Recent advances in data-driven modeling of remote sensing applications in hydrology

Artificial neural networks (ANNs) are very effective statistical models for (1) extracting significant features or characteristics from complex data structures and/or for (2) learning nonlinear relationships involved in any input–output mapping. Another interesting aspect of ANN modeling is the fact that overall performance of these models is not greatly hampered by the presence of error-corrupted values in some input nodes. ANNs have gained …