基于多源数据的中国海岸带地区人口空间化模拟

doi:10.12082/dqxxkx.2020.190192

地球信息科学学报 ›› 2020, Vol. 22 ›› Issue (2): 207-217.doi: 10.12082/dqxxkx.2020.190192

• 地理空间分析综合应用 • 上一篇下一篇

基于多源数据的中国海岸带地区人口空间化模拟

杜培培^1,^2,^3,⁴, 侯西勇^1,^3,^4,^*()

^1. 中国科学院烟台海岸带研究所,烟台 264003
^2. 中国科学院大学,北京 100049
^3. 中国科学院海岸带环境过程与生态修复重点实验室,烟台 264003
^4. 中国科学院海洋大科学研究中心,青岛 266071

收稿日期:2019-04-24 修回日期:2019-09-16 出版日期:2020-02-25 发布日期:2020-04-13
通讯作者: 侯西勇 E-mail:xyhou@yic.ac.cn
作者简介:杜培培（1989— ）,女,河南开封人,博士生,主要从事中国沿海城市扩张研究。E-mail: ppdu@yic.ac.cn
基金资助:
中国科学院战略性先导科技专项(XDA19060205);国家自然科学基金项目(31461143032)

Spatial Simulation of Population in China's Coastal Zone based on Multi-source Data

DU Peipei^1,^2,^3,⁴, HOU Xiyong^1,^3,^4,^*()

^1. Yantai Institute of Coastal Zone Research, Chinese Academy of Sciences, Yantai 264003, China
^2. University of Chinese Academy of Sciences, Beijing 100049, China
^3. Key Laboratory of Coastal Environmental Processes and Ecological Remediation, Chinese Academy of Sciences, Yantai 264003, China
^4. Center for Ocean Mega-Science, Chinese Academy of Sciences, Qingdao 266071, China

Received:2019-04-24 Revised:2019-09-16 Online:2020-02-25 Published:2020-04-13
Contact: HOU Xiyong E-mail:xyhou@yic.ac.cn
Supported by:
Strategic Priority Research Program of the Chinese Academy of Sciences(XDA19060205);National Natural Science Foundation of China(31461143032)

摘要/Abstract

摘要：

海岸带人口聚集、经济增长迅速、生态环境脆弱,容易受到自然灾害的影响,细致的人口空间分布信息对解决海岸带地区资源配置、灾害风险管理等有重要意义。本文以中国沿海城市为研究区,基于NPP-VIIRS和NDVI数据构建人居指数HSI,并加入居住地面积比例系数反映人口内部差异,利用样本动态分区及建模方法,得到2015年中国海岸带1000 m格网人口分布数据（POP）,并将其与已公布的相同年份的中国公里格网人口数据（TPOP）和100 m全球人口数据（WorldPOP）进行对比分析。研究表明,3种数据均能反映中国海岸带地区人口的宏观分布特征,但是对于人口分布城乡差异特征以及城市内部人口分布细节特征的刻画,则是以POP数据最为理想。由县域统计值和POP数据可知,主要受沿海地貌、国家及区域经济发展战略等的影响,中国海岸带地区人口分布具有明显的空间差异,具体来说：① 地形差异,山地和滩涂区域的人口密度普遍较低（小于5 人/hm ²）,而平原和河口三角洲区域的人口密度则普遍较高（大于10 人/hm ²）;② 宏观区域差异,环渤海、长江三角洲和珠江三角洲是人口分布最密集的区域（大于25 人/hm ²）;长江以北地区人口分布多层级重心离散分布的特征较为显著,尤其以山东和江苏最为明显,长江以南地区人口分布相对比较集中,主要集中在沿海低地和平原,如浙江—福建—广东一带;③ 城乡差异,由各级城镇向乡村区域递减的趋势非常明显,城市等级越高,人口分布的梯度特征越显著,中心城区、城市近郊、城市远郊之间相比人口密度差异巨大。

关键词: 人口, 阈值, 动态分区, 空间化, 人居指数, 海岸带, 中国

Abstract:

Coastal zone is not only the hotspot of population aggregation and rapid economic growth, but also eco-environmentally sensitive, vulnerable to natural disasters. Detailed spatial distribution information of population is of great significance for solving resource allocation and disaster risk management in the coastal zone. This paper took the coastal cities in China as the study area. We combined the NPP - VIIRS data and NDVI data to construct Human Settlements Index (HSI), and selected the proportion of residential area per unit grid as a parameter to enhance the inter-demographic difference. Then, we used the dynamic partitioning samples and model to obtain the 1000 m grid population distribution data in the coastal zone of China (POP). To show the advantages of our proposed modeling approach, the published Chinese 1000 m grid population data (TPOP) and world population data with 100 m resolution (WorldPOP) were used to compare with our simulated POP data. For the comparison, three indicators were chosen: the macroscopic distribution characteristics, difference between urban and rural area, and population distribution within city. Results show that all the three data can reflect the macroscopic distribution characteristics of population in China's coastal zone, while POP has the best performance of depicting urban and rural differences in population distribution and the most detailed features of population distribution within city. According to the census and POP data, due to the influence of the coastal terrain and regional to national economic development strategies, the population distribution in China's coastal zone has obvious regional characteristics: (1) Topographically, the population density of montane and tidal flats areas is generally low (below 5 person/hm ²), while that of plain and estuary delta areas is generally high (over 10 person/hm ²). (2) At macroscopic scale, areas with high population density (over 25 person/hm ²) are mainly concentrated in coastal plain areas such as the Circum Bohai Sea region, the Yangtze River delta and the Pearl River delta; the population distribution in the north of the Yangtze River has the pattern of large dispersion and small concentration, especially in the provinces of Shandong and Jiangsu, the population distribution in the south of the Yangtze River is relatively concentrated, mainly in the coastal lowlands and plains in Zhejiang, Fujian, and Guangdong. (3) Regarding the urban and rural differences, the higher the urban level is, the more significant the gradient characteristics of population distribution will be; meanwhile, there is a huge difference in population density among urban, suburbs and exurban areas.

Key words: population, threshold, dynamic partitioning, spatialization, human settlements index, coastal zone, China

杜培培, 侯西勇. 基于多源数据的中国海岸带地区人口空间化模拟[J]. 地球信息科学学报, 2020, 22(2): 207-217.DOI:10.12082/dqxxkx.2020.190192

DU Peipei, HOU Xiyong. Spatial Simulation of Population in China's Coastal Zone based on Multi-source Data[J]. Journal of Geo-information Science, 2020, 22(2): 207-217.DOI:10.12082/dqxxkx.2020.190192

图/表 7

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数据类别	数据格式	数据年份	数据来源	比例尺或分辨率
人口统计数据	属性数据	2015	各省、市、县统计年鉴	—
土地利用类型数据	矢量数据	2015	中国沿海土地利用矢量数据^[30]	1:10万
夜间灯光数据^[31]	栅格数据	2015	美国国家地理数据中心	0.15弧度
NDVI数据^[32]	栅格数据	2015	中国科学院资源环境科学数据中心	1000 m

建模区域	R²	回归系数k	保留区域及其县域个数	需分区进一步建模的县域个数
建模区域	R²	回归系数k	│δ│< 20%	δ ≤ -20%	δ ≥ 20%
全部区域	0.761	16 647.391	124	214（A组）	100（C组）
A	0.855	31 662.685	54	103（A1组）	57（C1组）
A1	0.865	53 309.364	55	37（A11组）	11*
A11	0.964	102721.997	13	6*	18（C111组）
C111	0.995	73 712.440	18	—	—
C1	0.995	24 140.734	57	—	—
C	0.970	11 060.171	75	2*	23（C3组）
C3	0.970	7494.718	19	—	4*

基于多源数据的中国海岸带地区人口空间化模拟

Spatial Simulation of Population in China's Coastal Zone based on Multi-source Data

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