The Spatial-Temporal Pattern Analysis of City Development in Countries along the Belt and Road Initiative Based on Nighttime Light Data

LI Deren; YU Hanruo; LI Xi

doi:10.13203/j.whugis20170100

Volume 42 Issue 6

Jun. 2017

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Article Navigation > Geomatics and Information Science of Wuhan University > 2017 > 42(6): 711-720

LI Deren, YU Hanruo, LI Xi. The Spatial-Temporal Pattern Analysis of City Development in Countries along the Belt and Road Initiative Based on Nighttime Light Data[J]. Geomatics and Information Science of Wuhan University, 2017, 42(6): 711-720. doi: 10.13203/j.whugis20170100

Citation:

LI Deren, YU Hanruo, LI Xi. The Spatial-Temporal Pattern Analysis of City Development in Countries along the Belt and Road Initiative Based on Nighttime Light Data[J]. Geomatics and Information Science of Wuhan University, 2017, 42(6): 711-720. doi: 10.13203/j.whugis20170100

The Spatial-Temporal Pattern Analysis of City Development in Countries along the Belt and Road Initiative Based on Nighttime Light Data

doi: 10.13203/j.whugis20170100

LI Deren^{1, 2
,},
YU Hanruo³,
LI Xi^{1, 2
,
,}

1.
State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China
2.
Collaborative Innovation Center of Geospatial Technology, Wuhan University, Wuhan 430079, China
3.
School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China

Funds:

The National Natural Science Foundation of Hubei Province 2014CFB726

Open Research Fund Program of Key Laboratory of Spatial Data Mining and Information Sharing of the Ministry of Education (Fuzhou University) 2016LSDMIS03

Special Scientific Research Fund of Public Welfare Profession on Surveying, Mapping and GeoInformation 201512026

Fundamental Research Funds for the Central Universities 2042016kf0162

More Information

Author Bio:
LI Deren, PhD, professor, academician of Chinese Academy of Science, Chinese Academy of Engineering, and Eurasian Academy of Sciences, specialize in photogrammetry and remote sensing. drli@whu.edu.cn
Corresponding author: LI Xi, associate PhD, professor. E-mail:lixi@whu.edu.cn
Received Date: 2017-04-11
Publish Date: 2017-06-05

Abstract

Based on the DMSP/OLS nighttime light data for the years 1993-2012 and spatial analysis methods including standard deviational ellipse and rank-size distribution, this paper systematically analyzes the spatial structure and spatiotemporal dynamics of the urban system in countries along B & R (The Belt and Road Initiative). We found that nighttime light increased in most countries along B & R. These fast growing countries are undergoing economic reforms and post-war reconstruction, while nighttime light reduction occurs in areas of social and economic unrest. The trend of size distribution of nighttime light in B&R is continuous spatial expansion, and the center of the nighttime light is moving to southeast Asia. The nighttime light distribution in the top 2000 urban places in B&R follows the rank-size distribution, thus urban land distribution is more concentrated than the past. The high rank cities are fairly well developed, but the development of the small cities is lagging behind. The general distribution trend toward, concentration is stronger than decentralization in B&R.
- nighttime light,
- the belt and road initiative,
- city development,
- standard deviational ellipse,
- rank-size distribution

References

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2013年，“一带一路”国家战略(共建“丝绸之路经济带”和“21世纪海上丝绸之路”合作倡议)使亚、欧、非各国联系更加紧密，形成命运共同体^[1]，沿线国家的发展也逐渐成为社会关注的热点。“一带一路”战略地跨亚、欧、非三大洲，涉及国家超过60个，人口超过40亿，了解这些国家与区域的经济发展和社会动态信息有利于中国进行经济战略部署。现阶段利用传统日间可见光遥感影像对“一带一路”区域内的土地覆盖^[2]、生态环境^[3]、灾害监测^[4]等研究较多。夜光遥感影像被广泛地应用于社会经济参数估算^[5]、区域发展研究^[6]、城市化监测^[7]、光污染^[8]等诸多研究领域，能够客观地反应社会经济的变化趋势，便于在空间大尺度下进行时空动态分布研究^[9]，对分析“一带一路”区域内的国家城市发展具有重要意义。

多位学者利用美国军事气象卫星的线性扫描业务系统(Defense Meteorological Satellite Program/Operational Linescan System, DMSP/OLS)和可见红外成像辐射仪(visible infrared imaging radiometer suite, VIIRS)的夜光遥感影像对“一带一路”区域内国家及全球范围进行了相关研究。对于大尺度下的城市研究，Gao等人^[10]利用夜间灯光数据分析了1992~2012年间中国城市化水平动态，发现用DMSP/OLS夜间稳定灯光数据能够相对准确地反映城市化空间扩张水平。对于大尺度下的生态环境研究，Shi等^[11]利用DMSP数据建立二氧化碳排放模型分析中国碳排放与治理情况，发现中国东部地区碳排放明显高于中西部地区；Nghiem等^[12]利用DMSP/OLS夜间灯光数据、日间遥感影像和人口住房数据建立数字表面模型，研究了全球城市土地利用和环境变化情况。在区域经济领域，Yu等^[13]利用夜间灯光数据建立中国县级贫困评估体系，证明了夜光遥感影像可作为评估工具衡量贫困程度；Small等^[14]定性、定量地探究了全球尺度下夜间灯光的时空变化规律；Zhou等^[15]利用夜间灯光数据与国民生产总值数据进行相关性分析，发现在南亚地区夜间灯光与人口、城市范围均呈正相关；李德仁等^[16]从夜间灯光变化量方面评估了“一带一路”沿线部分国家的经济社会发展情况。以上研究主要利用夜光遥感影像针对“一带一路”中某个子区域或个别国家进行定量分析，鲜有对“一带一路”整体区域的城市夜光规模分布的时空动态研究。

各个城市的内外条件不同形成城市间不同的职能分工，城市规模分布的规律性也不尽相同。城市规模分布理论中的位序-规模法则^[17]可用于研究城市人口规模与经济发展阶段的关系^[18]，并适用于国家尺度(美国^[19]、中国^[20]、印度^[21]等)与区域尺度(长三角^[22]、珠三角^[23]、辽中南^[24]等)的城市体系规模分布研究。DMSP/OLS夜光遥感数据能够为大尺度城市规模分布的时空动态研究提供良好支持，杨洋^[24]等将夜光遥感数据与植被数据、地表温度数据结合，研究我国环渤海地区三大城市群的城市规模分布动态。Small等^{[25, 26]}通过对全球尺度下的稳定夜间灯光进行量化，发现位序-规模法则适用于各种强度的人类发展的空间范围研究。Jiang^[27]等人探讨了在全球范围下，基于夜间灯光定义自然城市范围的方法，指出在全球和国家尺度上，夜间灯光分布基本符合捷夫定律。以上研究试图界定城市的行政范围，并不能准确地反应城市发展阶段，通过设定夜间灯光阈值区分城市与非城市区域则更为客观。

本文基于1993~2012年的DMSP/OLS夜间遥感影像数据，利用统计分析、标准差椭圆分析、城市规模分布理论中的位序-规模法则对“一带一路”沿线国家进行夜光规模分布动态研究，从空间内部探究城市夜间灯光整体空间格局变化和时空演化特征。揭示20年间“一带一路”区域夜光规模分布时空动态和演变规律，有助于更好地认识和理解区域发展、空间格局变化、时空演化特征，为经济社会的发展提供参考。

2. 研究方法

本文首先对1993~2012年“一带一路”沿线国家和地区的夜间灯光总量与增量进行统计性研究；其次，基于标准差椭圆方法，分析“一带一路”区域夜间灯光的整体性演化方向；最后，利用城市位序-规模法则分析“一带一路”整体区域与中国的夜光规模分布空间形态和时空演化特征。

2.1. 夜间灯光统计方法

夜光总量L、增长率r分别为：

式中，x_i为第i个像元的DN值。

2.2. 标准差椭圆方法

标准差椭圆空间统计方法(standard deviational ellipse，SDE)能够精确地揭示地理要素空间分布整体特征。标准差椭圆方法基于研究对象的空间区位和空间结构，从全局性空间的角度定量解释地理要素空间分布的中心性、展布性、方向性、空间形态等特征，揭示地理要素的空间分布及时空演化过程。此方法被广泛地用于地形均衡分布^[33]、经济空间格局^[34]、城市问题^[35]等各个领域。标准差椭圆的参数主要包括椭圆重心、方位角、标准差椭圆长短轴。

标准差椭圆的重心(X_w, Y_w)为：

方位角α为：

x轴标准差σ_x和y轴标准差σ_y分别为：

式中，(x_i, y_i)表示研究对象的空间区位；w_i表示对应权重；$\left( {{{\tilde x}_i},{{\tilde y}_i}} \right)$表示各研究对象区位到重心(X_w, Y_w)的坐标偏差。

2.3. 城市位序-规模法则

城市规模分布首先利用DMSP/OLS夜光遥感影像提取出城市建成区范围^{[9, 36, 37]}，再利用位序-规模法则进行分析^{[24, 38]}。Small^[25]指出夜光遥感影像能够提供一个全球一致的亮度阈值以验证捷夫定律。本文选取夜间灯光强度DN=40作为城市识别阈值，即DN≥40的区域被视为城市^[22]，对这些城市区域进行夜间灯光空间规模分布研究。利用位序-规模法则从城市夜光规模和位序的关系分析“一带一路”框架区域和子区域内的夜光规模分布。位序-规模法则用数学模型阐述城市位序与规模分布之间的关系，其公式为：

它是捷夫模式q=1时的特例。对式(7) 作对数变化：

式中，P_i是第i个区域的夜光总量；P₁是最大城市夜光规模；R_i是第i位区域的位序；q是捷夫指数，常用于描述区域规模与位序之间的集中与分散程度。lgP₁值反映第一城市的夜光规模。|q|值接近于1，说明夜光规模分布接近捷夫的理想状态；|q|大于1，说明夜光规模比较集中，大的城市比较发育，中小型城市则不够发育，首位度较高；|q|小于1，说明夜光分布比较分散，高位次城市的夜光规模不是很突出，中小型城市比较发育。对整个区域进行长时间序列动态分析，若|q|增大，说明夜光规模分布趋于集中力量大于分散的力量；反之，若|q|减小，则说明分散的力量大于集中的力量。

4. 结语

本文基于1993~2012年DMSP/OLS夜间灯光影像数据，利用数学统计分析、标准差椭圆、位序-规模法则分析方法，对“一带一路”以及其子区域的夜间灯光城市规模分布进行空间分析。1993~2012年这20年间中国夜光增长率为137%，占“一带一路”总夜光增量的38.37%，夜光空间演化特征不断向西扩张，证实了中国这20年间展开的“西部大开发”等促进区域经济快速均衡化发展的政策富有成效。“一带一路”区域近20年来呈现出不同发展阶段的夜间灯光时空动态变化特征：① 东西轴向性。近20年来“一带一路”区域城市夜间灯光在发育的过程中呈现出明显的东西成长轴线，其中中国、南亚、东南亚的夜间灯光发展成为整个夜光规模体系演化的主导力量。② 区域差异性。区域差异性主要体现在各个子区域的夜光增长情况和空间格局变化差异，“一带一路”区域东亚、东南亚的夜光增长总量和增长率明显高于西部的欧洲和西亚，中亚地区甚至呈现负增长。③ 首位聚集性，指原有的城市对其他区域规模增长起着巨大的辐射和带动作用，整个“一带一路”的城市首位度增大。从区域均衡化发展来看，夜光总量增多而城市体系首位度增大，说明大城市仍有发展空间与趋势，也说明中小城市急需转变经济增长方式，促进产业结构转化升级。

在未来“一带一路”覆盖范围更广的国际大局势下，各个子区域间的相互辐射作用将会增强。利用夜光遥感数据与现有的社会经济统计数据和其他类型遥感数据相结合获取沿线国家的社会经济情况，监测“一带一路”沿线国家发展动态，为区域资源分配和社会评估提供支持。

本研究从统计与空间两个角度分析了“一带一路”夜间灯光的时空格局，但仍存在局限性，数据集在像元聚集区存在“饱和现象”，产生的灯光强度误差和数据波动性对研究结果产生的影响将会在以后的研究中进一步讨论。

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主要地区	国家
蒙中俄	蒙古、俄罗斯、中国
中亚5国	哈萨克斯坦、吉尔吉斯斯坦、塔吉克斯坦、乌兹别克斯坦、土库曼斯坦
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欧洲20国	波兰、捷克、斯洛伐克、匈牙利、斯洛文尼亚、克罗地亚、罗马尼亚、保加利亚、塞尔维亚、黑山、马其顿、波黑、阿尔巴尼亚、爱沙尼亚、立陶宛、拉脱维亚、乌克兰、白俄罗斯、摩尔多瓦、希腊

主要地区	年份	范围/km²	重心坐标	空间增长率/%	空间变化	重心移动距离/km	重心主要移动方向
中亚	1993 2012	1 936 862 2 061 522	(67°57′E，44°00′N) (68°31′E，44°27′N)	6	扩张	70	西南
南亚	1993 2012	2 511 894 2 429 953	(76°57′E，23°00′N) (77°06′E，22°14′N)	-3	收缩	95	南
东南亚	1993 2012	4 977 804 4 497 249	(105°29′E，5°14′N) (105°01′E，6°41′N)	-10	收缩	178	西北
西亚埃及	1993 2012	3 502 919 3 572 633	(43°03′E，30°57′N) (43°27′E，30°28′N)	2	扩张	69	东南
欧洲	1993 2012	1 422 474 1 238 823	(22°44′E，48°17′N) (22°36′E，48°36′N)	-13	收缩	167	西
中国	1993 2012	3 253 791 3 487 545	(115°14′E，34°09′N) (114°04′E，33°32′N)	7	扩张	86	西南

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