Data/hora: 09/06/2024 02:10:23

Provedor de dados: | 86
País: | Brazil
Título: | Artificial neural network for ecological-economic zoning as a tool for spatial planning
Autores: | Sadeck,Luis Waldyr Rodrigues; Lima,Aline Maria Meiguins de; Adami,Marcos.
Data: | 2017-11-01
Ano: | 2017
Palavras-chave: | Amazon; Regional planning; Regionalization; Self-organizing maps.
Resumo: | Abstract: The objective of this work was to analyze social and environmental information through an artificial neural network-self-organizing map (ANN-SOM), in order to provide subsidy to ecological-economic zoning (EEZ) as a tool to reduce the subjectivity of the process. The study area comprises 16 municipalities in the northeast of the state of Pará, Brazil, representative of the agricultural development in the state. Data processing involved three steps: preparation of the data in a geographic information system (GIS) environment; mathematical processing (ANN-SOM) of the data; and visualization and interpretation of the processing results, allowing the spatial planning of northeastern Pará. The results comprised 13 classes, regrouped according to behavioral similarity criteria into four categories, which represent the main areas of sustainability proposed for the state of Pará, according to existing EEZ. The proposed methodology allows individualizing areas in the region that EEZ had not defined, mainly due to the greater possibility of combining and integrating a large number of physical, social, and economic variables through the SOM.
Tipo: | Info:eu-repo/semantics/article
Idioma: | Inglês
Identificador: | http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-204X2017001101050

Editor:

Embrapa Secretaria de Pesquisa e Desenvolvimento

Pesquisa Agropecuária Brasileira

Relação: | 10.1590/s0100-204x2017001100011
Formato: | text/html
Fonte: | Pesquisa Agropecuária Brasileira  v.52 n.11 2017
Fonte: | info:eu-repo/semantics/openAccess