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Measurements of Forest Biomass Change Using P-Band Synthetic Aperture Radar Backscatter

Gustaf Sandberg (Institutionen för rymd- och geovetenskap, Radarfjärranalys) ; Lars M. H. Ulander (Institutionen för rymd- och geovetenskap, Radarfjärranalys) ; J. Wallerman ; J. E. S. Fransson
IEEE Transactions on Geoscience and Remote Sensing (0196-2892). Vol. 52 (2014), 10, p. 6047-6061.
[Artikel, refereegranskad vetenskaplig]

Methods to estimate forest biomass change have been investigated using experimental P-band synthetic aperture radar (SAR) data from the recent airborne campaigns BioSAR 2007 and BioSAR 2010 conducted over a hemiboreal test site in southern Sweden. Regression models based on backscatter change were developed using reference biomass change maps derived from high-density laser scanning data. Different regression models were developed for linear, square root, and logarithmic biomass change scales. The models were compared to the change maps based on laser data using twofold cross-validation, and estimation errors were evaluated using six 80 m by 80 m plots with detailed in situ measurements. The results indicate that the root-mean-square error of biomass change estimates based on P-band SAR backscatter data is about 15% or 20 t/ha. This suggests that not only clear-cuts but also growth and thinning can be measured. Simulations were performed in order to evaluate the possibility of using a space-borne P-band SAR for measurements of forest biomass change. The simulations show that, with 64 equivalent number of looks (ENL) and a 50% change in biomass, it is possible to correctly indicate whether the forest has gained or lost biomass. Similarly, for a biomass loss of more than 75%, a correct indication of the sign of biomass change can be achieved with only 8 ENL.

Nyckelord: Biomass, forestry, P-band, radar, UHF

Denna post skapades 2014-07-10. Senast ändrad 2016-05-24.
CPL Pubid: 200369


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Institutioner (Chalmers)

Institutionen för rymd- och geovetenskap, Radarfjärranalys (2010-2017)


Geovetenskap och miljövetenskap

Chalmers infrastruktur