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Understanding the dynamics of vegetative greenness and how it interacts with various hydroclimatic factors is crucial for comprehending the implications of global climate change. The present study utilized the MODIS-derived normalized difference vegetation index (NDVI) to understand the vegetation patterns over 21 years (2001–2021) in Rajasthan, India. The rainfall, land surface temperature (LST), and evapotranspiration (ET) were also analyzed. The changes, at a 30 m pixel resolution, were evaluated using Mann–Kendall's trend test. The results reveal that the NDVI, ET, and rainfall had increasing trends, whereas the LST had a decreasing trend in Rajasthan. The NDVI increased for 96.5% of the total pixels, while it decreased for 3.4% of the pixels, of theh indicates vegetation improvement rather than degradation. The findings of this study provide direct proof of a significant reduction in degraded lands throughout Rajasthan, particularly in the vicinity of the Indira Gandhi Canal command area. Concurrently, there has been a noticeable expansion in the cultivated land area. The trend of vegetation decline, particularly in the metro cities, has occurred as a result of urbanization and industrialization. In contrast to the LST, which has a decreasing gradient from the western to eastern portions, the spatial variability in the NDVI, ET, and rainfall have decreasing gradients from the southern and eastern to western regions. The results of correlations between the vegetative indices and hydroclimatic variables indicate that the NDVI has a strong positive correlation with ET (r2 = 0.86), and a negative correlation with LST (r2 = −0.55). This research provides scientific insights into vegetation change across Rajasthan, and may help the state to monitor vegetation changes, conserve ecosystems, and implement sustainable ecosystem management. [ABSTRACT FROM AUTHOR]

Wind erosion is a major natural disaster worldwide, and it is a key problem in western Rajasthan in India. The Analytical Hierarchy Process (AHP), the Geographic Information System (GIS), and remote sensing satellite images are effective tools for modeling and risk assessment of land degradation. The present study aimed to assess and model the land degradation vulnerable (LDV) zones based on the AHP and geospatial techniques in the Luni River basin in Rajasthan, India. This study was carried out by examining important thematic layers, such as vegetation parameters (normalized difference vegetation index and land use/land cover), a terrain parameter (slope), climatic parameters (mean annual rainfall and land surface temperature), and soil parameters (soil organic carbon, soil erosion, soil texture, and soil depth), using the Analytical Hierarchical Process (AHP) and geospatial techniques in the Luni River basin in Rajasthan, India. The weights derived for the thematic layers using AHP were as follows: NDVI (0.27) > MAR (0.22) > LST (0.15) > soil erosion (0.12) > slope (0.08) > LULC (0.06) > SOC (0.04) > soil texture (0.03) > soil depth (0.02). The result indicates that nearly 21.4 % of the total area is prone to very high degradation risks; 12.3% is prone to high risks; and 16%, 24.3%, and 26% are prone to moderate, low, and very low risks, respectively. The validation of LDV was carried out using high-resolution Google Earth images and field photographs. Additionally, the Receiver Operating Characteristic (ROC) curve found an area under the curve (AUC) value of 82%, approving the prediction accuracy of the AHP technique in the study area. This study contributes by providing a better understanding of land degradation neutrality and sustainable soil and water management practices in the river basin. [ABSTRACT FROM AUTHOR]