气候变化领域集成服务门户(CCPortal): SAR data for tropical forest disturbance alerts in French Guiana: Benefit over optical imagery

CCPortal

DOI	10.1016/j.rse.2020.112159
	SAR data for tropical forest disturbance alerts in French Guiana: Benefit over optical imagery
	Ballère M.; Bouvet A.; Mermoz S.; Le Toan T.; Koleck T.; Bedeau C.; André M.; Forestier E.; Frison P.-L.; Lardeux C.
发表日期	2021
ISSN	00344257
卷号	252
英文摘要	French Guiana forests cover 8 million hectares. With 98% of emerged land covered by forests, French Guiana is the area with the highest proportion of forest cover in the world. These forests are home to an exceptionally rich and diverse wealth of biodiversity that is both vulnerable and under threat due to high levels of pressure from human activity. As part of the French territory, French Guiana benefits from determined and continuous national efforts in the preservation of biodiversity and the environmental functionalities of ecosystems. The loss and fragmentation of forest cover caused by gold mining (legal and illegal), smallholder agriculture and forest exploitation, are considered as small-scale disturbances, although representing strong effects to vulnerable natural habitats, landscapes, and local populations. To monitor forest management programs and combat illegal deforestation and forest opening near-real time alerts system based on remote sensing data are required. For this large territory under frequent cloud cover, Synthetic-Aperture Radar (SAR) data appear to be the best adapted. In this paper, a method for forest alerts in a near-real time context based on Sentinel-1 data over the whole of French Guiana (83,534 km2) was developed and evaluated. The assessment was conducted for 2 years between 2016 and 2018 and includes comparisons with reference data provided by French Guiana forest organizations and comparisons with the existing University of Maryland Global Land Analysis and Discovery Forest Alerts datasets based on Landsat data. The reference datasets include 1,867 plots covering 2,124.5 ha of gold mining, smallholder agriculture and forest exploitation. The validation results showed high user accuracies (96.2%) and producer accuracies (81.5%) for forest loss detection, with the latter much higher than for optical forest alerts (36.4%). The forest alerts maps were also compared in terms of detection timing, showing systematic temporal delays of up to one year in the optical method compared to the SAR method. These results highlight the benefits of SAR over optical imagery for forest alerts detection in French Guiana. Finally, the potential of the SAR method applied to tropical forests is discussed. The SAR-based map of this study is available on http://cesbiomass.net/. © 2020 The Author(s)
英文关键词	Forest alert; French Guiana; Near real time deforestation; Optical-SAR comparison; Sentinel-1; Tropical forest
语种	英语
scopus关键词	Agricultural robots; Biodiversity; Crime; Deforestation; Economic geology; Gold mines; Information management; Remote sensing; Synthetic aperture radar; Tropics; Human activities; Local populations; Management programs; Optical imagery; Remote sensing data; Small-scale disturbances; University of Maryland; Validation results; Radar imaging; biodiversity; deforestation; disturbance; forest cover; mining; remote sensing; smallholder; synthetic aperture radar; tropical forest; French Guiana; 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/179061
作者单位	Centre National d'Etudes Spatiales, Toulouse, 31400, France; World Wildlife Fund France, Le Pré-Saint-Gervais, 93310, France; LaSTIG, University of Gustave Eiffel, IGN, Champs-sur-Marne, 77420, France; CESBIO, Université de Toulouse, CNES/CNRS/INRAE/IRD/UPS, Toulouse, 31400, France; GlobEO, Toulouse, 31400, France; Office National des Forêts Guyane, Cayenne, 97300, France; ONF International, Paris, France
推荐引用方式 GB/T 7714	Ballère M.,Bouvet A.,Mermoz S.,et al. SAR data for tropical forest disturbance alerts in French Guiana: Benefit over optical imagery[J],2021,252.
APA	Ballère M..,Bouvet A..,Mermoz S..,Le Toan T..,Koleck T..,...&Lardeux C..(2021).SAR data for tropical forest disturbance alerts in French Guiana: Benefit over optical imagery.Remote Sensing of Environment,252.
MLA	Ballère M.,et al."SAR data for tropical forest disturbance alerts in French Guiana: Benefit over optical imagery".Remote Sensing of Environment 252(2021).