Monitoring deforestation in the Amazon basin using Sentinel-1 interferometric SAR time series

Abstract

The need for stopping illegal deforestation activities in the rainforest areas is nowadays strongly recognised. In this paper, a novel approach to detect and monitor forest degradation in the Amazon rainforest basin is performed using Sentinel-1 interferometric SAR data. A preliminary classification approach based on the characterization of temporal decorrelation and radar backscattering is introduced. More consolidated results, supported by interferometric nonlocal pre-filtering and a machine learning classifier, will be presented in the final paper.