Efficient nonparametric extraction of urban footprint from VHR SAR images

Andrea Garzelli; Claudia Zoppetti

doi:10.1117/12.2326677

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9 October 2018 Efficient nonparametric extraction of urban footprint from VHR SAR images

Andrea Garzelli, Claudia Zoppetti

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Proceedings Volume 10789, Image and Signal Processing for Remote Sensing XXIV; 1078910 (2018) https://doi.org/10.1117/12.2326677
Event: SPIE Remote Sensing, 2018, Berlin, Germany

Abstract

Very-High-Resolution Synthetic Aperture Radar (VHR-SAR) images are of particular interest to characterize and monitor urban areas at a global scale. While automatic urban footprint extraction from SAR images can be theoretically performed at very high spatial and temporal resolutions, in practice it requires a huge amount of processing time and memory resources for a global coverage. The paper presents a fast procedure for 1mresolution Spotlight mode scene analysis which shows limited memory requirements and robustness to one-look speckle disturbance. The proposed method adopts a multiscale approach, with a radiometrically scalable scheme. Experimental results with objective assessment on Spotlight Cosmo-SkyMED images are presented and validated on reference urban classes provided by the Copernicus Urban Atlas 2012 of the European Space Agency.

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Andrea Garzelli and Claudia Zoppetti "Efficient nonparametric extraction of urban footprint from VHR SAR images", Proc. SPIE 10789, Image and Signal Processing for Remote Sensing XXIV, 1078910 (9 October 2018); https://doi.org/10.1117/12.2326677

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