Socioeconomic spatial analysis through fuzzy system as a tool for territorial planning applied to watersheds
The watersheds are fundamental in the management of social policies, allowing for the measurement of physical and socioeconomic characteristics through indicators such as the HDI and SII. This study aims to develop the Socioeconomic Analysis Indicator (SAI) for the sub-basins of the Sorocabuçu River (SRB), using a fuzzy system and geoprocessing tools for zoning information by sub-basins. The HDI of the SRB resulted in high values, with income showing the lowest indices, followed by education and longevity. The SII showed low values, with income and literacy significantly contributing to socioeconomic vulnerability. The SAI results indicated reasonable socioeconomic conditions, with lower values in the sub-basins farther from urban and urbanized areas. This study provides data for the establishment of public policies aimed at reducing social and economic inequalities, prioritizing the most vulnerable sub-basins. The data obtained serve as an effective tool to support public management, promoting decisions that improve the quality of life of the local population through the integration of socioeconomic variables for a more holistic and sustainable approach to watershed management.
Authors
- Camille Vasconcelos Silva (ORCID: https://orcid.org/0000-0002-5810-0026)
- Letícia Tondato Arantes (ORCID: https://orcid.org/0000-0002-5541-1304)
- Roberto W. S. Rodrigues (ORCID: https://orcid.org/0000-0002-9221-4326)
- Liliane Moreira Nery (ORCID: https://orcid.org/0000-0002-5352-5316)
- Darllan Collins da Cunha e Silva (ORCID: https://orcid.org/0000-0003-3280-0478)
- Vanessa Cézar Simonetti (ORCID: https://orcid.org/0000-0001-6845-4875)
- Arthur Pereira dos Santos (ORCID: https://orcid.org/0000-0002-1913-3562)
- Mayra Vannessa Lizcano Toledo
Institutions
- Universidade de Sorocaba (BR)
- Universidade Estadual Paulista (Unesp) (BR)
Publication Details
- Journal
- International Journal of River Basin Management
- Published
- 2024-08-19
- DOI
- https://doi.org/10.1080/15715124.2024.2387579
- Citations
- 6
- Primary Topic
- Automated Road and Building Extraction
- Type
- article
- Field-Weighted Citation Impact
- 2.01
Funders
- Coordenação de Aperfeiçoamento de Pessoal de Nível Superior