25 October 2012 Object-based urban change detection analyzing high resolution optical satellite images
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Change detection in urban areas by investigating image data of remote sensing satellites is an important topic. Of special interest is, for example, the detection of changes in terms of monitoring and disaster management, where accurate information about dimension and category of changes are frequently requested. Hence, in this paper, a workflow for object-oriented multispectral classification is presented to differentiate between traffic infrastructure, water, vegetation and non-vegetation areas. Changes are detected by analyzing multi-temporal classification results. For this, multitemporal QuickBird images covering the city Karlsruhe and LiDAR data are investigated to detect urban change areas.
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Markus Boldt, Markus Boldt, Antje Thiele, Antje Thiele, Karsten Schulz, Karsten Schulz, "Object-based urban change detection analyzing high resolution optical satellite images", Proc. SPIE 8538, Earth Resources and Environmental Remote Sensing/GIS Applications III, 85380E (25 October 2012); doi: 10.1117/12.973687; https://doi.org/10.1117/12.973687

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