<?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%">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>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%">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>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>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></records></xml>