Tracing Vegetation Resilience and Recovery Pathways to Drought Through Time Series Decomposition

India's vegetation dynamics are highly sensitive to water stress, with meteorological droughts posing significant risks to ecosystems and agriculture. Understanding the interaction between drought and vegetation health remains a critical challenge. Existing methods for analysing vegetation trends often fail to accurately capture abrupt changes in vegetation health and their relation with drought periods, limiting our understanding of how vegetation responds to water stress. This study introduces an integrated approach that combines the Breaks For Additive Season and Trend (BFAST) methodology with drought metrics to examine vegetation responses across various land cover types in India. Compared to other conventional methods for detecting trends and breakpoints in a time series, BFAST does not assume a rigid trend or seasonal trajectory. This flexibility allows it to identify abrupt breaks in vegetation health, which are often overlooked in traditional analyses. The identified breaks, trends, and seasonal patterns are then examined to determine the timing, magnitude, and frequency of changes in NDVI, correlating them with drought responses identified using the Standard Precipitation Index (SPI). Findings indicate that arid and semi‐arid regions in India experience the highest overlap between drought occurrences and negative NDVI transition points, periods where vegetation health shows a significant decline; therefore, highlighting a heightened vulnerability to water stress. Conversely, agriculturally intensive regions like the Indo‐Gangetic Plain demonstrate greater resilience. Seasonal analysis suggests that vegetation health is closely tied to monsoon variability, with most breaks occurring during peak monsoon months. Additionally, analysis of the post‐drought period revealed that the vegetation response is highly sensitive to precipitation deficits during the recovery period following a drought.