气候变化领域集成服务门户(CCPortal): Evaluation and comparison of Landsat 8, Sentinel-2 and Deimos-1 remote sensing indices for assessing burn severity in Mediterranean fire-prone ecosystems

CCPortal

DOI	10.1016/j.jag.2019.04.006
	Evaluation and comparison of Landsat 8, Sentinel-2 and Deimos-1 remote sensing indices for assessing burn severity in Mediterranean fire-prone ecosystems
	García-Llamas P.; Suárez-Seoane S.; Fernández-Guisuraga J.M.; Fernández-García V.; Fernández-Manso A.; Quintano C.; Taboada A.; Marcos E.; Calvo L.
发表日期	2019
ISSN	15698432
起始页码	137
结束页码	144
卷号	80
英文摘要	The development of improved spatial and spectral resolution sensors provides new opportunities to assess burn severity more accurately. This study evaluates the ability of remote sensing indices derived from three remote sensing sensors (i.e., Landsat 8 OLI/TIRS, Sentinel-2 MSI and Deimos-1 SLIM-6-22) to assess burn severity (site, vegetation and soil burn severity). As a case study, we used a megafire (9,939 ha) that occurred in a Mediterranean ecosystem in northwestern Spain. Remote sensing indices included seven reflective, two thermal and four mixed indices, which were derived from each satellite and were validated with field burn severity metrics obtained from CBI index. Correlation patterns of field burn severity and remote sensing indices were relatively consistent across the different sensors. Additionally, regardless of the sensor, indices that incorporated SWIR bands (i.e., NBR-based indices), exceed those using red and NIR bands, and thermal and mixed indices. High resolution Sentinel-2 imagery only slightly improved the performance of indices based on NBR compared to Landsat 8. The dNDVI index from Landsat 8 and Sentinel-2 images showed relatively similar correlation values to NBR-based indices for site and soil burn severity, but showed limitations using Deimos-1. In general, mono-temporal and relativized indices better correlated with vegetation burn severity in heterogeneous systems than differenced indices. This study showed good potential for Landsat 8 OLI/TIRS and Sentinel-2 MSI for burn severity assessment in fire-prone heterogeneous ecosystems, although we highlight the need for further evaluation of Deimos-1 SLIM-6-22 in different fire scenarios, especially using bi-temporal indices. © 2019 Elsevier B.V.
英文关键词	Composition burn index; Remote sensing; Spectral indices; Thermal indices
语种	英语
scopus关键词	fire behavior; Landsat; Mediterranean environment; NDVI; remote sensing; satellite imagery; Sentinel; spatial resolution; spectral analysis; spectral resolution; Spain
来源期刊	International Journal of Applied Earth Observation and Geoinformation
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/156451
作者单位	Biodiversity and Environmental Management Dpt., Faculty of Biological and Environmental Sciences, University of León, Campus de Vegazana s/n, León, 24071, Spain; Institute of Environmental Research (IMA), University of Léon, León, 24071, Spain; Agrarian Science and Engineering Department, University of León, Av. Astorga s/n, Ponferrada, 24400, Spain; Electronic Technology Department, University of Valladolid, Spain; Sustainable Forest Management Research Institute, Universidad of Valladolid, Spanish National Institute for Agriculture and Food Research and Technology (INIA), Spain
推荐引用方式 GB/T 7714	García-Llamas P.,Suárez-Seoane S.,Fernández-Guisuraga J.M.,et al. Evaluation and comparison of Landsat 8, Sentinel-2 and Deimos-1 remote sensing indices for assessing burn severity in Mediterranean fire-prone ecosystems[J],2019,80.
APA	García-Llamas P..,Suárez-Seoane S..,Fernández-Guisuraga J.M..,Fernández-García V..,Fernández-Manso A..,...&Calvo L..(2019).Evaluation and comparison of Landsat 8, Sentinel-2 and Deimos-1 remote sensing indices for assessing burn severity in Mediterranean fire-prone ecosystems.International Journal of Applied Earth Observation and Geoinformation,80.
MLA	García-Llamas P.,et al."Evaluation and comparison of Landsat 8, Sentinel-2 and Deimos-1 remote sensing indices for assessing burn severity in Mediterranean fire-prone ecosystems".International Journal of Applied Earth Observation and Geoinformation 80(2019).