APPLICATION OF GOOGLE EARTH ENGINE FOR AGRICULTURAL DROUGHT A NALYSIS USING NDVI, LST AND VTCI INDICES IN THE DONG NAI RIVER BASIN

Abstract

Drought is an extreme climatic phenomenon that exerts significant impacts on agricultural production and water-resource management strategies within the Dong Nai river basin. This study employs Landsat 8 Collection 2 Level-1 (TOA) imagery in combination with the Google Earth Engine (GEE) platform to develop an agricultural drought-zoning map for areas located outside the service range of irrigation infrastructure, using three key indicators: NDVI, LST and VTCI. Landsat 8 dry-season imagery (2014 - 2024) was processed to derive NDVI from top-of-atmosphere (TOA) reflectance and LST from Thermal Band 10 through brightness-temperature conversion and emissivity correction. Based on these NDVI and LST datasets, the VTCI index was computed to quantify drought severity and classify drought into four levels. The results show that VTCI exhibits a strong and consistent correlation with the reference drought indicators SPEI and VHI. Moreover, the drought-zoning maps generated from satellite imagery demonstrate a high degree of agreement with field observations collected at 116 survey sites across the basin. The use of GEE enables rapid processing of large-scale Landsat data, ensures temporal consistency and significantly improves monitoring efficiency. These findings confirm that GEE is a powerful tool for water-resource management and for developing sustainable drought-adaptation strategies.