Title :
An Error Model for Biomass Estimates Derived From Polarimetric Radar Backscatter
Author :
Hensley, Scott ; Oveisgharan, Shadi ; Saatchi, S. ; Simard, Marc ; Ahmed, Rizwan ; Haddad, Ziad
Author_Institution :
Propulsion Lab., California Inst. of Technol., Pasadena, CA, USA
Abstract :
Estimating the amount of above ground biomass in forested areas and the measurement of carbon flux through the quantification of disturbance and regrowth are critical to develop a better understanding of ecosystem processes. Well-resolved and globally consistent inventories of forest carbon must rely on remote sensing measurements, particularly from polarimetric radars. While a wide variety of studies conducted over the past three decades have shown how radar polarimetric measurements can be used to estimate above ground carbon for regions with less than 100 Mg of biomass per hectare, there is no established methodology for assessing biomass estimation accuracy based on a priori instrument and mission parameters. In this paper, a framework for assessing biomass estimation accuracy is presented that is a blend of the basic imaging physics and empirically derived parameters that describe various relationships between biomass and radar polarimetric observable quantities. The implications of this error model on the design and performance of a polarimetric radar are explored using instrument, mission, and science parameters from a notional Earth observing mission.
Keywords :
air pollution; carbon capture and storage; remote sensing by radar; vegetation; above ground biomass; basic imaging physics; biomass estimation accuracy; carbon flux measurement; carbon storage; disturbance quantification; ecosystem processes; error model; forest carbon inventories; forested areas; ground carbon; instrument parameter; mission parameter; notional Earth observing mission; polarimetric radar backscatter; radar polarimetric measurements; regrowth quantification; remote sensing measurements; Backscatter; Biological system modeling; Biomass; Radar measurements; Radar polarimetry; Signal to noise ratio; Backscatter error model; forest biomass; polarimetry; synthetic aperture radar (SAR);
Journal_Title :
Geoscience and Remote Sensing, IEEE Transactions on
DOI :
10.1109/TGRS.2013.2279400