Imperial College London
Portrait Picture

ProfessorRobertEwers

Faculty of Natural Sciences, Department of Life Sciences (Silwood Park)

Professor of Ecology
 
 
 
//

Contact

 

+44 (0)20 7594 2223r.ewers

 
 
//

Location

 

1.4Centre for Population BiologySilwood Park

//

Summary

 

Publications

Citation

BibTex format

@article{Nunes:2017:10.3390/rs9080816,
author = {Nunes, MH and Ewers, RM and Turner, EC and Coomes, DA},
doi = {10.3390/rs9080816},
journal = {Remote Sensing},
title = {Mapping Aboveground Carbon in Oil Palm Plantations Using LiDAR: A Comparison of Tree-Centric versus Area-Based Approaches},
url = {http://dx.doi.org/10.3390/rs9080816},
volume = {9},
year = {2017}
}
Download

RIS format (EndNote, RefMan)

TY  - JOUR
AB  - 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 asairborne 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 todetect, extract and count oil palm trees automatically from images.
AU  - Nunes,MH
AU  - Ewers,RM
AU  - Turner,EC
AU  - Coomes,DA
DO  - 10.3390/rs9080816
PY  - 2017///
SN  - 2072-4292
TI  - Mapping Aboveground Carbon in Oil Palm Plantations Using LiDAR: A Comparison of Tree-Centric versus Area-Based Approaches
T2  - Remote Sensing
UR  - http://dx.doi.org/10.3390/rs9080816
UR  - http://hdl.handle.net/10044/1/50361
VL  - 9
ER  -
Download