Abstract
The “Sentinel-1 Interferometric Coherence for Vegetation and Mapping”, SInCohMap, project (sincohmap.org) is an ESA-founded project with the objective of developing, analyzing and validating novel methodologies for land cover and vegetation mapping using time series of Sentinel-1 (S1) Interferometric (InSAR) Coherence.
The experiments and analysis carried out from 2017 to 2020 demonstrated the contribution of the time series of interferometric coherence derived from S1 data in the generation of accurate land cover and vegetation-type maps. This analysis was done over three different test sites (South Tyrol in Italy, Doñana in Spain, and West Wielkopolska in Poland) which are characterised by different classes and geographical features. The results obtained in the SInCohMap project showed that time series of interferometric coherence from both polarimetric channels are complementary sources of information for land cover. They can be exploited along the intensity to improve mapping classification (Mestre-Quereda et al. 2020). Experiments included many different classification algorithms and strategies, as detailed by Jacob et al. (2020), which demonstrate the robustness of the project outcomes.
Along with the development of the SInCohMap project, several topics were identified for further analysis. Thus, the SInCohMap project has been extended to explore three new aspects:
A) Improvement of the land cover classification when combining both ascending and descending acquisitions. They offer different observation geometry of the same scene as well as different acquisition times. It has been found very relevant over mountainous terrain to increase the spatial coverage of the maps by avoiding shadow and layover areas.
B) Improvement of the land cover classification when combining S1 coherence and Sentinel-2 optical imagery. The complementarity of information provided at these two wavelengths (optical and microwave) is relevant for some classes which are better identified at one or another.
C) Exploratory application of 6-day S1 interferometric coherence for forest monitoring and classification. The dependence on repeat-pass coherence upon forest characteristics has been studied.
The main results of these three new aspects will be presented at the conference