Remote Sensing-Based Evaluation of Vegetation Condition and Drought-Related Spatial Dynamics in Bursa Province, Türkiye

Abstract

This study assessed vegetation condition and drought dynamics in Bursa Province, northwestern Türkiye, using Sentinel-2-derived annual NDVI and VCI products for 2017-2025. Sentinel-2 Surface Reflectance Harmonized imagery was processed in Google Earth Engine, where cloud-contaminated pixels were masked and annual median NDVI composites were generated. VCI was calculated from pixel-based long-term NDVI minimum and maximum values, and annual NDVI and VCI maps were produced for spatial analysis. In addition, annual mean NDVI and VCI values and drought-class area percentages were derived from raster outputs. The results revealed clear interannual variability in vegetation conditions across Bursa. Annual mean NDVI ranged from 0.52 in 2017 to 0.55 in 2021, while annual mean VCI varied between 61.06 and 63.74. The maps also showed that vegetation stress was spatially heterogeneous across the province. Overall, drought and vegetation stress in Bursa did not follow a monotonic trend but fluctuated between relatively favorable and unfavorable years. These findings demonstrate that Sentinel-2-based NDVI and VCI products provide an effective framework for monitoring provincial-scale vegetation variability and drought conditions and can support irrigation planning and water-resources management.