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In this paper an improved procedure for the automatic recognition of built-up areas, using the so-called PANTEX index is presented. This index is based on analysis of image textural measures extracted using anisotropic rotation-invariant GLCM statistics. These measures may overestimate the built-up areas in case of presence of scattered vegetation having the same spatial pattern of settlements. In...
The state of built-up features after their destruction, as well as the process of their rehabilitation, are assessed through the analysis of conflict and postconflict very high spatial resolution Ikonos images using a pixel-level support vector machine (SVM) learning classification approach. Different input vectors of the supervised SVM classifier are tested in order to assess the discrimination power...
A procedure for the calculation of a "built-up presence index" is presented. The index is based on fuzzy rule-based composition of anisotropic textural measures derived from the satellite data by the gray-level co-occurrence matrix (GLCM). The case study includes multi-temporal analysis, wide area coverage (65times135 kilometers) with multiple datasets, scattered settlements, and presence...
A procedure for automatic recognition of the state of built-up structures after a conflict, using 1-meter-resolution optical satellite imagery, is presented. The procedure is based on a priori fuzzy rules formalized using two basic information derived from satellite data: structural information extracted by calculation of the derivative of the morphological profile using the panchromatic data, and...
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