Ecological and economic assessment of the cooling ecosystem services of green infrastructure considering functional resilience in urban land management

<ns0:p>Urbanization and climate change reduce the effectiveness of the cooling regulating ecosystem services (RES) of urban green infrastructure; however, their ecological and economic assessment considering functional resilience—especially for suburban urban ecosystems under conditions of armed conflict—remains insufficiently developed. The aim of this study is to provide an ecological and economic assessment of urban green infrastructure as climate-regulating natural capital and to develop an approach for assessing cooling RES considering functional resilience using the case of Irpin during 2015–2024.The analysis was based on summer median Landsat 8/9 composites, ERA5-Land climate data, and pixel-based regression analysis in Google Earth Engine using NDVI, LST, NDBI, the Cooling Efficiency Index (CEI), and thermal hotspot dynamics analysis. A stable cooling effect of vegetation throughout the study period was identified (NDVI–LST regression coefficients ranging from −13.27 to −18.96), alongside a pronounced thermal impact of built-up areas (NDBI–LST ranging from +44.08 to +64.24). Despite relatively stable NDVI values (0.260–0.300), the area of thermal hotspots increased sharply after 2020, reaching 25.63% of the territory in 2024, while CEI indicated the maximum decline in cooling efficiency.The scientific novelty of the study is the proposed Functional Resilience Index (FRI), which integrates vegetation cooling performance, greenness level, cooling efficiency, and spatial thermal vulnerability. The critical decline of FRI from 1.72 in 2015 to 0.11 in 2024 empirically demonstrates that quantitative vegetation indicators alone are insufficient for assessing the functional resilience of RES. The proposed resilience-adjusted approach provides a more differentiated ecological and economic assessment of the natural capital of urban green infrastructure compared to the classical avoided cost method and may serve as an instrumental basis for decision-making in climate adaptation and urban land management.Received: 14.05.2026;Accepted: 08.06.2026;</ns0:p>