AUTOMATED CHAIN FOR LARGE-SCALE 3D RECONSTRUCTION OF URBAN SCENES FROM SATELLITE IMAGES

• Published in: International archives of the photogrammetry, remote sensing and spatial information sciences. Vol. XLII-2/W16; pp. 243 - 250
• Main Authors: Tripodi, S., Duan, L., Trastour, F., Poujad, V., Laurore, L., Tarabalka, Y.
• Format: Journal Article Conference Proceeding
• Language: English
• Published: Gottingen Copernicus GmbH 17.09.2019; Copernicus Publications
• Subjects: Automation; Buildings; Chains; Digital imaging; Image reconstruction; Imagery; Machine learning; Polygonization; Remote sensing; Satellite imagery; Satellites; Spaceborne remote sensing; Telecommunications; Terrain models
• ISSN: 2194-9034; 1682-1750; 2194-9034
• DOI: 10.5194/isprs-archives-XLII-2-W16-243-2019

Automatic city modeling from satellite imagery is a popular yet challenging topic in remote sensing, driven by numerous applications such as telecommunications, defence and urban mamagement. In this paper, we present an automated chain for large-scale 3D reconstruction of urban scenes with a Level of Detail 1 from satellite images. The proposed framework relies on two key ingredient. First, from a stereo pair of images, we estimate a digital terrain model and a digital height model, by using a novel set of feature descriptors based on multiscale morphological analysis. Second, inspired by recent works in machine learning, we extract in an automatic way contour polygons of buildings, by adopting a fully convolutional network U-Net followed by a polygonization of the predicted mask of buildings. We demonstrate the potential of our chain by reconstructing in an automated way different areas of the world.