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Guo Qingsheng, Li Liusuo, Jia Yuming et al. Journal of Changde Teachers University (Natural Science Edition), 2000, 12(1): 78-81. On the method of model distinguishing in grading statistical data of thematic maps.
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Annals of the Association of American Geographers, 2002, 92(4): 662-681. Evaluation of methods for classifying epidemiological data on choropleth maps in series. Annals of the Association of American Geographers, 2003, 93(3): 595-623. Using genetic algorithms to create multicriteria class intervals for choropleth maps. Armstrong Marc P, Xiao Ningchuan, Bennett David A. Key words: population density, population gravity center, curve of population gravity centers, GIS, population More than 3/4 of the Chinese population is concentrated in less than 1/5 of the land area, and more than half of the land area is inhabited by less than 2% of the population, the result reveals a better space law of China's population distribution. The reclassification research on the population density map based on the curve of population gravity centers shows that the Chinese population densities can be divided into nine classes, hereby, the Chinese population geographical distribution can be divided into nine type regions: the concentration core zone, high concentration zone, moderate concentration zone, low concentration zone, general transition zone, relatively sparse area, sparse area, extreme sparse area, and basic no-man's land. The curve of population gravity centers shows the population distribution transits from the high density region to the low one on the whole, however, there are high density region in the low density area and vice versa. The multi-layer superposition based on the population density classification shows that with the increasing of population densities, the population gravity centers of different layers move from the Northwest to the Southeast and have a tendency of becoming dense the multi-layer clustering phenomenon of the Chinese population distribution is obvious, the populations have a water-based characteristic gathering towards the rivers and coastlines. In this paper, with the spatial analysis functions in ArcGIS and the county-level census data of 2000 in China, the population density map was divided and shown by classes, meanwhile, the map system of population distribution and a curve of population gravity centers were formed in accordance with the geographical proximity principle, the classes of population densities were reclassified to obtain a population density map which had the spatial clustering characteristic.