Sensing Vegetation Resistance and Recovery Along Urban–Rural Gradients

Understanding vegetation-mediated mitigation of urban heat islands (UHI) is essential for sustainable urban adaptation strategies. Although vegetation responses to extreme heat events have been widely explored using satellite remote sensing and statistical methods, evidence remains limited regarding how these responses vary along urban–rural gradients, particularly in terms of resistance and recovery dynamics. This study focuses on the North Tianshan Slope Urban Agglomeration (TNSUA) in Xinjiang, China. Based on Enhanced Vegetation Index (EVI) data from 2000 to 2022, an urban–rural gradient was delineated using impervious surface fraction. Vegetation resistance and recovery during extreme heat events were quantified to reveal spatiotemporal response patterns. Generalized additive models (GAMs) and Random Forest (RF) models were applied to identify key driving factors and to evaluate their relative importance across multiple spatial scales. The results indicate that rural land cover along the gradient provides a strong cooling effect, particularly in areas with an urban development intensity (UDI) of 70–85%. Vegetation responses show pronounced seasonal differences, with urban vegetation generally exhibiting lower resistance and recovery than rural vegetation. At the county scale, local UHI intensity is the dominant driver of vegetation responses, whereas at the pixel scale, precipitation and vapor pressure deficit (VPD) play the most critical roles. Overall, this study improves the understanding of vegetation responses to extreme heat events in arid regions and provides scientific support for nature-based urban heat adaptation strategies.