Monthly Deforestation Monitoring with Sentinel-1 Multi-temporal Signatures and InSAR Coherences




Forest mapping, deforestation, change detection, Synthetic Aperture Radar, Interferometry, interferometric coherence, temporal decorrelation, Sentinel-1, Sentinel-2


Sentinel-1 interferometric time-series allow for the accurate retrieval of the target’s temporal decorrelation and, therefore, the inversion of land cover information and its temporal monitoring. This paper describes the development of an observation scenario for monitoring monthly deforestation over the Amazon rainforest, which relies on the use of radar for overcoming the physical limitations of optical sensors caused by the presence of cloud coverage. Speciï¬cally, we implement a classiï¬cation scheme that exploits multi-temporal SAR features, such as backscatter, spatial textures, and interferometric parameters, to map forested areas. Distinct forest maps are generated for consecutive months and further processed to detect deforestation phenomena and map clear-cuts evolution. The obtained results are validated by selecting cloud-free Sentinel-2 multispectral data on the selected area and acquired during the same observation time.


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Author Biographies

A. Pulella, German Aerospace Center (DLR)

DLR: Microwaves and Radar Institute, Satellite SAR Systems Department

Position: Research Engineer

Background: MSc in Telecommunications Engineering at University of Pisa

F. Sica, German Aerospace Center (DLR)

DLR: Microwaves and Radar Institute, Satellite SAR Systems Department

P. Rizzoli, German Aerospace Center (DLR)

DLR: Microwaves and Radar Institute, Satellite SAR Systems Department


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