Skip to main content
SLU publication database (SLUpub)

Conference paper2012Peer reviewed

Estimating biomass and height using DSM from satellite data and DEM from high-resolution laser scanning data

Persson, Henrik; Wallerman, Jörgen; Olsson, Håkan; Fransson, Johan


In this study, dense hemi-boreal forest biomass and height estimation was investigated based on optical satellite data and a high quality Digital Elevation Model (DEM) from airborne laser scanning. This analysis was carried out on data collected 2008-2010 over the test site Remningstorp in southern Sweden. The optical sensors SPOT-5 HRS and ASTER were tested to process a Digital Surface Model (DSM), i.e. the vegetation height above mean sea level, that is used together with the DEM (derived from laser data) to calculate a Canopy Height Model (CHM) as the difference between the former ones. By modeling biomass and height using regression analysis on spectral data from SPOT-5 HRG and height metrics from the CHM an improved Root Mean Squared Error (RMSE) and adjusted R2 is expected, compared to using the single data sources alone. The best results showed a relative RMSE for standwise prediction of mean biomass and height of 30.3% and 23.3%, respectively. Adding CHM data to a spectral based (HRG) prediction model improved the mapping accuracy roughly 3%. In conclusion, the estimation accuracy did not improve significantly by adding height metrics to spectral data.

Published in

IEEE International Geoscience and Remote Sensing Symposium proceedings
2012, pages: 1649-1651
ISBN: 978-1-4673-1159-5
Publisher: IEEE


2012 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)