EventsOHOW 2022 – The 1st International Symposium on One Health, One World
Published
with-doi10.3390/ohow2022-13589 (registering DOI)
This submission belongs to the session S2. Climate Change and Green Recovery of the event OHOW 2022 – The 1st International Symposium on One Health, One World
Published date
16 Nov, 2022
Academic Editor
author-avatarWataru Takeuchi
Citation
Thitimar Chongtaku, Salvatore G.P. Virdis, Sangam Shrestha, Thi Phuoc Lai Nguyen, Hiroyuki Miyazaki, DETECTING SPATIOTEMPORAL HEATWAVE IN URBAN, PERI-URBAN, AND RURAL AREAS OF THAILAND USING SATELLITE-BASED THERMAL ANOMALIES, in Proceedings of OHOW 2022 – The 1st International Symposium on One Health, One World, Amari Pattaya Hotel, 8 December–10 December 2022, MDPI: Basel, Switzerland, doi: 10.3390/ohow2022-13589
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DETECTING SPATIOTEMPORAL HEATWAVE IN URBAN, PERI-URBAN, AND RURAL AREAS OF THAILAND USING SATELLITE-BASED THERMAL ANOMALIES

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1. Remote Sensing and GIS, School of Engineering and Technology, Asian Institute of Technology, Pathum Thani, Thailand
2. Water Engineering and Management, School of Engineering and Technology, Asian Institute of Technology, Thailand
3. Environment and Sustainable Development, School of Environment, Resources and Development, Asian Institute of Technology, Thailand
4. Center for Spatial Information Science, University of Tokyo, Japan
Abstract

Heatwaves cause mortality and morbidity worldwide. Critically, it contributes to various detrimental impacts on sustainable development, human safety, and the environment, but policymakers and the public pay little attention. During the heatwave period from 2015 to 2018, El Nio Southern Oscillation (ENSO) generated dry and warm temperatures in Thailand, leading to 158 deaths during the heatwave period. This study examines spatial and temporal heatwave variability (number, duration, frequency, magnitude, and amplitude). We also analyze the heatwave in urban, peri-urban, and rural Thailand. The result revealed that land surface temperature (LST) as a proxy for air temperature in heatwave assessment with a high correlation at r = 0.62 (HWN) and 0.71 (HWF) and a moderate relationship r = 0.48 (HWD), 0.39 (HWM), and 0.40 (HWA), respectively. It has been associated with heatwave occurrences far from the methodological station, especially duration and frequency. Northern Bangkok and Pathum Thani have the highest daytime and overnight heatwave intensities. Ultimately, our findings help decision-makers, and the public comprehends descriptive spatiotemporal heatwave trends, helping them to cope with extreme weather situations and contributing to future heatwave forecasts over Thailand's provinces.

Keywords
Heatwaves
Climate Extremes
Air Temperature
Land Surface Temperature
MODIS
Thailand
Application of a latest-model ground water flow meter