10. Assessment of Land Surface Phenology and Its Response to Climate Change in the Tawa River Basin, India

This study analyzes the vegetation phenology using time-ordered data remote sensing data such as MODIS data 250 m, and 16-day Synthesis NDVI data from 2002 to 2021 to understand seasonal and interannual variations. Key phenological parameter start and end of the developing season, season length, baseline, and amplitude were extracted using TIMESAT software. An adaptive Savitzky-Golay smoothing technique was employed to the NDVI time-ordered data to improve the clarity and accuracy of seasonal pattern detection. Over 19 growing seasons, the longest season occurred in 2010, indicating significant variability. The Identifying Shifts in Additive Seasonal and Trend Patterns was also employed to identify structural changes and Transitions in Perpetual vegetation trends. The combined use of TIMESAT and BFAST enabled a comprehensive assessment of both seasonal dynamics and long-term vegetation changes. These insights support ecological monitoring, informing land use, management, and conservation strategies by providing a robust framework for tracking phenological responses to environmental changes across landscapes.