气候变化领域集成服务门户(CCPortal): A voxel matching method for effective leaf area index estimation in temperate deciduous forests from leaf-on and leaf-off airborne LiDAR data

CCPortal

DOI	10.1016/j.rse.2020.111696
	A voxel matching method for effective leaf area index estimation in temperate deciduous forests from leaf-on and leaf-off airborne LiDAR data
	Zhu X.; Liu J.; Skidmore A.K.; Premier J.; Heurich M.
发表日期	2020
ISSN	00344257
卷号	240
英文摘要	The quantification of leaf area index (LAI) is essential for modeling the interaction between atmosphere and biosphere. The airborne LiDAR has emerged as an effective tool for mapping plant area index (PAI) in a landscape consisting of both woody and leaf materials. However, the discrimination between woody and leaf materials and the estimation of effective LAI (eLAI) have, to date, rarely been studied at landscape scale. We applied a voxel matching algorithm to estimate eLAI of deciduous forests using simulated and field LiDAR data under leaf-on and leaf-off conditions. We classified LiDAR points as either a leaf or a woody hit on leaf-on LiDAR data by matching the point with leaf-off data. We compared the eLAI result of our voxel matching algorithm against the subtraction method, where the leaf-off effective woody area index (eWAI) is subtracted from the effective leaf-on PAI (ePAI). Our results, which were validated against terrestrial LiDAR derived eLAI, showed that the voxel matching method, with an optimal voxel size of 0.1 m, produced an unbiased estimation of terrestrial LiDAR derived eLAI with an R2 of 0.70 and an RMSE of 0.41 (RRMSE: 20.1%). The subtraction method, however, yielded an R2 of 0.62 and an RMSE of 1.02 (RRMSE: 50.1%) with a significant underestimation of 0.94. Reassuringly, the same outcome was observed using a simulated dataset. In addition, we evaluated the performance of 96 LiDAR metrics under leaf-on conditions for eLAI prediction using a statistical model. Based on the importance scores derived from the random forest regression, nine of the 96 leaf-on LiDAR metrics were selected. Cross-validation showed that eLAI could be predicted using these metrics under leaf-on conditions with an R2 of 0.73 and an RMSE of 0.27 (RRMSE: 17.4%). The voxel matching method yielded a slightly lower accuracy (R2: 0.70, RMSE:0.41, RRMSE: 20.1%) than the statistical model. We, therefore, suggest that the voxel matching method offers a new opportunity for the estimating eLAI and other ecological applications that require the classification between leaf and woody materials using airborne LiDAR data. It potentially allows transferability to different sites and flight campaigns. © 2020 The Authors
英文关键词	Airborne LiDAR; Effective leaf area index; Leaf-off; Leaf-on; Voxel matching
语种	英语
scopus关键词	Decision trees; Plants (botany); Airborne LiDAR; Leaf Area Index; Leaf-off; Leaf-on; Voxel matching; Optical radar; algorithm; data set; deciduous forest; estimation method; leaf area index; lidar; model validation; satellite data
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/179420
作者单位	Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, P.O. Box 217, AE, Enschede, 7500, Netherlands; Key Laboratory of Virtual Geographic Environment, Ministry of Education, Nanjing Normal University, Nanjing, 210023, China; School of Geography, Nanjing Normal University, Nanjing, 210023, China; Department of Environmental Science, Macquarie UniversityNSW 2109, Australia; Bavarian Forest National Park, Freyunger Straße 2, Grafenau, 94481, Germany; Chair of Wildlife Ecology and Management, Faculty of Environment and Natural Resources, University of Freiburg, Freiburg, Germany
推荐引用方式 GB/T 7714	Zhu X.,Liu J.,Skidmore A.K.,et al. A voxel matching method for effective leaf area index estimation in temperate deciduous forests from leaf-on and leaf-off airborne LiDAR data[J],2020,240.
APA	Zhu X.,Liu J.,Skidmore A.K.,Premier J.,&Heurich M..(2020).A voxel matching method for effective leaf area index estimation in temperate deciduous forests from leaf-on and leaf-off airborne LiDAR data.Remote Sensing of Environment,240.
MLA	Zhu X.,et al."A voxel matching method for effective leaf area index estimation in temperate deciduous forests from leaf-on and leaf-off airborne LiDAR data".Remote Sensing of Environment 240(2020).