Microwave scattering from mixed-species forests, Queensland, Australia

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Type Article
Original languageEnglish
Pages (from-to)2142-2159
Number of pages18
JournalIEEE Transactions on Geoscience and Remote Sensing
Volume42
Issue number10
DOI
Publication statusPublished - Oct 2004
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Abstract

The potential of synthetic aperture radar (SAR) data for retrieving the above-ground and component (e.g., branch, trunk) biomass of mixed-species forests (including woodlands) typical to subtropical Queensland, Australia, was evaluated using a wave scattering model based on that of Durden et al. (1989). The model was parameterized using field data collected for nine forest types, which were selected through combined analysis of 1 : 4000 aerial photographs and light detection and ranging data. The simulated SAR backscatter data demonstrated a good correspondence at most frequencies and polarizations with Airborne SAR data. Analysis of scattering mechanisms revealed dominance of C-band horizontal-vertical (HV) volume scattering and increases with small-branch/foliage biomass, dominance of L- and P-band HH trunk-ground scattering and increases with trunk biomass, and dominance of L-band HV volume (branch) scattering and increases with large-branch biomass. The study concluded that above-ground biomass estimated using empirical relationships with selected SAR channels will be more reliable for forests of similar structural form due to dominance of microwave interaction with particular biomass components and the strength and consistency of relationships between these and the affiliated components that represent the total. In mixed-species forests, retrieval will be compromised by interaction with a greater diversity of structures and variability in relationships between structural components. Although empirical relationships with selected combinations of channels (e.g., L-band HH/HV) might allow retrieval of component and total biomass of forests containing trees of similar form (e.g., as mapped using Landsat sensor data), the use of SAR inversion models was considered a more appropriate route for retrieving the biomass of forests containing a mix of structural forms.