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	title = {Impacts of disaster and land-use change on food security and adaptation: Evidence from the delta community in Bangladesh},
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	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}
}
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	title = {A Taxi Zoning Analysis Using Large-Scale Probe Data: A Case Study for Metropolitan Bangkok},
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	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 {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},
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	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}
}
