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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

The effectiveness of lidar remote sensing for monitoring forest cover attributes and landscape restoration

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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]
Total Authors: 16
[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 Eastern Finland, Sch Forest Sci, POB 111, Joensuu - Finland
[7] Univ Cambridge, Dept Plant Sci Forest Ecol & Conservat, Cambridge - England
[8] NASA, Goddard Space Flight Ctr, Biosci Lab, Greenbelt, MD 20707 - USA
Total Affiliations: 8
Document type: Journal article
Source: FOREST ECOLOGY AND MANAGEMENT; v. 438, p. 34-43, APR 15 2019.
Web of Science Citations: 7

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. (AU)

FAPESP's process: 16/05219-9 - Monitoring forest landscape restoration through Light Detection and Ranging (LiDAR).
Grantee:Danilo Roberti Alves de Almeida
Support type: Scholarships in Brazil - Doctorate
FAPESP's process: 16/00052-9 - Understanding ecological, legal and social aspects of the forest-water relation with importance for ecosystem services
Grantee:Paula Meli
Support type: Scholarships in Brazil - Post-Doctorate
FAPESP's process: 14/14503-7 - Chronosequence and landscape effects in tropical forest succession
Grantee:Ricardo Gomes César
Support type: Scholarships in Brazil - Doctorate