Temporal Decorrelation of C-Band Backscatter Coefficient in Mediterranean Burned Areas

• Published in: Remote sensing (Basel, Switzerland) Vol. 11; no. 22; p. 2661
• Main Authors: Belenguer-Plomer, Miguel A., Chuvieco, Emilio, Tanase, Mihai A.
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 14-11-2019
• Subjects: Algorithms; Backscattering; C band; Climate change; Coefficients; Datasets; Land cover; Machine learning; Moisture content; Monitoring; Radar; Radar imaging; Radar scattering; Remote sensing; Satellites; Sensors; Soil moisture; Soil water; Synthetic aperture radar; Topography; Variables; Vegetation; Water content
• ISSN: 2072-4292; 2072-4292
• DOI: 10.3390/rs11222661

Burned area algorithms from radar images are often based on temporal differences between pre- and post-fire backscatter values. However, such differences may occur long past the fire event, an effect known as temporal decorrelation. Improvements in radar-based burned areas monitoring depend on a better understanding of the temporal decorrelation effects as well as its sources. This paper analyses the temporal decorrelation of the Sentinel-1 C-band backscatter coefficient over burned areas in Mediterranean ecosystems. Several environmental variables influenced the radar scattering such as fire severity, post-fire vegetation recovery, water content, soil moisture, and local slope and aspect were analyzed. The ensemble learning method random forests was employed to estimate the importance of these variables to the decorrelation process by land cover classes. Temporal decorrelation was observed for over 32% of the burned pixels located within the study area. Fire severity, vegetation water content, and soil moisture were the main drivers behind temporal decorrelation processes and are of the utmost importance for areas detected as burned immediately after fire events. When burned areas were detected long after fire (decorrelated areas), due to reduced backscatter coefficient variations between pre- to post-fire acquisitions, water content (soil and vegetation) was the main driver behind the backscatter coefficient changes. Therefore, for efficient synthetic aperture radar (SAR)-based monitoring of burned areas, detection, and mapping algorithms need to account for the interaction between fire impact and soil and vegetation water content.