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Remote Sens. 2018, 10(9), 1446; https://doi.org/10.3390/rs10091446

Exploring the Inclusion of Small Regenerating Trees to Improve Above-Ground Forest Biomass Estimation Using Geospatial Data

1
School of Physical, Environmental and Mathematical Sciences, University of New South Wales, Canberra, ACT BC 2610, Australia
2
Institute of Geography, Vietnam Academy of Science and Technology, Hanoi 100000, Vietnam
3
Graduate University of Science and Technology, Vietnam Academy of Science and Technology, Hanoi 100000, Vietnam
4
School of Science, RMIT University, Melbourne, VIC 3001, Australia
*
Author to whom correspondence should be addressed.
Received: 21 June 2018 / Revised: 3 September 2018 / Accepted: 6 September 2018 / Published: 10 September 2018
(This article belongs to the Section Forest Remote Sensing)
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Abstract

Research on the contribution of understory components to the total above ground biomass (AGB) has to date received very little attention because most prior biomass estimation studies have ignored small regenerating trees beneath the main canopy with the assumption that their contribution to biomass is generally negligible. Only a few biomass studies have emphasized a considerable contribution to biomass of understory components in forest ecosystems. However, this study of native, tropical, deciduous forest biomass in the Central Highlands of Vietnam was able to explore the contribution of small regenerating trees to total biomass by exploiting a large field inventory of hundreds to thousands of individually-counted small regenerating trees per hectare. Thus, this study investigated the influence of small regenerating tree biomass on models of the relationship between total AGB and remote sensing data. These analyses were trained with and without topographic variables derived from ASTER-GDEM. Our results demonstrate that the inclusion of small regenerating understory trees (R2 = 0.42, NRMSE or %RMSE = 30.5%) provides a quantifiable improvement in total estimated AGB compared to using only large woody canopy trees (R2 = 0.21, NRMSE or %RMSE = 36.6%) when correlating field-based biomass measurements with optical image-derived variables. All analyses show that the inclusion of terrain factors made an important contribution to biomass modeling. This study suggests that for young, open forests where there are many small regenerating trees, the contribution of understory biomass should be taken into consideration to improve total AGB estimation. View Full-Text
Keywords: small regenerating trees; understory; above ground biomass (AGB); deciduous forests; biomass estimation small regenerating trees; understory; above ground biomass (AGB); deciduous forests; biomass estimation
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Le, A.V.; Paull, D.J.; Griffin, A.L. Exploring the Inclusion of Small Regenerating Trees to Improve Above-Ground Forest Biomass Estimation Using Geospatial Data. Remote Sens. 2018, 10, 1446.

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