Please use this identifier to cite or link to this item: http://cmuir.cmu.ac.th/jspui/handle/6653943832/77615
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dc.contributor.authorMasanobu Kiien_US
dc.contributor.authorNopadon Kronpraserten_US
dc.contributor.authorBoonsong Satayopasen_US
dc.date.accessioned2022-10-16T08:03:45Z-
dc.date.available2022-10-16T08:03:45Z-
dc.date.issued2020-01-01en_US
dc.identifier.issn21862982en_US
dc.identifier.other2-s2.0-85116475474en_US
dc.identifier.other10.21660/2020.69.9304en_US
dc.identifier.urihttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85116475474&origin=inwarden_US
dc.identifier.urihttp://cmuir.cmu.ac.th/jspui/handle/6653943832/77615-
dc.description.abstractTransport demand is one of the essential datasets for urban / transport planning and policy development. However, the full size of travel demand survey requires large amount of cost, therefore the survey is merely conducted in developing countries. Their policy decision might be based on the old and limited datasets. In this study we propose a new approach to estimate transport demand using the night-time light satellite image based on the correlation of these two factors. Taking the case of Chiang Mai Metropolitan area, we found a soft relationship between the night-time light intensity and trip generation/trip attraction. Transport survey data is provided by Chiang Mai University for the year 2016. NOAA provides cloud free monthly composite of night-time light satellite image (VIIRS-DNB) by Suomi-NPP satellite of which resolution is 15 arc-second (about 500m by 500m at equator). It is spatially more precise than zones of travel demand survey and monthly frequency. Applying the relationship between transport demand and night-time light intensity, we propose a method to update the transport demand with higher spatial resolution.en_US
dc.subjectAgricultural and Biological Sciencesen_US
dc.subjectEarth and Planetary Sciencesen_US
dc.subjectEngineeringen_US
dc.subjectEnvironmental Scienceen_US
dc.titleESTIMATION OF TRANSPORT DEMAND USING SATELLITE IMAGE: CASE STUDY OF CHIANG MAI, THAILANDen_US
dc.typeJournalen_US
article.title.sourcetitleInternational Journal of GEOMATEen_US
article.volume18en_US
article.stream.affiliationsKagawa Universityen_US
article.stream.affiliationsChiang Mai Universityen_US
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