Estimation of stem volume in hemi-boreal forests using airborne low-frequency Synthetic Aperture Radar and lidar data
Paper in proceedings, 2013

Synthetic Aperture Radar (SAR) backscatter data from the Swedish airborne CARABAS-II and LORA systems were used to estimate stem volume at stand level. The study was performed in hemi-boreal forests at the Remningstorp test site, located in southern Sweden. In total, ten 80 m × 80 m stands, where all trees were measured in situ, with stem volumes in the range of 70-530 m 3 ha-1 (on average 347 m3 ha-1) were analyzed. SAR data from CARABAS-II and LORA were acquired from two different years, with nine unique flight headings that were repeated for each system and year. Regression analysis was used to estimate stem volume and the accuracy was assessed in terms of Root Mean Square Error (RMSE). As a first step, stem volume was estimated for each flight heading separately. The accuracy assessment was then performed by weighting the separate estimates for each system and year inversely proportionally to the variance about the regression function. The best results for CARABAS-II and LORA showed a relative RMSE of 7% and 24% of the mean stem volume, respectively. In a previous study, stem volume was estimated using LiDAR data and the same forest stands, resulting in an RMSE of about 12%. In conclusion, the estimation accuracy of stem volume using combined low-frequency CARABAS SAR images was found to be superior to that from using LiDAR data for the stands investigated.

estimation

forest management

SAR

backscatter

regression

Author

J.E.S. Fransson

Swedish University of Agricultural Sciences (SLU)

J. Wallerman

Swedish University of Agricultural Sciences (SLU)

A. Gustavsson

Swedish Defence Research Agency (FOI)

Lars Ulander

Chalmers, Earth and Space Sciences, Radar Remote Sensing

International Geoscience and Remote Sensing Symposium (IGARSS)

161-164

Subject Categories

Earth and Related Environmental Sciences

DOI

10.1109/IGARSS.2013.6721116

ISBN

978-147991114-1

More information

Latest update

4/11/2018