style></keyword><keyword><style  face="normal" font="default" size="100%">Transportation</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2019</style></year><pub-dates><date><style  face="normal" font="default" size="100%">12/2019</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://jiist.aiat.or.th/assets/uploads/1588686091433SRGAmjiist.aiat.or.th-23.pdf</style></url></web-urls></urls><pub-location><style face="normal" font="default" size="100%">Chiang Mai, Thailand</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Transportation is one of the basic infrastructures that has become an important factor for urban planning and development. In order to develop a better transportation system can lead to better infrastructure, studying the traffic system, current situation and its behavior, is necessary. However, to reveal every object and its dynamic that happens in the traffic system is impossible without a tool and techniques. MATSim is a simulation model software used to assign the traffic between origins and destinations. Most of MATSim applications have been used for developed countries. Nevertheless, Bangkok is one of several cities challenging on the over-saturated situation on road traffic. To check the situation, the simulation can be used to explore highly concentrated traffic flow. Thus, the objective of this study is to examine the applicability of the Multi-Agents Transportation Simulation (MATSim) framework to Bangkok situation. For the travel demand forecasting, it commonly referred to as the four step model. And MATSim framework is one model for the fourth step of the model which is traffic assignment or route assignment. Therefore, this study explored MATSim by experimenting with two plans of agents represented by people travelling from home to work and work to home over Chatuchak district, Bangkok. The sample size of agents using in the simulation are 10, 100, and 500 agents. The results show the traffic flow differently because of the volume of agent effect on the traffic flow.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>10</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Hiroyuki Miyazaki</style></author><author><style face="normal" font="default" size="100%">Himanshu Bhushan</style></author><author><style face="normal" font="default" size="100%">Kotone Wakiya</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Urban Growth Modeling using Historical Landsat Satellite Data Archive on Google Earth Engine</style></title><secondary-title><style face="normal" font="default" size="100%">2019 First International Conference on Smart Technology &amp; Urban Development (STUD)</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2019</style></year><pub-dates><date><style  face="normal" font="default" size="100%">12/2019</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://ieeexplore.ieee.org/document/9018846</style></url></web-urls></urls><pub-location><style face="normal" font="default" size="100%">Chiang Mai, Thailand</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">This paper presents a pilot of data analysis for urban growth modeling using historical Landsat satellite data archive on Google Earth Engine and SLEUTH cellular automata model. The systems were organized for non-expert so that it could be useful for other applications. The developed system was applied to urban growth modeling for the cities of Hue, Ha Giang, and Vinh Yen in Viet Nam. Although the results indicated that further tuning will be needed in applying SLEUTH for urban growth modeling, the system was well established enabling users to efficiently polish the quality of the modeling results.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Devkota, Bidur</style></author><author><style face="normal" font="default" size="100%">Miyazaki, Hiroyuki</style></author><author><style face="normal" font="default" size="100%">Witayangkurn, Apichon</style></author><author><style face="normal" font="default" size="100%">Kim, Sohee Minsun</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Using Volunteered Geographic Information and Nighttime Light Remote Sensing Data to Identify Tourism Areas of Interest</style></title><secondary-title><style face="normal" font="default" size="100%">Sustainability</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2019</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://www.mdpi.com/2071-1050/11/17/4718</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">11</style></volume><pages><style face="normal" font="default" size="100%">4718</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Easy, economical, and near-real-time identification of tourism areas of interest is useful for tourism planning and management. Numerous studies have been accomplished to analyze and evaluate the tourism conditions of a place using free and near-real-time data sources such as social media. This study demonstrates the potential of volunteered geographic information, mainly Twitter and OpenStreetMap, for discovering tourism areas of interest. Active tweet clusters generated using Density-Based Spatial Clustering of Applications with Noise (DBSCAN) clustering algorithm and building footprint information are used to identify touristic places that ensure the availability of basic essential facilities for travelers. Furthermore, an investigation is made to examine the usefulness of nighttime light remotely sensed data to recognize such tourism areas. The study successfully discovered important tourism areas in urban and remote regions in Nepal which have relatively low social media penetration. The effectiveness of the proposed framework is examined using the F1 measure. The accuracy assessment showed F1 score of 0.72 and 0.74 in the selected regions. Hence, the outcomes of this study can provide a valuable reference for various stakeholders such as tourism planners, urban planners, and so on.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>10</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Bidur Devkota</style></author><author><style face="normal" font="default" size="100%">Hiroyuki Miyazaki</style></author><author><style face="normal" font="default" size="100%">Niraj Pahari</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Utilizing User Generated Contents to describe Tourism Areas of Interest</style></title><secondary-title><style face="normal" font="default" size="100%">2019 First International Conference on Smart Technology &amp; Urban Development (STUD)</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Flickr</style></keyword><keyword><style  face="normal" font="default" size="100%">TFIDF</style></keyword><keyword><style  face="normal" font="default" size="100%">Tourism Area of Interest</style></keyword><keyword><style  face="normal" font="default" size="100%">Twitter</style></keyword><keyword><style  face="normal" font="default" size="100%">User Generated Contents</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2019</style></year><pub-dates><date><style  face="normal" font="default" size="100%">12/2019</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://ieeexplore.ieee.org/document/9018810</style></url></web-urls></urls><pub-location><style face="normal" font="default" size="100%">Chiang Mai, Thailand</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">The use of available place databases (like GeoNamesand traditional maps) to obtain descriptive keywords of a user defined place is not possible because such data sources mainlymaintain location definitions of the well-known places only.Traditional sources may not be updated dynamically and maynot ensure diverse information. Additionally, they do not give anyinformation on the popularity, e.g., which is more popular amongthe places indexed by the same keyword. A bottom-up approach,based on real user attention, can address these problems. Wepropose a method to describe tourism area of interest (TAOI) byaggregating user generated social media text. We match the cooccurrence of important keywords in a particular location andselect such words to describe TAOIs. We applied the proposedmethod to data on micro blogging service Twitter and photosharing service Flickr and confirmed that our method made itpossible to extract TAOI description. The recommended bottomup approach enables the extraction of valuable information thatis not possible by using traditional top-down approaches.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Kanbara, Sakiko</style></author><author><style face="normal" font="default" size="100%">Ngatu, Nlandu Roger</style></author><author><style face="normal" font="default" size="100%">Pokhrel, Tara</style></author><author><style face="normal" font="default" size="100%">Pandey, Apsara</style></author><author><style face="normal" font="default" size="100%">Sharma, Chandrakara</style></author><author><style face="normal" font="default" size="100%">Lee, Hyeon J</style></author><author><style face="normal" font="default" size="100%">Miyagawa, Shoko</style></author><author><style face="normal" font="default" size="100%">Miyazaki, Hiroyuki</style></author><author><style face="normal" font="default" size="100%">Nojima, Sayumi</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">The 2015 Nepal Earthquake Disaster: Is the Threat of Occurrence of Communicable Disease Epidemic Over?</style></title><secondary-title><style face="normal" font="default" size="100%">International Journal of Indonesian National Nurses Association (IJINNA)</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2018</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://ijinna-ppni.org/ijinna2/index.php/IJINNA/article/view/32</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">1</style></volume><pages><style face="normal" font="default" size="100%">105-110</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><work-type><style face="normal" font="default" size="100%">Journal Article</style></work-type></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Dwivedi, Uttam</style></author><author><style face="normal" font="default" size="100%">Miyazaki, Hiroyuki</style></author><author><style face="normal" font="default" size="100%">Shibasaki, Ryosuke</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Building type classification in Mozambique using mobile phone data, high-res satellite images, night-time light data and digital surface model</style></title><secondary-title><style face="normal" font="default" size="100%">Mapping Urban Areas from Space Conference 2018</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">digital surface model</style></keyword><keyword><style  face="normal" font="default" size="100%">high-rise residential buildings</style></keyword><keyword><style  face="normal" font="default" size="100%">low-rise residential</style></keyword><keyword><style  face="normal" font="default" size="100%">non-residential buildings</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2018</style></year><pub-dates><date><style  face="normal" font="default" size="100%">10/2018</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://muas2018.esa.int/agenda/</style></url></web-urls></urls><pub-location><style face="normal" font="default" size="100%">Roma, Italy</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">According to the UN DESA report “World Population Prospects: The 2015 Revision”, The world population is expected to grow 33% by the year 2050. With the highest rate of population growth, Africa is expected to account for more than the half of the world’s population growth between 2015 and 2050. The study area presented in this paper is the Republic of Mozambique, an African country with 70% of its population of 28 million (2016) living and working in rural areas. The Real gross domestic product (GDP) of the country was 3.7% in 2017 shows it’s struggle of poor macroeconomic stability and investment of private sector.

High income countries often have extensive mapping resources and expertise to create reliable and accurate building maps and population databases, but across the low-income regions of the world, relevant data are either lacking or are of poor quality. For low-income regions of the world, accurate maps of human population distribution together with the knowledge of building types and its quantitative measures can play an essential part in planning for elections, calculating per-capita gross domestic product (GDP), poverty mapping, city planning, disaster management amongst countless other applications.

The rapid growth in availability of high resolution satellite imagery, computing power and expansion of geospatial analysis tools over the past decade are providing new opportunities to solve such problems. The use of high resolution images, geospatial data and road network together with state of the art machine learning technology can improve the understanding of human population distribution and building type estimation, which is necessary to predict the future infrastructure management for increasing population because it can be expanded to a bigger scale easily unlike the traditionally used method based on human visual interpretation and survey data collection.

In this paper, we proposed a methodology to classify the types of buildings in three classes; high- rise residential buildings, low-rise residential and non-residential buildings. We have used state- of-the-art machine learning algorithm on the combination of mobile phone sample data collected from a survey, high resolution satellite images, digital surface model and night time light data to extract the building footprints and classify the types of the buildings. The comparing results indicated that our methodology classified types of buildings efficiently with the accuracy of 84%.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Koga, Yohei</style></author><author><style face="normal" font="default" size="100%">Miyazaki, Hiroyuki</style></author><author><style face="normal" font="default" size="100%">Shibasaki, Ryosuke</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A CNN-Based Method of Vehicle Detection from Aerial Images Using Hard Example Mining</style></title><secondary-title><style face="normal" font="default" size="100%">Remote Sensing</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2018</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.mdpi.com/2072-4292/10/1/124</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">10</style></volume><pages><style face="normal" font="default" size="100%">124</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><work-type><style face="normal" font="default" size="100%">Journal Article</style></work-type></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>10</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Yohei Koga</style></author><author><style face="normal" font="default" size="100%">Hiroyuki Miyazaki</style></author><author><style face="normal" font="default" size="100%">Ryosuke Shibasaki</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Deep Domain Adaptation for Single-Shot Vehicle Detector in Satellite Images</style></title><secondary-title><style face="normal" font="default" size="100%">IEEE International Geoscience and Remote Sensing Symposium</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2018</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://ieeexplore.ieee.org/abstract/document/8519129</style></url></web-urls></urls><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>5</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Miyazaki, Hiroyuki</style></author><author><style face="normal" font="default" size="100%">Shibasaki, Ryosuke</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Development of On-Demand Human Settlement Mapping System Using Historical Satellite Archives</style></title><secondary-title><style face="normal" font="default" size="100%">Urban Remote Sensing</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2018</style></year></dates><pages><style face="normal" font="default" size="100%">15</style></pages><isbn><style face="normal" font="default" size="100%">0429888554</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>10</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Uttam Dwivedi</style></author><author><style face="normal" font="default" size="100%">Zhiling Guo</style></author><author><style face="normal" font="default" size="100%">Hiroyuki Miyazaki</style></author><author><style face="normal" font="default" size="100%">Mohamed Batran</style></author><author><style face="normal" font="default" size="100%">Ryosuke Shibasaki</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Development of Population Distribution Map and Automated Human Settlement Map Using High Resolution Remote Sensing Images</style></title><secondary-title><style face="normal" font="default" size="100%">IEEE International Geoscience and Remote Sensing Symposium</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2018</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://ieeexplore.ieee.org/abstract/document/8517827</style></url></web-urls></urls><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>10</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">B. Devkota</style></author><author><style face="normal" font="default" size="100%">H. Miyazaki</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">An Exploratory Study on the Generation and Distribution of Geotagged Tweets in Nepal</style></title><secondary-title><style face="normal" font="default" size="100%">2018 IEEE 3rd International Conference on Computing, Communication and Security (ICCCS)</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">active user locations</style></keyword><keyword><style  face="normal" font="default" size="100%">clustering</style></keyword><keyword><style  face="normal" font="default" size="100%">Conferences</style></keyword><keyword><style  face="normal" font="default" size="100%">data mining</style></keyword><keyword><style  face="normal" font="default" size="100%">geotagged tweets</style></keyword><keyword><style  face="normal" font="default" size="100%">hotspots</style></keyword><keyword><style  face="normal" font="default" size="100%">human information behaviors</style></keyword><keyword><style  face="normal" font="default" size="100%">Kernel</style></keyword><keyword><style  face="normal" font="default" size="100%">live human sensors</style></keyword><keyword><style  face="normal" font="default" size="100%">Media</style></keyword><keyword><style  face="normal" font="default" size="100%">microblogging platform</style></keyword><keyword><style  face="normal" font="default" size="100%">Nepal</style></keyword><keyword><style  face="normal" font="default" size="100%">pattern clustering</style></keyword><keyword><style  face="normal" font="default" size="100%">Security</style></keyword><keyword><style  face="normal" font="default" size="100%">social media</style></keyword><keyword><style  face="normal" font="default" size="100%">social media platforms</style></keyword><keyword><style  face="normal" font="default" size="100%">social networking (online)</style></keyword><keyword><style  face="normal" font="default" size="100%">spatial clustering</style></keyword><keyword><style  face="normal" font="default" size="100%">spatial distribution</style></keyword><keyword><style  face="normal" font="default" size="100%">spatial patterns</style></keyword><keyword><style  face="normal" font="default" size="100%">spatial penetration</style></keyword><keyword><style  face="normal" font="default" size="100%">spatiotemporal patterns</style></keyword><keyword><style  face="normal" font="default" size="100%">spatiotemporal public opinion</style></keyword><keyword><style  face="normal" font="default" size="100%">time data</style></keyword><keyword><style  face="normal" font="default" size="100%">travel industry</style></keyword><keyword><style  face="normal" font="default" size="100%">tweet clusters</style></keyword><keyword><style  face="normal" font="default" size="100%">Twitter</style></keyword><keyword><style  face="normal" font="default" size="100%">twitter activities</style></keyword><keyword><style  face="normal" font="default" size="100%">twitter data</style></keyword><keyword><style  face="normal" font="default" size="100%">Urban areas</style></keyword><keyword><style  face="normal" font="default" size="100%">world wide web today</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2018</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Oct</style></date></pub-dates></dates><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Social media platforms contribute a huge part of the content available on the world wide web today. These platforms act as a rich source of real time data from live human sensors. These media disseminate spatiotemporal public opinion regarding a range of events, activities and human information behaviors. This paper explores the active user locations and spatial penetration of popular microblogging platform, Twitter, in Nepal. A heatmap visualization is used to show the intensity and distribution of the spatial patterns of Twitter activities in different parts of Nepal. Clustering is a popular technique for knowledge discovery, so spatial clustering is applied to groups tweets spatially into different classes. Such spatial clustering helps in the identification of areas of similar twitter activities and shows the distribution of the spatial patterns in different parts of Nepal. Tweet clusters are observed mainly in the main cities and the tourism centers. Further, an examination of the twitter data shared by the local Nepalese people and the foreigners are shown. This study contributes the research line by providing insights to better understand the spatiotemporal patterns and hotspots of tweets in Nepal. Such patterns and hotspots have an immense practical value that can be attributable to a place in order to derive meaningful insights related to various domains like a disease, crime, tourism, etc.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>6</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Shibasaki, Ryosuke</style></author><author><style face="normal" font="default" size="100%">Fukuyo, Takayoshi</style></author><author><style face="normal" font="default" size="100%">Miyazaki, Hiroyuki</style></author><author><style face="normal" font="default" size="100%">Verspieren, Quentin</style></author><author><style face="normal" font="default" size="100%">Anbumozhi, Venkatachalam</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Integrated Spaced-Based Geospatial System: Strengthening ASEAN&#039;s Resilience and Connectivity</style></title></titles><dates><year><style  face="normal" font="default" size="100%">2018</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.eria.org/publications/integrated-space-based-geospatial-system-strengthening-aseans-resilience-and-connectivity/</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">Economic Research Institute for ASEAN and East Asia</style></publisher><pub-location><style face="normal" font="default" size="100%">Jakarta, Indonesia</style></pub-location><isbn><style face="normal" font="default" size="100%">978-602-5460-05-0</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">In recent decades, regional organisations have become increasingly active in connectivity disasters. This reflects a broader growing trend of intensifying regional cooperation for building resilient communities. However, the potentials of space and geospatial technology and their role in sustainable development and strengthening resilience is not clear. They can improve the efficiency and resilience of industrial operations and effectively address issues in the regional economic integration of the Association of Southeast Asian Nations (ASEAN). This report examines the possibilities and models of transborder mechanisms to deliver geospatial and space-based information from data providers to end users in disaster-affected areas, and financial schemes involving the private sector or public–private partnerships to enable the collaborative integration of the technologies in practical ways. It provides vital information about what combinations of technologies have been applied and how they have contributed to the resilience of urban development, infrastructure planning and management, transportation management, and agricultural operations.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Peungnumsai, Apantri</style></author><author><style face="normal" font="default" size="100%">Witayangkurn, Apichon</style></author><author><style face="normal" font="default" size="100%">Nagai, Masahiko</style></author><author><style face="normal" font="default" size="100%">Miyazaki, Hiroyuki</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A Taxi Zoning Analysis Using Large-Scale Probe Data: A Case Study for Metropolitan Bangkok</style></title><secondary-title><style face="normal" font="default" size="100%">The Review of Socionetwork Strategies</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2018</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://doi.org/10.1007/s12626-018-0019-4</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">12</style></volume><pages><style face="normal" font="default" size="100%">21-45</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><work-type><style face="normal" font="default" size="100%">Journal Article</style></work-type></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>10</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Miyazaki, Hiroyuki</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Development of an On-demand Service of Settlement Mapping Using Landsat Archive</style></title><secondary-title><style face="normal" font="default" size="100%">International Conference on Urban Geoinformatics</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2017</style></year></dates><pub-location><style face="normal" font="default" size="100%">New Delhi, India</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>10</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Devkota, Bidur</style></author><author><style face="normal" font="default" size="100%">Miyazaki, Hiroyuki</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Development of Social Media Data Collection System and Its Preliminary Analysis</style></title><secondary-title><style face="normal" font="default" size="100%">International Conference on Urban Geoinformatics</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2017</style></year></dates><pub-location><style face="normal" font="default" size="100%">New Delhi, India</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>10</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Kanbara, Sakiko</style></author><author><style face="normal" font="default" size="100%">Aharonson-Daniel, Limor</style></author><author><style face="normal" font="default" size="100%">Miyazaki, Hiroyuki</style></author><author><style face="normal" font="default" size="100%">Cohen, Odeya</style></author><author><style face="normal" font="default" size="100%">Benin-Goren, Odeda</style></author><author><style face="normal" font="default" size="100%">Yifrah, Dror</style></author><author><style face="normal" font="default" size="100%">Arai, Ayumi</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Innovative Technological Approaches for Community Resilience</style></title><secondary-title><style face="normal" font="default" size="100%">Prehospital and Disaster Medicine</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2017</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://www.cambridge.org/core/article/innovative-technological-approaches-for-community-resilience/2CDC3530F65C3A6625D58C1E6E9EAE79</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">32</style></volume><pages><style face="normal" font="default" size="100%">S191-S191</style></pages><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>10</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Miyazaki, H.</style></author><author><style face="normal" font="default" size="100%">Nagai, M.</style></author><author><style face="normal" font="default" size="100%">Shibasaki, R.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">An Automated Method for Time-Series Human Settlement Mapping using Landsat Data and Existing Land Cover Maps</style></title><secondary-title><style face="normal" font="default" size="100%">2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2016</style></year></dates><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>10</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Koga, Yohei</style></author><author><style face="normal" font="default" size="100%">Miyazaki, Hiroyuki</style></author><author><style face="normal" font="default" size="100%">Shibasaki, Ryosuke</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Counting Vehicles By Deep Neural Network In High Resolution Satellite Images</style></title><secondary-title><style face="normal" font="default" size="100%">The 37th Asian Conference on Remote Sensing</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2016</style></year></dates><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>10</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Miyazaki, H.</style></author><author><style face="normal" font="default" size="100%">Kuwata, K.</style></author><author><style face="normal" font="default" size="100%">Ohira, W.</style></author><author><style face="normal" font="default" size="100%">Guo, Z.</style></author><author><style face="normal" font="default" size="100%">Shao, X.</style></author><author><style face="normal" font="default" size="100%">Xu, Y.</style></author><author><style face="normal" font="default" size="100%">Shibasaki, R.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Development of an automated system for building detection from high-resolution satellite images</style></title><secondary-title><style face="normal" font="default" size="100%">2016 4th International Workshop on Earth Observation and Remote Sensing Applications (EORSA)</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2016</style></year></dates><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>10</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Miyazaki, Hiroyuki</style></author><author><style face="normal" font="default" size="100%">Nagai, Masahiko</style></author><author><style face="normal" font="default" size="100%">Shibasaki, Ryosuke</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Development of Time-Series Human Settlement Mapping System using Historical Landsat Archive</style></title><secondary-title><style face="normal" font="default" size="100%">ISPRS-International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2016</style></year></dates><pages><style face="normal" font="default" size="100%">1385-1388</style></pages><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Guo, Zhiling</style></author><author><style face="normal" font="default" size="100%">Shao, Xiaowei</style></author><author><style face="normal" font="default" size="100%">Xu, Yongwei</style></author><author><style face="normal" font="default" size="100%">Miyazaki, Hiroyuki</style></author><author><style face="normal" font="default" size="100%">Ohira, Wataru</style></author><author><style face="normal" font="default" size="100%">Shibasaki, Ryosuke</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Identification of Village Building via Google Earth Images and Supervised Machine Learning Methods</style></title><secondary-title><style face="normal" font="default" size="100%">Remote Sensing</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2016</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.mdpi.com/2072-4292/8/4/271</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">8</style></volume><pages><style face="normal" font="default" size="100%">271</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">In this study, a method based on supervised machine learning is proposed to identify village buildings from open high-resolution remote sensing images. We select Google Earth (GE) RGB images to perform the classification in order to examine its suitability for village mapping, and investigate the feasibility of using machine learning methods to provide automatic classification in such fields. By analyzing the characteristics of GE images, we design different features on the basis of two kinds of supervised machine learning methods for classification: adaptive boosting (AdaBoost) and convolutional neural networks (CNN). To recognize village buildings via their color and texture information, the RGB color features and a large number of Haar-like features in a local window are utilized in the AdaBoost method; with multilayer trained networks based on gradient descent algorithms and back propagation, CNN perform the identification by mining deeper information from buildings and their neighborhood. Experimental results from the testing area at Savannakhet province in Laos show that our proposed AdaBoost method achieves an overall accuracy of 96.22% and the CNN method is also competitive with an overall accuracy of 96.30%.</style></abstract><work-type><style face="normal" font="default" size="100%">Journal Article</style></work-type></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>10</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Detchev, I.</style></author><author><style face="normal" font="default" size="100%">Kanjir, U.</style></author><author><style face="normal" font="default" size="100%">Reyes, S.R.</style></author><author><style face="normal" font="default" size="100%">Miyazaki, H.</style></author><author><style face="normal" font="default" size="100%">Aktas, A.F.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Latest Developments of the Isprs Student Consortium</style></title><secondary-title><style face="normal" font="default" size="100%">ISPRS-International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2016</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLI-B6/79/2016/isprs-archives-XLI-B6-79-2016.pdf</style></url></web-urls></urls><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">The International Society for Photogrammetry and Remote Sensing (ISPRS) Student Consortium (SC) is a network for young professionals studying or working within the fields of photogrammetry, remote sensing, Geographical Information Systems (GIS), and other related geo-spatial sciences. The main goal of the network is to provide means for information exchange for its young members and thus help promote and integrate youth into the ISPRS. Over the past four years the Student Consortium has successfully continued to fulfil its mission in both formal and informal ways. The formal means of communication of the SC are its website, newsletter, e-mail announcements and summer schools, while its informal ones are multiple social media outlets and various social activities during student related events. The newsletter is published every three to four months and provides both technical and experiential content relevant for the young people in the ISPRS. The SC has been in charge or at least has helped with organizing one or more summer schools every year. The organization&#039;s e-mail list has over 1,100 subscribers, its website hosts over 1,300 members from 100 countries across the entire globe, and its public Facebook group currently has over 4,500 joined visitors, who connect among one another and share information relevant for their professional careers. These numbers show that the Student Consortium has grown into a significant online-united community. The paper will present the organization&#039;s on-going and past activities for the last four years, its current priorities and a strategic plan and aspirations for the future four-year period. </style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>10</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Miyazaki, Hiroyuki</style></author><author><style face="normal" font="default" size="100%">Shibasaki, Ryosuke</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Preliminary Development of Time-Series Human Settlement Maps using Landsat Data</style></title><secondary-title><style face="normal" font="default" size="100%">36th Asian Conference on Remote Sensing</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2015</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2015</style></date></pub-dates></dates><pub-location><style face="normal" font="default" size="100%">Manila, Philippines</style></pub-location><volume><style face="normal" font="default" size="100%">36</style></volume><pages><style face="normal" font="default" size="100%">SP.FR3.3</style></pages><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Miyazaki, Hiroyuki</style></author><author><style face="normal" font="default" size="100%">Nagai, Masahiko</style></author><author><style face="normal" font="default" size="100%">Shibasaki, Ryosuke</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Reviews of Geospatial Information Technology and Collaborative Data Delivery for Disaster Risk Management</style></title><secondary-title><style face="normal" font="default" size="100%">ISPRS International Journal of Geo-Information</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2015</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2015</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.mdpi.com/2220-9964/4/4/1936</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">4</style></volume><pages><style face="normal" font="default" size="100%">1936</style></pages><isbn><style face="normal" font="default" size="100%">2220-9964</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Duan, Yulin</style></author><author><style face="normal" font="default" size="100%">Shao, Xiaowei</style></author><author><style face="normal" font="default" size="100%">Shi, Yun</style></author><author><style face="normal" font="default" size="100%">Miyazaki, Hiroyuki</style></author><author><style face="normal" font="default" size="100%">Iwao, Koki</style></author><author><style face="normal" font="default" size="100%">Shibasaki, Ryosuke</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Unsupervised Global Urban Area Mapping via Automatic Labeling from ASTER and PALSAR Satellite Images</style></title><secondary-title><style face="normal" font="default" size="100%">Remote Sensing</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2015</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2015</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.mdpi.com/2072-4292/7/2/2171</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">7</style></volume><pages><style face="normal" font="default" size="100%">2171-2192</style></pages><isbn><style face="normal" font="default" size="100%">2072-4292</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>5</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Miyazaki, Hiroyuki</style></author><author><style face="normal" font="default" size="100%">Shao, Xiaowei</style></author><author><style face="normal" font="default" size="100%">Iwao, Koki</style></author><author><style face="normal" font="default" size="100%">Shibasaki, Ryosuke</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Development of a Global Built-Up Area Map Using ASTER Satellite Images and Existing GIS Data</style></title><secondary-title><style face="normal" font="default" size="100%">Global Urban Monitoring and Assessment through Earth Observation</style></secondary-title><short-title><style face="normal" font="default" size="100%">Global Urban Monitoring and Assessment through Earth Observation</style></short-title></titles><dates><year><style  face="normal" font="default" size="100%">2014</style></year></dates><publisher><style face="normal" font="default" size="100%">CRC Press</style></publisher><pub-location><style face="normal" font="default" size="100%">London</style></pub-location><pages><style face="normal" font="default" size="100%">121</style></pages><isbn><style face="normal" font="default" size="100%">1466564490</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><section><style face="normal" font="default" size="100%">7</style></section></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>10</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Miyazaki, Hiroyuki</style></author><author><style face="normal" font="default" size="100%">Iwao, Koki</style></author><author><style face="normal" font="default" size="100%">Shibasaki, Ryosuke</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">Weng, Qihao</style></author><author><style face="normal" font="default" size="100%">Zeng, Siqi</style></author><author><style face="normal" font="default" size="100%">Zhu, Jianjun</style></author><author><style face="normal" font="default" size="100%">Zhu, Chuanqu</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Development of High-Resolution Population Database from ASTER-Derived Urban Area Map</style></title><secondary-title><style face="normal" font="default" size="100%">The Third International Workshop on Earth Observation and Remote Sensing Applications</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2014</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2014</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://ieeexplore.ieee.org/document/6927879</style></url></web-urls></urls><pub-location><style face="normal" font="default" size="100%">Changsha, China</style></pub-location><isbn><style face="normal" font="default" size="100%">978-1-4799-5757-6</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>5</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Weng, Qihao</style></author><author><style face="normal" font="default" size="100%">Gamba, Paolo</style></author><author><style face="normal" font="default" size="100%">Mountrakis, Giorgos</style></author><author><style face="normal" font="default" size="100%">Pesaresi, Martino</style></author><author><style face="normal" font="default" size="100%">Lu, Linlin</style></author><author><style face="normal" font="default" size="100%">Kemper, Thomas</style></author><author><style face="normal" font="default" size="100%">Heinzel, Johannes</style></author><author><style face="normal" font="default" size="100%">Xian, George</style></author><author><style face="normal" font="default" size="100%">Jin, Huiran</style></author><author><style face="normal" font="default" size="100%">Miyazaki, Hiroyuki</style></author><author><style face="normal" font="default" size="100%">Xu, Bing</style></author><author><style face="normal" font="default" size="100%">Quresh, Salman</style></author><author><style face="normal" font="default" size="100%">Keramitsoglou, Iphigenia</style></author><author><style face="normal" font="default" size="100%">Ban, Yifang</style></author><author><style face="normal" font="default" size="100%">Esch, Thomas</style></author><author><style face="normal" font="default" size="100%">Roth, Achim</style></author><author><style face="normal" font="default" size="100%">Elvidge, Christopher D.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Urban Observing Sensors</style></title><secondary-title><style face="normal" font="default" size="100%">Global Urban Monitoring and Assessment through Earth Observation</style></secondary-title><tertiary-title><style face="normal" font="default" size="100%">Remote Sensing Applications Series</style></tertiary-title></titles><dates><year><style  face="normal" font="default" size="100%">2014</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2014</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1201/b17012-6</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">CRC Press</style></publisher><pages><style face="normal" font="default" size="100%">49-80</style></pages><isbn><style face="normal" font="default" size="100%">978-1-4665-6449-7</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><notes><style face="normal" font="default" size="100%">doi:10.1201/b17012-6</style></notes></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Miyazaki, H</style></author><author><style face="normal" font="default" size="100%">Shao, X.</style></author><author><style face="normal" font="default" size="100%">Iwao, K.</style></author><author><style face="normal" font="default" size="100%">Shibasaki, R.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">An Automated Method for Global Urban Area Mapping by Integrating ASTER Satellite Images and GIS Data</style></title><secondary-title><style face="normal" font="default" size="100%">Selected Topics in Applied Earth Observations and Remote Sensing, IEEE Journal of</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">ASTER/VNIR</style></keyword><keyword><style  face="normal" font="default" size="100%">Learning with Local and Global Consistency</style></keyword><keyword><style  face="normal" font="default" size="100%">logistic regression</style></keyword><keyword><style  face="normal" font="default" size="100%">urban area mapping</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2013</style></year><pub-dates><date><style  face="normal" font="default" size="100%">30 November 2012</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">6</style></volume><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">We present an automated classification method for global urban area mapping by integrating satellite images taken by Visible and Near-Infrared Radiometer of Advanced Spaceborne Thermal Emission and Reflection radiometer (ASTER/VNIR) and GIS data derived from existing urban area maps. The method consists of two steps. First, we extracted urban areas from ASTER/VNIR satellite images by using an iterative machine-learning classification method known as Learning with Local and Global Consistency (LLGC). This method is capable of automatically performing classification with a noisy training dataset, in our case, low-resolution urban maps. Therefore, we were able to perform supervised classification of ASTER/VNIR images without using labor-intensive visual interpretation. Second, we integrated the LLGC confidence map with other maps by logistic regression. The logistic regression complemented misclassifications in the LLGC map and provided useful information for further improvement of the model. In an experiment including 194 scenes of ASTER/VNIR images, the integrated maps were developed at a resolution of 15 m resolution, which is much finer than existing maps with resolutions of 300 to 1000 m. The maps achieved an overall accuracy of 90.0% and a kappa coefficient of 0.565, both of which are higher than or almost equal to the values for major existing global urban area maps.</style></abstract><issue><style face="normal" font="default" size="100%">2</style></issue><section><style face="normal" font="default" size="100%">1004-1019</style></section></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>10</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Miyazaki, Hiroyuki</style></author><author><style face="normal" font="default" size="100%">Iwao, Koki</style></author><author><style face="normal" font="default" size="100%">Shibasaki, Ryosuke</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Building High-Resolution Population Dataset with ASTER-derived Urban Area Map and Existing Population Data</style></title><secondary-title><style face="normal" font="default" size="100%">34th Asian Conference on Remote Sensing</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2013</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2013</style></date></pub-dates></dates><pub-location><style face="normal" font="default" size="100%">Bali, Indonesia</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>13</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Kimijima, Satomi</style></author><author><style face="normal" font="default" size="100%">Nagai, Masahiko</style></author><author><style face="normal" font="default" size="100%">Miyazaki, Hiroyuki</style></author><author><style face="normal" font="default" size="100%">Shibasaki, Ryosuke</style></author><author><style face="normal" font="default" size="100%">Iwao, Koki</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Crowdsourcing for urban area mapping</style></title><secondary-title><style face="normal" font="default" size="100%">Asia Geospatial Digest</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2013</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2013</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://geospatialworld.net/Paper/Application/ArticleView.aspx?aid=30462</style></url></web-urls></urls><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>10</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Miyazaki, Hiroyuki</style></author><author><style face="normal" font="default" size="100%">Lo, Chao-yuan</style></author><author><style face="normal" font="default" size="100%">Cho, Kohei</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Activities of Asian Students and Young Scientists on Photogrammetry and Remote Sensing</style></title><secondary-title><style face="normal" font="default" size="100%">International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">aars</style></keyword><keyword><style  face="normal" font="default" size="100%">acrs</style></keyword><keyword><style  face="normal" font="default" size="100%">asian association on remote</style></keyword><keyword><style  face="normal" font="default" size="100%">asian conference on remote</style></keyword><keyword><style  face="normal" font="default" size="100%">sensing</style></keyword><keyword><style  face="normal" font="default" size="100%">student activities</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2012</style></year></dates><number><style face="normal" font="default" size="100%">September</style></number><volume><style face="normal" font="default" size="100%">XXXIX</style></volume><pages><style face="normal" font="default" size="100%">79–82</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">This paper reports a history and future prospects of the activities by Asian students and young scientists on photogrammetry and remote sensing. For future growths of academic fields, active communications among students and young scientists are indispensable. In some countries and regions in Asia, local communities are already established by youths and playing important roles of building networks among various schools and institutes. The networks are expected to evolve innovative cooperations after the youths achieve their professions. Although local communities are getting solid growth, Asian youths had had little opportunities to make contacts with youths of other countries and regions. To promote youth activities among Asian regions, in 2007, Asian Association on Remote Sensing (AARS) started a series of programs involving students and young scientists within the annual conferences, the Asian Conference on Remote Sensing (ACRS). The programs have provided opportunities and motivations to create networks among students and young scientists. As a result of the achievements, the number of youth interested and involved in the programs is on growing. In addition, through the events held in Asian region by ISPRS Student Consortium (ISPRS-SC) and WG VI/5, the Asian youths have built friendly partnership with ISPRS-SC. Currently, many Asian youth are keeping contacts with ACRS friends via internet even when they are away from ACRS. To keep and expand the network, they are planning to establish an Asian youth organization on remote sensing. This paper describes about the proposals and future prospects on the Asian youth organization.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>10</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Oba, A</style></author><author><style face="normal" font="default" size="100%">Miyazaki, H</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Activities of the Studnt Forum of the Geoinformation Forum Japan</style></title><secondary-title><style face="normal" font="default" size="100%">International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">academic activities</style></keyword><keyword><style  face="normal" font="default" size="100%">geoinformation forum</style></keyword><keyword><style  face="normal" font="default" size="100%">japan</style></keyword><keyword><style  face="normal" font="default" size="100%">student forum</style></keyword><keyword><style  face="normal" font="default" size="100%">youth network</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2012</style></year></dates><number><style face="normal" font="default" size="100%">September</style></number><volume><style face="normal" font="default" size="100%">XXXIX</style></volume><pages><style face="normal" font="default" size="100%">153–154</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">This reports a history and future prospects of the activities by the Student Forum of the Geoinformation Forum Japan. For growths of academic fields, active communications among students and young scientists are indispensable. Several academic communities in geoinformation fields are established by youths and play important roles of building networks over schools and institutes. The networks are expected to be innovative cooperation after the youths achieve their professions. Although academic communities are getting fixed growth particularly in Japan, youths had gotten little opportunities to make contacts with youths themselves. To promote gotten youth activities among geoinformation fields, in 1998, we started a series of programs that named the Student Forum of the Geoinformation Forum Japan involving students and young scientists within the annual conferences, Geoinformation Forum Japan. The programs have provided opportunities to do presentation their studies by posters, some events, and motivations to create networks among students and young scientists. From 2009, some members of our activities set additional conference in west area of Japan. Thus our activities are spread within Japan. As a result of these achievements, the number of youth dedicating to the programs keeps growing. From 2009, it’s getting international gradually, however, almost all the participants are still Japanese. To keep and expand the network, we are planning to make some nodes with some Asian youth organizations in the field of geoinformation. This paper is concluded with proposals and future prospects on the Student Forum of the Geoinformation Forum Japan.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>10</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Miyazaki, Hiroyuki</style></author><author><style face="normal" font="default" size="100%">Iwao, Koki</style></author><author><style face="normal" font="default" size="100%">Shibasaki, Ryosuke</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Automated Construction of Coverage Catalogues of ASTER Satellite Image for Urban Areas of the World</style></title><secondary-title><style face="normal" font="default" size="100%">International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">ASTER</style></keyword><keyword><style  face="normal" font="default" size="100%">coverage catalogue</style></keyword><keyword><style  face="normal" font="default" size="100%">gazetteer</style></keyword><keyword><style  face="normal" font="default" size="100%">metadata database</style></keyword><keyword><style  face="normal" font="default" size="100%">urban area</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2012</style></year></dates><number><style face="normal" font="default" size="100%">B8</style></number><volume><style face="normal" font="default" size="100%">XXXIX</style></volume><pages><style face="normal" font="default" size="100%">497–500</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">We developed an algorithm to determine a combination of satellite images according to observation extent and image quality. The algorithm was for testing necessity for completing coverage of the search extent. The tests excluded unnecessary images with low quality and preserve necessary images with good quality. The search conditions of the satellite images could be extended, indicating the catalogue could be constructed with specified periods required for time series analysis. We applied the method to a database of metadata of ASTER satellite images archived in GEO Grid of National Institute of Advanced Industrial Science and Technology (AIST), Japan. As indexes of populated places with geographical coordinates, we used a database of 3372 populated place of more than 0.1 million populations retrieved from GRUMP Settlement Points, a global gazetteer of cities, which has geographical names of populated places associated with geographical coordinates and population data. From the coordinates of populated places, 3372 extents were generated with radiuses of 30 km, a half of swath of ASTER satellite images. By merging extents overlapping each other, they were assembled into 2214 extents. As a result, we acquired combinations of good quality for 1244 extents, those of low quality for 96 extents, incomplete combinations for 611 extents. Further improvements would be expected by introducing pixel- based cloud assessment and pixel value correction over seasonal variations.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>10</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Miyazaki, Hiroyuki</style></author><author><style face="normal" font="default" size="100%">Kimijima, Satomi</style></author><author><style face="normal" font="default" size="100%">Nagai, Masahiko</style></author><author><style face="normal" font="default" size="100%">Iwao, Koki</style></author><author><style face="normal" font="default" size="100%">Shibasaki, Ryosuke</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Crowd-Sourcing GIS for Global Urban Area Mapping</style></title><secondary-title><style face="normal" font="default" size="100%">33rd Asian Conference on Remote Sensing</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">ASTER</style></keyword><keyword><style  face="normal" font="default" size="100%">crowd sourcing</style></keyword><keyword><style  face="normal" font="default" size="100%">urban area mapping</style></keyword><keyword><style  face="normal" font="default" size="100%">Web-GIS</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2012</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2012</style></date></pub-dates></dates><pub-location><style face="normal" font="default" size="100%">Pattaya, Thailand</style></pub-location><pages><style face="normal" font="default" size="100%">A4-2</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">We present an internet-based data development, called crowd sourcing, for global urban area mapping. Crowd sourcing is an approach in which non-expert people, called crowds, join a project of producing data with simple procedures. To introducing crowd sourcing for our global urban area mapping, we constructed a crowd sourcing platform with open source GIS software and developed a ground truth data development system the platform. The data development system was for producing ground truth data by digitizing boundaries of urban area with visual interpretation of satellite images. By using the system, we successfully developed over 160,000 records of boundary data in five month. We had an experiment with operation of the system to measure working time by several sizes of work unit: 80 km × 80 km, 20 km × 20 km, and 10 km × 10 km. Medians of working time were 87.2, 6.2, and 1.4 hours, respectively. Our result would be helpful for estimate total working time of crowd sourcing of ground truth data by visual interpretation and would contribute to progress of data-intensive studies of geospatial information, remote sensing, and photogrammetry.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Miyazaki, Hiroyuki</style></author><author><style face="normal" font="default" size="100%">Iwao, Koki</style></author><author><style face="normal" font="default" size="100%">Shibasaki, Ryosuke</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A Crowd-Sourcing System with Web Mapping Systems for Ground Information Database of Global Urban Area Mapping</style></title><secondary-title><style face="normal" font="default" size="100%">3rd Geospatial Information Forum for Students and Young Engineers</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2011</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2011</style></date></pub-dates></dates><pub-location><style face="normal" font="default" size="100%">Osaka, Japan</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Miyazaki, Hiroyuki</style></author><author><style face="normal" font="default" size="100%">Iwao, Koki</style></author><author><style face="normal" font="default" size="100%">Shibasaki, Ryosuke</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Development of a New Ground Truth Database for Global Urban Area Mapping from a Gazetteer</style></title><secondary-title><style face="normal" font="default" size="100%">Remote Sensing</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">crowd sourcing</style></keyword><keyword><style  face="normal" font="default" size="100%">global urban</style></keyword><keyword><style  face="normal" font="default" size="100%">ground truth database</style></keyword><keyword><style  face="normal" font="default" size="100%">web feature service</style></keyword><keyword><style  face="normal" font="default" size="100%">web mapping service</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2011</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.mdpi.com/2072-4292/3/6/1177/</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">6</style></number><pub-location><style face="normal" font="default" size="100%">Taipei</style></pub-location><volume><style face="normal" font="default" size="100%">3</style></volume><pages><style face="normal" font="default" size="100%">1177–1187</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">We present a practical system for collecting ground truth data needed for global urban area mapping. To collect visually interpreted information effectively, we implemented crowd sourcing, with which the operators collect and send very accurate data generated by visual interpretation through the Internet. The system was constructed with Web Map Service (WMS) and Web Feature Service (WFS), which are standardized scheme of publishing and updating map data over the Internet. Within the system, the conductor and the operators of visual interpretation campaign would save labor and time for transferring data, keeping consistency, and assuring data security. In addition to that, owing to the standardized scheme, the system was flexibly extensible and transferrable to the other purpose. We regard that the system would contribute to improve ground information for global urban area mapping as well as statistical investigation on precision of visual interpretations. 1. INTRODUCTION Global urban area maps, which represent location, area and shape of urban area of the world,</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>10</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Miyazaki, Hiroyuki</style></author><author><style face="normal" font="default" size="100%">Itabashi, Koichiro</style></author><author><style face="normal" font="default" size="100%">Shao, Xiaowei</style></author><author><style face="normal" font="default" size="100%">Iwao, Koki</style></author><author><style face="normal" font="default" size="100%">Shibasaki, Ryosuke</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">High-Resolution Urban Area Map for 3372 Cities of the World</style></title><secondary-title><style face="normal" font="default" size="100%">32nd Asian Conference on Remote Sensing</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">ASTER</style></keyword><keyword><style  face="normal" font="default" size="100%">automated image selection</style></keyword><keyword><style  face="normal" font="default" size="100%">automated urban area mapping</style></keyword><keyword><style  face="normal" font="default" size="100%">global urban area map</style></keyword><keyword><style  face="normal" font="default" size="100%">Learning with Local and Global Consistency</style></keyword><keyword><style  face="normal" font="default" size="100%">logistic regression</style></keyword><keyword><style  face="normal" font="default" size="100%">multi-source classification</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2011</style></year></dates><pub-location><style face="normal" font="default" size="100%">Taipei</style></pub-location><pages><style face="normal" font="default" size="100%">PS–3</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">We developed an automated method of image selection and urban area mapping for developing high-resolution global urban area maps. The method was successfully implemented and applied to 3372 cities of more than 0.1 million people of the world. As the result, the algorithm of image selection determined 11802 scenes of ASTER/VNIR satellite images and yielded good combinations for more than 60% of the cities. For the merged satellite images with the determined combinations, we applied the automated method of urban area mapping in high resolution. The method was consist of semi-supervised classifications by a machine learning method, called Learning with Local and Global Consistency (LLGC), and integrating the LLGC-derived maps and existing maps by logistic regression. As the result, we acquired urban area maps of 15-m resolution originated from ASTER/VNIR images, which is much finer than 500-m resolution of existing urban area maps. The method had still much space to be improved, especially in avoiding cloud contaminations. However, the method would contribute to complete high-resolution urban area maps of the world and realizing Global Earth Observation Systems of System (GEOSS).</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>10</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Itabashi, Koichiro</style></author><author><style face="normal" font="default" size="100%">Miyazaki, Hiroyuki</style></author><author><style face="normal" font="default" size="100%">Iwao, Koki</style></author><author><style face="normal" font="default" size="100%">Nakamura, Kazuki</style></author><author><style face="normal" font="default" size="100%">MATSUOKA, Masashi</style></author><author><style face="normal" font="default" size="100%">Shibasaki, Ryosuke</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A Method for Constructing Urban Extent Map from ALOS/PALSAR Satellite Data</style></title><secondary-title><style face="normal" font="default" size="100%">32nd Asian Conference on Remote Sensing</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">ALOS/PALSAR</style></keyword><keyword><style  face="normal" font="default" size="100%">classification</style></keyword><keyword><style  face="normal" font="default" size="100%">microwave sensor</style></keyword><keyword><style  face="normal" font="default" size="100%">urban extent map</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2011</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2011</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://a-a-r-s.org/acrs/index.php/acrs/acrs-overview/proceedings-1?view=publication&amp;task=show&amp;id=1005</style></url></web-urls></urls><pub-location><style face="normal" font="default" size="100%">Taipei</style></pub-location><pages><style face="normal" font="default" size="100%">TS9-1</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Currently, global urban extent map of high accuracy and high resolution have been constructed mainly using optical sensor including ASTER/VNIR. However, there are some regions where urban areas are not correctly detected due to cloud cover and similar reflectance among land cover classes. To solve the problems, we used microwave sensor images of ALOS/PALSAR, which has an advantage in enabling observation in all weather conditions. This study aims at examining the possibility of using ALOS/PALSAR images as an alternative data resource for constructing urban extent map. Firstly, to determine useful ALOS/PALSAR observation mode, we examined how often ALOS/PALSAR images are taken in the regions for which an existing method using ASTER/VNIR images could not detect urban area correctly. Secondly, we collected ALOS/PALSAR satellite images, and examined effect of local-incident-angle-corrected images of ALOS/PALSAR taken by Fine Resolution Mode which can reduce distortion of pixel values due to local incident angle. We also performed unsupervised classifications on the ALOS/PALSAR and local-incident-angle-corrected images. Finally, we discussed ground truth datasets for image classification.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Miyazaki, Hiroyuki</style></author><author><style face="normal" font="default" size="100%">Iwao, Koki</style></author><author><style face="normal" font="default" size="100%">Shibasaki, Ryosuke</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A Study on Global Urban Area Mapping using Satellite Data</style></title><secondary-title><style face="normal" font="default" size="100%">20th IIS Forum on Broad-Scale Collection and Application of Environment and Disaster Risk Information</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2011</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2011</style></date></pub-dates></dates><pub-location><style face="normal" font="default" size="100%">Tokyo, Japan</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>32</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Miyazaki, Hiroyuki</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A Study on Global Urban Area Mapping using Satellite Images</style></title></titles><dates><year><style  face="normal" font="default" size="100%">2011</style></year></dates><publisher><style face="normal" font="default" size="100%">The University of Tokyo</style></publisher><pages><style face="normal" font="default" size="100%">110</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><work-type><style face="normal" font="default" size="100%">phd</style></work-type></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Miyazaki, Hiroyuki</style></author><author><style face="normal" font="default" size="100%">Shao, Xiaowei</style></author><author><style face="normal" font="default" size="100%">Iwao, Koki</style></author><author><style face="normal" font="default" size="100%">Shibasaki, Ryosuke</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Automatic Mapping of Urban Area in High Resolution with ASTER satellite images</style></title><secondary-title><style face="normal" font="default" size="100%">19th IIS Forum on Broad-Scale Collection and Application of Environment and Disaster Risk Information</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2010</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2010</style></date></pub-dates></dates><pub-location><style face="normal" font="default" size="100%">Tokyo, Japan</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>10</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Miyazaki, Hiroyuki</style></author><author><style face="normal" font="default" size="100%">Shao, Xiaowei</style></author><author><style face="normal" font="default" size="100%">Iwao, Koki</style></author><author><style face="normal" font="default" size="100%">Shibasaki, Ryosuke</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Automatic Mapping of Urban Area in High Resolution with LLGC and Integration with Existing Urban Area Maps</style></title><secondary-title><style face="normal" font="default" size="100%">Proceedings of AGILE 2010</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">ASTER</style></keyword><keyword><style  face="normal" font="default" size="100%">land cover classification</style></keyword><keyword><style  face="normal" font="default" size="100%">urban area mapping</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2010</style></year></dates><pub-location><style face="normal" font="default" size="100%">Guimaraes, Portugal</style></pub-location><pages><style face="normal" font="default" size="100%">1–9</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">We present development of automated algorithm for mapping global urban area in high resolution using ASTER satellite images and coarse-resolution urban area maps. The algorithm consists of two steps: classifying pixels of ASTER satellite images into urban or non-urban by Learning with Global and Local Consistency (LLGC) technique; and integration with existing urban area maps using logistic regression. We implemented the algorithm and demonstrated it against 340 scenes of ASTER satellite images. LLGC trimmed up 500-m-resolution clusters of urban area into 15-m-resoluton clusters. However accuracy assessment on LLGC result showed 75% user’s accuracy, 41% producer’s accuracy, 94% overall accuracy and 0.50 kappa coefficient, indicating LLGC had considerable misclassifications due to similarity in surface reflectance among non-vegetative land cover. To complement the misclassifications, we integrated LLGC result with existing urban area maps. Accuracy assessment on result of the integration showed 74% user’s accuracy, 43% producer’s accuracy, 94% overall accuracy and 0.51 kappa coefficient, indicating that the results were more accurate than LLGC result and existing urban area maps. We concluded our method would improve global urban area map not only in terms of spatial resolution, but also in that of accuracy.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>10</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Miyazaki, Hiroyuki</style></author><author><style face="normal" font="default" size="100%">Shao, Xiaowei</style></author><author><style face="normal" font="default" size="100%">Iwao, Koki</style></author><author><style face="normal" font="default" size="100%">Shibasaki, Ryosuke</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Global Urban Area Mapping in High Resolution using ASTER Satellite Images</style></title><secondary-title><style face="normal" font="default" size="100%">International Archives of the Photogrammetry, Remote Sensing and Spatial Information Science</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">ASTER</style></keyword><keyword><style  face="normal" font="default" size="100%">land cover classification</style></keyword><keyword><style  face="normal" font="default" size="100%">urban area mapping</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2010</style></year></dates><pub-location><style face="normal" font="default" size="100%">Kyoto</style></pub-location><volume><style face="normal" font="default" size="100%">XXXVIII</style></volume><pages><style face="normal" font="default" size="100%">847–852</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">We present development of automated algorithm for mapping global urban area in high resolution using ASTER satellite images and coarse-resolution urban area maps. The algorithm consists of two steps: classifying pixels of ASTER satellite images into urban or non-urban by Learning with Global and Local Consistency (LLGC) technique; and integration with existing urban area maps using logistic regression. We implemented the algorithm and demonstrated it against 340 scenes of ASTER satellite images. LLGC trimmed up 500-m-resolution clusters of urban area into 15-m-resoluton clusters. However accuracy assessment on LLGC result showed 75% user’s accuracy, 41% producer’s accuracy, 94% overall accuracy and 0.50 kappa coefficient, indicating LLGC had considerable misclassifications due to similarity in surface reflectance among non-vegetative land cover. To complement the misclassifications, we integrated LLGC result with existing urban area maps. Accuracy assessment on result of the integration showed 74% user’s accuracy, 43% producer’s accuracy, 94% overall accuracy and 0.51 kappa coefficient, indicating that the results were more accurate than LLGC result and existing urban area maps. We concluded our method would improve global urban area map not only in terms of spatial resolution, but also in that of accuracy.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>10</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Miyazaki, Hiroyuki</style></author><author><style face="normal" font="default" size="100%">Shao, Xiaowei</style></author><author><style face="normal" font="default" size="100%">Iwao, Koki</style></author><author><style face="normal" font="default" size="100%">Shibasaki, Ryosuke</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Global Urban Area Mapping using Global ASTER Satellite Images</style></title><secondary-title><style face="normal" font="default" size="100%">31th Asian Conference on Remote Sensing</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">ASTER</style></keyword><keyword><style  face="normal" font="default" size="100%">cover classification</style></keyword><keyword><style  face="normal" font="default" size="100%">high resolution</style></keyword><keyword><style  face="normal" font="default" size="100%">land</style></keyword><keyword><style  face="normal" font="default" size="100%">LLGC</style></keyword><keyword><style  face="normal" font="default" size="100%">logistic regression</style></keyword><keyword><style  face="normal" font="default" size="100%">urban area mapping</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2010</style></year></dates><pub-location><style face="normal" font="default" size="100%">Hanoi</style></pub-location><pages><style face="normal" font="default" size="100%">TS07–2</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">We present development of global urban area map using ASTER satellite images, which has much higher resolution than that of existing global urban area maps. To complete the map for world’s cities, we developed automated algorithm for mapping urban area in high resolution. The algorithm consists of two steps: classifying pixels of ASTER satellite images into urban or non-urban by Learning with Global and Local Consistency (LLGC) technique; and integration with existing urban area maps using logistic regression. We implemented the algorithm and demonstrated it on 775 scenes of ASTER satellite images. LLGC classified pixels of ASTER satellite images into urban or non-urban in 15-m resolution, though it had considerable amount of misclassification due to similarity in surface reflectance among non-vegetative land cover. To complement the misclassifications, we integrated LLGC results with existing urban area maps using logistic regression. The misclassifications were corrected well, especially in dry zone. We also developed ground truth database using global gazetteer of world’s cities so that we conduct comprehensive accuracy assessment on the urban area map. We visually interpreted land cover of urban or non-urban on 3734 points coordinates derived from global gazetteer, and combined them with 4211 data points of Degree Confluence Project into a database, which had 2185 data points of urban and 5559 of non-urban. Accuracy assessment using the database indicates that our map is more accurate than existing urban area maps. Finally, we applied the method on broad coverage of ASTER satellite images rather than single one scene. The result showed quite well classification as a whole, indicating possibility of developing global urban area map in high-resolution; however considerable problems due to availability of cloud-free satellite image is still remained.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>10</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Miyazaki, Hiroyuki</style></author><author><style face="normal" font="default" size="100%">Iwao, Koki</style></author><author><style face="normal" font="default" size="100%">Shibasaki, Ryosuke</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">High-Resolution Urban Area Mapping of World&#039;s Cities Using Satellite Images</style></title><secondary-title><style face="normal" font="default" size="100%">19th Annual Conference of GIS Association of Japan</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2010</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2010</style></date></pub-dates></dates><pub-location><style face="normal" font="default" size="100%">Kyoto, Japan</style></pub-location><volume><style face="normal" font="default" size="100%">19</style></volume><pages><style face="normal" font="default" size="100%">1C-3</style></pages><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>10</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Itabashi, Koichiro</style></author><author><style face="normal" font="default" size="100%">Miyazaki, Hiroyuki</style></author><author><style face="normal" font="default" size="100%">Iwao, Koki</style></author><author><style face="normal" font="default" size="100%">Nakamura, Kazuki</style></author><author><style face="normal" font="default" size="100%">Shibasaki, Ryosuke</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A method for detecting and mapping Urban Area by ALOS/PALSAR data</style></title><secondary-title><style face="normal" font="default" size="100%">31st Asian Conference on Remote Sensing</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">ALOS PALSAR urban extent map high resolution</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2010</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2010</style></date></pub-dates></dates><pub-location><style face="normal" font="default" size="100%">Hanoi, Vietnam</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Currently, global urban extent map of high accuracy and resolution have been constructed mainly using optical sensor including ASTER/VNIR. However, there are some regions where urban area is not detected because of cloud cover and similar reflectance among land cover classes. In the present work, by using ALOS/PALSAR, a microwave sensor, we proposed a method for detecting urban area which cannot be detected by ASTER/VNIR optical sensor and developing urban extent map in high accuracy and resolution. We mainly used satellite images taken by Fine Resolution Mode of ALOS/PALSAR. Local-incident-angle corrected images by Fine Resolution Mode were used for this method. The proposed method consists of sampling pixel values and ground truth data at urban and non-urban area from ALOS/PALSAR images; constructing classifier based on the pixel values and ground truth data; and classifying pixels into urban or non-urban area. We compared the results with urban extent map derived from ASTER/VNIR optical sensor images, and evaluated the possibility of using ALOS/PALSAR data for developing urban extent map. In addition, we examined accuracy improvement of detecting urban area using both ASTER/VNIR and ALOS/PALSAR images. The proposed method could classify regions which were misclassified by ASTER/VNIR optical sensor images, and develop urban extent map in high accuracy and resolution.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>10</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Miyazaki, Hiroyuki</style></author><author><style face="normal" font="default" size="100%">Iwao, Koki</style></author><author><style face="normal" font="default" size="100%">Shibasaki, Ryosuke</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Assessing Validity of Global Gazetteers as Ground Truth Data for Urban Mapping</style></title><secondary-title><style face="normal" font="default" size="100%">30th Asian Conference on Remote Sensing</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2009</style></year></dates><pub-location><style face="normal" font="default" size="100%">Beijing</style></pub-location><pages><style face="normal" font="default" size="100%">TS17–01</style></pages><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Miyazaki, Hiroyuki</style></author><author><style face="normal" font="default" size="100%">Iwao, Koki</style></author><author><style face="normal" font="default" size="100%">Shibasaki, Ryosuke</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Assessment of Usability of Gazetteer as Ground Truth Data</style></title><secondary-title><style face="normal" font="default" size="100%">Japan Society of Photogrammetry and Remote Sensing Spring Meeting</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2009</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2009</style></date></pub-dates></dates><pub-location><style face="normal" font="default" size="100%">Yokohama, Japan</style></pub-location><pages><style face="normal" font="default" size="100%">I-1</style></pages><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Miyazaki, Hiroyuki</style></author><author><style face="normal" font="default" size="100%">Iwao, Koki</style></author><author><style face="normal" font="default" size="100%">Shibasaki, Ryosuke</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Developing Global Urban Extent Map of High Resolution with ASTER Satellite Images</style></title><secondary-title><style face="normal" font="default" size="100%">7th International Conference on Urban Climate</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2009</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2009</style></date></pub-dates></dates><pub-location><style face="normal" font="default" size="100%">Yokohama, Japan</style></pub-location><pages><style face="normal" font="default" size="100%">4-16</style></pages><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Miyazaki, Hiroyuki</style></author><author><style face="normal" font="default" size="100%">Iwao, Koki</style></author><author><style face="normal" font="default" size="100%">Shibasaki, Ryosuke</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Development of New Urban Extent Map with Integration of ASTER Satellite Images and Existing Urban Extent Maps</style></title><secondary-title><style face="normal" font="default" size="100%">1st Geoinformation Student Forum in Kansai</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2009</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2009</style></date></pub-dates></dates><pub-location><style face="normal" font="default" size="100%">Kyoto, Japan</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Miyazaki, Hiroyuki</style></author><author><style face="normal" font="default" size="100%">Tanaka, Ayako</style></author><author><style face="normal" font="default" size="100%">Iwao, Koki</style></author><author><style face="normal" font="default" size="100%">Shibasaki, Ryosuke</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A Method for Developing Urban Extent Map of High Accuracy and Resolution by Integrating ASTER/VNIR Images and Existing Urban Extent Maps</style></title><secondary-title><style face="normal" font="default" size="100%">Journal of the Japan Society of Photogrammetry and Remote Sensing</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2009</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://ci.nii.ac.jp/naid/10025572312/en/</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">2</style></number><publisher><style face="normal" font="default" size="100%">日本写真測量学会</style></publisher><volume><style face="normal" font="default" size="100%">48</style></volume><pages><style face="normal" font="default" size="100%">82–96</style></pages><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Miyazaki, Hiroyuki</style></author><author><style face="normal" font="default" size="100%">Iwao, Koki</style></author><author><style face="normal" font="default" size="100%">Shibasaki, Ryosuke</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Urban Extent Mapping with Textural Information of Satellite Image</style></title><secondary-title><style face="normal" font="default" size="100%">18th IIS Forum on Broad-Scale Collection and Application of Environment and Disaster Risk Information</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2009</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2009</style></date></pub-dates></dates><pub-location><style face="normal" font="default" size="100%">Tokyo, Japan</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Miyazaki, Hiroyuki</style></author><author><style face="normal" font="default" size="100%">Iwao, Koki</style></author><author><style face="normal" font="default" size="100%">Shibasaki, Ryosuke</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Validation on Availability of Gazetteer for Global Urban Mapping</style></title><secondary-title><style face="normal" font="default" size="100%">16th Remote Sensing Forum, Society of Instrument and Control Engineers</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2009</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2009</style></date></pub-dates></dates><pub-location><style face="normal" font="default" size="100%">Tokyo, Japan</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>32</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Miyazaki, Hiroyuki</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Developing Method for Estimation of Affection by Grazing Activities against Vegetation with Multi-Temporal Satellite Images and Application for Mapping Grazing Activities</style></title></titles><dates><year><style  face="normal" font="default" size="100%">2008</style></year></dates><pages><style face="normal" font="default" size="100%">54</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><work-type><style face="normal" font="default" size="100%">Master dissertation</style></work-type></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>10</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Miyazaki, Hiroyuki</style></author><author><style face="normal" font="default" size="100%">Iwao, Koki</style></author><author><style face="normal" font="default" size="100%">Shibasaki, Ryosuke</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Developing Urban Extent Map of High Accuracy and Resolution by Integrating ASTER satellite Images and Existing Urban Extent Maps</style></title><secondary-title><style face="normal" font="default" size="100%">17th Annual Conference of GIS Association of Japan</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2008</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2008</style></date></pub-dates></dates><pub-location><style face="normal" font="default" size="100%">Tokyo, Japan</style></pub-location><volume><style face="normal" font="default" size="100%">17</style></volume><pages><style face="normal" font="default" size="100%">89-92</style></pages><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Miyazaki, Hiroyuki</style></author><author><style face="normal" font="default" size="100%">Iwao, Koki</style></author><author><style face="normal" font="default" size="100%">Shibasaki, Ryosuke</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Development of New Urban Extent Map with lntegration of ASTER/VNIR Classified Map and Existing Urban Extent Maps</style></title><secondary-title><style face="normal" font="default" size="100%">ASTER Workshop - ASTER Science Team Meeting</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2008</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2008</style></date></pub-dates></dates><pub-location><style face="normal" font="default" size="100%">Tokyo, Japan</style></pub-location><pages><style face="normal" font="default" size="100%">10-11</style></pages><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Miyazaki, Hiroyuki</style></author><author><style face="normal" font="default" size="100%">Shibasaki, Ryosuke</style></author><author><style face="normal" font="default" size="100%">Yan, Wanglin</style></author><author><style face="normal" font="default" size="100%">Zhao, Zhizhong</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Estimation of infuluence of grazing activities against vegetation with multi-temporal satellite images on Qinghai-Tibet plateau [in Japanese]</style></title><secondary-title><style face="normal" font="default" size="100%">Papers on environmental information science</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">grazing activities</style></keyword><keyword><style  face="normal" font="default" size="100%">MODIS</style></keyword><keyword><style  face="normal" font="default" size="100%">multi-temporal satellite images</style></keyword><keyword><style  face="normal" font="default" size="100%">Qinghai-Tibet Plateau</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2008</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://ci.nii.ac.jp/naid/40016406716/en/</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">22</style></volume><pages><style face="normal" font="default" size="100%">565–570</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">In Qinghai-Tibet Plateau, west part of China, there are serious land degradations caused by overgrazing and climatic change, and mapping the influence is urgently needed. This study proposes method for estimation of influence by grazing activities on grassland with 16-day dataset derived from MODIS satellite imagery and meteorological observation dataset. The result of application on Maduo-Xian in Qnghai province shows estimated influence is correspond to actual condition recognized with field study, and degraded land, grazed land and conserved land are discriminated with the estimation. In addition, the period of grazing at grazing land for summer or winter is estimated with time series profile of the estimation. The method is expected to be developed for observation on conditions of grazing land.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>10</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Miyazaki, Hiroyuki</style></author><author><style face="normal" font="default" size="100%">Tanaka, Ayako</style></author><author><style face="normal" font="default" size="100%">Iwao, Koki</style></author><author><style face="normal" font="default" size="100%">Shibasaki, Ryosuke</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Study on Automatic Global Urban Mapping Method using Satellite Imagery and the Existing Land Cover Data</style></title><secondary-title><style face="normal" font="default" size="100%">Japan Society of Photogrammetry and Remote Sensing Spring Meeting</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2008</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2008</style></date></pub-dates></dates><pub-location><style face="normal" font="default" size="100%">Yokohama, Japan</style></pub-location><pages><style face="normal" font="default" size="100%">S-4</style></pages><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>10</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Miyazaki, Hiroyuki</style></author><author><style face="normal" font="default" size="100%">Shibasaki, Ryosuke</style></author><author><style face="normal" font="default" size="100%">Yan, Wanglin</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Analysis of the Geographical Process of Grazing Impacts in Tibetan Plateau using Time-series Satellite Images</style></title><secondary-title><style face="normal" font="default" size="100%">9th Geospatial Information Student Forum</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2007</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2007</style></date></pub-dates></dates><pub-location><style face="normal" font="default" size="100%">Yokohama, Japan</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>10</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Miyazaki, Hiroyuki</style></author><author><style face="normal" font="default" size="100%">Yan, Wanglin</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Assessment of Grazing Pressure with Gegraphical Heterogeneity: A Case Study in Maduo, Qinghai Province, China</style></title><secondary-title><style face="normal" font="default" size="100%">Japan Society of Photogrammetry and Remote Sensing Spring Meeting</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2007</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2007</style></date></pub-dates></dates><pub-location><style face="normal" font="default" size="100%">Yokohama, Japan</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>10</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Miyazaki, Hiroyuki</style></author><author><style face="normal" font="default" size="100%">Shibasaki, Ryosuke</style></author><author><style face="normal" font="default" size="100%">Yan, Wanglin</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Development of Method for Detection of Grazing Activities with Time-Series Satellite images in Plateau Region</style></title><secondary-title><style face="normal" font="default" size="100%">28th Asian Conference on Remote Sensing</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2007</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2007</style></date></pub-dates></dates><pub-location><style face="normal" font="default" size="100%">Kuala Lumpur, Malaysia</style></pub-location><pages><style face="normal" font="default" size="100%">TS25.5</style></pages><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>10</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Miyazaki, Hiroyuki</style></author><author><style face="normal" font="default" size="100%">Shibasaki, Ryosuke</style></author><author><style face="normal" font="default" size="100%">Yan, Wanglin</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Analysis of the Geographical Process of Land Degrations in Plateau Region with Time-series Satellite Images</style></title><secondary-title><style face="normal" font="default" size="100%">27th Asian Conference on Remote Sensing</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2006</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2006</style></date></pub-dates></dates><pub-location><style face="normal" font="default" size="100%">Ulaanbaatar, Mongolia</style></pub-location><pages><style face="normal" font="default" size="100%">T-1_T2</style></pages><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>10</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Miyazaki, Hiroyuki</style></author><author><style face="normal" font="default" size="100%">Yan, Wanglin</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Assessment of the grazing pressure to pasture in plateau region: a case study in Maduo Xian, Qinghai Province</style></title><secondary-title><style face="normal" font="default" size="100%">8th Geospatial Information Student Forum</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2006</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2006</style></date></pub-dates></dates><pub-location><style face="normal" font="default" size="100%">Yokohama, Japan</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Miyazaki, Hiroyuki</style></author><author><style face="normal" font="default" size="100%">Yan, Wanglin</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Estimation of the grazing pressure with geographical heterogeneity in pasture of plateau region: a case study in Maduo Xian, Qinghai Province [in Japanese]</style></title><secondary-title><style face="normal" font="default" size="100%">Papers on environmental information science</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">geographical heterogeneity</style></keyword><keyword><style  face="normal" font="default" size="100%">grazing pressure</style></keyword><keyword><style  face="normal" font="default" size="100%">MODIS</style></keyword><keyword><style  face="normal" font="default" size="100%">Qinghai-Tibet Plateau</style></keyword><keyword><style  face="normal" font="default" size="100%">remote sensing</style></keyword><keyword><style  face="normal" font="default" size="100%">SRTM</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2006</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://ci.nii.ac.jp/naid/40015321174/en/</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">20</style></volume><pages><style face="normal" font="default" size="100%">367–372</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">There are serious land degradations caused by overgrazing in Qinghai-Tibet Plateau. Regional planning to preserve the plateau ecosystem is urgently needed. This study estimates grazing pressure considering the geographical heterogeneity of pasture productivity and grazing intensity using MODIS images and SRTM DEM. A case study in Maduo Xian, Qinghai Province shows the accessible lands are limited. At the accessible land, grazing activities are notably intense and grazing pressure is high. Additionally, this study shows that the extent of overgrazing is huge in comparison with accessible lands although the actual area is small. This knowledge will assist to make plans for the land conservation.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>10</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Miyazaki, Hiroyuki</style></author><author><style face="normal" font="default" size="100%">Yan, Wanglin</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Analysis of Interrelation between Natural Conditions and Industrial Structure on Tibet Plateau: Case Study in Qinghai Province</style></title><secondary-title><style face="normal" font="default" size="100%">14th Annual Conference of GIS Association of Japan</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2005</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2005</style></date></pub-dates></dates><pub-location><style face="normal" font="default" size="100%">Osaka, Japan</style></pub-location><volume><style face="normal" font="default" size="100%">14</style></volume><pages><style face="normal" font="default" size="100%">181-184</style></pages><language><style face="normal" font="default" size="100%">eng</style></language></record></records></xml>