Estimation of Forest Biomass and Faraday Rotation Using Polarimetric L-/P-band SAR
Licentiate thesis, 2009
At present the greatest source of uncertainty in the global carbon cycle is in the terrestrial
ecosystems. In order to reduce these uncertainties it is necessary to provide consistent and
accurate global estimates of the biomass contained in the forests of the world. One of the
most promising methods for obtaining such estimates is through polarimetric SAR
backscatter measurements at L-and P-band frequencies. This thesis aims to investigate the
possibility of retrieving forest biomass from L- or P-band SAR backscatter data. It also
concerns SAR image calibration. Well calibrated systems are necessary to ensure that errors
in estimates of physical properties, e.g. forest biomass, are not enlarged by noise or image
distortions. Both system distortions, such as leakage between polarization channels, and
distortions caused by the ionosphere are studied.
A calibration analysis was made on data from the L-band PALSAR system onboard the
Japanese ALOS satellite. The data was shown to be of good quality, especially in terms of
radiometric stability and leakage between polarization channels. Following this an analysis of
Faraday rotation, i.e. image distortions caused by the ionosphere, was made for the PALSAR
images. It was shown that Faraday rotation can be measured and corrected in PALSAR
image, at least if the Faraday rotation is small.
Forest biomass retrieval algorithms for P- and L-band SAR backscatter were developed and
evaluated using data from the BioSAR-I campaign conducted in southern Sweden in 2007. It
was found that HV- and HH-polarized backscatter was strongly related to biomass for both Land
P-band. However, the L-band backscatter was found to have decreased sensitivity to
biomass for forest stands with biomass larger than about 200 tons/ha, resulting in an
increased error in the biomass estimates. For P-band this problem was not seen, and it was
found that the biomass on stand level could be estimated using HV- and /or HH-polarized Pband
backscatter with an error of 20-25% of the mean biomass for stands with biomass
ranging from 10 to 290 tons/ha.
linear regression
Remote sensing
forest biomass retrieval
P-band
synthetic aperture radar (SAR)
calibration
L-band
EA-salen, EDIT huset, Hörsalsvägen 11, Chalmers, Göteborg.
Opponent: Mats Pettersson, Department of Signal Processing, Blekinge Institute of Technology, Sweden