气候变化领域集成服务门户(CCPortal): Spectral mapping methods applied to LiDAR data: Application to fuel type mapping

CCPortal

DOI	10.1016/j.jag.2018.08.020
	Spectral mapping methods applied to LiDAR data: Application to fuel type mapping
	Huesca M.; Riaño D.; Ustin S.L.
发表日期	2019
ISSN	15698432
起始页码	159
结束页码	168
卷号	74
英文摘要	Originally developed to classify multispectral and hyperspectral images, spectral mapping methods were used to classify Light Detection and Ranging (LiDAR) data to estimate the vertical structure of vegetation for Fuel Type (FT) mapping. Three spectral mapping methods generated spatially comprehensive FT maps for Cabañeros National Park (Spain): (1) Spectral Mixture Analysis (SMA), (2) Spectral Angle Mapper (SAM), and (3) Multiple Endmember Spectral Mixture Analysis (MESMA). The Vegetation Vertical Profiles (VVPs) describe the vertical distribution of the vegetation and are used to define each FT endmember in a LiDAR signature library. Two different approaches were used to define the endmembers, one based on the field data collected in 1998 and 1999 (Approach 1) and the other on exploring spatial patterns of the singular FT discriminating factors (Approach 2). The overall accuracy is higher for Approach 2 and with best results when considering a five-FT model rather than a seven-FT model. The agreement with field data of 44% for MESMA and SMA and 40% for SAM is higher than the 38% of the official Cabañeros National Park FTs map. The principal spatial patterns for the different FTs were well captured, demonstrating the value of this novel approach using spectral mapping methods applied to LiDAR data. The error sources included the time gap between field data and LiDAR acquisition, the steep topography in parts of the study site, and the low LiDAR point density among others. © 2018 Elsevier B.V.
英文关键词	Fuel types; LiDAR; Multiple endmember spectral mixture analysis; Spectral angle mapper; Spectral mixture analysis; Vegetation vertical profile; Wildfires
语种	英语
scopus关键词	data set; image analysis; lidar; mapping method; spatiotemporal analysis; spectral analysis; vegetation mapping; Cabaneros National Park; Castilla-La Mancha; 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/156555
作者单位	Center for Spatial Technologies And Remote Sensing (CSTARS), John Muir Institute of the Environment, University of California, Davis, United States; Center for Spatial Technologies And Remote Sensing (CSTARS), Department of Land, Air, and Water Resources, University of California Davis, United States; Instituto de Economía, Geografía y Demografía (IEGD), Centro de Ciencias Humanas y Sociales (CCHS), Consejo Superior de Investigaciones Científicas (CSIC), Albasanz 26-28 28037, Madrid, Spain
推荐引用方式 GB/T 7714	Huesca M.,Riaño D.,Ustin S.L.. Spectral mapping methods applied to LiDAR data: Application to fuel type mapping[J],2019,74.
APA	Huesca M.,Riaño D.,&Ustin S.L..(2019).Spectral mapping methods applied to LiDAR data: Application to fuel type mapping.International Journal of Applied Earth Observation and Geoinformation,74.
MLA	Huesca M.,et al."Spectral mapping methods applied to LiDAR data: Application to fuel type mapping".International Journal of Applied Earth Observation and Geoinformation 74(2019).