Abstract
Abstract The variation in the vegetation pattern reflects the change in the regional environment. Normalized Difference Vegetation Index (NDVI) data from 2000 to 2022 for the Upper Bhima sub-basin in Western India has been used to identify the response of vegetation to the El Niño-Southern Oscillations (ENSO) and Indian Ocean Dipole (IOD) events. As a novelty, the present study identifies the ENSO-sensitive and IOD-sensitive vegetation areas within the watershed using vegetation mean to difference anomalies. Monthly NDVI anomalies are used to determine sensitive pixels of vegetation using mean monthly NDVI. Local spatial autocorrelation (LISA) is performed to analyze the pattern of the NDVI anomalies and cluster maps are generated. The results of spatial variation show that NDVI is adversely affected in El Niño years. During La Niña years, the percentage area covered by dense vegetation is more than 80%, which is significantly higher than that of El Niño years in the monsoon and post-monsoon periods. Positive IOD years show significantly more sparse vegetation cover than negative IOD years. The results of LISA analysis show that the rainfall shadow zone in the study area has a cluster of negative sensitive pixels even in the monsoon and post-monsoon period except in negative IOD year.
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