Abstract

not-yet-known not-yet-known not-yet-known unknown Vegetation serves as a critical indicator of environmental health, reflecting soil, water and air quality. Monitoring changes in vegetation distribution and extent is essential, especially in regions prone to climatic extremes. Traditional vegetation monitoring methods are labor-intensive, costly, and time-consuming. Remote sensing offers a powerful alternative, providing extensive spatial coverage and enabling efficient analysis. This study examines the impact of rainfall on vegetation growth in Latur, a drought-prone district in Maharashtra, India, utilizing Sentinel-2 satellite data and the Vegetation Condition Index (VCI) from 2017 to 2023. The 10-meter spatial resolution annual maps from ESRI, covering the years 2017 to 2023, were utilized to assess changes in land use and land cover (LULC). The LULC data were classified into seven classes: Water, Trees, Flooded Vegetation, Agricultural Land, Built Area, Bare Ground, and Rangeland. In 2017, Agricultural Land constituted 92% of the total area, decreasing to 90.28% by 2023, while the built-up area rose from 2.81% to 3.41%. Additionally, the annual mean VCI decreased from 36.28 in 2017 to 15.29 in 2023. The study assessed land use changes from 2017 to 2023, revealing a strong correlation between rainfall and vegetative growth. Spatial maps show significant seasonal variations in vegetation, emphasizing the need for continuous monitoring. This research highlights the effectiveness of Sentinel-2 data and Google Earth Engine for large-scale vegetation monitoring in drought-prone areas. Keywords: Vegetation dynamics, Sentinel-2, VCI, Google Earth Engine, rainfall impact, drought-prone regions.