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Performance of Laser-Based Electronic Devices for Structural Analysis of Amazonian Terra-Firme Forests.

Authors :
Pereira, Iokanam Sales
Mendonça do Nascimento, Henrique E.
Boni Vicari, Matheus
Disney, Mathias
DeLucia, Evan H.
Domingues, Tomas
Kruijt, Bart
Lapola, David
Meir, Patrick
Norby, Richard J.
Ometto, Jean P.H.B.
Quesada, Carlos A.
Rammig, Anja
Hofhansl, Florian
Source :
Remote Sensing; 3/1/2019, Vol. 11 Issue 5, p510, 1p
Publication Year :
2019

Abstract

Tropical vegetation biomass represents a key component of the carbon stored in global forest ecosystems. Estimates of aboveground biomass commonly rely on measurements of tree size (diameter and height) and then indirectly relate, via allometric relationships and wood density, to biomass sampled from a relatively small number of harvested and weighed trees. Recently, however, novel in situ remote sensing techniques have been proposed, which may provide nondestructive alternative approaches to derive biomass estimates. Nonetheless, we still lack knowledge of the measurement uncertainties, as both the calibration and validation of estimates using different techniques and instruments requires consistent assessment of the underlying errors. To that end, we investigate different approaches estimating the tropical aboveground biomass in situ. We quantify the total and systematic errors among measurements obtained from terrestrial light detection and ranging (LiDAR), hypsometer-based trigonometry, and traditional forest inventory. We show that laser-based estimates of aboveground biomass are in good agreement (<10% measurement uncertainty) with traditional measurements. However, relative uncertainties vary among the allometric equations based on the vegetation parameters used for parameterization. We report the error metrics for measurements of tree diameter and tree height and discuss the consequences for estimated biomass. Despite methodological differences detected in this study, we conclude that laser-based electronic devices could complement conventional measurement techniques, thereby potentially improving estimates of tropical vegetation biomass. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
20724292
Volume :
11
Issue :
5
Database :
Complementary Index
Journal :
Remote Sensing
Publication Type :
Academic Journal
Accession number :
135297067
Full Text :
https://doi.org/10.3390/rs11050510