气候变化领域集成服务门户(CCPortal): Estimation of forest leaf water content through inversion of a radiative transfer model from LiDAR and hyperspectral data

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DOI	10.1016/j.jag.2018.09.008
	Estimation of forest leaf water content through inversion of a radiative transfer model from LiDAR and hyperspectral data
	Zhu X.; Skidmore A.K.; Darvishzadeh R.; Wang T.
发表日期	2019
ISSN	15698432
起始页码	120
结束页码	129
卷号	74
英文摘要	The accurate estimation of leaf water content (LWC) and knowledge about its spatial variation are important for forest and agricultural management since LWC provides key information for evaluating plant physiology. Hyperspectral data have been widely used to estimate LWC. However, the canopy reflectance can be affected by canopy structure, thereby introducing error to the retrieval of LWC from hyperspectral data alone. Radiative transfer models (RTM) provide a robust approach to combine LiDAR and hyperspectral data in order to address the confounding effects caused by the variation of canopy structure. In this study, the INFORM model was adjusted to retrieve LWC from airborne hyperspectral and LiDAR data. Two structural parameters (i.e. stem density and crown diameter) in the input of the INFORM model that affect canopy reflectance most were replaced by canopy cover which could be directly obtained from LiDAR data. The LiDAR-derived canopy cover was used to constrain in the inversion procedure to alleviate the ill-posed problem. The models were validated against field measurements obtained from 26 forest plots and then used to map LWC in the southern part of the Bavarian Forest National Park in Germany. The results show that with the introduction of prior information of canopy cover obtained from LiDAR data, LWC could be retrieved with a good accuracy (R 2 = 0.87, RMSE = 0.0022 g/cm 2 , nRMSE = 0.13). The adjustment of the INFORM model facilitated the introduction of prior information over a large extent, as the estimation of canopy cover can be achieved from airborne LiDAR data. © 2018 Elsevier B.V.
英文关键词	Canopy cover; INFORM; Leaf water content; Prior information
语种	英语
scopus关键词	estimation method; forest canopy; forest cover; leaf area index; lidar; radiative transfer; spectral analysis; water content; Bavaria; Bavarian Forest National Park; Germany
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/156560
作者单位	Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, P.O. Box 217, Enschede, AE 7500, Netherlands; Department of Environmental Science, Macquarie UniversityNSW 2109, Australia
推荐引用方式 GB/T 7714	Zhu X.,Skidmore A.K.,Darvishzadeh R.,et al. Estimation of forest leaf water content through inversion of a radiative transfer model from LiDAR and hyperspectral data[J],2019,74.
APA	Zhu X.,Skidmore A.K.,Darvishzadeh R.,&Wang T..(2019).Estimation of forest leaf water content through inversion of a radiative transfer model from LiDAR and hyperspectral data.International Journal of Applied Earth Observation and Geoinformation,74.
MLA	Zhu X.,et al."Estimation of forest leaf water content through inversion of a radiative transfer model from LiDAR and hyperspectral data".International Journal of Applied Earth Observation and Geoinformation 74(2019).