Abstract
Abstract: In this work we introduce an object-based method, applied to urban land cover mapping. The method is implemented with two open-source tools: SIPINA, a data mining software package; and InterIMAGE, an object-based image analysis system. Initially, segmentation, feature extraction and sample selection procedures are performed with InterIMAGE. In order to reduce the time and subjectivity involved to develop the decision rules in InterIMAGE, a data mining step is then carried out with SIPINA. In sequence, the decision trees delivered by SIPINA are analysed and encoded into InterIMAGE decision rules for the final classification step. Experiments were conducted using a subset of a GeoEye image, acquired in January 01, 2013, covering the urban portion of the municipality of Goianésia, Brazil. Five decision tree induction algorithms, available in SIPINA, were tested: ID3, C45, GID3, Assistant86 and CHAID. The TAU and Kappa coefficients were used to evaluate the results. The TAU values obtained were in the range of 0.66 and 0.70, while those for Kappa varied from 0.65 to 0.69.
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