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Inter-comparison of optical and SAR-based forest disturbance warning systems in the Amazon shows the potential of combined SAR-optical monitoring
An article of Juan Doblas Prieto, Lucas Lima, Stephane Mermoz, Alexandre Bouvet, Johannes Reiche, Manabu Watanabe, Sidnei Sant Anna, Yosio Shimabukuro: Inter-comparison of optical and SAR-based forest disturbance warning systems in the Amazon shows the potential of combined SAR-optical monitoring, has been published in the International Journal of Remote Sensing (volume 44, issue 1).
Abstract
More than half a decade after the launch of the Sentinel-1A C-band SAR satellite, several near real-time forest disturbances detection systems based on backscattering time series analysis have been developed and made operational. Every system has its own particular approach to change detection. Here, we have compared the performance of the main SAR-based near real-time operational forest disturbance detection systems produced by research agencies (INPE, in Brazil, CESBIO, in France, JAXA, in Japan, and Wageningen University, in the Netherlands), and compared them to the state-of-the-art optical algorithm, University of Maryland’s GLAD-S2. We implemented an innovative validation protocol, specially conceived to encompass all the analysed systems, which measured every system’s accuracy and detection speed in four different areas of the Amazon basin. The results indicated that, when parametrized equally, all the Sentinel-1 SAR methods outperformed the reference optical method in terms of sample-count F1-Score, having comparable results among them. The GLAD-S2 optical method showed superior results in terms of user’s accuracy (UA), issuing no false detections, but had a lower producer accuracy (PA, 84.88%) when compared to the Sentinel-1 SAR-based systems (PA∼90%). Wageningen University’s system, RADD, proved to be relatively faster, especially in heavily clouded regions, where RADD warnings were issued 41 days before optical ones, and the one that better performs on small disturbed patches
More than half a decade after the launch of the Sentinel-1A C-band SAR satellite, several near real-time forest disturbances detection systems based on backscattering time series analysis have been developed and made operational. Every system has its own particular approach to change detection. Here, we have compared the performance of the main SAR-based near real-time operational forest disturbance detection systems produced by research agencies (INPE, in Brazil, CESBIO, in France, JAXA, in Japan, and Wageningen University, in the Netherlands), and compared them to the state-of-the-art optical algorithm, University of Maryland’s GLAD-S2. We implemented an innovative validation protocol, specially conceived to encompass all the analysed systems, which measured every system’s accuracy and detection speed in four different areas of the Amazon basin. The results indicated that, when parametrized equally, all the Sentinel-1 SAR methods outperformed the reference optical method in terms of sample-count F1-Score, having comparable results among them. The GLAD-S2 optical method showed superior results in terms of user’s accuracy (UA), issuing no false detections, but had a lower producer accuracy (PA, 84.88%) when compared to the Sentinel-1 SAR-based systems (PA∼90%). Wageningen University’s system, RADD, proved to be relatively faster, especially in heavily clouded regions, where RADD warnings were issued 41 days before optical ones, and the one that better performs on small disturbed patches