气候变化领域集成服务门户(CCPortal): Hybrid inversion of radiative transfer models based on high spatial resolution satellite reflectance data improves fractional vegetation cover retrieval in heterogeneous ecological systems after fire

CCPortal

DOI	10.1016/j.rse.2021.112304
	Hybrid inversion of radiative transfer models based on high spatial resolution satellite reflectance data improves fractional vegetation cover retrieval in heterogeneous ecological systems after fire
	Fernández-Guisuraga J.M.; Verrelst J.; Calvo L.; Suárez-Seoane S.
发表日期	2021
ISSN	00344257
卷号	255
英文摘要	In forest landscapes affected by fire, the estimation of fractional vegetation cover (FVC) from remote sensing data using radiative transfer models (RTMs) enables to evaluate the ecological impact of such disturbance across plant communities at different spatio-temporal scales. Even though, when landscapes are highly heterogeneous, the fine-scale ground spatial variation might not be properly captured if FVC products are provided at moderate or coarse spatial scales, as typical of most of operational Earth observing satellite missions. The objective of this study was to evaluate the potential of a RTM inversion approach for estimating FVC from satellite reflectance data at high spatial resolution as compared to the standard use of coarser imagery. The study was conducted both at landscape and plant community levels within the perimeter of a megafire that occurred in western Mediterranean Basin. We developed a hybrid retrieval scheme based on PROSAIL-D RTM simulations to create a training dataset of top-of-canopy spectral reflectance and the corresponding FVC for the dominant plant communities. The machine learning algorithm Gaussian Processes Regression (GPR) was learned on the training dataset to model the relationship between canopy reflectance and FVC. The GPR model was then applied to retrieve FVC from WorldView-3 (spatial resolution of 2 m) and Sentinel-2 (spatial resolution of 20 m) surface reflectance bands. A set of 75 plots of 2x2m and 45 plots of 20x20m was distributed under a stratified schema across the focal plant communities within the fire perimeter to validate FVC satellite derived retrieval. At landscape scale, the accuracy of the FVC retrieval was substantially higher from WorldView-3 (R2 = 0.83; RMSE = 7.92%) than from Sentinel-2 (R2 = 0.73; RMSE = 11.89%). At community level, FVC retrieval was more accurate for oak forests than for heathlands and broomlands. The retrieval from WorldView-3 minimized the over- and underestimation effects at low and high field sampled vegetation cover, respectively. These findings emphasize the effectiveness of high spatial resolution satellite reflectance data to capture FVC ground spatial variability in heterogeneous burned areas using a hybrid RTM retrieval method. © 2021 Elsevier Inc.
英文关键词	Forest fire; Fractional vegetation cover; Radiative transfer modeling; Sentinel-2; WorldView-3
语种	英语
scopus关键词	Data communication systems; Ecology; Forestry; Geophysical prospecting; Ground penetrating radar systems; Image resolution; Learning algorithms; Machine learning; Radiative transfer; Reflection; Remote sensing; Satellite imagery; Vegetation; Canopy spectral reflectance; Dominant plant community; Earth observing satellite; Fractional vegetation cover; Gaussian processes regressions (GPR); High spatial resolution; Radiative transfer model; Western Mediterranean basin; Search engines
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/178959
作者单位	Area of Ecology, Faculty of Biological and Environmental Sciences, University of León, León, 24071, Spain; Department of Organisms and Systems Biology (Ecology Unit) and Research Unit of Biodiversity (UO-CSIC-PA), University of Oviedo, Oviedo, Mieres, Spain; Image Processing Laboratory (IPL), Parc Científic, University of Valencia, Paterna, Valencia 46980, Spain
推荐引用方式 GB/T 7714	Fernández-Guisuraga J.M.,Verrelst J.,Calvo L.,et al. Hybrid inversion of radiative transfer models based on high spatial resolution satellite reflectance data improves fractional vegetation cover retrieval in heterogeneous ecological systems after fire[J],2021,255.
APA	Fernández-Guisuraga J.M.,Verrelst J.,Calvo L.,&Suárez-Seoane S..(2021).Hybrid inversion of radiative transfer models based on high spatial resolution satellite reflectance data improves fractional vegetation cover retrieval in heterogeneous ecological systems after fire.Remote Sensing of Environment,255.
MLA	Fernández-Guisuraga J.M.,et al."Hybrid inversion of radiative transfer models based on high spatial resolution satellite reflectance data improves fractional vegetation cover retrieval in heterogeneous ecological systems after fire".Remote Sensing of Environment 255(2021).