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Geo-environmental zoning using physiographic compartmentalization: a proposal for supporting sustainable decision-making

Overview of attention for article published in Anais da Academia Brasileira de Ciências, September 2017
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Title
Geo-environmental zoning using physiographic compartmentalization: a proposal for supporting sustainable decision-making
Published in
Anais da Academia Brasileira de Ciências, September 2017
DOI 10.1590/0001-3765201720160915
Pubmed ID
Authors

Claudia V S Corrêa, Fábio A G V Reis, Lucilia C Giordano, Adriano Bressane, Camila J Chaves, Ana Maria C DO Amaral, Hermes D Brito, Gerson A DE Medeiros

Abstract

The geo-environmental zoning represents an important strategy in the territorial management. However, it requires a logical and structured procedure. Therefore, an approach using physiographic compartmentalization is proposed and applied as case study in a region covered by the topographic maps of São José dos Campos and Jacareí, Brazil. This region has great geological and geomorphological peculiarities, beyond being a place with large human interventions because of its quickly economic growth. The methodology is based on photointerpretation techniques and remote sensing in GIS environment. As a result, seven geo-environmental zones were obtained from a weighted integration by multicriteria analysis of physiographic units with land-use classes. In conclusion, taking into account potentialities and limitations, the proposed approach can be considered able to support sustainable decision-making, being applicable in other regions.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 17 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 17 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 3 18%
Professor 2 12%
Student > Ph. D. Student 2 12%
Lecturer 1 6%
Student > Doctoral Student 1 6%
Other 3 18%
Unknown 5 29%
Readers by discipline Count As %
Environmental Science 3 18%
Chemical Engineering 2 12%
Engineering 2 12%
Earth and Planetary Sciences 2 12%
Computer Science 1 6%
Other 2 12%
Unknown 5 29%