Building extraction in built-up area is of great interest for visualization, simulation and monitoring urban landscape which is used for town/city planning as well as regional planning. Building extraction in urban areas based on merely a single high resolution optical data is often hard to conduct and to improve quality of building detection with consistency, completeness and correctness. Optical images are one of the major sources of individual building extraction from orthoimage but most of these do not produce anticipated result especially to building’s shape and outlines in dense urban environment. Extraction of objects from InSAR images is a complicated phenomenon for interpretability due to side looking geometry and effects of layover, foreshortening, shadowing and multi bounce scattering. In this study, buildings and building blocks are extracted from fusion of optical and InSAR data using object oriented analysis (OOA) technique. The improvement of building footprint has done with rectangular fit for building hypothesis and building height from normalized digital surface model (nDSM) based on fuzzy membership function. The results of building extraction has found reasonably good and accurate in planned urban layouts. The quality of building extraction has highly dependent on settlement density, contrast and other image characteristics.Nepalese Journal on Geoinformatics -13, 2014, Page: 16-23
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