气候变化领域集成服务门户(CCPortal): Detecting tropical selective logging with C-band SAR data may require a time series approach

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DOI	10.1016/j.rse.2021.112411
	Detecting tropical selective logging with C-band SAR data may require a time series approach
	Hethcoat M.G.; Carreiras J.M.B.; Edwards D.P.; Bryant R.G.; Quegan S.
发表日期	2021
ISSN	00344257
卷号	259
英文摘要	Selective logging is the primary driver of forest degradation in the tropics and reduces the capacity of forests to harbour biodiversity, maintain key ecosystem processes, sequester carbon, and support human livelihoods. While the preceding decade has seen a tremendous improvement in the ability to monitor forest disturbances from space, large-scale (spatial and temporal) forest monitoring systems have almost universally relied on optical satellite data from the Landsat program, whose effectiveness is limited in tropical regions with frequent cloud cover. Synthetic aperture radar (SAR) data can penetrate clouds and have been utilized in forest mapping applications since the early 1990s, but only recently has SAR data been widely available on a scale sufficient to facilitate pan-tropical selective logging detection systems. Here, a detailed selective logging dataset from three lowland tropical forest regions in the Brazilian Amazon was used to assess the effectiveness of SAR data from Sentinel-1, RADARSAT-2, and Advanced Land Observing Satellite-2 Phased Arrayed L-band Synthetic Aperture Radar-2 (ALOS-2 PALSAR-2) for monitoring tropical selective logging. We built Random Forests models aimed at classifying pixel-based differences between logged and unlogged areas. In addition, we used the Breaks For Additive Season and Trend (BFAST) algorithm to assess if a dense time series of Sentinel-1 imagery displayed recognizable shifts in pixel values after selective logging. In general, Random Forests classification with SAR data (Sentinel-1, RADARSAT-2, and ALOS-2 PALSAR-2) performed poorly, having high commission and omission errors for logged observations. This suggests little to no difference in pixel-based metrics between logged and unlogged areas for these sensors, particularly at lower logging intensities. In contrast, the Sentinel-1 time series analyses indicated that areas under higher intensity selective logging (> 20 m3 ha−1) show a distinct spike in the number of pixels that included a breakpoint during the logging season. BFAST detected breakpoints in 50% of logged pixels and exhibited a false alarm rate of approximately <5% in unlogged forest. Overall our results suggest that SAR data can be used in time series analyses to detect tropical selective logging at high intensity logging locations (> 20 m3 ha−1) within the Amazon. © 2021 The Author(s)
英文关键词	ALOS-2; Brazil; Degradation; Forest disturbance; PALSAR-2; RADARSAT-2; Random Forest; Selective logging; Sentinel-1; Synthetic aperture radar; Time series; Tropical forest
语种	英语
scopus关键词	Biodiversity; Decision trees; Degradation; Ecosystems; Harmonic analysis; Pixels; Synthetic aperture radar; Time series; Time series analysis; ALOS-2; Brazil; Forest disturbances; PALSAR-2; Radarsat-2; Random forests; Selective logging; Sentinel-1; Times series; Tropical forest; Tropics; Varanidae
来源期刊	Remote Sensing of Environment
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/178855
作者单位	School of Mathematics and Statistics, University of Sheffield, Sheffield, S3 7RH, United Kingdom; Department of Animal and Plant Sciences, University of Sheffield, Sheffield, S10 2TN, United Kingdom; Grantham Centre for Sustainable Futures, University of Sheffield, Sheffield, S10 2TN, United Kingdom; National Centre for Earth Observation, University of Sheffield, Sheffield, S3 7RH, United Kingdom; Department of Geography, University of Sheffield, Sheffield, S3 7ND, United Kingdom
推荐引用方式 GB/T 7714	Hethcoat M.G.,Carreiras J.M.B.,Edwards D.P.,et al. Detecting tropical selective logging with C-band SAR data may require a time series approach[J],2021,259.
APA	Hethcoat M.G.,Carreiras J.M.B.,Edwards D.P.,Bryant R.G.,&Quegan S..(2021).Detecting tropical selective logging with C-band SAR data may require a time series approach.Remote Sensing of Environment,259.
MLA	Hethcoat M.G.,et al."Detecting tropical selective logging with C-band SAR data may require a time series approach".Remote Sensing of Environment 259(2021).