DocumentCode
576121
Title
Airborne LiDAR measurements to estimate tropical peat swamp forest Above Ground Biomass
Author
Ballhorn, Uwe ; Jubanski, Juilson ; Kronseder, Karin ; Siegert, Florian
Author_Institution
RSS Remote Sensing Solutions GmbH, Baierbrunn, Germany
fYear
2012
fDate
22-27 July 2012
Firstpage
1660
Lastpage
1663
Abstract
We estimated forest Above Ground Biomass (AGB) of tropical peat swamp forests in the Indonesian province of Central Kalimantan through correlating airborne Light Detection And Ranging (LiDAR) data to forest inventory data. Two LiDAR point cloud metrics, the Quadratic Mean Canopy profile Height (QMCH) and the Centroid Height (CH), were correlated to the field derived AGB estimates. The regression models could be improved through the use of the LiDAR point densities as input. The highest coefficient of determination was achieved for CH (R2= 0.88; n= 52). Surveying with a LiDAR point density between 2-4 points per square meter (pt/m2) resulted in the best cost-benefit ratio. It was also shown that impact from logging and the associated AGB losses dating back more than 10 years could still be assessed by LiDAR but not by multispectral satellite imagery. Comparison with a Landsat based AGB estimate showed an overestimation of 60.8% in a 3.0 million ha study area.
Keywords
airborne radar; cost-benefit analysis; geophysical image processing; optical radar; regression analysis; remote sensing by radar; vegetation; vegetation mapping; AGB losses; Central Kalimantan; Centroid Height; Indonesian province; Landsat based AGB estimate; LiDAR point cloud metrics; LiDAR point densities; Quadratic Mean Canopy profile Height; airborne LiDAR measurements; airborne Light Detection And Ranging data; coefficient of determination; cost-benefit ratio; field derived AGB estimates; forest inventory data; multispectral satellite imagery; regression models; tropical peat swamp forest above ground biomass; Accuracy; Biomass; Carbon dioxide; Estimation; Laser radar; Remote sensing; Satellites; Indonesia; LiDAR; REDD; forest biomass; tropical peat swamp forest;
fLanguage
English
Publisher
ieee
Conference_Titel
Geoscience and Remote Sensing Symposium (IGARSS), 2012 IEEE International
Conference_Location
Munich
ISSN
2153-6996
Print_ISBN
978-1-4673-1160-1
Electronic_ISBN
2153-6996
Type
conf
DOI
10.1109/IGARSS.2012.6351208
Filename
6351208
Link To Document