PreprintArticleVersion 1Preserved in Portico This version is not peer-reviewed
Spatial-Multitemporal Analysis of Heatwaves in Thailand: Discrepancies between In-Situ Air Temperature and Remote Sensing-Derived Land Surface Temperature
Version 1
: Received: 22 February 2024 / Approved: 22 February 2024 / Online: 23 February 2024 (08:40:08 CET)
How to cite:
Chongtaku, T.; Taparugssanagorn, A.; Miyazaki, H.; Tsusaka, T.W. Spatial-Multitemporal Analysis of Heatwaves in Thailand: Discrepancies between In-Situ Air Temperature and Remote Sensing-Derived Land Surface Temperature. Preprints2024, 2024021324. https://doi.org/10.20944/preprints202402.1324.v1
Chongtaku, T.; Taparugssanagorn, A.; Miyazaki, H.; Tsusaka, T.W. Spatial-Multitemporal Analysis of Heatwaves in Thailand: Discrepancies between In-Situ Air Temperature and Remote Sensing-Derived Land Surface Temperature. Preprints 2024, 2024021324. https://doi.org/10.20944/preprints202402.1324.v1
Chongtaku, T.; Taparugssanagorn, A.; Miyazaki, H.; Tsusaka, T.W. Spatial-Multitemporal Analysis of Heatwaves in Thailand: Discrepancies between In-Situ Air Temperature and Remote Sensing-Derived Land Surface Temperature. Preprints2024, 2024021324. https://doi.org/10.20944/preprints202402.1324.v1
APA Style
Chongtaku, T., Taparugssanagorn, A., Miyazaki, H., & Tsusaka, T.W. (2024). Spatial-Multitemporal Analysis of Heatwaves in Thailand: Discrepancies between In-Situ Air Temperature and Remote Sensing-Derived Land Surface Temperature. Preprints. https://doi.org/10.20944/preprints202402.1324.v1
Chicago/Turabian Style
Chongtaku, T., Hiroyuki Miyazaki and Takuji W Tsusaka. 2024 "Spatial-Multitemporal Analysis of Heatwaves in Thailand: Discrepancies between In-Situ Air Temperature and Remote Sensing-Derived Land Surface Temperature" Preprints. https://doi.org/10.20944/preprints202402.1324.v1
Abstract
In light of the critical and emerging global challenge posed by the increasing frequency and severity of heatwaves in recent decades, this study demonstrates a practical and robust workflow that bridges the gap in understanding how the effective integration of remote sensing data with ground-based observations can facilitate a comprehensive assessment of spatiotemporal heatwave patterns and trends in the central region of Thailand. This research transcends traditional methods, utilizing air temperature (Tair) and satellite-derived land surface temperature (LST) data from 1981 to 2019. Results exhibit that an analysis of Tair indicates increasing daytime heatwaves in peri-urban areas, with significant trends in heatwave number (HWN), heatwave frequency (HWF), and heatwave duration (HWD), heatwave amplitude (HWA) rises in urban settings while nighttime heatwaves significantly intensify in rural locales. Notably, LST trends reveal varied patterns, with peri-urban areas showing marked daytime increases in heatwave magnitude (HWM), HWA, and HWF. Correlation analysis (p=0.05) highlights strong daytime associations between Tair and LST in rural (HWN, HWF, HWD, r>0.90) and peri-urban (HWM, HWA, r>0.65) regions. Overall, this study advances approaches to the adaptable measurement and spatial-temporal pattern of heatwave-related risk areas, providing insights for decision-makers to develop sustainable practices and strategies for climate change adaptation.
Keywords
heat wave; heatwaves detection; land surface heatwaves; data gap-filling; machine learning algorithm; random forest regression; spatio-temporal databases; geospatial analysis; air temperature; land surface temperature
Subject
Environmental and Earth Sciences, Remote Sensing
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
