摘要
选择1992、2000和2010年的DMSPOLS灯光数据，改进了基于统计数据提取城镇用地的算法，使用Py．thon语言编程实现3个时期中国城市建成区的提取。利用ArcGIS10、VisualFoxPro6．0等软件，选择城市形态紧凑度和城市扩张速度2个指标，分别从城市规模（超大城市、特大城市、大城市、中等城市和小城市）、大区域（东部、中部、西部和东北区）、省级行政区划（省、自治区和直辖市）3个空间尺度分析了城市的空间扩张情况。结果表明：①从城市形态紧凑度来看，同一年份，城市规模越大，城市外部形态紧凑度越小；而中、西部城市平均紧凑度大于东部、东北部。1992～2010年，除大城市和小城市平均紧凑度指数略微变小、基本不变外，其余各等级城市均变大；东部和西部城市平均紧凑度指数变小，而东北和中部变大。②从城市扩张速度来看，同一时间段内，城市规模越大，城市建成区年均扩张速度越大；1992-2010年，东部城市建成区扩张速度最大，东北最小，中、西部次之；其中，北京、重庆、上海、天津扩张速度大，广东、江苏、山东、浙江和福建扩张速度次之，其余省份扩张速度较小；近20a来，所有等级城市、不同区域城市以及各个省份内城市建成区在加速扩张。关键词：城市空间扩张；灯光数据；紧凑度；扩张速度；
An existing algorithm based on the statistical data was refined, and a Python implementation of the improved algorithm was programmed to extract the built-up areas of 656 cities in 1992, 2000, and 2010 based on DMSP OLS nighttime light data. ArcGIS 10 and Visual FoxPro 6.0 were used to analyze the characteristics of the expansion of the cities. This study selected 2 indices, the compactness of urban external spatial morphol- ogy （CUESM） and the speed of urban spatial expansion （SUSE）, to analyze the spatial expansion of county- and higher-level cities in China from 3 aspects： the sizes of cities （metropolises, large cities, medium-sized cit- ies, and small cities）, large regions （eastern, central, western, and northeastern China）, and administrative divi- sions of China （provinces, autonomous regions, and municipalities）. The results are as follows. First, during the same year, the values of CUESM were getting smaller with increasing city, and were larger in central and western China than those in the eastern and northeastern China. During the period of 1992-2010, the values of CUESM became slightly smaller in large cities, almost unchanged in small cities, and got larger in the cities of other sizes. The values of CUESM became smaller in the eastern and western China, but they got larger in the central and northeastern China from 1992 to 2010. Secondly, during the same period, SUSE increased with ur- ban size. From 1992 to 2010, SUSE was high in the eastern China, low in the central and western China, and the lowest in the northeastern China. SUSE was high in Beijing, Chongqing, Shanghai, and Tianjin, low in Guangdong, Jiangsu, Shandong, Zhejiang, and Fujian, and the lowest in the rest of the provinces in China. From 1992 to 2010, SUSE accelerated in all sizes, regions and provinces.
出处
《地理科学》
CSCD
北大核心
2014年第2期129-136,共8页
Scientia Geographica Sinica
基金
国家自然科学基金(41171143
40771064)
教育部新世纪优秀人才计划(NCET-07-0398)
中央高校基本科研业务费专项资金重点项目(lzujbky-2012-k35)资助
