Fuzzy-based Support System for Urban Green Infrastructure Management
Dealing with the challenges of rapid urban growth while preserving ecological ecosystems and human quality of life is a hard task and a cornerstone of sustainable urban development. This study proposes a Decision Support System (DSS) for the management of Urban Green Infrastructure (UGI). The DSS wa...
| Autores: | , , , , |
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| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2024 |
| País: | Brasil |
| Institución: | Universidade Estadual Paulista (UNESP) |
| Repositorio: | Repositório Institucional da UNESP |
| Idioma: | inglés |
| OAI Identifier: | oai:repositorio.unesp.br:11449/306200 |
| Acceso en línea: | http://dx.doi.org/10.5380/raega.v61i1.95323 https://hdl.handle.net/11449/306200 |
| Access Level: | acceso abierto |
| Palabra clave: | Artificial Intelligence Fuzzy Logic Green Infrastructure Sustainable Cities |
| Sumario: | Dealing with the challenges of rapid urban growth while preserving ecological ecosystems and human quality of life is a hard task and a cornerstone of sustainable urban development. This study proposes a Decision Support System (DSS) for the management of Urban Green Infrastructure (UGI). The DSS was developed using fuzzy artificial intelligence to address uncertainties inherent in the integration of geospatial data within the computational environment of a Geographic Information System. The selection of variables and configuration parameters was based on a literature review and expert consultation through the Delphi method. To verify the potential of the DSS, a case study was developed in the Biological Reserve of Serra do Japi. The results indicate that the DSS serves as a promising tool for planners, policymakers, and researchers, capable of supporting data-driven recommendations through case-by-case analyses. Future research could explore the integration of additional indicators, enhance the inference mechanism, and extend the application of the DSS across diverse urban contexts to optimize its versatility and effectiveness in UGI management. |
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