Spatiotemporal modeling of urban green space connectivity and landscape structure for climate adaptation in Tehran, Iran

Urban heat island (UHI) effects, exacerbated by climate change, highlight the urgent need for effective management of urban green spaces (UGSs) to regulate city temperatures. However, previous studies primarily concentrated on the effects of landscape composition and configuration on mitigating urban heat islands. To address this gap, this study develops a connectivity-based framework to examine the spatiotemporal evolution of urban green spaces in Tehran, Iran, using satellite data from 2015 to 2023 processed in Google Earth Engine. Landsat-derived land surface temperature (LST) and NDVI maps were used to identify urban heat and cool islands. ROC and TSS metrics were applied to determine an optimal NDVI threshold for classifying green and non-green areas. Landscape morphology metrics quantified spatial configuration changes, while Foreground Area Density and inverse NDVI maps were used to detect core green spaces and resistance surfaces, respectively. Connectivity flows between cold cores were modeled using electrical circuit theory. Results revealed a significant decrease of 1,400 ha in cold areas in northern Tehran and a 1,618 ha increase in hot zones in the south and southwest. Spatial analysis revealed increased cold patch fragmentation and hot zone expansion, reducing green space continuity and intensifying the UHI effect. While cold cores in 2015 showed weak, scattered connectivity, by 2023 they became more concentrated in northern Tehran with a marked increase in current flow, indicating improved local connectivity. However, this concentration reveals growing imbalance in UGS distribution and cooling capacity, highlighting the need for targeted green infrastructure in southern, western, and central areas. The findings offer valuable insights for urban planners to enhance UGS connectivity and mitigate UHI effects, supporting climate resilience and improving urban quality of life.