2nd Workshop with international participation under the EU Copernicus Programme COPE4BG 2020
Published April 27, 2022 | Version v1
Conference paper Open

Application of mean statistics derived from Sentinel-1 time series on forest – examine forest type and correlation with biomass layers

Creators

  • 1. Space Research and Technology Institute - Bulgarian Academy of Sciences, Sofia, Bulgaria

Description

This study is focused on the mean characteristics derived from Sentinel-1 time series, on mountainous forest in Bulgaria, for a four year period of continuous observation. General aim is to demonstrate the utilization of resulted SAR observables in C-band by means of dual polarimetry, in mountainous disturbed forest, along the diversity of forest layer and local incidence angle. To study also statistical relationship between the SAR observables and forest parameters. The SAR observables consists of statistical mean values of both VH and VV backscatter intensities, and the dual-pol Radar Vegetation Index (dRVI). Three layers describing forest parameters are used as dependent variables, where - GlobBIomass-2010© and CCI-Biomass-2018©, freely provided by University of Jena (Lehrstuhl für Fernerkundung), and also Tree-Cover-Density-2015 in the scope of COPERNICUS Services. Time series processing is performed within the OS framework “PyroSAR”, developed there. Disturbed forest is considered, resulted from past Icethrow disaster event. Various RGBs are calculated, in order to distinguish particular backscatter behavior related to different conditions. Particular SAR responses are summarized for mean - dRVI, VH and VV, and used for supervised classification using SVM. Forest type and Forest/Non-forest masks are resulted from SVM-classifications, where highest accuracy achieved is 78%, whereas about forest masks highest accuracy is 91%. Additional SAR indices - such as dual-pol SAR Vegetation Index (dSVI) and Polarization Ratio (PR) are also calculated, showing non-significant contribution. Performed regression analysis shown that none significant correlation is observed between the SAR observables and biomass layers in mountainous forest. Nonetheless, high correlation exists between dRVI and local incidence angle, with R2 = 0.78. Therefore, the mean characteristics calculated from the Sentinel-1 C-band using time series approach, show good feasibility to study forest areas. This study was kindly supported by Prof. C. Schmullius, PhD F. Cremer, Dr. N. Salepci from FSU-Jena, Lehrstuhl für Fernerkundung, in the framework of ERASMUS+ Programme.

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