Abstract
<title>Abstract</title> <p>Geospatial technologies and analytical methods provide valuable tools for assessing land productivity and identifying environmental factors determining agricultural performance. Therefore, this study develops an integrated different environmental factors to assess land productivity by linking vegetation dynamics with climatic variability and soil properties in Dewgain, India. Multi-temporal Normalized Difference Vegetation Index (NDVI) derived from Sentinel-2 imagery was integrated with climatic data from the India Meteorological Department (IMD) and soil datasets from Soilgirds. Trend analysis, climate indices, and statistical modelling were applied to assess climate variability and its implications for agricultural productivity. Annual NDVI showed a moderate linear fit (R² = 0.534) but a non-significant declining trend (Mann–Kendall τ = −0.500, p = 0.108; Sen’s slope = − 0.0192 NDVI units’ year⁻¹), indicating partial vegetation coverage, while April–June exhibited negligible change (R² = 0.032) and January–March showed high variability (CV = 42.40%). Climatic analysis revealed notable variability in rainfall (19.25%) and minimum temperature (2.87%), with major drought events identified in 1983, 1989, and 2010. Correlation analysis revealed moderate positive associations between NDVI and soil organic carbon (ρ = 0.441, p < 0.001) and total nitrogen (ρ = 0.399, p < 0.001) while soil moisture showed a relatively strong but non-significant positive association (r = 0.683, p < 0.062). Among climate variables, rainfall showed a strong positive association with NDVI (r = 0.782, p < 0.05) whereas temperature and relative humidity showed non-significant associations. Spatial zonation reveals that low-productivity areas (NDVI < 0.2) dominate (47.18%), followed by moderate (38.14%) and high-productivity zones (14.67%). The findings identified spatial patterns of land productivity, key climatic and soil associated with NDVI, and priority zones for sustainable land management.</p>