This study aims to investigate the spatio-temporal patterns of vegetation dynamics and land surface temperature (LST) in Guilan Province, northern Iran, over the period 2020–2024 through an integrated multi-index remote sensing approach. Using satellite-derived indicators including the Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), and Land Surface Temperature (LST), the research provides a comprehensive assessment of environmental change, vegetation responses, and their linkages with climatic variability. The multi-year satellite analysis was conducted to identify long-term vegetation trends, detect anomalies associated with climatic stress, and quantify the degree to which vegetation fluctuations correspond to temperature and precipitation changes.



The findings reveal substantial interannual variability in vegetation density across the province. Both NDVI and EVI indicate a marked decline in vegetation greenness in 2022, which coincides with a period of elevated surface temperatures and reduced precipitation. Partial recovery in vegetation conditions is observed in 2024, although not uniformly across all regions. Conversely, LST patterns exhibit notable increases during years associated with vegetation stress, highlighting the intensifying role of thermal conditions in shaping ecosystem function. Correlation analysis shows a strong negative relationship between vegetation indices and LST, underscoring the vulnerability of Guilan’s ecosystems to climatic pressures, particularly under warming trends.



Overall, the results illustrate the importance of integrating multi-source satellite data to deepen understanding of vegetation–climate interactions in ecologically sensitive and humid subtropical regions. The study’s outcomes offer valuable insights for regional environmental planning, sustainable agriculture, and climate adaptation strategies in the Caspian coastal zone. By emphasizing the role of remote sensing in monitoring ecosystem change, this research contributes to improved decision-making frameworks aimed at mitigating climate impacts in northern Iran.