Skip to content
Home
About Us
Resources
Profiles Metrics
Authors Directory
Institutions Directory
Top Authors
Top Institutions
Top Sponsors
AI Digest
Contact Us
Menu
Home
About Us
Resources
Profiles Metrics
Authors Directory
Institutions Directory
Top Authors
Top Institutions
Top Sponsors
AI Digest
Contact Us
Home
About Us
Resources
Profiles Metrics
Authors Directory
Institutions Directory
Top Authors
Top Institutions
Top Sponsors
AI Digest
Contact Us
Menu
Home
About Us
Resources
Profiles Metrics
Authors Directory
Institutions Directory
Top Authors
Top Institutions
Top Sponsors
AI Digest
Contact Us
Publication Details
AFRICAN RESEARCH NEXUS
SHINING A SPOTLIGHT ON AFRICAN RESEARCH
agricultural and biological sciences
A universal airborne LiDAR approach for tropical forest carbon mapping
Oecologia, Volume 168, No. 4, Year 2012
Notification
URL copied to clipboard!
Description
Airborne light detection and ranging (LiDAR) is fast turning the corner from demonstration technology to a key tool for assessing carbon stocks in tropical forests. With its ability to penetrate tropical forest canopies and detect three-dimensional forest structure, LiDAR may prove to be a major component of international strategies to measure and account for carbon emissions from and uptake by tropical forests. To date, however, basic ecological information such as height-diameter allometry and stand-level wood density have not been mechanistically incorporated into methods for mapping forest carbon at regional and global scales. A better incorporation of these structural patterns in forests may reduce the considerable time needed to calibrate airborne data with ground-based forest inventory plots, which presently necessitate exhaustive measurements of tree diameters and heights, as well as tree identifications for wood density estimation. Here, we develop a new approach that can facilitate rapid LiDAR calibration with minimal field data. Throughout four tropical regions (Panama, Peru, Madagascar, and Hawaii), we were able to predict aboveground carbon density estimated in field inventory plots using a single universal LiDAR model (r2 = 0.80, RMSE = 27.6 Mg C ha-1). This model is comparable in predictive power to locally calibrated models, but relies on limited inputs of basal area and wood density information for a given region, rather than on traditional plot inventories. With this approach, we propose to radically decrease the time required to calibrate airborne LiDAR data and thus increase the output of high-resolution carbon maps, supporting tropical forest conservation and climate mitigation policy. © 2011 Springer-Verlag.
Authors & Co-Authors
Asner, Gregory P.
United States, Washington, D.c.
Carnegie Institution of Washington
Mascaro, Joseph
United States, Washington, D.c.
Carnegie Institution of Washington
United States, Washington, D.c.
Smithsonian Tropical Research Institute
Muller-Landau, Helene C.
United States, Washington, D.c.
Smithsonian Tropical Research Institute
Vieilledent, Ghislain
France, Paris
Cirad
Vaudry, Romuald
France, Paris
Goodplanet Foundation
Rasamoelina, Maminiaina
Madagascar, Antananarivo
Wwf Antananarivo
Hall, Jefferson Scott
United States, Washington, D.c.
Smithsonian Tropical Research Institute
Van Breugel, Michiel
United States, Washington, D.c.
Smithsonian Tropical Research Institute
Statistics
Citations: 376
Authors: 8
Affiliations: 5
Identifiers
Doi:
10.1007/s00442-011-2165-z
ISSN:
00298549
Research Areas
Environmental
Health System And Policy
Study Locations
Madagascar