2017
DOI: 10.1590/s0100-204x2017001100011
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Artificial neural network for ecological-economic zoning as a tool for spatial planning

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 ecologicaleconomic 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 (GI… Show more

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Cited by 4 publications
(3 citation statements)
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“…To classify zones in cities, besides consider ecological information, it is necessary include social and economic variables in urban zoning (Freitas & Santos, 2014;Sadeck et al, 2017). The inclusion of this information can be done through data spatialization, with geotechnologies attached to landscape ecology that assist areas classification (Freitas & Santos, 2014).…”
Section: Landscape Ecology In Urban Planningmentioning
confidence: 99%
See 1 more Smart Citation
“…To classify zones in cities, besides consider ecological information, it is necessary include social and economic variables in urban zoning (Freitas & Santos, 2014;Sadeck et al, 2017). The inclusion of this information can be done through data spatialization, with geotechnologies attached to landscape ecology that assist areas classification (Freitas & Santos, 2014).…”
Section: Landscape Ecology In Urban Planningmentioning
confidence: 99%
“…The inclusion of this information can be done through data spatialization, with geotechnologies attached to landscape ecology that assist areas classification (Freitas & Santos, 2014). With an integrated data base (environmental, social and economic information), urban landscape can be categorized into four interest classes: consolidation, expansion, recovery and conservation (Sadeck et al, 2017). Zone categories in cities protects environmental interests (e.g.…”
Section: Landscape Ecology In Urban Planningmentioning
confidence: 99%
“…In the artificial neural network class of models, the Self-Organizing Map (SOM) excels at preserving statistical properties from the dataset and allows visualization of high-dimensional input patterns. SOM's recent use in territorial zoning applications is increasing, such as in [Silva et al 2018] and [Sadeck et al 2022].…”
Section: Introductionmentioning
confidence: 99%