Abstract
In the framework of the ESA-funded research project entitled SInCohMap “Sentinel-1 Interferometric Coherence for Vegetation and Mapping” (sincohmap.org), undertaken from 2017 to 2020, a large number of tests and options were analyzed regarding the exploitation of the interferometric coherence derived from Sentinel-1 data in multitemporal land cover and vegetation mapping.
It was demonstrated that time series of coherence provide information complementary to backscatter intensity, hence contributing to improve classification both alone and in combination with intensity. Moreover, the coherence measured at VV channel contributes more than the coherence measured at the VH channel, contrarily to backscatter, so the usage of both polarimetric channels is recommended in classification. As a third key conclusion from that project, it was found that the shortest temporal baseline (i.e., 6 days) outperforms the rest of possible temporal baselines and, in addition, there is no significant improvement in the results when more temporal baselines are added to the 6-day one as input features.
All these conclusions were drawn from experiments carried out in three different test sites with diverse class sets and distributions: South Tyrol alpine environment (Italy), Doñana wetland and crops environment (Spain), and West Wielkopolska forest/agricultural/urban environment (Poland). Moreover, a specific study case on crop-type mapping was performed (Mestre-Quereda et al. 2020). Experiments included many different classification algorithms and strategies, as detailed in Jacob et al. (2020), which demonstrate the robustness of the project outcomes.
That project is currently being extended by exploring 3 new aspects related to the same topic:
A) Added value for classification of the combination of both ascending and descending acquisitions, since they offer different observation geometry of the same scene as well as different acquisition times (e.g., 6 am vs 6 pm in Europe).
B) Added value of the combination of Sentinel-1 coherence with Sentinel-2 optical imagery.
C) Potential usage of 6-day Sentinel-1 coherence for forest mapping and characterization in temperate and boreal regions.
Based on the results obtained with these experiments, recommendations will be presented for obtaining maximum performance in land cover and vegetation mapping by multi-track Sentinel-1 (ascending and descending) and by combination of Sentinel-1 and Sentinel-2 data.
References
A. Jacob, et al. “Sentinel-1 InSAR Coherence for Land Cover Mapping: A Comparison of Multiple Feature-Based Classifiers,” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol. 13, pp. 535-552, January 2020.
A. Mestre-Quereda, et al. “Time Series of Sentinel-1 Interferometric Coherence and Backscatter for Crop-Type Mapping,” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol. 13, pp. 4070-4084, July 2020.