Abstract
The Global Digital Elevation Model produced from stereo images of Advanced Spaceborne Thermal Emission and Reflection Radiometer data (ASTER GDEM) covers land surfaces between latitudes of 83°N and 83°S. The Phased Array type L-band Synthetic Aperture Radar (PALSAR) onboard Advanced Land Observing Satellite (ALOS) collected many SAR images since it was launched on 24 January 2006. The combination of ALOS/PALSAR interferometric data and ASTER GDEM should provide the penetration depth of SAR data assuming ASTER GDEM was the elevation of vegetation canopy top. It would be correlated with forest biomass because penetration depth could be affected by forest density and forest canopy height. Their combination held great promises for the forest biomass mapping over large area. The feasibility of forest biomass mapping through the data synthesis of ALOS/PALSAR InSAR data and ASTER GDEM was investigated in this study. A procedure for the extraction of penetration depth was firstly proposed. Then three models were built for biomass estimation: (I) model only using backscattering coefficients of ALOS/PALSAR data; (II) model only using penetration depth; (III) model using both of them. The biomass estimated from Lidar data was taken as reference data to evaluate the three different models. The results showed that the combination of backscattering coefficients and penetration depth gave the best accuracy. The forest disturbance has to be considered in forest biomass estimation because of the long time span of ASTER data for generating ASTER GDEM. The spatial homogeneity could be used to improve estimation accuracy.
Highlights
Forest biomass estimation over large area and in higher accuracy becomes more and more important for the research on global climate change and carbon cycle
The accuracy of forest biomass estimation based on the Synthetic Aperture Radar (SAR) backscattering coefficients is limited because backscattering coefficients are affected by environmental factors, such as soil roughness and soil moistures
The concept of penetration depth was proposed based on the synthesis of a digital surface model from stereo images (ASTER Global Digital Elevation Model (GDEM)) and interferometric SAR (ALOS/Phased Array type L-band Synthetic Aperture Radar (PALSAR))
Summary
Forest biomass estimation over large area and in higher accuracy becomes more and more important for the research on global climate change and carbon cycle. Synthetic Aperture Radar (SAR) has been effectively used for assessing forest biomass through the campaigns of airborne and spaceborne SARs. SAR penetrates farther into forest canopies than optical sensors, so the SAR data from forested area are primarily related to standing woody biomass, especially at longer wavelength such as L and P bands. The effect of soil parameters and precipitation prior data acquisition is severe on long wavelength [1,2]. Kasischke et al [1] found that the influence of variations in soil moisture had to be accounted in the mapping of forest biomass. The sensitivity of backscattering coefficients to forest biomass is always reduced when the biomass reaches certain level. As reported by Dobson et al [3], the biomass saturation level for backscattering coefficients was about 200 Mg/ha at P-band and
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
