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Title: 3D object-based feature extraction from 3-stereo DSM in urban context
Authors: Kulessa, K.
Issue Date: 2016
Citation: In: GEOBIA 2016 : Solutions and Synergies., 14 September 2016 - 16 September 2016, University of Twente Faculty of Geo-Information and Earth Observation (ITC) .
Abstract: For urban planning purposes updated information on land-use and urban structures and change dynamics are essential. Satellite Earth observation is a very effective information source, to provide actual representations of the situation ‘as is’ in regular time steps. The Pléiades constellation offers very high resolution imagery with a triple-stereo acquisition. The intrinsic combination of thematic and height information is an additional asset provided by recent VHR stereo imagery. Digital surface models (DSM) can be derived through stereo matching algorithms, one of which is semi-global matching (SGM). SGM integrates local and global matching methods with a short processing time and accurate surface generation. We use the generated DSM for extracting 3-D features which enrich object-based class models of composite urban objects. These multi-purpose 3-D object feature datasets can be used for various planning and monitoring purposes, revealing height-related characteristics of urban objects (blocks, neighbourhoods, parks, industrial sites, etc.). In addition object-wise aggregated height information can be used to better assess the adherence of actual building activities to zoning or land development plans, e.g. with respect to maximum or average height in recreational areas etc. As compared to detailed and potentially more accurate DSMs generated from LiDAR data, a (3-)stereo DSM has the advantage of recording height and spectral information instantaneously, so not to lose any information in high dynamic urban settings due to a time gap. Height and colour information, when integrated by spatial context and multi-scale OBIA methods, enable a wealth of new applications in urban feature characterisation and 3D city model applications.
URI: http://tailieuso.tlu.edu.vn/handle/DHTL/4374
Source: https://proceedings.utwente.nl/409/1/Kulessa-3-D%20object-based%20feature%20extraction%20from%203-stereo%20DSM-156.pdf
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