The high-quality development of the new urbanization in China is focused on man-earth harmony, people-oriented principle, low-carbon, ecology, innovation, wisdom and safety. It is an organic unity of high quality citizenization, infrastructure, living environment, urban construction, public service and urban management. Promoting the new urbanization is an important way for China to build a moderately prosperous society in all respects and achieve modernization basically, and it is an important way to realize the strategy of rural revitalization. To promote the development of China's new urbanization, we need to follow the four stage rule and gradual development rule. To realize the strategy transformation of new urbanization, it is necessary to make more changes: from the quantitative to the quality-oriented, from the "one step" to "step by step" in realizing our goals, from radical to gradual, from inducing "negative effect" to releasing the "positive energy", from passive to active, from "land-oriented" to "people-oriented". The current situation and background conditions of China's urbanization are very different from one place to another. Thus, we should avoid "one-size-fits-all" in promoting the development of new urbanization. Adhering to the principle of adapting local conditions and appropriate conditions, the paper divides the new urbanization area into five major types, including urban agglomeration region (I), major grain-producing region (II), farming, forestry, and animal husbandry region (III), linked poverty alleviation region (IV), and ethnic autonomous region (V), which are further divided into 47 sub-regions. The urbanization development mode between different regions and different subregions cannot be copied from each other, and we need to implement some diversified and differentiated models. According to the main functions of different types of urbanization regions, the different development policies of urbanization should be formulated, and development goals and priorities should be put forward according to local conditions, and the classification guidance should be proposed according to the appropriate conditions. The key paths to promote the high-quality development of China's new urbanization include: enhance the overall synergy of high-quality development and improve the quality of urban agglomeration development; promote the integrated development of industrial and urban areas and the equalization of basic urban public services, and improve the quality of urban development; propel integrated development between urban and rural areas and accelerate the revitalization of rural areas; highlight the main functions of urbanization quality development in different types of areas in accordance with local conditions; innovate institutional mechanisms and ensure that high-quality development is carried out throughout the trial process of new urbanization; standardize small towns with distinctive features and lay a solid foundation for the high-quality development of new urbanization; strengthen the analysis and regulation of the capacity of resources and environment for the high-quality development of new urbanization.

中国新型城镇化高质量发展是一种人地和谐、高效低碳、生态环保、节约创新、智慧平安的质量提升型城镇化,是高质量的城市建设、高质量的基础设施、高质量的公共服务、高质量的人居环境、高质量的城市管理和高质量的市民化的有机统一。高质量推进新型城镇化发展需要遵循城镇化发展的四阶段性规律和渐进式规律,实现新型城镇化由数量型向质量型、由“一步到位”向“分步到位”、由激进式向渐进式、由诱发“负效应”向释放“正能量”、由被动性向主动型、由“地为本”向“人为本”的战略转型。考虑到中国新型城镇化发展的地域差异显著,新型城镇化高质量发展客观上要因地制宜、因类指导,可将全国新型城镇化高质量发展区域划分为城市群地区（Ⅰ）、粮食主产区（Ⅱ）、农林牧地区（Ⅲ）、连片扶贫区（Ⅳ）、民族自治区（Ⅴ）共5大高质量发展类型区和47个亚区。未来推进中国新型城镇化高质量发展的重点路径包括：增强新型城镇化高质量发展的整体协同性,提高城市群发展质量;推动产城深度融合发展,加快实现基本公共服务均等化,提升城市发展品质与质量;推动城乡深度融合发展,在新型城镇化高质量发展中实现乡村振兴;突出因地制宜,明确不同类型地区城镇化高质量发展的主体功能;创新体制机制,全过程推进城镇化高质量发展;量力而行,以特取胜,规范建设特色小镇,夯实新型城镇化高质量发展的基石;把新型城镇化高质量发展与区域资源环境承载力及高质量保护有机结合起来。

Through subdividing the spatial changes of each land use type into three categories of components,i.e.,the unchanged part,the converted part and the newly-increased part,this paper finds out that the two existing models for measuring the rate of land use changes have serious limitations.The traditional quantity analysis model only considers the quantitative change of land use but completely neglects the spatial changes of land use.The GIS-based dynamic degree model would seriously underestimate the change rate of those land use with rapid growth,in par-ticular urban land use because it only takes the conversion process into account but neglects the spatial expansion process of land use change.Therefore,a new spatial analysis model is then pro-posed to modify those limitations and to improve the measuring precision.Secondly,the proposed spatial analysis model is applied in a detailed case study on land use change in urban fringe of Beijing and the measuring results from the3models are compared which substantially demon-strate that the proposed spatial analysis model can more precisely measure the dynamic change rate of land use.

Based on the land use maps of Beijing in 1982, 1992 and 1997, its spatial and temporal process of urban land use growth was analyzed through spatial clustering and historical morphological approaches. The growth intensity index （GII）, was employed instead of growth speed to describe the spatial differentiation of urban land use growth. Assisted by spatial analysis techniques of GIS, the average GIIs per year （AGIIPY） of 155 communes or towns during 1982～1992 and 1992～1997 were calculated and then classified through the Natural Breaks method, and the spatial differentiation maps of urban land use growth in Beijing during 1982～1992 and 1992～1997 were made. This paper found: （1） Industrial land is the most important element of urban land use growth in Beijing, and its contribution rate is on the increase, which is different from the general Western urban growth model driven by residential expansion. Since 1982, the industrial land had been keeping expanded at the average rate of 24～25 km² per year. It is extraordinary high especially during the 1992～1997 period, while that of residential land and urban land use dropped by 59% and 24%, to 3 4 km² per year and 29 8 km² per year respectively. Thus, the contribution rate of industrial land to urban land use growth increased from 64 91% in 1982～1992 to 80 67% in 1992～1997. （2） The spatial pattern of urban land use growth in Beijing was in distinct concentric sprawl. With the growth centers’ gradual shift from the inner to outside, the new added urban land use were increased in distinct concentric zones and continually encroached upon the green spaces among the central mass and those “dispersed constellations”. The total area of green spaces for isolating built up areas in General Plan of Beijing, was 314 km² in 1958, reduced to 260 km² in 1983 and 160 km² in 1993. The concentric sprawl pattern seriously destroyed the spatial structure of “dispersed constellations” designed by the General Plan of Beijing, and also badly worsened the regional ecological environment. （3） The growth axes of urban land use in the southern and eastern part of Beijing had stepped into their decline period. The southern and eastern part of Beijing is located in the North China Plain and have advantages in urban development space, economic and transport communication, etc., so that they are determined as the main urban development areas and direction by the latest General Plan （1991～2010）. But this paper found, the two major growth axes of urban land use along the Beijing Tian Jin and Beijing Shen Zhen highways in the southern and eastern part of Beijing, had stepped into their decline period during 1992～1997. Their AGIIPY decreased from 1 63 and 1 58 during 1982～1992 to 0 86 and 0 67 respectively, and the spatial growth pattern have also switched from vigorous axial expansion to fill in among axes.

采用GIS空间分析技术,对1982～1997年期间北京城市土地利用扩展的时空过程进行空间聚类和历史形态分析。证实工业用地的高速外向扩展是北京城市土地利用规模“超常膨胀”的主要原因。

Expand intensity index (EII) is an index commonly used to characterize the extent and speed of urban expansion. In other words, it is simply used to describe and analyze the physical spatial change from the perspective of urban area. But this index only represents the result of urban expansion neglecting the feeling of people to space and the underlying mechanisms of urban expansion. Moreover, an in-depth study is ignored on the evolving pattern of urban space and cannot reflect human activities in urban space. This paper presents a new expansion intensity index based on space syntax by considering the driving effect of transport network on urban expansion, namely space syntax expand intensity Index (SS-EII). SS-EII can reflect the syntactic variables about spatial clustering and dispersion and analyze the changes of spatial accessibility. Compared to the conventional expand intensity index, SS-EII not only cares about the result of urban expansion, but also captures the effect of transportation on the pattern and direction of urban expansion as well as the feeling of human to urban space. With Cotton Lake Town in Guangdong Province, China as an example, SS-EII is utilized to compare expansion speeds of built-up areas in different directions. It can be concluded that the result based on SS-EII is consistent to the actual situation of urban expansion and the correlation coefficient with EII is higher than 0.95.

扩张强度指数（Expand Intensity Index, EII）是目前城市扩展数量特征研究的常用指标,用以表征城市扩张程度和速度,但该指标是从城市扩张的结果,即从城市用地面积变化角度对物质空间变化的简单描述与分析,忽略了人在空间中的感受,未能从城市扩张的动因角度揭示城市扩张特征,缺乏对城市外部空间形态演变模式的深入研究,不能反映人在城市扩展空间上的活动。本文从交通网络对城市扩张的驱动作用入手,基于空间句法,提出一种新的扩张强度指数——基于空间句法的扩张强度指数（Space Syntax Expand Intensity Index, SS-EII）,SS-EII包涵可反映空间集聚和离散程度的句法变量,可用于分析空间可达性的变化等情况。与传统扩张强度指数相比,SS-EII是基于空间句法从城市扩张的驱动力方面计算扩张强度,不仅关注城市扩张的结果,同时关注交通对城市扩张模式、方向的导向作用和人主观感知下城市空间的变化。将SS-EII应用于广东省棉湖镇2002-2014年期间的城镇扩展特征分析中,研究结果表明,SS-EII可用于分析比较建成区不同方向的扩张速率与建设状况,其计算结果与棉湖镇建成区实际扩张情况相符,与EII相关度R²达0.95以上。

Research into urban expansion patterns and their driving forces is of great significance. Under the background of the integrated development of the Beijing-Tianjin-Hebei (Jing-Jin-Ji) urban agglomeration, it is important to study the temporal and spatial patterns of urban land expansion and the driving forces development. This paper uses land-use data of the Jing-Jin-Ji urban agglomeration from 1990 to 2015 and reveals the multi-dimensional characteristics of the urban land expansion patterns. We then combine the urban spatial interaction and the spatial and temporal nonstationarity of the urban land expansion process and build the center of gravity-geographically and temporally weighted regression (GTWR) model by coupling the center of gravity model with the GTWR model. Using the center of gravity-GTWR model, we analyze the driving forces of urban land expansion at the city scale, and summarize the dominant mode and core driving forces of the Jing-Jin-Ji urban agglomeration. The results show that: (1) Between 1990 and 2015, the expansion intensity of the Jing-Jin-Ji urban agglomeration showed a down-up-down trend, and the peak period of expansion was in 2005-2010. Before 2005, high-speed development was seen in Beijing, Tianjin, Baoding, and Langfang, which were then followed by rapid development in Xingtai and Handan. (2) Although the center of gravity of cities in the Jing-Jin-Ji urban agglomeration showed a divergent trend, the local interaction between cities was enhanced, and the driving forces of urban land expansion showed a characteristic of spatial spillover. (3) The spatial development mode of the Jing-Jin-Ji urban agglomeration changed from a dual-core development mode to a multi-core development mode, which was made up of three function cores: the transportation core in the northern part, the economic development core in the central part, and the investment core in the southern part. The integrated development between functional cores led to the multi-core development mode. (4) The center of gravity-GTWR model analyzes urban land expansion as a space-time dynamic system. The model proved to be feasible in the analysis of the driving forces of urban land expansion.

城镇用地扩展格局及驱动力研究对城市群发展规划与决策具有重要意义。以京津冀地区为例,基于城镇用地扩展强度指数、城镇用地扩展差异指数、分形维数、土地城镇化率和重心转移模型,多维解析了城市群城镇用地扩展格局特征,并耦合重心转移模型和时空地理加权回归（GTWR）模型构建重心-GTWR模型,在对空间格局进行长时间序列多维度指标分析的基础上,运用该模型依序对其特征进行驱动力解读,进而总结凝练京津冀区域发展的主导模式与城市核心驱动力。主要结论为：① 1990-2015年,京津冀城市群城镇用地扩展强度呈现“下降—上升—下降”的趋势,高峰时期在2005-2010年,在2005年之前高速发展城市集中在北京、天津、保定和廊坊,2005年之后集中在邢台和邯郸;② 城市群城镇用地重心虽呈现出发散态势,但城市之间的局部相互作用力逐渐增强,城镇用地扩展驱动力表现出空间溢出特征;③ 京津冀城市群空间发展模式由以北京和天津为中心的双核发展模式向多核发展模式转变,并出现北部资源运输核心、中部经济发展核心和南部投资发展核心三大功能核心组团,城市群趋向于多核功能协同发展模式;④ 重心-GTWR模型结合了时空非平稳性和城市空间相互作用,将城市群城镇用地扩展作为一个时空变化系统进行分析,经验证,该模型在城镇用地扩展格局驱动力分析研究中具有可行性。

Built-up land sprawl is the most drastic and visual manifestation of urban land-use change. Understanding spatiotemporal change of built-up land sprawl and its driving forces can reveal the inherent laws of urban sprawl, and thus scientifically regulate urban land use. In this study, we used multisource data (e.g., 30 m resolution Landsat images in 1995, 2000, 2005, 2010, and 2015) and socioeconomic data to analyze spatiotemporal changes of built-up land sprawl in Yangzhou City. Further, we employed the boosted regression tree method to quantify the effects of geographic, social and economic factors on such sprawl. Results showed that the built-up land area gradually increased from 725.4 km² in 1995 to 1076.5 km² in 2015. With the increasing urbanization, the spatial form of built-up land tended to be compact and regular, and the gravity coordinates also migrated accordingly, showing local attraction and linkage of municipal districts (e.g., Hanjiang and Guangling). Among geographic, social, and economic factors, geographic factors (e.g., altitude, the distance from the county core, the distance from built-up land) had the greatest influence on built-up land sprawl, with the relative influence gradually decreasing from 73.9% in 1995-2000 to 60.2% in 2010-2015. The influence of social and economic factors gradually increased from 5.2% and 20.9% in 1995-2000 to 7.9% and 31.9% in 2010-2015. Geographic factors (e.g., the distance from the county core and the distance from built-up land) generally had negative effect on built-up land sprawl, but the effects of social and economic factors were inconsistent. For example, population density, GDP per capita and fiscal revenue promoted built-up land sprawl, gross population inhibited it, and secondary industry first inhibited built-up land sprawl and then promoted it.

建设用地扩张是城市土地利用变化中最剧烈、最直观的表现。探究其时空演变特征及其驱动力将有助于揭示城市空间扩张机理，促进城市用地调控的科学化。以快速城市化的中型城市——扬州市为例，基于多期Landsat遥感影像（1995、2000、2005、2010和2015年）、社会经济数据等资料，分析建设用地扩张的时空演变特征，进而利用增强回归树（boosted regression tree）方法，探讨城市化进程中地理空间、社会和经济因子对建设用地扩张的影响。研究发现，1995—2015年，建设用地面积从725.4 km²持续增加到1076.5 km²。随着城市化的推进，建设用地的空间形态趋于紧凑、形状变得规则，重心也随之转移，表现出市辖区的局部吸引和联动特征。在地理空间、社会和经济因子中，地理空间因子（如海拔、距县市核心区和建成区的距离）对建设用地扩张的影响最大，但其相对影响却从1995—2000年的73.9%逐渐下降到2010—2015年的60.2%；社会和经济因子的相对影响则呈增加的趋势，即1995—2000年的5.2%和20.9%分别增加到2010—2015年的7.9%和31.9%。地理空间因子（如距县市核心区和建成区的距离）对建设用地扩张的影响以抑制作用为主，但不同社会经济因子的作用呈现较大差异，例如，人口密度、人均GDP和财政收入能够促进建设用地的形成，人口数量表现为抑制作用，第二产业则为先抑制后促进的作用。

Spatial stratified heterogeneity is the spatial expression of natural and socio-economic process, which is an important approach for human to recognize nature since Aristotle. Geodetector is a new statistical method to detect spatial stratified heterogeneity and reveal the driving factors behind it. This method with no linear hypothesis has elegant form and definite physical meaning. Here is the basic idea behind Geodetector: assuming that the study area is divided into several subareas. The study area is characterized by spatial stratified heterogeneity if the sum of the variance of subareas is less than the regional total variance; and if the spatial distribution of the two variables tends to be consistent, there is statistical correlation between them. Q-statistic in Geodetector has already been applied in many fields of natural and social sciences which can be used to measure spatial stratified heterogeneity, detect explanatory factors and analyze the interactive relationship between variables. In this paper, the authors will illustrate the principle of Geodetector and summarize the characteristics and applications in order to facilitate the using of Geodetector and help readers to recognize, mine and utilize spatial stratified heterogeneity.

空间分异是自然和社会经济过程的空间表现,也是自亚里士多德以来人类认识自然的重要途径。地理探测器是探测空间分异性,以及揭示其背后驱动因子的一种新的统计学方法,此方法无线性假设,具有优雅的形式和明确的物理含义。基本思想是：假设研究区分为若干子区域,如果子区域的方差之和小于区域总方差,则存在空间分异性;如果两变量的空间分布趋于一致,则两者存在统计关联性。地理探测器q统计量,可用以度量空间分异性、探测解释因子、分析变量之间交互关系,已经在自然和社会科学多领域应用。本文阐述地理探测器的原理,并对其特点及应用进行了归纳总结,以利于读者方便灵活地使用地理探测器来认识、挖掘和利用空间分异性。

The questionnaires are surveyed including the passengers’ travel destination, traffic mode choice and the travel distance, etc., in the Nanjing Station of Shanghai-Nanjing Intercity high-speed railway. Collecting the address, industry category, set-up time of 6 145 companies surrounding station within 3 000 m as the study samples, using spatial analysis methods, this article analyzes the distribution of industries and spatial clusters by high-speed railway station. The resluts are as follows. 1) Generally speaking, industry location has obvious circle structure around high-speed station. The company density shows a circle structure with the Nanjing Station as the center and 500 m as the buffer radius. The company density ascends to the top at 1 500-2 000 m, and has break in the point of 2 000 m far from the Nanjing Station. The wholesale and retail industry has the largest number, business service industry in second, science and technology service industry in third. Comparing industry proportion in each circle, we come to the conclution that business service industry, accommodation and catering industry increase gradually at 0-1 500 m, reduce significantly at 2 000 m, which confirms the high-speed railway passengers on business service industry and accommodation and catering industry needs a 1 500 m-radius concentration. 2) The trend of spatial industrial concentration is similar, decreasing with the distance. Owing to the different spatial scales, the location of wholesale and retail industry has most options; transportation industry and real estate industry tend to have a significant traffic location. The accommodation and catering industry, computer service industry, science and technology service industry as well as the resident service industry show homogeneous distribution based on the cluster distribution. 3) There is a significant difference in the spatial distribution of the industry, featured by “higher in the west and lower in the east”. The spatial distribution patterns are generally identified in three modes of concentration. The transportation industry and real estate industry have a "small scatter, large cluster" mode, that is, the spatial distribution of companies show relative concentration and form a single hotspot. The resident service industry, wholesale and retail industry as well as accommodation and catering industry present a “large scatter, large cluster” mode. Business service industry, science and technology service industry and computer service industry have a “large scatter, small cluster” mode. The results above confirm the Ripley' s K function analysis.

分析沪宁城铁南京站乘客的出行距离特性,初步确定高铁站区圈层范围为3 000 m。以南京站周边3 000 m范围内6 145个企业的地址、行业隶属、成立时间等为研究数据,运用空间分析方法,探讨高铁站区产业的分布与空间集聚特征。 ① 从总体看,高铁站区产业的空间分布具有明显的圈层结构,以车站为中心,以500 m为缓冲半径,在1 500~2 000 m范围企业密度最大,2 000 m以外企业密度陡然降低。② 各行业空间集聚趋势类似,随着距离增大集聚程度降低。但空间尺度上存在差异,交通运输业和房地产业集聚现象更为明显,交通指向性显著;批发和零售业集聚峰值相对最大,在大范围上有分散分布的趋势。③ 各行业空间分异特征显著,整体呈现“东低西高”,空间分异特征大致存在以下三种模式,即“小分散、大集聚”、 “大分散、大集聚”、“大分散、小集聚”。

High-speed railway (HSR) station is regarded as a new type of space for driving urban economic growth, and studying its surrounding industrial structure is of great significance to guide the development of HSR station areas. In this paper, nine HSR stations with different locations and different levels in China are selected as the research object. The Point of Interest (POI) information data of 10 industries within 3000 m around the HSR station are used as the research basis. Based on the Ripley's K function, kernel density estimation and industrial indexes, the characteristics of industrial distribution of HSR station areas in different locations are explored. Our result indicates that when the grade of high-speed rail stations is the same, the farther the high-speed rail stations are from the city center, the smaller the total number of industrial POIs in the station area. Among 10 kinds of industries, the number of POIs in four types of industry, namely, shopping services, catering services, life services and companies, is much larger than that of other industries. Secondly, all industries in the HSR station areas show a significant agglomeration within an observation distance of 1500 m. In terms of the industrial agglomeration degree, the change of the central station is relatively gentle, the change of the urban station is the highest, and the change range is greater, and the regularity of new-town station is not obvious. Thirdly, the industrial agglomeration area of the central station is mainly distributed in the range of 0-2500 m around the high-speed rail station, the industrial agglomeration area of??the urban station is more obvious in the range of 500-2500 m, and the industrial agglomeration area of the new-town station is concentrated in the ranges of 0-1500 m and 2000-3000 m. Fourthly, the basic service industry and derivative service industry are mainly concentrated in the inner and the middle circle layers, and the related service industries are mainly distributed in the middle and the outer circle layers. The compound characteristics of the industries in each circle layer are obvious, and the farther away from the city center, the weaker the radiation effect on the industry, the more obviously the trend of industry decays. Finally, based on the research findings, it is believed that the government should pay more attention to the intensification of land development and the integration of industrial development while developing the industries in HSR station areas.

高铁站被视为拉动城市经济增长的新型空间,研究其周边产业结构对指导高铁站区的开发具有重要意义。本文选取了全国范围内9个不同区位、不同等级的高铁站为研究对象,以高铁站周边3000 m范围内10类产业的POI信息作为研究数据,通过Ripley's K函数、核密度估计和产业指数等方法探索不同区位下高铁站区的产业结构特征。研究发现：① 当高铁站的等级规模相同时,高铁站距离城市中心越远,站区内产业POI总数一般就越少。其中,购物服务、餐饮服务、生活服务和公司企业4类产业的POI数量显著高于其他产业。② 所有高铁站区的产业在1500 m的观测距离内均呈现出显著的集聚分布特征。其中,中心站产业集聚程度的变化较为平缓,城区站产业集聚程度最高,变化幅度也更大,而新城站的规律特征不明显。③ 中心站的产业集聚区域主要分布在高铁站周边0~2500 m的范围内,城区站的产业集聚现象在500~2500 m范围内较为明显,而新城站的产业集聚区域则集中在0~1500 m、2000~3000 m的范围以内。④ 基本服务产业和衍生服务产业主要集中于内圈层和中间圈层,相关服务产业则主要分布在中间圈层和外圈层,各圈层内产业复合特征明显,且高铁站越远离城市中心,其对产业的辐射作用越弱,产业衰减趋势也越明显。基于以上结论,本文认为未来高铁站区的产业开发更应关注土地开发集约化和产业发展复合化。

A transportation hub is the key link in the construction of the comprehensive three-dimensional transportation corridor of the Yangtze River Economic Belt (YREB), and it is the basic factor responsible for the promotion of this belt. A high-speed railway hub has the effect of "last kilometer of time-space compression" and is the key to building an efficient, convenient, modern, and comprehensive transportation system. Based on the principle of this effect, this study constructed a model for measuring the connection-distribution performance of the high-speed railway hub, determined the connection-distribution performance of the urban high-speed railway hub in the YREB, and analyzed its spatial differentiation characteristics, and further revealed the influencing mechanism of the connection-distribution performance of the high-speed railway hub. The main results are as follows: (1) the connection-distribution performance of the high-speed railway hub in the YREB presented an "olive type" grade structure with two small ends and a large middle section, that is, there are fewer high-speed railway stations with high performance and average performance, and there are more high-speed railway stations with good performance and medium performance. (2) The connection-distribution performance of the high-speed railway hub in this economic belt showed a regional differentiation pattern of "high in the east and low in the west" and "high in the north and low in the south", and showed an urban agglomeration differentiation pattern of "high in the core area and low in the marginal area". Moreover, spatial differences were prominent in the distribution of nine evaluation indexes of the connection-distribution performance of the high-speed railway hub. (3) GDP, urbanization rate, city level, station passenger flow and frequency of shuttle bus were key driving factors affecting the connection-distribution performance of the high-speed railway hub. At the same time, there were significant differences in the key driving factors for the connection-distribution performance grades of high-quality, good, medium and average levels.

作为长江经济带综合立体交通走廊建设的关键环节,交通枢纽是推动长江经济带发展的基础保障。高铁枢纽承载着“时空压缩最后一公里”效应,是构筑高效便捷的现代化综合交通体系的关键。首先诠释了高铁枢纽“时空压缩最后一公里”效应原理,其次构建高铁枢纽接驳—集疏运绩效指标体系,进而对长江经济带37个城市高铁枢纽的接驳—集疏运绩效进行测度,并分析绩效空间分异特征,最后揭示高铁枢纽接驳—集疏运绩效的影响机理。结果显示：① 长江经济带高铁枢纽接驳—集疏运绩效等级分异呈“橄榄型”结构,即优质绩效和一般绩效的高铁站数量较少,良好绩效和中等绩效的高铁站数量较多;② 地带分异呈“东高西低、北高南低”格局,而城市群分异则呈“核心高、边缘低”格局,且9个评价指标值空间差异明显;③ GDP、城镇化率、城市等级、车站客流量和发送班车次数是影响高铁枢纽接驳—集疏运绩效的关键驱动因子;同时,优质、良好、中等和一般等不同等级绩效的关键驱动因子存在显著差异。

The international theoretical and practical studies suggest that the construction of high-speed rail (HSR) usually influences the development of suburban area. In China, the large-scale construction of HSR, together with the rapid urbanization, makes such influence more complex and profound. In the development of HSR new town, the HSR station works as an "amplifier", thus it promotes suburbanization. In the case study of Beijing-Shanghai High-speed Rail, this article takes both quantitative and qualitative approaches to explore suburbanization’s patterns in HSR new town: 1) relatively active suburbanization in major cities; 2) exorbitant scale and expectation of urban construction; 3) rapidly shifted urban forms. From the perspectives of government, market and society, this article uses urban regime theory to analyze the inter-mechanism of HSR-driven suburbanization. In conclusion, selectivity and uncertainty of HSR’s suburbanization are proposed. This article also suggests that it is important to coordinate the locations and relationships of the high-speed railway and cities along the lines at a regional level. Furthermore, the development of HSR and urban space in the new towns should be integrated, and the public participation during the planning and development of HSR new towns should be strengthened. Therefore, the goal of sustainable suburban development by HSR can be reached.

国际理论与实践表明高铁的建设能够推动城市郊区化的发展。现阶段中国高铁大规模建设,与快速城市化同步推进,使得这一影响更为深刻和复杂。在高铁新城形成的过程中,高铁站点发挥了一个“放大器”的功能,推动了以高铁新城为主体的城市郊区化进程。以京沪高铁为例,定性与定量相结合分析了以高铁新城为代表的郊区化模式特征：① 大城市相对主动的郊区化;② 规划建设的规模与定位偏高;③ 迅速改变城市原有空间格局等。从政府、市场和社会三者的角度,利用城市政体理论分析了高铁驱动城市郊区化的内在机制。最后指出高铁对于城市郊区化的带动效应存在着选择性和不确定性,应从区域层面对高铁沿线及周边城市的定位及关系进行协调,将高铁新城的选址、规划、开发和建设纳入到城市整体空间发展的脉络之中,同时应加强高铁新城规划的公众参与,从而更好的利用高铁驱动中国城市郊区化的可持续发展。