An Efficient Multi-stage Object-Based Classification to Extract Urban Building Footprints from HR Satellite Images

نویسندگان

چکیده

Urban building information can be effectively extracted by applying object-based image segmentation and multi-stage thresholding on High Resolution (HR) remote sensing satellite imageries. This study provides the results obtained using this method images of Indian satellite, CARTOSAT-2S launched Space Research Organization (ISRO). In study, a is developed to extract urban footprints from HR images. The first step process consists generating highly dense per pixel Digital Surface Model (DSM) semi global matching algorithm stereo robust ground filtering generate Terrain (DTM). second step, approach adopted bases PAN sharpened image, normalized (nDSM) derived DSM DTM, Normalised Difference Vegetation Index (NDVI). are compared with manual drawing cartographers. An average precision 0.930, recall 0.917, f-score 0.922 obtained. found in match high resolution Airborne LiDAR providing solution for large areas, low cost time.

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ژورنال

عنوان ژورنال: Traitement Du Signal

سال: 2021

ISSN: ['0765-0019', '1958-5608']

DOI: https://doi.org/10.18280/ts.380120