{'fraction_non_alphanumeric': 0.022128060263653482, 'fraction_numerical': 0.006591337099811676, 'mean_word_length': 5.088825214899713, '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}}
Creating urban data using AVHRR thermal-infrared data

Using 1-km advanced very high resolution radiometer (AVHRR) satellite data, relative temperature differences caused by thermal conductivity and inertia allow the separation of urban and nonurban land covers. The goal of this research is to investigate a method of creating a global urban data layer from recent satellite data. AHVRR data that were composited on a biweekly basis and distributed by the U.S. Geological Survey EROS Data Center in Sioux Falls, South Dakota, were used for the classification process. These composited images are based on the maximum normalized difference vegetation index (NDVI) of each pixel during a 2-week period. The resultant images are nearly cloud free and reduce the need for extensive preclassification. In areas of the Western United States, where precipitation is low, the temperature difference between urban areas and rural areas is much less than in the more humid, well-vegetated Eastern United States. Because of this, the initial study was limited to the eastern half of the United States. In the East, the time of maximum temperature difference between the urban surfaces and the vegetated nonurban areas is the peak greenness period. Composite images of the Eastern United States for three 2-week periods were used for determining the urban areas. Two channels of thermal data (channels 3 and 4) and a composited NDVI image were classified using conventional image processing techniques. Although the overall accuracy is low compared with other large-scale urban area delineations, the results indicate the intensity of urban activities within large urban areas. Introduction Global mapping of the Earth's surface on a regular basis is becoming feasible using satellite sensors with moderate surface resolution and daily coverage. The advanced very high resolution radiometer (AVHRR) onboard the NO A A-11 satellite collects data in several spectral bands that have proved valuable for collecting global vegetation data with a resolution of 1-km (table 1). Table 1. Spectral bandwidths of AVHRR data [From Kidwell, 1991]