A Novel Visual Data Mining Module for the Geographical Information System gvSIG

Romel Vázquez-Rodríguez, Carlos Pérez-Risquet, Juan Carlos Torres-Cantero

Abstract


The exploration of large GIS models containing spatio-temporal information is a challenge. In this paper we propose the integration of scientific visualization (ScVis) techniques into geographic information systems (GIS) as an alternative for the visual analysis of data. Providing GIS with such tools improves the analysis and understanding of datasets with very low spatial density and allows to find correlations between variables in time and space. In this regard, we present a new visual data mining tool for the GIS gvSIG. This tool has been implemented as a gvSIG module and contains several ScVis techniques for multiparameter data with a wide range of possibilities to explore interactively the data. The developed module is a powerful visual data mining and data visualization tool to obtain knowledge from multiple datasets in time and space. A real case study with meteorological data from Villa Clara province (Cuba) is presented, where the implemented visualization techniques were used to analyze the available datasets. Although it is tested with meteorological data, the developed module is of general application in the sense that it can be used in multiple application fields related with Earth Sciences.

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DOI: https://doi.org/10.11137/2013_1_98_111

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