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Remote Sens. 2017, 9(8), 816; doi:10.3390/rs9080816

Mapping Aboveground Carbon in Oil Palm Plantations Using LiDAR: A Comparison of Tree-Centric versus Area-Based Approaches

1
Forest Ecology and Conservation Group, Department of Plant Sciences, University of Cambridge, Downing Street, Cambridge CB2 3EA, UK
2
Silwood Park Campus, Imperial College London, Buckhusrt Road, Ascot SL5 7PY, UK
3
Department of Zoology, University of Cambridge, Downing Street, Cambridge CB2 3EJ, UK
*
Author to whom correspondence should be addressed.
Received: 19 June 2017 / Revised: 23 July 2017 / Accepted: 4 August 2017 / Published: 9 August 2017
(This article belongs to the Section Forest Remote Sensing)
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Abstract

Southeast Asia is the epicentre of world palm oil production. Plantations in Malaysia have increased 150% in area within the last decade, mostly at the expense of tropical forests. Maps of the aboveground carbon density (ACD) of vegetation generated by remote sensing technologies, such as airborne LiDAR, are vital for quantifying the effects of land use change for greenhouse gas emissions, and many papers have developed methods for mapping forests. However, nobody has yet mapped oil palm ACD from LiDAR. The development of carbon prediction models would open doors to remote monitoring of plantations as part of efforts to make the industry more environmentally sustainable. This paper compares the performance of tree-centric and area-based approaches to mapping ACD in oil palm plantations. We find that an area-based approach gave more accurate estimates of carbon density than tree-centric methods and that the most accurate estimation model includes LiDAR measurements of top-of-canopy height and canopy cover. We show that tree crown segmentation is sensitive to crown density, resulting in less accurate tree density and ACD predictions, but argue that tree-centric approach can nevertheless be useful for monitoring purposes, providing a method to detect, extract and count oil palm trees automatically from images. View Full-Text
Keywords: oil palm plantation; aboveground carbon density; laser scanning, LiDAR; crown segmentation; canopy cover; top of canopy height oil palm plantation; aboveground carbon density; laser scanning, LiDAR; crown segmentation; canopy cover; top of canopy height
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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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Nunes, M.H.; Ewers, R.M.; Turner, E.C.; Coomes, D.A. Mapping Aboveground Carbon in Oil Palm Plantations Using LiDAR: A Comparison of Tree-Centric versus Area-Based Approaches. Remote Sens. 2017, 9, 816.

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