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

J.E.S. Fransson ; J. Wallerman ; A. Gustavsson ; Lars M. H. Ulander (Institutionen för rymd- och geovetenskap, Radarfjärranalys)
International Geoscience and Remote Sensing Symposium (IGARSS) p. 161-164. (2013)
[Konferensbidrag, refereegranskat]

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.

Nyckelord: backscatter , estimation , forest management , regression , SAR



Denna post skapades 2014-03-14. Senast ändrad 2016-05-24.
CPL Pubid: 195018

 

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Institutioner (Chalmers)

Institutionen för rymd- och geovetenskap, Radarfjärranalys

Ämnesområden

Geovetenskap och miljövetenskap

Chalmers infrastruktur