{'fraction_non_alphanumeric': 0.017857142857142856, 'fraction_numerical': 0.0, 'mean_word_length': 5.494736842105263, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
A fractal-based algorithm for the retrieval of surface parameters from microwave remote-sensed data

The fractional Brownian motion surface model and the small perturbation scattering model are used to devise a new theoretical retrieval algorithm. The surface dielectric constant is estimated by properly combining hh and vv channels, and surface roughness fractal parameters are estimated by using a simple linear regression (in a proper plane) among data measured at different angles (and/or frequencies). The effectiveness of the presented method is assessed by direct comparison with simulated and measured data.