A reproducible remote sensing landscape metrics framework for assessing long term changes in urban green spaces

Rapid urban expansion and land-use change have altered the extent and spatial configuration of urban green spaces, with important implications for ecological sustainability and urban quality of life. This study provides a framework for assessing spatiotemporal dynamics of urban green spaces by examining long-term changes in Shiraz, Iran, over 20 years, focusing on fragmentation and connectivity patterns. Using Landsat imagery and NDVI, vegetation changes were quantified and analyzed in ENVI, ArcMap, and R. Results indicate increased fragmentation, reduced connectivity, and dominance of small, isolated patches in central and southern parts of the city. Landscape metrics reveal a decline in spatial diversity and ecological coherence, suggesting reduced capacity for ecosystem service delivery. By integrating remote sensing, landscape metrics, and statistical analysis, this study offers an assessment of green space transformations applicable to other urban contexts. Findings emphasize the need for targeted planning to mitigate fragmentation and strengthen green space connectivity.