Clear-Cut Detection in Swedish Boreal Forest Using Multi-Temporal ALOS PALSAR Backscatter Data
Journal article, 2010

An extensive dataset of images acquired by the Advanced Land Observing Satellite (ALOS) Phased Array type L-band Synthetic Aperture Radar (PALSAR) is investigated for clear-cut detection in the county of Västerbotten, Sweden. Strong forest/non-forest contrast and temporal consistency were found for the Fine Beam Dual HV-polarized backscatter in summer/fall. In consequence of a clear-cut between image acquisitions, the HV-backscatter dropped in most cases between 2 and 3 dB. Thus, a simple thresholding algorithm that exploits the temporal consistency of time series of HV-backscatter measurements has been developed for clear-cut detection. The detection algorithm was applied at pixel level to ALOS PALSAR strip images with a pixel size of 50 m. The performance of the detection algorithm was tested with three different threshold values (2.0, 2.5 and 3.0 dB). The classification accuracy increased from 57.4% to 78.2% for decreasing value of the threshold. Conversely, the classification error increased from 3.0% to 9.7%. For about 90% of the clear-felled polygons used for accuracy assessment the proportion of pixels correctly detected as clear-felled was above 50% when using a threshold value of 2.0 dB. For the threshold values of 2.5 and 3.0 dB the corresponding figures were 80% and 65%, respectively. The total area classified as clear-felled during the time frame of the ALOS PALSAR data differed by 5% compared to an estimate of notified fellings for the same period of time when using a detection threshold of 2.5 dB. The performance of the simple detection algorithm is reasonable when aiming at detecting clear-cuts, whereas there are shortcomings in terms of delineation.


SAR backscatter



Kyoto & Carbon Initiative

boreal forest



M. Santoro

Gamma Remote Sensing AG

J.E.S. Fransson

Swedish University of Agricultural Sciences (SLU)

Leif Eriksson

Chalmers, Department of Radio and Space Science, Radar Remote Sensing

Lars Ulander

Chalmers, Department of Radio and Space Science, Radar Remote Sensing

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing

1939-1404 (ISSN)

Vol. 3 4 618-631

Driving Forces

Sustainable development

Subject Categories

Aerospace Engineering

Agricultural Science


Basic sciences



More information

Latest update

9/6/2018 1