Japan Geoscience Union Meeting 2023

Presentation information

[E] Oral

H (Human Geosciences ) » H-TT Technology & Techniques

[H-TT14] Geographic Information Systems and Cartography

Wed. May 24, 2023 1:45 PM - 3:00 PM 201A (International Conference Hall, Makuhari Messe)

convener:Takashi Oguchi(Center for Spatial Information Science, The University of Tokyo), Yoshiki Wakabayashi(Graduate School of Urban Environmental Sciences, Tokyo Metropolitan University), Yuei-An Liou(National Central University), Ruci Wang(Center for Environmrntal Remote Sensing, Chiba University), Chairperson:Yoshiki Wakabayashi(Graduate School of Urban Environmental Sciences, Tokyo Metropolitan University), Yuei-An Liou(National Central University)


1:45 PM - 2:00 PM

[HTT14-06] The spatial relationship between building composition and land surface temperature: A case study in the central Tokyo area Japan

*Ruci Wang1,2, Yuji Murayama2, Takehiro Morimoto2 (1.Center for Environmrntal Remote Sensing, Chiba University, 2.Faculty of Life and Environmental Science, University of Tsukuba)

Keywords:Building composition, Urban heat island, Land surface temperature, Land use/cover change, Tokyo

In recent decades, rapid urban development has raised concerns about land use/cover (LULC) change as it affects climate change, the living environment, and sustainable development. In conjunction with this, the construction or renovation plan also altered the composition of the buildings, particularly in metropolitan areas. Urban planners try to reduce the urban heat island (UHI) effect through effective policy and city planning. But it is currently difficult to understand how building composition affects land surface temperature (LST) due to the limitation in the data resolution. In order to evaluate the effects of building composition on LST and to investigate probable anthropogenic reasons for driving these effects, this study chooses the central Tokyo area as a study area. We used ArcGIS software to conduct spatial analysis using remote sensing and Zenrin data. The relationship between LST, land use/cover, building volume, building function, and other variables (e.g., distance to the road) was examined for each building function using regression analysis. Our findings indicate that residential and business buildings have increased the LST the most compared with the other two building functions. Discussing the building compositions in the central Tokyo area can also help other countries explore the proper developing way.