Title
Sensitivity of multi-source SAR backscatter to changes of forest aboveground biomass
Abstract
Accurate estimates of aboveground biomass (AGB) from forest after disturbance could reduce the uncertainties in carbon budget of terrestrial ecosystem and provide critical information to related carbon policy. Yet the loss of carbon from forest disturbance and the gain from post-disturbance recovery have not been well assessed. In this study, sensitivity analysis was conducted to investigate: (1) influence of factors other than the change of AGB (i.e. distortion caused by incident angle, soil moisture) on SAR backscatter; (2) feasibility of cross-image calibration between multi-temporal and multi-sensor SAR data; and (3) possibility of applying normalized backscatter to detect the post-disturbance AGB recovery. A semi-automatic empirical model was proposed to reduce the incident angle effect. Then, a cross-image normalization procedure was performed in order to remove the radiometric distortions among multi-source SAR data. The results indicate that effect of incident angle and soil moisture on SAR backscatter could be reduced by the proposed procedure, and a detection of biomass changes is possible using multi-temporal and multi-sensor SAR data.
Year
DOI
Venue
2013
10.1109/IGARSS.2013.6723318
IGARSS
Keywords
Field
DocType
radiometry,synthetic aperture radar,post-disturbance aboveground biomass recovery,calibration,sar,moisture,multisource sar backscatter,terrestrial ecosystem,carbon budget,incident angle effect,post-disturbance recovery,cross-image normalization procedure,carbon loss,semiautomatic empirical model,aboveground biomass,remote sensing by radar,carbon policy,forest disturbance,radiometric distortions,soil moisture,multitemporal multisensor sar data,biomass change detection,normalized backscatter,multisource sar data,soil,radar imaging,forest,cross-image calibration,ecology,sensitivity analysis,backscatter,carbon,biomass
Biomass,Soil science,Moisture,Radar imaging,Normalization (statistics),Computer science,Synthetic aperture radar,Remote sensing,Terrestrial ecosystem,Backscatter,Radiometry
Conference
Volume
Issue
ISSN
null
null
2153-6996
ISBN
Citations 
PageRank 
978-1-4799-1114-1
0
0.34
References 
Authors
8
4
Name
Order
Citations
PageRank
Wenli Huang1305.75
Guoqing Sun216249.24
Zhiyu Zhang34113.64
Wenjian Ni43213.56