Authors: Sangwoo Sung*, East Carolina University, Bumseok Chun, Texas Southern University, Jiwan Pun Thapa, Texas Southern University, Sugie Lee, Hanyang University
Topics: Remote Sensing, Land Use and Land Cover Change, Urban and Regional Planning
Keywords: Land surface temperature, Air temperature Big Data, Urban thermal environment
Session Type: Paper
Start / End Time: 9:55 AM / 11:35 AM
Room: Taylor, Marriott, Mezzanine Level
Presentation File: No File Uploaded
Accurate microclimate temperature information is a pivotal parameter to explore urban determinants of the urban thermal environment (UTE) associated with extreme heat events and the urban heat island (UHI) effect (Oke, 1981). Many UTE studies use the land surface temperature (LST) retrieved from satellite imagery because of a wide geographic and temporal coverage availability. However, its applicability to the UHI or the extream heat event studies is limited by a coarse spatial resolution, relatively infrequent temporal resolution and poorer accuracy compared to air temperate (AT) data from local automated weather stations (AWS). This study discusses the usefulness of AWS AT big data to analyze the impact of urbanization on diurnal and nocturnal UTE changes in the Seoul Metropolitan Area (SMA). We collect and compare the Moderate Resolution Imaging Spectroradiometer (MODIS) data and in-situ climate data, AWS AT big data readings above the ground from 1294 weather stations in SMA during an early summer day. To identify the impact factors on temperature changes, we perform advanced statistical analysis including land use/land cover, physical and built environment, and anthropogenic factors. We anticipate our finding would provide not only reliable conversion factor between LST and AT, but also effective UHI mitigation strategies in SMA.