摘要:基于大数据分析思路和数据挖掘工具，在县级尺度上，利用2010年第六次人口普查数据，计算各县的平均人口密度，以及合成海拔（地带性因素）、环境脆弱性、人生气候指数、农业生产潜力、适宜水资源偏离度、交通便捷性、区位指数等，克鲁格曼Krugman所谓的区域地理本性特征，对胡焕庸线的存在的地理基础和生态学基础进行了分析。研究结果表明：（1）中国人口密度与合成海拔、环境脆弱性、人生气候指数、适宜水资源偏离度、农业生产潜力等生态学因素密切相关，与交通便捷性、GDP和区位指数等显著相关。（2）对大多数省的人口密度的影响的贡献率排在强烈的是合成海拔、农业生产潜力和和水资源适应度，其次是交通便捷性和区位指数；它们是克鲁格曼Krugman新经济地理学认识的第一次区域本性和第二次地理本性因素。（3）新疆、山东、宁夏、内蒙古、黑龙江、江苏、北京和天津的人口分布比较独特，还需引入新的因子来解释其人口分布的影响因素；（4）胡焕庸线沿线是一个生态脆弱地带。研究基本展现了中国人口的空间分布的胡焕庸线的地理学与生态基础。



Abstract:Based on big-data analysis, this paper used the data of the sixth census in 2010 to calculate the average population density of each county. Based on Krugman's geographic nature features, including synthesis of altitude, environmental vulnerability, and productive potentiality of agriculture, human climate index, and appropriate deviation degree of water resources, traffic convenience, the locational index and GDP were selected, the geographical and ecological basis of HU Line existence are analyzed. The results showed that:(1) China's population density was closely related to ecological factors such as synthetic altitude, environmental vulnerability, human climate index, appropriate deviation degree of water resources, and productive potentiality of agriculture, and was significantly related to traffic convenience, GDP, and location index. (2) In most provinces, the synthetic altitude, productive potentiality of agriculture and appropriate deviation degree of water resources contributed most to the population density, followed by transportation convenience and location index. They wew the first nature and the second nature factors recognized by Krugman's new geography. (3) The population distribution is special in Xinjiang, Shandong, Ningxia, Inner Mongolia, Heilongjiang, Jiangsu, Beijing and Tianjin, and new factors should be introduced to explain the population distribution. (4) The HU Line is an ecologically fragile zone. This paper presents the geographical and ecological basis of HU Line, which is the dividing line of spatial distribution of Chinese population.





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