GIS-Based Assessment of Urban Green Infrastructure: A Systematic Review of Advances, Gaps, and Interdisciplinary Integration (2020–2024)

Urban Green Infrastructure (UGI) is essential for the sustainable expansion of urban areas due to its ecological, social, and economic advantages. Geographic Information Systems (GIS) enable comprehensive, multi-scale spatial evaluations of Urban Green Infrastructure (UGI); however, current research is fragmented, exhibiting voids in scope, methodological integration, and cross-disciplinary coverage of benefits.This systematic review was designed to (a) identify the components of UGI that were evaluated using GIS from 2020 to mid-2024, (b) evaluate the data sources, models, and analytical techniques used, and (c) assess methodological advancements, such as the integration of interdisciplinary strategies and artificial intelligence (AI).Scopus and the Web of Science Core Collection (Science Citation Index, Social Science Citation Index) were searched for peer-reviewed English publications published between January 1, 2020, and June 30, 2024, in accordance with the PRISMA 2020 standards. Empirical GIS- based studies of urban green infrastructure were identified by the inclusion criteria. Titles, abstracts, and complete texts were independently reviewed by a reviewer, who resolved any discrepancies through consensus. The quality was evaluated based on four criteria: the provision of optimization plans, methodological transparency, GIS detail, and clarity of objectives. Out of 1,592 records that were identified, 20 studies satisfied all the inclusion criteria.The most significantly represented countries were China, Saudi Arabia, and Spain, with research conducted in 13 countries. GIS applications encompassed ecological benefits (such as carbon sequestration), resilience, environmental equity, social benefits, and aesthetic evaluation. The analytical methods employed in this study included multi-criteria decision analysis (e.g., AHP, OWA, CoCoSo), spatial statistics, network analysis, and model integration (e.g., InVEST), with data sources included governmental, commercial, academic, and open platforms. AI- assisted data processing, enhanced weighting systems, improved visualization, and expanded interdisciplinarity were among the methodological advancements.GIS-based UGI assessments have developed into multidimensional, integrated research; however, there are still deficiencies in the evaluation of social benefits, the incorporation of 2 resident perspectives, and the establishment of clear definitions. The precision, inclusivity, and policy significance of future UGI planning can be enhanced by implementing participatory approaches, leveraging AI, and improving transdisciplinary frameworks.