Assessing correlation between Rainfall, normalized difference Vegetation Index (NDVI) and land surface temperature (LST) in Eastern India

Establishing an understanding on correlation between Rainfall, Normalized Difference Vegetation Index (NDVI) and Land Surface Temperature (LST) is vital to plan afforestation interventions in a region. The present study aims to assess the correlation between the rainfall, NDVI and LST in West Bengal, eastern India, for the period 2011 to 2020. We used Moderate Resolution Imaging Spectroradiometer (MODIS) products for deriving the LST and NDVI using Google Earth Engine (GEE). We determined the mean rainfall value of the study area using rainfall data for the period 2011–2020, acquired from the Centre of Hydrometeorology and Remote Sensing (CHRS). We used a polynomial regression (PR) model for assessing the relationship between rainfall, NDVI and LST. The result showed highest mean rainfall (~ 34.31 mm) occurred in 2017 and lowest mean rainfall (~ 0.01 mm) occurred in 2011. The outcome shows that the highest mean NDVI value was found in 2019 (~ 0.65) and lowest NDVI value in 2011 (~ 0.53). Further, the highest mean LST occurred in 2020 (~ 29.65ºC) and lowest LST value in 2012 (~ 26.96ºC). The PR model showed rainfall directly proportional to NDVI, and inversely proportional to LST with R 2 value ~ 0.736 and ~ 0.704 respectively. The study also demonstrated inverse correlation between NDVI and LST and with R 2 value ~ 0.864. Outcome of the study indicates rainfall is the most significant factor in the distribution of vegetation in West Bengal. The study enables prioritisation of areas for afforestation interventions in West Bengal. We recommend introduction and promotion of native flora characterised by the higher LST.