Identification of priority urban areas for the implementation of green infrastructure: a proposal based on a fuzzy inference system

• Grant number: 22/09230-8
• Support Opportunities: Scholarships in Brazil - Scientific Initiation
• Start date: February 01, 2023
• End date: January 31, 2024
• Field of knowledge: Interdisciplinary Subjects
• Principal Investigator: Adriano Bressane
• Grantee: Vitória Valente Monteiro
• Host Institution: Instituto de Ciência e Tecnologia (ICT). Universidade Estadual Paulista (UNESP). Campus de São José dos Campos. São José dos Campos , SP, Brazil

Abstract

With the growth of cities and the respective expansion of built-up areas, the pressure on natural areas has increased. In addition to impacts on climate and biodiversity, the suppression of nature due to urbanization also compromises ecological cycles and processes, and the health and well-being of the population. As an alternative, the implementation of green infrastructure has become a trend recommended by the United Nations, as a strategy to achieve sustainable development goals and the promotion of healthy cities. In this context, this project aims to develop and evaluate a methodological proposal applied to the identification of priority urban areas for the implementation of green infrastructure, in a computational modeling environment of a Geographic Information System (GIS). Considering that there are inherent uncertainties in the acquisition, representation and analysis of spatial data, the hypothesis that the use of a fuzzy inference system should provide an adequate methodological alternative for multicriteria analysis in a GIS environment will be verified. For that, case studies will be developed through the application of the proposal in hydrographic basins, considered strategic units of territorial management in the municipality of São José dos Campos/SP. The methodological development, as well as its application to case studies, will be carried out using the free software Quantum-GIS. The necessary materials will consist of cartographic information available in existing databases, ensuring the feasibility of the research.