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Human activities and climate changes significantly affect our environment, altering hydrologic cycles. Several environmental, social, political, and economical factors contribute to land transformation as well as environmental changes. This study first identified the most critical factors that affect the environment in Al-Anbar city including population growth, urbanization expansion, bare land expansion,...
High spectral and spatial resolution hyperspectral data provides great potential to characterize intra-urban land cover classes at material level. In this study, AISA airborne hyperspectral image with 0.68m pixel size were used to classify 12 feature classes. In order to conduct the classification, Support Vector Machine (SVM) classifier was used in pixel-based and object-based approach to test the...
Although rule-based object-based classification can often perform better than the supervised approaches, its attribute selection is very time consuming and hardly transferable between different urban areas. The purpose of this study is to identify transferable rule-sets for different areas from QuickBird satellite imagery for urban areas consisting heterogeneous man-made and natural features. Object-based...
Although object-based image analysis (OBIA) has been used for detailed classification of urban areas, its attribute selection and knowledge discovery have been time consuming and subjective to analysts' performance. In this study, Data Mining was performed using C4.5 algorithm to select the appropriate attributes for object-based classification. This algorithm provides a decision tree output to represent...
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