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DOI10.1016/j.foreco.2019.02.002
The effectiveness of lidar remote sensing for monitoring forest cover attributes and landscape restoration
Almeida D.R.A.; Stark S.C.; Chazdon R.; Nelson B.W.; Cesar R.G.; Meli P.; Gorgens E.B.; Duarte M.M.; Valbuena R.; Moreno V.S.; Mendes A.F.; Amazonas N.; Gonçalves N.B.; Silva C.A.; Schietti J.; Brancalion P.H.S.
发表日期2019
ISSN0378-1127
起始页码34
结束页码43
卷号438
英文摘要Ambitious pledges to restore over 400 million hectares of degraded lands by 2030 have been made by several countries within the Global Partnership for Forest Landscape Restoration (FLR). Monitoring restoration outcomes at this scale requires cost-effective methods to quantify not only forest cover, but also forest structure and the diversity of useful species. Here we obtain and analyze structural attributes of forest canopies undergoing restoration in the Atlantic Forest of Brazil using a portable ground lidar remote sensing device as a proxy for airborne laser scanners. We assess the ability of these attributes to distinguish forest cover types, to estimate aboveground dry woody biomass (AGB) and to estimate tree species diversity (Shannon index and richness). A set of six canopy structure attributes were able to classify five cover types with an overall accuracy of 75%, increasing to 87% when combining two secondary forest classes. Canopy height and the unprecedented “leaf area height volume” (a cumulative product of canopy height and vegetation density) were good predictors of AGB. An index based on the height and evenness of the leaf area density profile was weakly related to the Shannon Index of tree species diversity and showed no relationship to species richness or to change in species composition. These findings illustrate the potential and limitations of lidar remote sensing for monitoring compliance of FLR goals of landscape multifunctionality, beyond a simple assessment of forest cover gain and loss. © 2019 Elsevier B.V.
英文关键词Atlantic Forest; Forest canopy; Forest regeneration; Forest succession; Restoration accountability; Restoration monitoring; Tropical forest restoration; Tropical reforestation
语种英语
scopus关键词Biodiversity; Cost effectiveness; Land reclamation; Optical radar; Reforestation; Remote sensing; Restoration; Atlantic forest; Forest canopies; Forest regeneration; Forest succession; Tropical forest; Conservation; forest canopy; forest cover; forest ecosystem; landscape; laser method; leaf area; lidar; remote sensing; restoration ecology; secondary forest; species diversity; species richness; tree; tropical forest; Biodiversity; Cost Effectiveness; Land Reclamation; Reforestation; Remote Sensing; Restoration; Atlantic Forest; Brazil
来源期刊Forest Ecology and Management
文献类型期刊论文
条目标识符http://gcip.llas.ac.cn/handle/2XKMVOVA/156119
作者单位Department of Forest Sciences, “Luiz de Queiroz” College of Agriculture, University of São Paulo (USP/ESALQ), Piracicaba, SP, Brazil; Department of Forestry, Michigan State University, East Lansing, MI, United States; Department of Ecology & Evolutionary Biology, University of Connecticut, Storrs, CT, United States; National Institute for Amazon Research (INPA), Manaus, AM, Brazil; Department of Forestry, Federal University of Vales do Jequitinhonha e Mucuri (UFVJM), Diamantina, MG, Brazil; Department of Plant Sciences, Forest Ecology and Conservation, University of Cambridge, Cambridge, United Kingdom; School of Forest Sciences, University of Eastern Finland, PO Box 111, Joensuu, Finland; Biosciences Laboratory, NASA Goddard Space Flight Center, Greenbelt, MD 20707, United States
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Almeida D.R.A.,Stark S.C.,Chazdon R.,et al. The effectiveness of lidar remote sensing for monitoring forest cover attributes and landscape restoration[J],2019,438.
APA Almeida D.R.A..,Stark S.C..,Chazdon R..,Nelson B.W..,Cesar R.G..,...&Brancalion P.H.S..(2019).The effectiveness of lidar remote sensing for monitoring forest cover attributes and landscape restoration.Forest Ecology and Management,438.
MLA Almeida D.R.A.,et al."The effectiveness of lidar remote sensing for monitoring forest cover attributes and landscape restoration".Forest Ecology and Management 438(2019).
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