Spatiotemporal analysis of land surface temperature dynamics and biophysical influences across diverse climatic zones in Iranian cities

Abstract

Land surface temperature (LST), a key climatological variable, plays a crucial role in regulating environmental and ecological processes. This variable is modulated by numerous biophysical and anthropogenic factors and directly influences urban microclimate, air quality, energy demand, and public health. This study examines the spatiotemporal dynamics of LST and the impact of key biophysical indices (NDVI, NDWI, NDMI, NDLI, NDBI, DBSI, and DBI) on urban thermal patterns in six Iranian cities (Isfahan and Yazd, Sardasht, Yasouj, Rasht, and Gorgan) which represent diverse climatic conditions. Using Landsat satellite imageries were utilized to derived LST and biophysical indices. The analysis included assessing temporal trends and spatial patterns of LST through Global Moran's I for spatial autocorrelation and K-means analysis for multivariate clustering. The impacts of biophysical indices on LST were evaluated by Spearman's correlation analysis. Findings reveal distinct thermal trends: arid cities (Isfahan, Yazd) had declining mean LST, while humid and mountainous cities (Rasht, Gorgan, Sardasht, and Yasouj) displayed rising LST with increased spatial heterogeneity. Strong spatial autocorrelation (Moran's I: 0.444 to 0.948) confirmed thermal clustering, while multivariate clustering indicated a positive association between high-density urban areas (elevated NDBI/DBI) and elevated LST (urban heat island effect) and a negative correlation between vegetated areas (high NDVI) and reduced LST. This research provides a geospatial framework for sustainable land management, aiding policymakers in developing climate-adaptive urban strategies. For evidence-based urban planning, we suggest targeted strategies, including expanding green infrastructure in humid regions and using high-albedo materials in arid cities to reduce thermal absorption. © 2025