Paper Info
Title
Sensitivity of Multi-Source SAR Backscatter to Changes in Forest Aboveground Biomass
Abstract
Accurate estimates of forest aboveground biomass (AGB) after anthropogenic disturbance could reduce uncertainties in the carbon budget of terrestrial ecosystems and provide critical information to policy makers. Yet, the loss of carbon due to forest disturbance and the gain from post-disturbance recovery have not been sufficiently assessed. In this study, a sensitivity analysis was first conducted to investigate: (1) the influence of incidence angle and soil moisture on Synthetic Aperture Radar (SAR) backscatter; (2) the feasibility of cross-image normalization between multi-temporal and multi-sensor SAR data; and (3) the possibility of applying normalized backscatter data to detect forest biomass changes. An empirical model was used to reduce incidence angle effects, followed by cross-image normalization procedure to lessen soil moisture effect. Changes in forest biomass at medium spatial resolution (100 m) were mapped using both spaceborne and airborne SAR data. Results indicate that (1) the effect of incidence angle on SAR backscatter could be reduced to less than 1 dB by the correction model for airborne SAR data; (2) over 50% of the changes in SAR backscatter due to soil moisture could be eliminated by the cross-image normalization procedure; and (3) forest biomass changes greater than 100 Mg center dot ha(-1) or above 50% of 150 Mg center dot ha(-1) are detectable using cross-normalized SAR data.
Year
DOI
Venue
2015
10.3390/rs70809587
REMOTE SENSING
Keywords
Field
DocType
incidence angle
Biomass,Soil science,Normalization (statistics),Synthetic aperture radar,Remote sensing,Terrestrial ecosystem,Backscatter,Water content,Geology,Image resolution,Multi-source
Journal
Volume
Issue
ISSN
7
8
2072-4292
Citations 
PageRank 
References 
2
0.38
16
Authors
5
Name
Order
Citations
PageRank
Wenli Huang1305.75
Guoqing Sun216249.24
Wenjian Ni33213.56
Zhiyu Zhang44113.64
ralph o dubayah5356.74