Spatial planning for forthcoming shrimp farming in southern coast of Brazil: a tool to coastal management

Guilherme Caldieraro Viana; Luiz Henrique Sousa Salgado; Felipe Schwahofer Landuci

doi:10.20950/1678-2305/bip.2023.49.e789

Authors

Guilherme Caldieraro Viana Universidade Federal do Rio de Janeiro , Programa de Pós-Graduação em Biotecnologia Vegetal e Bioprocessos – Rio de Janeiro (RJ), Brasil. https://orcid.org/0000-0001-5376-7772
Luiz Henrique Sousa Salgado Fundação Instituto de Pesca do Rio de Janeiro , Diretoria de Pesquisa e Produção – Rio de Janeiro (RJ), Brasil. https://orcid.org/0000-0002-0881-598X
Felipe Schwahofer Landuci Fundação Instituto de Pesca do Rio de Janeiro , Diretoria de Pesquisa e Produção – Rio de Janeiro (RJ), Brazil | Universidade Federal do Rio de Janeiro , Instituto de Biologia, Departamento de Biologia Marinha– Rio de Janeiro (RJ), Brazil. https://orcid.org/0000-0001-7945-6796

DOI:

https://doi.org/10.20950/1678-2305/bip.2023.49.e789

Keywords:

geographic information systems (sig), analysis hierarchy process (ahp), aquaculture, carciniculture

Abstract

Geographic information systems, the integration technique of multi-criteria assessment, together with the analysis hierarchy process, are recognized in decision support to describe and predict locations for implementation of different projects. In Brazil, shrimp farming has been consolidated for more than 30 years in the Northeast and North regions and is emerging in the Southeast. The purposes of this study were to analyze, classify and quantify through spatial planning for the establishment of shrimp farming in the North Fluminense region of the state of Rio de Janeiro, Brazil. The composition of the final model was structured into hierarchical categories with two models, factors, and constraints. The model of factors was subdivided into five sub-models: water abstraction, environmental, transport, public, and economic infrastructure. In turn, restrictions were composed of urbanized areas, environmental reserves. The best areas were identified as those that were flat, close to rivers, related to the
environmental sub-model criteria (21%); followed by the sub-models of public, economic, and water abstraction infrastructure (20%), and transport with the lowest weight attributed (17%). The analyses indicated a great potential for the implementation of shrimp farming in the region, estimated in a total area of 628,088 ha, classified as adequate or very adequate (> 0.6).