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TerraSAR X data has been analyzed for its suitability of urban land cover mapping using our recently developed object based image analysis tool KTH-SEG, which is based on an edge aware region growing and merging algorithm and a support vector machine classifier. Classification results over the Shanghai International Airport area using 8 classes, Water, Grass, Roads, Buildings, Crops, Forest, Bare...
With regional economy development and the changes of urban development strategies, Shanghai experienced a distinct land use change process during the past 30 year. To explore the spatial pattern and temporal dynamics of urban land and industrial land over the past years, two independent datasets from multitemporal satellite images based on interpretation with computer-aids and object-oriented classification...
This research investigates the capability of the multitemporal RADARSAT Fine-Beam C-HH SAR imagery for land use/land-cover mapping and change detection in the rural-urban fringe of the Greater Toronto Area (GTA). Five-date RADARSAT fine-beam SAR images were acquired during May to August in 2002. One scene of Landsat TM imagery was acquired in 1988 for change detection. The major land use/land-cover...
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