{'fraction_non_alphanumeric': 0.014580801944106925, 'fraction_numerical': 0.0, 'mean_word_length': 5.699186991869919, '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}}
Use of Hyperspectral and High Spatial Resolution Image Data in an Asphalted Urban Road Extraction

With the popularization of the high spatial resolution images of commercial satellites several applications of remote sensing intended for urban tracking has been developed. These images of high spatial resolution generally have limited spectral information. Meanwhile, the main hyperspectrals images available have high spectral resolution and, in return, low spatial resolution. For most urban monitoring applications the spatial information is extremely relevant. Based on that, this work presents the use of high spatial and high resolution spectral images applied to urban monitoring, specifically the extraction and identification of the asphalted urban roads in the city of Mogiguaccedilu, state of Sao Paulo, Brazil.