Spatio-Temporal Analysis of Vegetation Health and Soil Characteristics across Rajasthan using NDVI Anomalies

This study presents a comprehensive spatio-temporal analysis of vegetation health and soil patterns across Rajasthan, India, using NDVI (Normalized Difference Vegetation Index) anomalies derived from MODIS satellite data for the period 2020– 2025. The research leverages Google Earth Engine (GEE) to process and visualize NDVI trends, generate anomaly maps, and correlate vegetation dynamics with soil properties and rainfall variability. District-level time series charts highlight spatial differences in vegetation re- sponse, while Sentinel-2 imagery validates regional patterns with finer detail. A GEE-based dashboard facilitates interactive exploration of NDVI anomalies, vegetation-soil relationships, and seasonal variation across all 33 districts. The results reveal persistent vegetation stress in arid western districts and stronger recovery in eastern regions with clay-rich soils and higher rainfall. The integration of soil classification, land use, and climatic datasets supports improved understanding of ecological vulnerability in dryland systems. The study proposes scalable methods for environmental monitoring, with potential applications in drought assessment, land-use planning, and agricultural decision-making in arid and semi-arid regions.