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作 者:赵国梁[1] 郑新奇[1] 刘飞[1] 刘东亚[1]
机构地区:中国地质大学[北京]信息工程学院,北京100083
出 处:《地理科学》2017年第8期1159-1169,共11页Scientia Geographica Sinica
基 金:国土资源部公益性行业科研专项经费项目(201511010)资助~~
摘 要:提出一种基于路网分割应用于区域尺度快速识别城乡边界的方法。该方法利用路网与城市空间格局的强耦合联系,通过城乡斑块地理分割与精度计算确定城市斑块的最优解,识别区域城乡空间。以京津冀为例开展方法验证,分析了区域城乡空间格局、路网特征及城市用地经济效率。结果表明,该方法识别精度较高,可用于低成本、快速、高效的区域城乡空间识别;京津冀城市空间格局呈现"大京津、小河北"的差异性,路网密度特征呈现京、津、石3个显著的高密度区域,二者存在高耦合性;2015年该区域城市用地经济效益总体良好,石家庄、保定、和承德3市综合效率值欠佳,需进一步提高土地利用效率。In recent years, urban expansion is grim with rapid urbanization in China. Border recognition for urban and rural space is the technical prerequisite of urban sprawl control. Existing urban-rural boundary identification methods could accurately extract the city boundaries in theory, but also has some difficulties including data acquisition, poor real-time and heavy workload. Therefore, we proposed an approach based road networks segmentation applied to quickly identify urban border in regional scale. The method was based on strong coupling link between road network and urban spatial structure. Rural patches and urban patches were generated with a geographic division of the road network. By calculating optimal solution of the evaluation accuracy with land use map, rural patches and urban patches were used to identify urban and rural space. Taking Jing-Jin-Ji as an example, the space of urban and rural area was extracted and the related accuracy was verified. Then this article analyzed the spatial pattern of urban and rural, characteristics of road network and economic efficiency of urban land. Results indicated that: 1) The extraction accuracy by this method is high, and it can be used for low-cost, fast and efficient identification for urban-rural space on regional scale; 2) Urban spatial distribution of Jing-Jin-Ji presented a significant differences of"bigger Beijing and Tianjin, smaller Hebei", and characteristics of road network density presented three remarkable high-density region in Beijing,Tianjin and Shijiazhuang, exhibiting high coupling with urban spatial distribution; 3) The economic efficiency of urban land in Jing-Jin-Ji was generally good in 2015 and overall efficiency value in Shijiazhuang, Baoding and Chengde was poor and needed to further improve the efficiency of land use. In total, spatial identification for urban and rural based on road network data have an advantage from real-time data and relatively high computational efficiency, furtherly enriching the existing urban-rural boun
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