Agricultural ecosystems in Northeastern Bangladesh are increasingly vulnerable to climate-induced stressors, particularly rising temperatures and seasonal droughts. This study aims to assess the spatiotemporal variations in vegetation health under climate stress in the Sylhet region over the last two decades using remote sensing techniques. The Normalized Difference Vegetation Index (NDVI) and Land Surface Temperature (LST) were derived from Landsat satellite imagery to evaluate trends in vegetation and surface thermal conditions. Seasonal NDVI and LST values were analyzed across major cropping seasons to understand the ecological response of agricultural land to climatic variability. The relationship between vegetation health and surface temperature was quantified using statistical comparison techniques to identify patterns and intensity of climate stress. Preliminary trends indicate that increased LST correlates with reduced vegetation cover in lowland agricultural zones, while elevated regions with forest or tree cover show inverse patterns. Spatial hotspots of thermal stress and drought-prone areas were also identified. The findings highlight the increasing pressure on agricultural productivity due to rising surface temperatures and vegetation stress, particularly during the dry Rabi season. This research provides actionable insights for agronomists, planners, and policymakers in promoting climate-resilient agriculture and sustainable land management in subtropical regions such as Sylhet.