Estimating aboveground carbon density and its uncertainty in Borneo's structurally complex tropical forests using airborne laser scanning
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Published version
Author(s)
Type
Journal Article
Abstract
Borneo contains some of the world's most biodiverse and carbon-dense tropical forest, but this 750 000 km2 island has lost 62 % of its old-growth forests within the last 40 years. Efforts to protect and restore the remaining forests of Borneo hinge on recognizing the ecosystem services they provide, including their ability to store and sequester carbon. Airborne laser scanning (ALS) is a remote sensing technology that allows forest structural properties to be captured in great detail across vast geographic areas. In recent years ALS has been integrated into statewide assessments of forest carbon in Neotropical and African regions, but not yet in Asia. For this to happen new regional models need to be developed for estimating carbon stocks from ALS in tropical Asia, as the forests of this region are structurally and compositionally distinct from those found elsewhere in the tropics. By combining ALS imagery with data from 173 permanent forest plots spanning the lowland rainforests of Sabah on the island of Borneo, we develop a simple yet general model for estimating forest carbon stocks using ALS-derived canopy height and canopy cover as input metrics. An advanced feature of this new model is the propagation of uncertainty in both ALS- and ground-based data, allowing uncertainty in hectare-scale estimates of carbon stocks to be quantified robustly. We show that the model effectively captures variation in aboveground carbon stocks across extreme disturbance gradients spanning tall dipterocarp forests and heavily logged regions and clearly outperforms existing ALS-based models calibrated for the tropics, as well as currently available satellite-derived products. Our model provides a simple, generalized and effective approach for mapping forest carbon stocks in Borneo and underpins ongoing efforts to safeguard and facilitate the restoration of its unique tropical forests.
Date Issued
2018-06-22
Date Acceptance
2018-06-08
Citation
BIOGEOSCIENCES, 2018, 15 (12), pp.3811-3830
ISSN
1726-4170
Publisher
COPERNICUS GESELLSCHAFT MBH
Start Page
3811
End Page
3830
Journal / Book Title
BIOGEOSCIENCES
Volume
15
Issue
12
Copyright Statement
© 2018 Author(s). This work is distributed under
the Creative Commons Attribution 4.0 License (https://creativecommons.org/licenses/by/4.0/).
the Creative Commons Attribution 4.0 License (https://creativecommons.org/licenses/by/4.0/).
Sponsor
Rainforest Research Sdn Bhd
Identifier
http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000435954900001&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
Grant Number
LBEE_P34395
Subjects
Science & Technology
Life Sciences & Biomedicine
Physical Sciences
Ecology
Geosciences, Multidisciplinary
Environmental Sciences & Ecology
Geology
LIDAR-ASSISTED ESTIMATION
SMALL-FOOTPRINT LIDAR
RAIN-FOREST
NEOTROPICAL FOREST
ALLOMETRIC MODELS
PLOT SIZE
BIOMASS
EMISSIONS
STOCKS
TREES
Publication Status
Published
Date Publish Online
2018-06-22