Estimation of forest biomass using L-band backscatter microwave satellite data.
Keywords: Biomass regression models, Synthetic Aperture Radar, L-band backscatter.
AbstractSynthetic Aperture Radar (SAR) satellite data can be used to monitor spatial and temporal changes in forest biomass and timber volume. Previous research suggest the SAR L-band backscatter signals saturate at a relatively low stand biomass threshold, making the application limited to thicket stage crops. In this study, new biomass and L-band backscatter regression models were developed using procedures to reduce interference due to radar incidence angle and surface moisture and by applying cross-image calibration using both forest and non-forest plot data to increase the biomass saturation point for stand biomass and volume. Many of the widely published model formulations were found not to provide a suitable model fit because of non-normal distribution and evidence of heteroskedasticity of model residuals. The model re-developed in this study performed better than published models, based on lower Akaike Information Criteria values and no heteroskedasticity of model residuals. The backscatter saturation for the re-developed model occurred at biomass values of c. 100 Mg ha-1, so accurate determination of biomass using this approach may be limited to immature forest stands. However, the L-band backscatter-biomass model may be suitable to detect changes in forest biomass or volume due to disturbance events.
How to Cite
Black, K., Nieuwenhuis, M., Cawkwell, F., & Balaji, P. (2017). Estimation of forest biomass using L-band backscatter microwave satellite data. Irish Forestry Journal. Retrieved from http://journal.societyofirishforesters.ie/index.php/forestry/article/view/10815