Spatiotemporal Variations of Land Surface Temperatures in Eastern South Asia

Abstract

Understanding the fluctuations in land surface temperature (LST) is essential for precisely forecasting climatic patterns and implementing effective measures. This study aimed to investigate the spatiotemporal patterns and trends of LST in Eastern South Asia from 2000 to 2024 using MODIS data. Cubic spline was used to assess seasonal patterns and auto-regressive model was used to assess the trend of LST. The average increase of LST was determined by the multivariate regression model. Daytime LST showed a general decreasing trend across most regions, while nighttime LST exhibited a consistent warming trend, with notable regional variations. The Lower North region experienced the most pronounced nighttime warming, while the Far East and Lower Central West regions showed higher increases in nighttime LST. The forecasting model indicated persistence of these trends, with daytime LST expected to continue cooling and nighttime LST forecast to steadily increase. The difference has significant implications for ecology, agriculture, human health, and urban development. In order to mitigate climate change and support evidence-based policymaking in South Asia, this study highlights the necessity for developing policies along with conducting further studies on LST trends.