Title :
Biomass retrieval algorithm based on P-band biosar experiments of boreal forest
Author :
Ulander, Lars M H ; Sandberg, Gustaf ; Soja, Maciej J.
Author_Institution :
Swedish Defence Res. Agency (FOI), Linkoping, Sweden
Abstract :
A new biomass retrieval algorithm based on P-band multi- polarization backscatter has been developed and evaluated based on SAR and ground data over boreal forest. SAR data collections were conducted on three dates at a test site in southern Sweden (Remningstorp, biomass <; 300 tons/ha; late winter to early summer 2007) and on a single date at a test site in northern Sweden (Krycklan, biomass <; 200 tons/ha; fall 2008). The retrieval algorithm is a multiple linear regression model including the HV-polarized backscatter coefficient, the VV/HH backscatter ratio and the ground slope. Regression coefficients were determined from Krycklan data followed by algorithm evaluation using Remningstorp data. The results from the latter show that RMS errors vary in the range 29-42 tons/ha depending on date and stand type. The new algorithm is also compared with alternative algorithms and found to give significantly better performance. The developed model is a significant step towards an algorithm which gives consistent results across multiple sites and dates, i.e. when forest structure, topography and moisture conditions is expected to vary.
Keywords :
forestry; geophysical signal processing; regression analysis; remote sensing by radar; synthetic aperture radar; topography (Earth); vegetation mapping; HV polarized backscatter coefficient; Krycklan; P-band BioSAR experiments; Remningstorp; VV-HH backscatter ratio; biomass retrieval algorithm; boreal forest; forest structure; ground slope; moisture conditions; multiple linear regression model; multipolarization backscatter SAR; northern Sweden; regression coefficients; southern Sweden; topography; Backscatter; Biological system modeling; Biomass; Contracts; Earth; Remote sensing; Surfaces; BIOMASS; BioSAR; P-band; SAR; backscatter; biomass; boreal forest; retrieval algorithm;
Conference_Titel :
Geoscience and Remote Sensing Symposium (IGARSS), 2011 IEEE International
Conference_Location :
Vancouver, BC
Print_ISBN :
978-1-4577-1003-2
DOI :
10.1109/IGARSS.2011.6050168