Enhanced automatic detection of human settlements using Sentinel-1 interferometric coherence
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.
CORBAN Christina;
LEMOINE Guido;
PESARESI Martino;
KEMPER Thomas;
SABO Filip;
FERRI Stefano;
SYRRIS Vasileios;
2017-10-24
TAYLOR & FRANCIS LTD
JRC105278
0143-1161,
http://www.tandfonline.com/doi/abs/10.1080/01431161.2017.1392642?journalCode=tres20,
https://publications.jrc.ec.europa.eu/repository/handle/JRC105278,
10.1080/01431161.2017.1392642,
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