Neural network based models for the retrieval of methane concentration vertical profiles from remote sensing data
نویسندگان
چکیده
Trace gas profile retrieval constitutes an ill-posed inverse problem. This paper explores the potential of the application of neural networks for the retrieval of methane vertical column densities from remote sensed radiances. Three types of neural networks have been tested using noiseless and noisy data. Here we focused on the reconstruction of vertical column densities using SCIAMACHY channel 8 nadir measurements (~ 2.3 mm). Overall, the use of neural networks was able to solve this difficult inverse problem even in the presence of noise in the data. A comparison among different network architectures was accomplished but it was not possible to detect great discrepancies in the performance of them.
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