Decadal High-Resolution Monitoring of Climate-Driven Phenological Shifts Across Diverse Vegetation Zones of the Great Himalayan National Park Conservation Area
DOI:
https://doi.org/10.58825/jog.2026.20.2.283Keywords:
Climate change, Google earth engine, Land Surface Phenology, Sentinel 2Abstract
Vegetation phenology is a sensitive indicator of climate change, particularly in mountainous ecosystems where elevation-driven climatic gradients strongly influence growing season dynamics. This study examined the spatial and inter-annual variability of the Start of Season (SoS), End of Season (EoS), and Length of Season (LoS) across distinct vegetation zones of the Great Himalayan National Park Conservation Area (GHNPCA) from 2015 to 2025. To achieve a decadal timeline, an integrated multi-sensor Enhanced Vegetation Index (EVI) time series was developed on Google Earth Engine, utilizing Landsat 8 (2015–2017) and Sentinel-2 (2018–2025) surface reflectance data. Minimum temperature (Tmin) and precipitation data from ERA5-Land and CHIRPS were topographically downscaled to 30 m using orographic gradients and analyzed to quantify climatic controls. Results showed pronounced altitudinal gradients, with earlier SoS, later EoS, and longer LoS in low-elevation forests, and short, thermally constrained seasons in alpine zones. Pre-season Tmin increases strongly advanced SoS, while precipitation effects were spatially heterogeneous and topographically mediated. These findings highlight the need for elevation and plant functional type specific monitoring to improve phenological projections mitigate the risks of trophic mismatches and guide climate adaptation strategies in the Himalaya.
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