Keynote and Invited Speakers
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"Progress in emulation: blending physical models with machine learning for fast vegetation properties
mapping" Dr. Jochem Verrelst University of Valencia, Spain |
Physical radiative transfer models (RTMs) of leaf and canopies with sufficient realism enable the quantitative retrieval of biophysical variables from imaging spectroscopy through numerical inversion. They can serve as tools for precision farming application, e.g. for mapping the health status of the crop. However, advanced RTMs are computationally intensive, which hampers practical applicability of inversion schemes against remote sensing images. To bypass the computational load of such RTMs, it has been proposed to approximate these models by means of statistical learning, i.e. emulation. The principle of emulation is, once an accurate emulator has been developed, it can approximate the original model - and this at a tiny fraction of the original speed - and be readily applied in tedious processing applications. This technique opens a variety of new opportunities in using complex RTM-like emulators in remote sensing applications. For instance, with respect to vegetation properties mapping, the hypothesis is that when the original RTM is replaced by its emulated counterpart, then numerical inversion can go very fast and can become again a truly attractive and generally applicable retrieval method. Moreover, when obtaining an accurate emulator of a computationally expensive RTM with high realism, then in principle the inversion scheme does not only run fast, but it can also infer vegetation properties more accurately.
In this contribution, I will give an overview of latest advances in the usage of emulators for vegetation properties mapping applications. Main emphasis will be on fast and automated quantification of vegetation properties from optical imagery. But also an overview of other emulation applications will be given, including global sensitivity analysis, synthetic scene generation and atmospheric correction strategies. This presentation will close with guidelines how emulation can be easily applied into tedious image processing applications.
