Efficient radiative transfer model inversion for remote sensing applications |
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Authors: | John Hedley Chris Roelfsema |
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Affiliation: | a School of Biosciences, University of Exeter, EX4 4PS, UK b Center for Remote Sensing and Spatial Information Science, School of Geography, Planning and Environmental Management, University of Queensland, Brisbane, Australia |
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Abstract: | A simple method for efficient inversion of arbitrary radiative transfer models for image analysis is presented. The method operates by representing the shape of the function that maps model parameters to spectral reflectance by an adaptive look-up tree (ALUT) that evenly distributes the discretization error of tabulated reflectances in spectral space. A post-processing step organizes the data into a binary space partitioning tree that facilitates an efficient inversion search algorithm. In an example shallow water remote sensing application, the method performs faster than an implementation of previously published methodology and has the same accuracy in bathymetric retrievals. The method has no user configuration parameters requiring expert knowledge and minimizes the number of forward model runs required, making it highly suitable for routine operational implementation of image analysis methods. For the research community, straightforward and robust inversion allows research to focus on improving the radiative transfer models themselves without the added complication of devising an inversion strategy. |
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Keywords: | Radiative transfer Inversion Look-up table (LUT) Successive approximation |
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