@conference {142,
	title = {Spatial Equity and Healthcare Access in the COVID-19 Pandemic},
	booktitle = {Proceedings of the 6th International Conference on Medical and Health Informatics},
	year = {2022},
	publisher = {Association for Computing Machinery},
	organization = {Association for Computing Machinery},
	address = {New York, NY, USA},
	abstract = {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.},
	isbn = {9781450396301},
	doi = {10.1145/3545729.3545782},
	url = {https://doi.org/10.1145/3545729.3545782},
	author = {Sritart, Hiranya and Taertulakarn, Somchat and Kanbara, Sakiko and Miyazaki, Hiroyuki}
}
@article {130,
	title = {Disparities in Healthcare Services and Spatial Assessments of Mobile Health Clinics in the Border Regions of Thailand},
	journal = {International Journal of Environmental Research and Public Health},
	volume = {18},
	year = {2021},
	month = {Jan-10-2021},
	pages = {10782},
	doi = {10.3390/ijerph182010782},
	url = {https://www.mdpi.com/1660-4601/18/20/10782},
	author = {Sritart, Hiranya and Tuntiwong, Kuson and Miyazaki, Hiroyuki and Taertulakarn, Somchat}
}
@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 {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 {MIYAZAKIHiroyuki:2009-05-08,
	title = {A Method for Developing Urban Extent Map of High Accuracy and Resolution by Integrating ASTER/VNIR Images and Existing Urban Extent Maps},
	journal = {Journal of the Japan Society of Photogrammetry and Remote Sensing},
	volume = {48},
	number = {2},
	year = {2009},
	pages = {82{\textendash}96},
	publisher = {日本写真測量学会},
	issn = {02855844},
	url = {http://ci.nii.ac.jp/naid/10025572312/en/},
	author = {Miyazaki, Hiroyuki and Tanaka, Ayako and Iwao, Koki and Shibasaki, Ryosuke}
}
@proceedings {53,
	title = {Study on Automatic Global Urban Mapping Method using Satellite Imagery and the Existing Land Cover Data},
	year = {2008},
	month = {2008},
	pages = {S-4},
	address = {Yokohama, Japan},
	author = {Miyazaki, Hiroyuki and Tanaka, Ayako and Iwao, Koki and Shibasaki, Ryosuke}
}
