Estimating landscape-scale vegetation carbon stocks using airborne multi-frequency polarimetric synthetic aperture radar (SAR) in the savannahs of north Australia

J COLLINS, Lindsay Hutley, Robyn Williams, Guy Boggs, Darren Bell, R BARTOLO

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    Abstract

    This study investigates the use of polarimetric AirSAR (TopSAR) data for estimating biomass and carbon storage of Eucalyptus miniata (Darwin Woolly Butt) and E. tetrodonta (Stringybark) dominated open-forest savannah in the Northern Territory, Australia. Radar backscatter intensity was correlated with basal area for 30 plots within the Wildman River Reserve, Northern Territory. Published allometric relationships were used to convert tree basal area to estimates of above-ground biomass for each of the measured plots. Below-ground biomass was also estimated for these plots, using additional published allometric relationships between below-ground and above-ground biomass. Backscatter of the L-HV channel had the highest regression co-efficient (r2 = 0.92) with ground-based tree basal area measurements. Using a linear regression equation of backscatter intensity for the L-HV channel versus above-ground biomass gave a mean above-ground biomass of 94 t DM (dry mass) ha-1 for the eucalypt dominated vegetation in the Wildman River Reserve, equivalent to 47 t C-1 stored in this biomass pool. Estimated below-ground biomass was 28t C-1, giving a total carbon biomass storage for this savannah ecosystem of 75t C ha-1. The results of this study indicate that the L-HV channel of polarimetric SAR is best suited to model biomass of the tropical savannahs of northern Australia. Given the vast spatial extent of savannah woodlands across north Australia, SAR has the potential to be a major tool in carbon stock assessment, critical for carbon accounting, as well as to contribute to gaining a better understanding of the role the tropical savannahs of northern Australia play in the biochemical cycles of Australia.
    Original languageEnglish
    Pages (from-to)1141-1159
    Number of pages19
    JournalInternational Journal for Remote Sensing
    Volume30
    Issue number5
    Publication statusPublished - 2009

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