This paper adopts a network approach and measures the connectivity of Chinese cities in an intercity corporate network. Fuelled by globalization and urbanization, the Chinese urban system has undergone dramatic changes in the past four decades, featuring amongst others expanded geographic scope and intensified intercity connections. More specifically, this study examines how 330 Chinese cities are connected through 108,570 ownership linkages of 307,915 local corporations for the year of 2010.Our analysis uses data visualization, social network analysis, network simulation, and complex network models to reveal spatial and network patterns. Major findings include: (1) the backbone of the Chinese intercity corporate network is diamond-shaped and anchored by four major metropolitan areas (Beijing in the North; Shanghai, East; Guangzhou-Shenzhen, South; Chengdu, West); (2) the underlying network generation process features both preferential attachment and spatial interaction; (3) the overall structure of the intercity corporate network is in a transition process from a simple random period to a complex but orderly one and also reveals small-world network properties; (4) degree distribution of cities in the intercity network is characterized by weak assortativity and rich-club effects; and (5) a combination interpretation of clustering coefficient and degree distribution identifies hierarchical and regional tendencies.
The trac networks reflect the pulse and structure of a city and show some dynamic characteristic. Previous research in mining structure from networks mostly focus on static networks and fail to exploit the temporal patterns. In this paper, we aim to solve the problem of discovering the urban spatio-temporal structure from time-evolving traffic networks. We model the time-evolving trac networks into a 3-order tensor, each element of which indicates the volume of trac from i-th origin area to j-th destination area in k-th time domain. Considering traffic data and urban contextual knowledge together, we propose a regularized Non-negative Tucker Decomposition (rNTD) method, which discovers the spatial clusters, temporal patterns and relations among them simultaneously. Abundant experiments are conducted in a large dataset collected from Beijing. Results show that our method outperforms the baseline method.
Based on the 2008 Xi’an city-wide household travel survey data, this manuscript investigates the jobs-housing balance and commuting efficiency in Xi’an, against the backdrop of the dramatic urban spatial/social transformations occurred in the city since the 1990s. It compares selected excess-commuting indicators of Xi’an with those in selected Chinese and foreign cities. It finds that (a) Xi’an has a short theoretical minimum commute, which indicates a good relative numerical balance of jobs with respect to housing; (b) Xi’an has a relatively low commuting efficiency as compared to most of the foreign cities and other Chinese cities----but this can be caused by differences in the size of units of analysis across studies; (c) Jobs-residents ratios would not significantly reduce the average commuting distance at the subarea level; (d) Job density and migrant ratio are significantly correlated to the average commuting distance at the subarea level; (e) The jobs-housing balance has bigger impacts on bus commutes than on car commutes. This manuscript re-confirms the importance of conducting separate studies of the jobs-housing balance and related issues in the Chinese context. It also shows such studies could generate new insights and policy implications.
There have been many scholars’ research indicating that local public goods such as education and green spaces are significant capitalized into house price around them, and this premium of local public goods has a critical influence on the spatial difference of house price within cities. Further theoretical studies show that the premium of some local public goods has spatial heterogeneity character, and will be higher in some area where residents’ demand intensity is higher and housing supply is constraint. Based on the transaction data of newly built commercial housing projects from 2006 to 2011, this article first examines the premium effect of local public goods and its heterogeneity employing GWR model, we find that premium of key primary schools and parks are significant and heterogeneity does exit. Based on that, we analysis the influence mechanism of demand intensity and housing supply on the heterogeneity in premium of two kinds of public goods, using instrumental variable method to overcome the endogenous problem. Results show that the influence of demand intensity and housing supply constraints on heterogeneity conforms to the theoretical expectation.
Population distribution and their temporal variation are a direct proxy of urbanization in China. This study evaluates population density variation during 2000-2010 of all Chinese sub-districts by using the fifth and sixth population censuses of China. The urbanization patterns in 2000 and 2010 are depicted respectively based on various levels of population density. The urbanization process of China during 2000-2010 is then analyzed via comparing pattern in 2000 and 2010. This article enables visualizing population density dynamics and urbanization pattern variation of China at the sub-district level.
This paper provides an overview of practices of mobile-source greenhouse gas (GHG) modeling in China and related data sharing issues, based on structured phone interviews and two on-line surveys conducted in 2011. This paper finds most cities have transportation-land use models but few have mobile-source GHG models. A group of entities housed in the government has the strongest GHG modeling capacities and dominates the relevant consulting market. Data hoarding of public entities is the biggest barrier for entities without government ties to compete in the market. The reasons for data hoarding are: the government’s concerns over political implications of data release, a tradition of data hoarding and lack of confidence in reliability and accuracy of data.
As a vital indicator for measuring urban development, urban areas are expected to be identified explicitly and conveniently with widely available dataset thereby benefiting the planning decisions and relevant urban studies. Existing approaches to identify urban areas normally based on mid-resolution sensing dataset, socioeconomic information (e.g. population density) generally associate with low-resolution in space, e.g. cells with several square kilometers or even larger towns/wards. Yet, few of them pay attention to defining urban areas with micro data in a fine-scaled manner with large extend scale by incorporating the morphological and functional characteristics. This paper investigates an automated framework to delineate urban areas in the parcel level, using increasingly available ordnance surveys for generating all parcels (or geo-units) and ubiquitous points of interest (POIs) for inferring density of each parcel. A vector cellular automata model was adopted for identifying urban parcels from all generated parcels, taking into account density, neighborhood condition, and other spatial variables of each parcel. We applied this approach for mapping urban areas of all 654 Chinese cities and compared them with those interpreted from mid-resolution remote sensing images and inferred by population density and road intersections. Our proposed framework is proved to be more straight-forward, time-saving and fine-scaled, compared with other existing ones, and reclaim the need for consistency, efficiency and availability in defining urban areas with well-consideration of omnipresent spatial and functional factors across cities.
We combine the activity-based analysis with movement-trajectory approach to model the intra-urban human mobility observed from about 15 million check-in records during one year in Shanghai, China. The proposed model is activity-based and includes two parts: the transition of activity demands during the specific time period and the movement between locations. For the first part, we find the transition among activity demands vary over time, and then we construct a temporal transition probability of activity demand matrix to represent the transition probability of activity demands. For the second part, we discover that the activity demand can be divided into two classes, locational mandatory activity (LMA) and locational stochastic activity (LSA), according to whether the demand is associated with fixed location or not. Note that when one person chooses his/her next activity, the LSA would be affected by not only the attraction of locations but the distance decay. On the contrary, the LMA has no need to consider the distance decay issues. As a result, there are three trip patterns judged by the combination of predecessor activity demand type and the successor activity motive type, being associated with a different decay exponent. To validate the model, we adopt the mechanism of agent-based modeling and compare it with the observed pattern from the distance distribution, the spatial distribution and the time distribution, respectively. The result shows that the simulate patterns fit the observed data well, indicating that these findings open new directions for combining the activity-based analysis with the movement-trajectory approach using social media data. More importantly, this model may positively impact many practical systems and applications that are centered on urban planning, traffic estimation and mobile location-based service.
With more than 15 million new urban residents entering its cities every year, China is witnessing one of the greatest socioeconomic and environmental transformations in human history. In addition to these ongoing changes, urbanization in China often involves a significant political dimension, as the government would purposely accord city status to settlements, regardless of their developmental level: Largely rural settlements could be turned into “cities” overnight by administrative power. Nevertheless, city status would often translate into real urban growth, as it is closely linked to the land use quota, provision of public services, as well as local governments’ power in China. While socioeconomic and environmental aspects of Chinese cities have been analyzed extensively with aggregated statistics and remote sensing data (Deng et al, 2012; Liu et al, 2012), little is known about the shifting political geography of Chinese cities, i.e., where new city status are being granted. It is this lacuna that our project aims to fill.
We focus on the basic building block of a city proper in China: Jiedao (sub-districts). Jiedao’s counterparts in the rural area are Xiang (township) and Zhen (town), and all three are termed as township-level administrative units. We geocoded the 41,871 towship-level units based the Population Census of China, and estimated the spatial extent of individual units with Voronoi diagrams for the years of 2000 and 2010.
The end product is the first ever map of “mushrooming” Jiedaos in China. The total number of Jiedaos has grown from 5,510 to 6,923 – a 25% increase – during 2000-2010. Most new city-propers are created around major urban regions along the economically more developed eastern coast (e.g., Yangtze River Delta, Pearl River Delta, Shandong Peninsula, and Beijing-Tianjin-Hebei (BTH)). Other regions with noticeable growth are Central Henan in Central China, as well as the Chengdu-Chongqing corridor in West China. As Zhens are often turned into Jiedaos and considered as “next in pipeline” for city status, we also map out the distribution of Zhens. Again, regions in East and Central China (e.g., Shandong and Henan) feature predominantly, revealing the potential for future urban expansion.
As city status often translates into real urban growth, we conjecture that the uneven geography of mushrooming Jiedaos would entrench the already huge East-West divide in China.
Large-scale models are generally associated with big modelling units in space, like counties or super grids (several to
dozens km2). Few applied urban models can pursue large-scale extent with fine-level units simultaneously due to data availability and computation load. The framework of automatic
identification and characterization parcels developed by Long and Liu (2013) makes such an ideal model possible by establishing existing urban parcels using road networks and points of interest
for a super large area (like a country or a continent). In this study, a mega-vector-parcels cellular automata model (MVP-CA) is developed for simulating urban expansion at the parcel level
for all 654 Chinese cities. Existing urban parcels in 2012, for initiating MVP-CA, are generated using multi-levelled road networks and ubiquitous points of interest, followed by simulating
parcel-based urban expansion of all cities during 2012-2017. Reflecting national spatial development strategies discussed extensively by academics and decision makers, the baseline scenario and
other two simulated urban expansion scenarios have been tested and compared horizontally. As the first fine-scale urban expansion model from the national scope, its academic contributions,
practical applications, and potential biases are discussed in this paper as well.
A number of scholars (see White, 1988; Horner, 2002) have established a framework for analyzing the efficiency of regional commuting patterns. Typically, this framework has a minimum and maximum commute (Tmin and Tmax). Commuting is considered excessive if actual commuting (Tact) deviates from Tmin in a given city region. Tmin assumes that individuals commute, on average, to the closest possible workplace in terms of some measure of zonal separation (e.g. distance, time) while Tmax assumes the opposite.
Our graphical maps of key origin-destination movements are an innovative approach to demonstrating flows of actual travel patterns as well as those associated with the minimum solution of the TPLP. In this sense they are a useful addition to aid with the interpretation of results emerging via the excess commuting framework. They demonstrate spatial variations in flow patterns associated with Tmin and Tact and provide useful insights into the geography of transport flows associated with these solutions which are otherwise lost in previous studies of the same nature.
Using Beijing as an example, this manuscript demonstrates that smartcard data can be used to (a) assembly the required data for excess commuting studies and (b) visualize related results. Based on both smartcard and household travel survey data, it finds that the theoretical minimum commute is considerably lower for the bus than for the car in Beijing. This suggests that there is a greater inter-mixing of jobs-housing functions (i.e. a better jobs-housing balance) associated with users of that mode compared to the corresponding land use arrangement for car users. Car users locate further from the central area (Tian’anmen) than bus users. The commuting range for car users is 9.4 kms greater than that for bus users. Excess commuting is slightly higher for bus users (69.5%) than for car users (68.8%). Commuting capacity values are slightly lower for car users than for bus users, implying that car users consume less overall of their available commuting resources than bus users, albeit only marginally.
The parcel direction, as a spatial index to evaluate the urban form in the parcel scale, is currently paid less attention in the urban morphology domain. In the paper we brought forward the term of the parcel direction and its definition as to analyze the urban form quantitatively. The approach for calculating the parcel direction was as well investigated, together with the empirical study of the urban form of Detailed Planning of the Beijing Central Metropolitan Area. We calculated the parcel direction of the historical urban form of Beijing in 1949, followed with the comparison of the historical and planned forms using the proposed parcel direction index. The demonstrated conclusions are as followed: (1) The urban form in terms of the parcel direction, can be divided into four types, including normal, slanting, mixed and ecological types. (2) The parcel direction index is not correlated with the perimeter, area, or compactness indictors of the parcel. (3) The parcel direction is explicitly spatial heterogeneous, and the probability density function of the parcel direction within the entire study area varies from that of local parts. Therefore, the probability density function of the parcel direction can be adopted to examine the urban form. (4) The parcel direction can be utilized to evaluate to what extent the planned form inherits the historical form via comparing the parcel direction index of the two forms.
The intrinsic factor that drives the human movement remains unclear for decades. While our observations from intra-urban and inter-urban trips both demonstrate a universal law in human mobility. Be specific, the probability from one location to another is inversely proportional to the number of population living in locations which are closer than the destination. A simple rank-based model is then presented, which is parameterless but predicts human flows with a convincing fidelity. Besides, comparison with other models shows that our model is more stable and fundamental at different spatial scales by implying the strong correlation between human mobility and social relationship.
Land use pattern, or land use layout, is one of the key issues in the compilation of an urban master plan. Establishing land use patterns using traditional planning means depending largely on the planners, comprehensive abilities of planners and the reasonability of their requirements and preferences have direct influence on the land use pattern. Government and residents, all with various requirements and preferences, are also the main agents participating in this process in China. In this paper, we propose the Planner Agent framework to support land use pattern scenario analysis (LUPSA), based on the existing Planning Support System (PSS) research. Planner Agents are divided into three types: Non-spatial Planner Agent (NPA), Spatial Planner Agent (SPA) and Chief Planner Agent (CPA). The NPA is responsible for formulating special plans (such as transport, municipal public facilities or nature reserve plans) that correspond to available data (such as road network, public facilities and nature reserve patterns) from LUPSA. The SPA is responsible for establishing and evaluating land use patterns. The SPA considers constraints of local development conditions, communicates and coordinates with the NPA to confirm special plans formulated by the NPA that can support implementation of the established land use pattern. The CPA is responsible for determining the final land use pattern after a public participation process involving local residents. In the Planner Agent framework, we emphasize the importance of planners, and the negotiation of different agents. This framework was initially tested in a hypothetical city, followed by an experiment in Beijing. Results show that the proposed Planner Agent theory is suitable for LUPSA, and can improve the efficiency and reasonability of LUPSA.
Extensive urban planning implementation evaluation research has reported that actual urban growth significantly deviates from planned urban forms officially approved by planning departments. Researchers, planners and decision makers are concern whether a planned urban form can be fully implemented in future. In this paper, we propose an approach “form scenario analysis” (FSA) for examining the “possibility of implementing planned urban forms. This process is of the opposite to conventional urban growth scenario analysis, in which development policies are set as the input scenario conditions to generate various urban forms. A constrained cellular automata tool as a planning support system is developed for applying the FSA approach to evaluate planned urban forms. This model employs a planned urban form as the input scenario condition, aiming to identify whether any of the existing development policies can be used to realize the predefined urban form. If yes, the development policies required for the scenario form can be followed. To illustrate the applicability of FSA, We evaluated four planning alternatives for the Beijing Metropolitan Area Master Plan 2020 using the tool. The corresponding policy parameters are generated, together with in-depth policy implications for the study area. Our finding is that the planned urban form approved by the State Council of P. R. China (Alternative A in the paper) cannot be realized in the context of the current development policies of Beijing. The other three alternatives (Alternative B, C and D) differ from each other in terms of implementation probability and development policies required. This suggests that planners can adopt this simple tool to eliminate impossible planned urban forms in the early stage of compiling plans.
Key words: urban planning evaluation; planned urban f
Now public service facilities in Chinese cities present a serious spatial mismatch issue. Since those public services are characterized by fixed location and durability, there is an urgent need for more scientific measurement methods and evaluation indexes, gaining insights into not only the current situation of the supply of public services but also the degree of matching according to residents’ demand, in order to promote rational site selection and supply-demand matching for public service facilities within the city. We construct a Spatial Supply-Demand Matching Index for urban public services in Beijing, in which the objects are three types of typical public services (primary schools, hospitals and parks) in the built-up area of Beijing, where a total number of 129 jiedaos are included. Besides, our Matching Index is applied for further discussion at two aspects, the first one is an efficiency loss issue caused by the spatial mismatch of public services and urban residents and find out that the current spatial imbalance of public services, resident population and employment in Beijing is: “Residents Suburbanization> Employment Suburbanization> Public Services Suburbanization”. The second one is a social equity issue among different income groups, revealing that 72 out of 129 jiedaos are lack of schools, which means about 65% of resident population are living in the places where they can’t get enough primary educational services for their children locally. Moreover, the even worse problem is that this spatial mismatch problem has exacerbated the inequality between high-income and low-income residents.
Miss LUN Liu and Dr LONG Ying interviewed with Prof Michael Batty in December 2013. We asked over ten questions on challenges and opportunities of applied urban modeling, especially in the big data era. The attached interview report, in the form of a BCL working paper, records our talk in the interview. We are to prepare to submit it to a Chinese journal with necessary adaptations.