@article {141,
	title = {Detection of River Plastic Using UAV Sensor Data and Deep Learning},
	journal = {Remote Sensing},
	volume = {14},
	year = {2022},
	month = {Jan-07-2022},
	pages = {3049},
	doi = {10.3390/rs14133049},
	url = {https://www.mdpi.com/2072-4292/14/13/3049},
	author = {Maharjan, Nisha and Miyazaki, Hiroyuki and Pati, Bipun Man and Dailey, Matthew N. and Shrestha, Sangam and Nakamura, Tai}
}
@article {140,
	title = {Impacts of disaster and land-use change on food security and adaptation: Evidence from the delta community in Bangladesh},
	journal = {International Journal of Disaster Risk Reduction},
	volume = {78},
	year = {2022},
	month = {Jan-08-2022},
	pages = {103119},
	issn = {22124209},
	doi = {10.1016/j.ijdrr.2022.103119},
	url = {https://www.sciencedirect.com/science/article/abs/pii/S2212420922003387},
	author = {Parven, Afshana and Pal, Indrajit and Witayangkurn, Apichon and Pramanik, Malay and Nagai, Masahiko and Miyazaki, Hiroyuki and Wuthisakkaroon, Chanakan}
}
@article {126,
	title = {Factors affecting decision-making in land valuation process using AHP: a case in the Philippines},
	journal = {International Journal of Housing Markets and Analysis},
	volume = {ahead-of-print},
	year = {2021},
	month = {2021},
	abstract = {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 < 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{\textquoteright} 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.},
	isbn = {1753-8270},
	url = {https://doi.org/10.1108/IJHMA-11-2020-0136},
	author = {Bencure, Jannet C. and Tripathi, Nitin K. and Miyazaki, Hiroyuki and Ninsawat, Sarawut and Kim, Sohee Minsun}
}
@article {127,
	title = {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},
	volume = {20},
	year = {2021},
	month = {2021/02/27},
	pages = {117},
	abstract = {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.},
	isbn = {1475-2875},
	url = {https://doi.org/10.1186/s12936-021-03647-9},
	author = {Ngatu, Nlandu Roger and Muzembo, Basilua Andre and Choomplang, Nattadech and Kanbara, Sakiko and Wumba, Roger and Ikeda, Mitsunori and Mbelambela, Etongola Papy and Muchanga, Sifa Marie-Joelle and Suzuki, Tomoko and Wada, Koji and Al Mahfuz, Hasan and Sugishita, Tomohiko and Miyazaki, Hiroyuki and Ikeda, Shunya and Hirao, Tomohiro}
}
@article {107,
	title = {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},
	journal = {Sustainability},
	volume = {11},
	year = {2019},
	abstract = {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).},
	issn = {2071-1050},
	doi = {10.3390/su11133731},
	url = {https://www.mdpi.com/2071-1050/11/13/3731},
	author = {Bencure, Jannet C. and Tripathi, Nitin K. and Miyazaki, Hiroyuki and Ninsawat, Sarawut and Kim, Sohee Minsun}
}
@proceedings {118,
	title = {Impact of Rainfall on Urban Traffic Flow based on Probe Vehicle Data in Bangkok},
	year = {2019},
	month = {12/2019},
	address = {Chiang Mai, Thailand},
	abstract = {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{\textquoteright}s  GDP.  Future  rainfall  forecast  data  makes  it  possible  to  assess  the  risk  of  climate  change on urban traffic flow.},
	keywords = {Climate  change, Probe  vehicle  data, Rainfall  impact, Regression model, Travel speed},
	url = {https://saki.siit.tu.ac.th/stud2019/uploads_final/111__18076cee1637baa6dafa754962eb2939/FinalFile_stud19_takano_v7_en.pdf},
	author = {Tsuyoshi Takano and Hiroyoshi Morita and Shinichiro Nakamura and Hiroyuki Miyazaki and Wasan Pattara-atikom and Napaporn Piamsa-nga}
}
@article {93,
	title = {The 2015 Nepal Earthquake Disaster: Is the Threat of Occurrence of Communicable Disease Epidemic Over?},
	journal = {International Journal of Indonesian National Nurses Association (IJINNA)},
	volume = {1},
	year = {2018},
	pages = {105-110},
	type = {Journal Article},
	issn = {2614-4794},
	url = {http://ijinna-ppni.org/ijinna2/index.php/IJINNA/article/view/32},
	author = {Kanbara, Sakiko and Ngatu, Nlandu Roger and Pokhrel, Tara and Pandey, Apsara and Sharma, Chandrakara and Lee, Hyeon J and Miyagawa, Shoko and Miyazaki, Hiroyuki and Nojima, Sayumi}
}
@article {96,
	title = {A Taxi Zoning Analysis Using Large-Scale Probe Data: A Case Study for Metropolitan Bangkok},
	journal = {The Review of Socionetwork Strategies},
	volume = {12},
	year = {2018},
	pages = {21-45},
	type = {Journal Article},
	issn = {1867-3236},
	doi = {10.1007/s12626-018-0019-4},
	url = {https://doi.org/10.1007/s12626-018-0019-4},
	author = {Peungnumsai, Apantri and Witayangkurn, Apichon and Nagai, Masahiko and Miyazaki, Hiroyuki}
}
@proceedings {90,
	title = {An Automated Method for Time-Series Human Settlement Mapping using Landsat Data and Existing Land Cover Maps},
	year = {2016},
	author = {Miyazaki, H. and Nagai, M. and Shibasaki, R.}
}
@proceedings {91,
	title = {Development of Time-Series Human Settlement Mapping System using Historical Landsat Archive},
	year = {2016},
	pages = {1385-1388},
	author = {Miyazaki, Hiroyuki and Nagai, Masahiko and Shibasaki, Ryosuke}
}
@article {61,
	title = {Reviews of Geospatial Information Technology and Collaborative Data Delivery for Disaster Risk Management},
	journal = {ISPRS International Journal of Geo-Information},
	volume = {4},
	year = {2015},
	month = {2015},
	pages = {1936},
	isbn = {2220-9964},
	url = {http://www.mdpi.com/2220-9964/4/4/1936},
	author = {Miyazaki, Hiroyuki and Nagai, Masahiko and Shibasaki, Ryosuke}
}
@booklet {66,
	title = {Crowdsourcing for urban area mapping},
	howpublished = {Asia Geospatial Digest},
	year = {2013},
	month = {2013},
	url = {http://geospatialworld.net/Paper/Application/ArticleView.aspx?aid=30462},
	author = {Kimijima, Satomi and Nagai, Masahiko and Miyazaki, Hiroyuki and Shibasaki, Ryosuke and Iwao, Koki}
}
@proceedings {78,
	title = {Crowd-Sourcing GIS for Global Urban Area Mapping},
	year = {2012},
	month = {2012},
	pages = {A4-2},
	address = {Pattaya, Thailand},
	abstract = {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 {\texttimes} 80 km, 20 km {\texttimes} 20 km, and 10 km {\texttimes} 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.},
	keywords = {ASTER, crowd sourcing, urban area mapping, Web-GIS},
	author = {Miyazaki, Hiroyuki and Kimijima, Satomi and Nagai, Masahiko and Iwao, Koki and Shibasaki, Ryosuke}
}
@proceedings {84,
	title = {A Method for Constructing Urban Extent Map from ALOS/PALSAR Satellite Data},
	year = {2011},
	month = {2011},
	pages = {TS9-1},
	address = {Taipei},
	abstract = {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.},
	keywords = {ALOS/PALSAR, classification, microwave sensor, urban extent map},
	url = {http://a-a-r-s.org/acrs/index.php/acrs/acrs-overview/proceedings-1?view=publication\&task=show\&id=1005},
	author = {Itabashi, Koichiro and Miyazaki, Hiroyuki and Iwao, Koki and Nakamura, Kazuki and MATSUOKA, Masashi and Shibasaki, Ryosuke}
}
@proceedings {37,
	title = {A method for detecting and mapping Urban Area by ALOS/PALSAR data},
	year = {2010},
	month = {2010},
	address = {Hanoi, Vietnam},
	abstract = {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.},
	keywords = {ALOS PALSAR urban extent map high resolution},
	author = {Itabashi, Koichiro and Miyazaki, Hiroyuki and Iwao, Koki and Nakamura, Kazuki and Shibasaki, Ryosuke}
}
