Enhanced automatic detection of human settlements using Sentinel-1 interferometric coherence. Issue 3 (1st February 2018) - Corbane, C.; Lemoine, G.; Pesaresi, M.; Kemper, T.; Sabo, F.; Ferri, S.; Syrris, V.
ABSTRACT: This article presents an experiment in which multi-temporal interferometric coherence calculated from 6-days Sentinel-1A and Sentinel-1B image pairs and backscatter intensity σ ° are jointly used for the extraction of built-up areas in the framework of the symbolic machine learning classification. The results obtained with the proposed approach confirm the enhanced capabilities of discriminating built-up areas when using coherence information in comparison to two available global human settlement layers derived: (1) from Landsat optical data and (2) from Sentinel-1 ground range detected data and based on backscatter intensity σ ° only. The experiment carried out in The Netherlands Randstad area is expected to be indicative of the results obtainable for urban areas having similar structures and types of built-up.