Remote sensing assessment of climate change impacts on staple crops and agricultural resilience in Thailand

Comprehending the impacts of climatic variability on agricultural resilience is essential for developing sustainable adaptation strategies in tropical monsoon regions. Thailand, where agriculture depends predominantly on rain-fed systems, remains highly vulnerable to both seasonal droughts and increasingly intense heavy rainfall events. This study evaluates the spatiotemporal dynamics of vegetation stress and extreme precipitation by integrating multi-temporal remote sensing datasets with climatic information within a geographic information system (GIS) framework. The Vegetation Health Index (VHI) was computed exclusively for agricultural areas identified from the Copernicus Land Cover map using MODIS Terra NDVI (MOD13Q1; 16-day, 250 m) and Land Surface Temperature (LST) (MOD11A2; 8-day, 1 km) based on Kogan’s method for the period 2000 2024, while extreme rainfall was assessed using the R95pTOT index derived from CHIRPS daily precipitation data spanning 1981–2024. Analyses were conducted across three meteorological seasons—hot (March–May), rainy (June October), and cool (November–February). Non-parametric Mann–Kendall trend tests, Sen’s slope estimation, and spatial anomaly detection were applied to identify long-term trends and vegetation responses to extreme rainfall variability. Results demonstrate a statistically significant increase in extreme rainfall (Sen’s slope = +4.12 mm yr⁻¹, p = 0.0312), particularly across coastal and mountainous areas in southern Thailand, indicating an escalating hazard from heavy precipitation. In contrast, the vegetation responses exhibited strong seasonal contrasts: VHI increased during the rainy and cool seasons due to enhanced moisture availability and favorable temperatures, but declined markedly during the hot season, especially across the Central and Northeastern regions where heat stress and soil moisture deficits were most severe. More than half of Thailand’s agricultural land showed positive VHI anomalies in the rainy and cool seasons, while persistent declines during the hot period highlight continuing vulnerability to early-season drought even as extreme rainfall intensifies in other regions. Collectively, these findings reveal Thailand’s dual climate-risk profile— seasonal drought stress and escalating extreme precipitation—and demonstrate that integrating MODIS-based vegetation indices with CHIRPS rainfall data provides an effective framework for climate monitoring and spatially informed planning for climate-resilient agriculture under rapidly changing environmental conditions.