Built-up areas mapping at global scale based on adapative parametric thresholding of sentinel-1 intensity & coherence time series

Authors

M. Chini, R. Pelich, R. Hostache, P. Matgen

Reference

9th International Workshop on the Analysis of Multitemporal Remote Sensing Images (MultiTemp 2017), June 27-29, 2017, Bruges, Belgium

Description

In this study we propose an automatic algorithm that aims to map built-up areas by using two multi-temporal SAR features: the backscattering intensity and the InSAR coherence. The proposed algorithm is based on an adaptive parametric thresholding methodology and makes use of a hierarchical split-based approach. With this approach, the size of the tiles is not set a priori but, rather, tiles of variable size are sought so that the distribution functions attributed to classes of interest can be parameterized in a robust way. The InSAR coherence makes it possible to discriminate false alarms caused by other land cover classes that also show high backscattering values but are not coherent in time (e.g. certain types of vegetated areas). Both intensity and coherence features are obtained by averaging multi-temporal SAR series allowing thus to reduce the speckle without losing spatial resolution. The algorithm has been developed in the framework of the Urban Round-Robin exercise supported by the European Space Agency (ESA) through the ESA Land Cover Climate Change Initiative (CCI), and tested on Sentinel-1 data from five different test sites located in semiarid and arid regions in the Mediterranean region and Northern Africa.

Link

doi:10.1109/Multi-Temp.2017.8035258