GSTDTAP  > 气候变化
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.1; Stark, S. C.2; Chazdon, R.3; Nelson, B. W.4; Cesar, R. G.1; Meli, P.1; Gorgens, E. B.5; Duarte, M. M.1; Valbuena, R.6,7; Moreno, V. S.1; Mendes, A. F.1; Amazonas, N.1; Goncalves, N. B.4; Silva, C. A.8; Schietti, J.4; Brancalion, P. H. S.1
2019-04-15
发表期刊FOREST ECOLOGY AND MANAGEMENT
ISSN0378-1127
EISSN1872-7042
出版年2019
卷号438页码:34-43
文章类型Article
语种英语
国家Brazil; USA; England; Finland
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 airbome 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.


英文关键词Atlantic Forest Forest canopy Forest regeneration Forest succession Restoration accountability Restoration monitoring Tropical forest restoration Tropical reforestation
领域气候变化
收录类别SCI-E
WOS记录号WOS:000463120500005
WOS关键词CANOPY LEAF-AREA ; ABOVEGROUND BIOMASS ; TROPICAL FOREST ; AIRBORNE LIDAR ; DIVERSITY ; PROFILES ; PLANTATIONS ; EUCALYPTUS ; SCIENCE ; HEIGHT
WOS类目Forestry
WOS研究方向Forestry
引用统计
文献类型期刊论文
条目标识符http://119.78.100.173/C666/handle/2XK7JSWQ/182336
专题气候变化
作者单位1.Univ Sao Paulo USP ESALQ, Dept Forest Sci, Luiz de Queiroz Coll Agr, Piracicaba, SP, Brazil;
2.Michigan State Univ, Dept Forestry, E Lansing, MI 48824 USA;
3.Univ Connecticut, Dept Ecol & Evolutionary Biol, Storrs, CT USA;
4.Natl Inst Amazon Res INPA, Manaus, AM, Brazil;
5.Fed Univ Vales Jequitinhonha & Mucuri UFVJM, Dept Forestry, Diamantina, MG, Brazil;
6.Univ Cambridge, Dept Plant Sci Forest Ecol & Conservat, Cambridge, England;
7.Univ Eastern Finland, Sch Forest Sci, POB 111, Joensuu, Finland;
8.NASA, Goddard Space Flight Ctr, Biosci Lab, Greenbelt, MD 20707 USA
推荐引用方式
GB/T 7714
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]. FOREST ECOLOGY AND MANAGEMENT,2019,438:34-43.
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,438,34-43.
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):34-43.
条目包含的文件
条目无相关文件。
个性服务
推荐该条目
保存到收藏夹
查看访问统计
导出为Endnote文件
谷歌学术
谷歌学术中相似的文章
[Almeida, D. R. A.]的文章
[Stark, S. C.]的文章
[Chazdon, R.]的文章
百度学术
百度学术中相似的文章
[Almeida, D. R. A.]的文章
[Stark, S. C.]的文章
[Chazdon, R.]的文章
必应学术
必应学术中相似的文章
[Almeida, D. R. A.]的文章
[Stark, S. C.]的文章
[Chazdon, R.]的文章
相关权益政策
暂无数据
收藏/分享
所有评论 (0)
暂无评论
 

除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。