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Spatial Data Mining to Support Environmental Management and Decision Making—A Case Study in Brazil




Author(s)

Carlos Roberto Valêncio, Fernando Tochio Ichiba, Guilherme Priólli Daniel, Rogéria Cristiane Gratão de Souza, Leandro Alves Neves and Angelo Cesar Colombini

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DOI:10.17265/1934-7332/2014.01.005

Department of Computer Science and Statistics, São Paulo State University

The growth of geo-technologies and the development of methods for spatial data collection have resulted in large spatial data repositories that require techniques for spatial information extraction, in order to transform raw data into useful previously unknown information. However, due to the high complexity of spatial data mining, the need for spatial relationship comprehension and its characteristics, efforts have been directed towards improving algorithms in order to provide an increase of performance and quality of results. Likewise, several issues have been addressed to spatial data mining, including environmental management, which is the focus of this paper. The main original contribution of this work is the demonstration of spatial data mining using a novel algorithm with a multi-relational approach that was applied to a database related to water resource from a certain region of São Paulo State, Brazil, and the discussion about obtained results. Some characteristics involving the location of water resources and the profile of who is administering the water exploration were discovered and discussed.

Water resource management, spatial data mining, multi-relational spatial data mining, spatial clustering, environmental management.