城市人口空间分布模拟与格局分析——以沈阳市为例

人口分布空间结构是城市空间结构的重要组成部分。为准确地模拟城市人口分布,清晰地反映城市人口分布格局,本文利用沈阳市第五次人口普查资料,采用网格计算方法空间化人口数据、地统计学的空间插值方法模拟人口分布。同时,用DEM模型方法识别城市人口分布格局,分析人口分布特征。结果是:沈阳城市内部人口分布具有较高的不均衡性和聚集性;城市人口密度分布不符合单核心圈层式范式,具有11个明显的人口分布核心;在城市中心区域,人口分布的区域化特征更为显著;人口分布主要受到相近的两个人口核心的影响。该研究同时表明中国市场经济体制背景下,城市人口分布特征具有较高的复杂性。对于城市人口分布规律及影响人口分布的动力机制,需进一步研究。     

沈阳市城市功能区分布与人口活动研究

从精细尺度上研究城市功能区分布与人口活动规律对于政府和相关部门合理调节城市内部资源配置、安排城市设施布局具有重要意义。以沈阳市中心城区为例,根据核密度估计原理,基于兴趣点（POI）数据探索沈阳市中心功能区分布情况,通过解读多时相百度热力图数据,探索工作日和周末城区人口时空分布规律,即从城市人口活动和城市功能设施分布2个角度解读沈阳市中心城区空间结构与组织形式。借助SPSS 20.0分析人口热度和设施分布的相关性关系,建立多元线性回归模型。主要结论如下：① 沈阳市城市活力区呈现多中心分布模式,大多位于商业中心、金融中心或者城市功能复合中心。② 工作日人口高热区空间分布较周末更为分散,面积较大,早晚波动较大。周末人口高热区主要集中在商业中心和城市复合功能区且白天存在较大波动。③ 功能区分布与人口热度显著相关,其中生活服务设施、金融设施、交通设施、住宿设施和景点设施是工作日人口热度的主要影响因子;教育设施、餐饮设施、交通设施、金融设施和公共服务设施是周末人口热度的主要影响因子。     

Character and Causes of Population Distribution in Shenyang City, China

1 Introduction Research on the character of urban population distribu- tion is one of the focuses of western urban geography. From the 1950s, the research has attracted the attention of many western researchers, and a series of classical theoretical models were put forward. For example, Clark (1951) found that with the increase of distance from the city center, the urban population density tends to de- crease in exponential. Through the statistical analysis of more than 20 cities, he put forw…     

Suburbanization and subcentering of population in Beijing metropolitan area: A nonparametric analysis

This study focuses on the suburbanization and subcentering of population and examines the nature of spatial restructuring in terms of the population distribution in the Beijing metropolitan area.Instead of the classic density function approach,we employ the nonparametric analysis to characterize the spatial pattern of population densities in the Beijing metropolitan area and identify the suburban subcenters.Our findings suggest that the population has spread with rapid urban growth in the Beijing metropolitan area,and the compact urban form has been replaced by a more dispersed polycentric spatial distribution.However,compared with the decentralization of western cities,the spatial extent of the decentralization of population in the Beijing metropolitan area is quite limited.The rapid growth of population in the near suburbs has expedited the sprawl of the central city,with a larger central agglomeration of population dominating the metropolitan area.In this sense,the spatial pattern of the Beijing metropolitan area is still characterized by the continuous compactness.However,our findings do provide the evidence that the city has been turning to a polycentric structure.We find significant population subcenters have emerged in the suburbs of Beijing since the 1980s.But the polycentricity emerged in the Beijing metropolitan area is very different by nature from that observed in Western cities.The subcenters emerged are adherent to the development scheme planned for the city,so it can be referred to as the so called ’planned polycentricity’.     

空间同位模式支持下城市服务业关联发现及特征分析

空间同位模式分析是数据挖掘中一种常见的方法,可有效挖掘城市设施在空间位置上的关联特征,进而发现城市设施的分布规律。本文基于POI数据同位模式挖掘用来获取城市服务业空间关联结构：首先,通过邻近实例获取、同位候选模式存储与筛选,得到城市服务业二阶同位模式;然后,据此构造产业空间关联图,得到产业间的关联结构;最后,分别构造了产业空间关联图密度和产业空间关联显著指数,用来衡量城市服务业空间关联的紧密程度和整体关联的显著程度。本文选取成都、兰州、郑州、沈阳、上海与深圳为试验区,实验结果表明：不同城市服务业的空间关联结构存在共性与特殊性,整体上,餐饮、购物等与居民日常生活相关的服务业易与其他服务业产生空间强相关,这几类服务业内部空间集聚明显;成都与沈阳的服务业整体表现空间关联度高且紧密,兰州其次,上海与深圳的服务业则整体表现空间关联较弱,郑州的服务业空间关联较紧密但强度较低。     

青藏高原城镇体系的时空演变

城镇体系的形成和发育对区域城镇化进程及社会经济发展起着至关重要的作用,并对生态环境产生重要影响。青藏高原特殊的地理环境与相对落后的社会经济基础,导致城镇体系不甚健全。目前国内外相关研究薄弱,不利于国家生态安全屏障建设及青藏高原可持续发展。为此,本文以建制镇以上的镇区和城市市区为研究对象,结合统计数据与遥感数据,借助GIS空间分析方法对青藏高原1990-2015年城镇体系的空间结构和规模结构进行时空演变格局分析,并采用重心移动模型揭示了青藏高原城镇人口规模和用地规模重心的迁移规律。结果表明：青藏高原城镇空间分布总体呈现出“东南密集、西北稀疏”、“大分散、小集聚”的格局;城镇分布在时间上具有阶段性增长特征且总体趋于集聚,在空间上不均衡程度呈上升趋势但2005年后明显减缓;虽然建制镇数量大幅增长,但96.88%的城镇规模在5万人以下,大中小城市发育不足;城镇人口规模重心呈现“先向西南,再向东北,又向西南”的移动轨迹;城镇用地规模重心呈现“先向东南,再向西北,再向东北”的迁移趋势。本文研究了青藏高原城镇体系的规模结构及其时空演变特征,为青藏高原新型城镇化及城镇空间格局优化提供基础依据;提出了资料缺乏和统计口径不一致的条件下城镇规模的合理估算方法,对我国城镇化相关研究具有一定的参考价值。     

Evolutionary Pattern and Effect of Administrative Division Adjustment During Urbanization of China: Empirical Analysis on Multiple Scales

The adjustment of administrative divisions is one of the important factors guiding China’s urbanization, which has profound economic and social effects for regional development. In this paper, we comprehensively describe the process of the adjustment of administrative divisions at provincial and municipal levels in China and summarize the effects on the basic structure and patterns of the spatial development. We quantitatively assess the effects on fields such as urbanization and social economy through the use of multidimensional scaling. The results show that: 1) Upgrading county to municipality (or city-governed district) is the main way of adjusting the administrative divisions. It is also an important factor in the spatial differentiation of interprovincial urbanization. China’s population urbanization can be divided into four patterns including interprovincial migration, provincial migration, natural growth, and growth caused by the adjustment of administrative divisions, which is also the main reason for the increased Chinese urbanization rate at the provincial level. 2) Taking the city of Beijing as an example, we generalize five adjustment patterns made to administrative divisions: the set-up of sub-districts, the set-up of regional offices, the upgrading of townships to sub-districts, the upgrading of townships to towns, and the set-up of towns and the addition of new regional offices. We summarize the municipal urban spatial structure, including the sub-district office area in the central urban area, the regional office area in the new urban area, the mixed area of villages, towns, and sub-district offices in the suburb area, and the township area in the outer suburb area. 3) The adjustment of administrative divisions triggers a significant circulative accumulation effect, resulting in the spatial locking of population and industrial agglomeration. It affects the evolution of the urban spatial form and plays an important role in shaping the urban spatial structure to move to the characteristic of multicenter. In general, the adjustment of administrative divisions was an important factor affecting the inflated statistical level of urbanization and also an important driving force for the evolution of Chinese urban spatial organization structure.     

京津冀都市圈人口集疏过程与空间格局分析

人口集疏过程及其空间格局变化是人口空间分布最直观的表现。以1982-2010年4期人口普查数据为基础,采用人口总量和人口密度指标,结合人口增减变化分级、人口商度等方法,定量分析了京津冀都市圈人口集疏过程及其空间格局变化。研究表明:近30年来,京津冀都市圈人口总量呈现持续增长趋势,人口空间分布日益不均衡,区域人口分布存在明显的南北、东西差异;人口增加是主要特征,人口集聚效应凸显,人口增加地区的县域单元比例在80%以上,以人口显著增加为主;人口减少只是零星分布,人口减少地区的县域单元比例占不到20%;人口流动比较频繁,以人口流入为主,主要流向北京、天津和河北的市辖区,人口流出地区仅是散落分布在张家口和承德的山区贫困县域;无论从静态人口指标还是动态人口分析方法,都表明京津冀都市圈人口地域集疏特征十分明显,已形成以北京、天津、石家庄为中心,其他地市(县域)人口分别向外依次扩展的人口多中心分布的圈层结构。     

城市边缘区空间发展探讨——以北京市海淀区为例

在快速城镇化时期,城市边缘区是城市扩张过程中空间结构变化最大、土地利用转变最快的地区,以过渡性、复杂性、动态性为突出特征。研究城市边缘区的空间演变对认识城镇化、优化城市空间结构等具有重要意义。本文在总结海淀区空间发展历史渊源的基础上,采用了RS/GIS技术对20世纪80年代以来海淀城市边缘区的范围、空间扩张进行了定量分析;并结合系统论方法,探索影响海淀城市边缘区空间演变的若干因素。研究发现：海淀城市边缘区空间发展有独特的地理优势和文化渊源,且在政策、经济、人口、交通等因素的综合作用下,处于不断动态变化之中;呈现出沿环线不规则分布、边界由清晰变模糊、整体向西北推移的空间特征;总面积逐渐增加、年扩张速率先升后降;1995-2007年以向外扩张为主,其他阶段以内部填充型发展为主;空间分布及扩张强度在不同乡镇街道具有区域差异性等。本文将RS/GIS技术与系统分析相结合,来研究城市边缘区相关问题的技术可行性。     

Spatio-temporal patterns of intra-urban land use change in Beijing, China between 1984 and 2008

Urban internal structure is essential information for urban geography researchers and urban planners or managers. This research aims to examine the spatial structure changes of internal urban land use based on the interpreted datasets of 1984 and 2008. Spatio-temporal patterns of internal land use conversion and urban expansion are analyzed, and then dominant driving factors (e.g., social economy, population growth and urban planning) were identified. The results indicate that Beijing′s intra-urban layout has experienced tremendous adjustment from compact to disperse configure, otherwise its function objects have shifted from the major economic and industrial development before the 1990s to the combination with cultural, high-technological and inhabitable city at present. The dominant urban land use transformations include the relocation of industrial lands from core districts to suburban or other provinces, and the accelerating expansion of residential areas and green spaces for supplying the demand of housing and ecological protection. Although Beijing′s urban planning has experienced three major adjustments and improvement since the 1980s, its optimization of urban internal patterns still remains a challenge.     

Analyzing Industrial Structure Evolution of Old Industrial Cities Using Evolutionary Resilience Theory: A Case Study in Shenyang of China

The recession and revitalization of old industrial cities concerns urban industrial evolution and its characteristics. Based on the theory of evolutionary resilience, we developed an analytical framework for the industrial structure evolution of old industrial cities, and applied the framework to a case study in Shenyang. The following conclusions are drawn. First, since 1978, Shenyang's industrial growth capacity has shown fluctuation between ‘contraction-expansion'. As the secondary industry has a much stronger expansionary and contractionary capacity for growth, this results in lacking stability leading to industrial structure transformation. Second, since 1999, the orientation towards a high-end manufacturing industry in Shenyang has weakened, and the evolution of the new and old growth path is characterized by low-end orientation. Third, since 2007, Shenyang's industrial innovation output capacity has dropped sharply which has been significantly affected by scientific and technological personnel and enterprise-owed science and technology institutions and to a less extent by RD expenditure. We applied the resilience theory to study the industrial evolution of an old industrial city, explored new study perspectives on industrial evolution and verified the applicability of the resilience theory. This paper provides a scientific reference for understanding the recent deceleration in economic growth in the Northeast old industrial base, and for exploring new paths toward revitalization.     

中国市级人口增长的多因素空间建模分析

本文以中国市域单元为研究对象,利用1990-2010年人口普查数据,采用探索性空间数据分析的方法,分析了过去20 年间中国市级人口增长率的空间分布特征和多变量的空间依赖关系。使用空间计量模型和空间滤波后的经典线性回归模型分别探究了经济、气候、地形、社会文化等因素对中国市级人口增长率的影响。模型对比结果显示,经过空间滤波后的经典线性回归模型能够更好的模拟中国市级人口增长率的变化。在该模型中,经济因素是影响中国城市人口增长率的主要因素,例如代表城市经济发展水平的城市夜光指数密度。气候因素对人口增长率也有着不可忽视的作用,如七月热指数随着等级的提升对人口增长率有着越来越强的负向影响。研究结果表明：人口的区域增长模式是多要素综合作用的结果,在相关建模研究和政策制定中需要重点考虑经济发展水平和气候条件因素对人口增长趋势的不同影响。     

City size distribution and its spatiotemporal evolution in China

Based on the National Land Use/Cover Database of China(NLUD-C) in the end of the 1980s(the 1980s,hereafter), 1995, 2000, 2005, and 2010, 665 cities were selected to study the size distribution and its changes of urban lands in China. In this study, the spatiotemporal evolutions of urban land size distribution as well as the influence of administrative-level on these cities were explored by combining urban spatial positions and administrative-levels. Results indicate that: 1) City size distribution using urban lands was more practical and reasonable than using non-agricultural population. 2) In the 1980s, cities with ascending urban land rank were centralized in Eastern China, specially the Changjiang(Yangtze) River Delta, the Zhujiang(Pearl) River Delta, and Beijing-Tianjin-Hebei region. Cities in Central, Western, and Northeast China mainly indicated descending urban land rank. 3) The transfer of national development focus resulted in cities with ascending urban land rank becoming evenly distributed nationwide; however, this trend was slightly centralized around Chengdu, Chongqing, and Wuhan in different periods. 4) During the 1980s to 2010, the proportion of cities with ascending urban land rank in provincial capitals, municipalities, and special administrative regions(high-level cities, hereafter) was consistently higher than those in prefecture- and county-level cities except for 2005–2010. The ranks of the majority of the prefecture- and county-level cities were mainly descending, supported by ascending; the proportion of cities with unchanged rank is small. This study breaks through the bottleneck of traditional research in the area of city size distribution by examining urban land replacing the non-agricultural population. The current study also provides scientific explanation for the healthy and reasonable development of urban land as well as the coordinated development of population urbanization and land urbanization.     

Spatiotemporal evolution of urban land uses in modern urbanization of China

Taking social statistic data as basic data,this paper extended the meaning of urban land uses,highlighted the meaning of urban land uses in modern urbanization,which includes direct,indirect and induced land uses,quantitatively simulated the indirect and induced land uses by the substitution method of agricultural consumption and urban carbon emission and then,analyzed the spatiotemporal evolution of urban land uses in China during 1952–2005 by spatial analysis tool of Geographic Information System. The results indicate that the area of urban land use in China had been increasing since 1952,showing an inversed pyramid structure,i.e.,the directthe indirectthe induced. Specifically,Chinese urban land use has changed from concentrated distribution in Northwest China to balanced spatial distribution,and the eastern coastal area is under great pressure. Moreover,the northeastern region has moved into the induced dominant stage,while the western region remains at the indirect dominant stage. Finally,it is proposed that in order to guarantee the future demand of urban land use in China,ensuring the induced land use in the eastern region should be taken as a priority goal of Chinese developing policy.     

基于移动监测数据的不同城市场景下PM2.5浓度精细模拟与时空特征解析

城市内部PM_2.5浓度分布具有明显的空间异质性,而传统方法基于遥感数据或监测站点数据进行分析,难以揭示高时空分辨率下城市内部的PM_2.5浓度分布特征,缺少不同时刻城市场景（如：道路、工业区、住宅区等）对PM_2.5浓度复杂非线性影响的解析。本研究将移动监测传感器安装于快递车上,采集福州市主城区南部不同类型场景的PM_2.5浓度,然后融合地理加权回归（Geographical Weighted Regression, GWR）和梯度提升决策树（Gradient Boosting Decision Tree, GBDT）方法,提出一种基于GWR-GBDT的PM_2.5模拟与场景解析模型,能够较好地拟合气象、场景因素与PM_2.5浓度的非线性关系,提升了城市PM_2.5污染精细监测能力;并结合部分依赖图解析不同时段不同场景因素对PM_2.5浓度的非线性作用影响。结果表明：① 基于移动PM_2.5浓度监测数据,利用GWR-GBDT模型能够较好地模拟城市场景、气象和PM_2.5浓度之间的非线性关系,能够有效精细模拟PM_2.5浓度的空间分布,十折验证R²结果为0.52~0.94;② 通过部分依赖图分析同一场景在不同时段对PM_2.5浓度响应的异质性,发现各类场景对PM_2.5浓度提升或抑制作用并不稳定;③ 解析不同时段人类活动与城市场景对PM_2.5浓度的交互作用发现,教育医疗单位和住宅区两类场景对PM_2.5浓度的提升作用都与人类通勤有密切关系,高污染场景中的建筑工地在采取的洒水降尘措施后能在数小时内有效缓解PM_2.5污染,公园文体服务区在多数时段对PM_2.5浓度具有抑制作用,工业区和道路多数时段会致使对PM_2.5浓度提升;④ 从PM_2.5浓度的空间分布来看,福州市主城区南部PM_2.5浓度总体呈现东南高-西北低的分布趋势,建筑工地、道路和工业区场景轻度以上污染面积占比明显高于其他场景,公园场景总体PM_2.5浓度较低,山体公园傍晚会受到周边工业区的影响而导致PM_2.5浓度升高,而城市陆地外围水域对沿岸PM_2.5浓度具有抑制作用;⑤ 研究结果可为不同场景下PM_2.5污染精细化治理、城市规划以及老人、儿童等高危人群的PM_2.5污染暴露风险防范提供支持。     

北京市人口密度空间分布及其尺度特性研究

利用北京市第六次人口普查数据,在对人口统计数据进行空间化处理的基础上,分析了城市人口密度分布的统计特征及其空间自相关性,充分证明了北京市人口密度分布具有非常强烈的空间自相关性,并已经凸显出城市人口密度多核心分布模型的特征;在对人口统计数据进行格网化处理的基础上,分析了6种不同尺度下北京市人口密度空间分布的统计学特性和空间自相关性,证明了北京市人口密度的空间分布具有尺度特性;本文进一步对尺度特性影响下的人口密度空间分布特性空间自相关性进行了对比研究,从而揭示出空间自相关性与尺度变化间的规律。     

基于多源数据的中国海岸带地区人口空间化模拟

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。     

THE PROGRESS IN URBAN SOCIAL SPACTIAL DIFFERENTIATION STUDY OF CHINA

Ｕｒｂａｎｓｏｃｉａｌｇｅｏｇｒａｐｈｙａｎｄｉｔｓｓｕｂｆｉｅｌｄ—ｕｒｂａｎｓｏｃｉａｌｓｐａｔｉａｌｄｉｆｆｅｒｅｎｔｉａｔｉｏｎｈａｖｅｂｅｅｎｄｅｖｅｌｏｐｅｄｓｉｎｃｅｔｈｅ１９６０ｓ．Ｔｉｌｌｎｏｗ，ｂｙｉｔｓｂａｓｅｍｅｎｔａｎｄｔｈｅｏｒｙ，ｉｔｃａｎｂｅｄｉｖｉｄｅｄｉｎｔｏｔｈｒｅｅｓｔａｇｅｓａｎｄｆｏｕｒｒｅｓｅａｒｃｈｓｃｈｏｏｌｓ：１）ｍｅｔｈｏｄｏｌｏｇｉｃａｌｄｅｓｃｒｉｐｔｉｏｎｓｔａｇｅ；２）ｂｅｈａｖｉｏｒｓｔｕｄｙｓｔａｇｅ；３）ｒａｄｉｃａｌＭａｒ…     

基于位置大数据的城市居住用地效率指标构建及评价研究

信息化赋能已经成为新时期国土空间规划的热点,但通过大数据整合进行国土空间利用评价研究仍有待探索。本文旨在借助腾讯位置大数据开展城市居住用地效率评价实证研究,综合运用多源地理空间数据,以居民区为评价单元构建居住用地效率指标,揭示常州市新城区不同居民区用地效率差异。结果表明：① 居民区范围内小时粒度的人口规模呈周期波动,峰值一般出现在21:00,符合城市居民昼出夜归的作息规律,且不同容积率水平的居民楼人口集聚度和规模值也存在预期性的差异;② 29个居民区按建成年份划分为1980s、1990s、2000s、2010—2015年、2015年以后共5组,各组效率指标平均值分别为1.74、2.45、2.31、0.95和0.91人/百m²,2010年之前建成的居民区明显高于2010年之后新建的,2010年以后建成的居民区低于全市2.06人/百m²的平均水平（2018年标准）;③ 效率指标值低并非完全等同于集约用地水平低,常州市新城新区开发建设的成长周期、居民对提升人居环境品质的需求,都是导致不同居民区用地效率差异的原因。研究表明,位置大数据作为高精度的人口数据源,能够客观反映居民区人口聚集的时空间特征,基于位置大数据构建的城市居住用地效率指数能够为高质量国土空间利用分析提供新途径。在我国以人为本的城市化进程中,以位置大数据为代表的新型人口数据源将在国土空间规划中发挥愈加重要的作用。     

基于手机数据的北京市城市与近郊交互模式挖掘

在城镇化进程中,城市与近郊之间通过职住、货运、游憩等活动产生越来越紧密的交互联系,对于这些交互联系的准确识别和定量刻画,是理解城乡空间关系的重要手段,也能为城市的资源有效配置与合理规划提供重要的现状信息。本文通过对全北京在一日之内的手机信令数据所反映的人群移动轨迹的深入分析,融合城市的POI信息形成顾及人类活动时空信息的空间交互类型推断。以北京市为例,对城市中心与近郊之间远距离的强交互进行定性、定量和定位的探索。本文发现了北京市多尺度下空间交互模式和距离衰减规律,判断了城乡异常交互类型,对比了城乡之间和城市内部的交互模式的异同,以及基于交互类型视角提取了城乡异常交互的空间特征。研究认为,基于手机信令数据,利用停留点提取和高斯核密度估计的空间交互类型推断有效地发现了北京市周末的远距离出行类型特点,提取了其空间交互强度和空间特征,揭示了基于人类活动的北京市周末城乡交互模式。