Estimating above-ground carbon biomass in a newly restored coastal plain wetland using remote sensing.

Developing accurate but inexpensive methods for estimating above-ground carbon biomass is an important technical challenge that must be overcome before a carbon offset market can be successfully implemented in the United States. Previous studies have shown that LiDAR (light detection and ranging) is...

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Main Authors: Joseph B Riegel, Emily Bernhardt, Jennifer Swenson
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2013-01-01
Series:PLoS ONE
Online Access:http://europepmc.org/articles/PMC3695897?pdf=render
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spelling doaj-226b75b6ee7c43baa50213f9dbfa92052020-11-25T02:35:18ZengPublic Library of Science (PLoS)PLoS ONE1932-62032013-01-0186e6825110.1371/journal.pone.0068251Estimating above-ground carbon biomass in a newly restored coastal plain wetland using remote sensing.Joseph B RiegelEmily BernhardtJennifer SwensonDeveloping accurate but inexpensive methods for estimating above-ground carbon biomass is an important technical challenge that must be overcome before a carbon offset market can be successfully implemented in the United States. Previous studies have shown that LiDAR (light detection and ranging) is well-suited for modeling above-ground biomass in mature forests; however, there has been little previous research on the ability of LiDAR to model above-ground biomass in areas with young, aggrading vegetation. This study compared the abilities of discrete-return LiDAR and high resolution optical imagery to model above-ground carbon biomass at a young restored forested wetland site in eastern North Carolina. We found that the optical imagery model explained more of the observed variation in carbon biomass than the LiDAR model (adj-R(2) values of 0.34 and 0.18 respectively; root mean squared errors of 0.14 Mg C/ha and 0.17 Mg C/ha respectively). Optical imagery was also better able to predict high and low biomass extremes than the LiDAR model. Combining both the optical and LiDAR improved upon the optical model but only marginally (adj-R(2) of 0.37). These results suggest that the ability of discrete-return LiDAR to model above-ground biomass may be rather limited in areas with young, small trees and that high spatial resolution optical imagery may be the better tool in such areas.http://europepmc.org/articles/PMC3695897?pdf=render
collection DOAJ
language English
format Article
sources DOAJ
author Joseph B Riegel
Emily Bernhardt
Jennifer Swenson
spellingShingle Joseph B Riegel
Emily Bernhardt
Jennifer Swenson
Estimating above-ground carbon biomass in a newly restored coastal plain wetland using remote sensing.
PLoS ONE
author_facet Joseph B Riegel
Emily Bernhardt
Jennifer Swenson
author_sort Joseph B Riegel
title Estimating above-ground carbon biomass in a newly restored coastal plain wetland using remote sensing.
title_short Estimating above-ground carbon biomass in a newly restored coastal plain wetland using remote sensing.
title_full Estimating above-ground carbon biomass in a newly restored coastal plain wetland using remote sensing.
title_fullStr Estimating above-ground carbon biomass in a newly restored coastal plain wetland using remote sensing.
title_full_unstemmed Estimating above-ground carbon biomass in a newly restored coastal plain wetland using remote sensing.
title_sort estimating above-ground carbon biomass in a newly restored coastal plain wetland using remote sensing.
publisher Public Library of Science (PLoS)
series PLoS ONE
issn 1932-6203
publishDate 2013-01-01
description Developing accurate but inexpensive methods for estimating above-ground carbon biomass is an important technical challenge that must be overcome before a carbon offset market can be successfully implemented in the United States. Previous studies have shown that LiDAR (light detection and ranging) is well-suited for modeling above-ground biomass in mature forests; however, there has been little previous research on the ability of LiDAR to model above-ground biomass in areas with young, aggrading vegetation. This study compared the abilities of discrete-return LiDAR and high resolution optical imagery to model above-ground carbon biomass at a young restored forested wetland site in eastern North Carolina. We found that the optical imagery model explained more of the observed variation in carbon biomass than the LiDAR model (adj-R(2) values of 0.34 and 0.18 respectively; root mean squared errors of 0.14 Mg C/ha and 0.17 Mg C/ha respectively). Optical imagery was also better able to predict high and low biomass extremes than the LiDAR model. Combining both the optical and LiDAR improved upon the optical model but only marginally (adj-R(2) of 0.37). These results suggest that the ability of discrete-return LiDAR to model above-ground biomass may be rather limited in areas with young, small trees and that high spatial resolution optical imagery may be the better tool in such areas.
url http://europepmc.org/articles/PMC3695897?pdf=render
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