17:15 〜 19:15
[ACG44-P04] Spatiotemporal variability of land surface temperature in Southeast Asia’s Megacities using geostationary satellites, Himawari-8/9
Soma Yamasaki, Yuhei Yamamoto, Kazuhito Ichii
Rapid urbanization is occurring in the megacities of Southeast Asia, leading to population growth, slum development, and increased energy consumption, which contribute to severe urban heat environmental conditions. Satellite observations are generally recognized as an effective method for monitoring urban thermal environments by retrieving land surface temperature (LST) under clear-sky conditions. However, in Southeast Asia, frequent cloud cover hinders land surface observations. Conventional polar-orbiting satellites have observation intervals longer than one day, making it difficult to capture urban thermal environments on timescale shorter than seasonal variations. On the other hand, Japan’s geostationary satellites, Himawari-8/9, can retrieve LST at a 10-min interval. This study aims to clarify the spatiotemporal variability of LST on diurnal, seasonal, and interannual timescales in megacities of Southeast Asia’s by leveraging the high temporal resolution of Himawari-8/9.
This study focuses on four megacities with populations exceeding 10 million: Bangkok, Ho Chi Minh City, Manila, and Jakarta. The target period was from January 1, 2016, to December 31, 2022. Daily maximum (Tmax) and minimum (Tmin) LST for each month were estimated using composite processing. The Tmax was estimated from LST within ±2 hours of solar noon, while Tmin was estimated from LST for two hours before sunrise. Local Climate Zones (LCZ) data were used to compare Tmax and Tmin characteristics across different land use types.
In Bangkok, Ho Chi Minh City, and Manila, Tmax and Tmin exhibited clear seasonal variations corresponding to dry and wet seasons. Jakarta, located near the equator, exhibited smaller seasonal variations throughout the year. All megacities showed similar relationships between LST and LCZ at both day and night. Suburban areas with compact low-rise tended to have higher Tmax, whereas urban cores with compact mid-rise and compact low-rise tended to have the highest Tmin.
Rapid urbanization is occurring in the megacities of Southeast Asia, leading to population growth, slum development, and increased energy consumption, which contribute to severe urban heat environmental conditions. Satellite observations are generally recognized as an effective method for monitoring urban thermal environments by retrieving land surface temperature (LST) under clear-sky conditions. However, in Southeast Asia, frequent cloud cover hinders land surface observations. Conventional polar-orbiting satellites have observation intervals longer than one day, making it difficult to capture urban thermal environments on timescale shorter than seasonal variations. On the other hand, Japan’s geostationary satellites, Himawari-8/9, can retrieve LST at a 10-min interval. This study aims to clarify the spatiotemporal variability of LST on diurnal, seasonal, and interannual timescales in megacities of Southeast Asia’s by leveraging the high temporal resolution of Himawari-8/9.
This study focuses on four megacities with populations exceeding 10 million: Bangkok, Ho Chi Minh City, Manila, and Jakarta. The target period was from January 1, 2016, to December 31, 2022. Daily maximum (Tmax) and minimum (Tmin) LST for each month were estimated using composite processing. The Tmax was estimated from LST within ±2 hours of solar noon, while Tmin was estimated from LST for two hours before sunrise. Local Climate Zones (LCZ) data were used to compare Tmax and Tmin characteristics across different land use types.
In Bangkok, Ho Chi Minh City, and Manila, Tmax and Tmin exhibited clear seasonal variations corresponding to dry and wet seasons. Jakarta, located near the equator, exhibited smaller seasonal variations throughout the year. All megacities showed similar relationships between LST and LCZ at both day and night. Suburban areas with compact low-rise tended to have higher Tmax, whereas urban cores with compact mid-rise and compact low-rise tended to have the highest Tmin.