| 基于遥感和GIS的城市扩张稳态指数及其应用 |
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| 引用本文： | 赵国梁,郑新奇,刘东亚,刘飞.基于遥感和GIS的城市扩张稳态指数及其应用[J].农业工程学报,2017,33(11):272-281. |
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| 作者姓名： | 赵国梁 郑新奇 刘东亚 刘飞 |
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| 作者单位： | 中国地质大学(北京)信息工程学院,北京,100083 |
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| 基金项目： | 国土资源部公益性行业科研专项经费项目资助(201511010)。 |
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| 摘 要： | 城市扩张是当今世界的全球化趋势,如何衡量城市扩张状态是城市扩张研究的热点问题。该文从道路网络与城市扩张的互动机制出发,提出一种计算城市扩张稳态的指数(urban expansion steady-state index,UESI)。选取纽约、伦敦、东京等13个世界级城市,利用核密度分析计算道路网络密度,通过遥感解译与空间分析提取近30 a城市扩张信息,最后建立路网密度-城市扩张模型。通过样本UESI指数计算开展比较分析,并对北京2025年城市扩张状态进行了预判。结果表明,UESI能够有效表征城市扩张状态,当UESI达到0.30,城市扩张处于稳定状态。该指数能够有效量化城市扩张状态和潜力,丰富了当前城市扩张量化研究。对于快速发展中城市具有重要的参考价值。
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| 关 键 词： | 土地利用 遥感 网络 城市扩张 稳态指数 扩张周期 特大都市 |
| 收稿时间： | 2017/1/23 0:00:00 |
| 修稿时间： | 2017/6/12 0:00:00 |
Urban expansion steady-state index of urban expansion based on remote sensing and GIS and its applications |
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| Zhao Guoliang,Zheng Xinqi,Liu Dongya and Liu Fei.Urban expansion steady-state index of urban expansion based on remote sensing and GIS and its applications[J].Transactions of the Chinese Society of Agricultural Engineering,2017,33(11):272-281. |
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| Authors: | Zhao Guoliang Zheng Xinqi Liu Dongya and Liu Fei |
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| Institution: | School of Information Engineering; China University of Geosciences, Beijing 100083, China,School of Information Engineering; China University of Geosciences, Beijing 100083, China,School of Information Engineering; China University of Geosciences, Beijing 100083, China and School of Information Engineering; China University of Geosciences, Beijing 100083, China |
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| Abstract: | Abstract: Urban expansion is a globalization trend nowadays, and how to measure the growing degree is a hotspot in the research of urban expansion. Road network is an extremely important factor that drives the increase of urban land. There is an interactive relationship between road network and urban land expansion. The research on the quantitative relationship between those 2 factors is helpful to provide an effective method for sustainable urban development. For the purpose of studying the quantitative index for steady-state urban expansion, in this paper, Beijing, New York, London and other 13 world-class cities were taken as the study areas, and the multi-period remote sensing images and vector data of urban road networks were adopted. Firstly, urban land use vector data were obtained through image interpretation with the aid of a remote sensing and GIS (geographic information system) platform. Then, overlay analysis was utilized to extract urban expansion information. A map of road network density was further generated and manufactured using the density analysis tool in ArcGIS. Secondly, the urban expansion - road network density model was established by regression analysis, which was used for fitting the relationship between road network density and urban expansion speed. Through the calculation and comparison of the sample cities'' values of the turning point and thresholds for urban expansion, urban expansion steady-state index (UESI) was proposed, and then 13 sample cities'' UESI values were calculated. Finally, the urban expansion state of Beijing in 2025 was predicted by using CA (cellular automaton) - Markov model and Logistic regression model. The results proved that (1) compared with the developed cities, Beijing''s urban land expansion was in a serious situation in the past 30 years, and Beijing required the dispersal of population and function in the future; the road network density in Beijing was relatively low and presented a single center, which should be improved and optimized; (2) UESI could effectively quantify the trend of urban expansion; assuming that external environment of urban development was stable, the urban expansion was in a relatively steady state, while UESI reached 0.30. New York, London, Tokyo and other cities'' UESIs were close to or greater than 0.30, while Beijing and Sao Paulo''s UESIs were less than 0.20; Sydney''s USEI was 0.21, which meant Sydney had a great potential for urban land expansion in the future; (3) according to urban expansion quantitative analysis and the theory of urban life cycle, the period of urban expansion could be divided into development period, growth period, maturity period and transition period; and the corresponding typical cities were Mexico City, Beijing, New York and Paris separately; (4) if the current city development trend was kept, the UESI of Beijing in 2025 would be 0.19, more than 0.17 in 2015, and the urban land expansion would remain in the growth period. UESI has the reference value for urban planning in fast-developing cities. The index effectively quantifies the status and potential of urban expansion, and enriches the quantitative study of urban expansion. Understanding the quantitative relationship between road network density and urban expansion is beneficial to define urban development phases, avoid the irregular expansion, and provide new ideas for addressing the inefficient utilization of land and other issues. |
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| Keywords: | land use remote sensing networks urban expansion steady-state index expansion period megalopolis |
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