China has been experiencing profound adjustments in its industrial structure. Meanwhile, the industrial upgrade is also an important route to reducing its carbon emissions. This study analyzes the driving force of industrial structure change, that is, the demand of goods of each sector. With China's transition from a developing to a developed economy, the consuming preference of its citizens is expected to converge toward that of developed countries. Based on this assumption, we built a Multi-sector Intertemporal Dynamic Optimization (MIDO) model combining the neoclassic optimal economic growth theory and the input-output production structure model to project consumer preference oriented industrial structure change and carbon emission trends in China based on four scenarios of future development path of China. The simulation result indicates that the share of agriculture as well as food and clothes sectors will shrink, while the other services sector sees its share enlarging under all scenarios. In the business as usual scenario (Scen-China), the shares of heavy-manufacturing, transport, chemicals, and metals sectors continue to increase, while the shares of these energy intensive sectors decrease in the US type of consumption preference scenario (Scen-US). The shares of transport and chemicals will decline slightly in the EU type of consumption preference scenario (Scen-EU); and in the Japan type of consumption preference scenario (Scen-JP) the share of the transport sector will rise and the share of the metals sector will drop. Aggregated energy use of China will show an inversed-U shaped trend due to industrial structure change and energy efficiency improvement. The gross energy use in the Scen-China, Scen-EU, Scen-JP, and Scen-US scenarios will considerably decline from the peak value of 2810 Mtoe to 2166 Mtoe. Accordingly, the accumulated carbon emission will be in the range of 94 GtC to 72.6 GtC. The consuming preference pattern of US, due to its heavy reliance on the services sector, is better than that of JP, followed by EU and China from the perspective of energy conservation and emission reduction.
In this study, we created 2005 and 2010 A-share listed companies network database of the Yangtze River Delta and used social network analysis and rank-size analysis methods to analyze the spatial structure of urban network in the Yangtze River Delta. The result shows that: (1) The Yangtze River Delta listed companies' headquarters tended to agglomerate in the Shanghai-Hangzhou-Ningbo Z-shaped corridor. The most important change of the spatial structure of company headquarter distribution during the study period was the development from three centers to four centers. Suzhou replaced Nanjing and became the third largest hub of company headquarters, after Shanghai and Hangzhou; (2) Urban network structure maintained a core-periphery pattern. Cities along the Z-shaped corridor showed higher centrality and have strong influences on the spatial pattern of the urban network; (3) The network structure showed hierarchical diffusion, neighborhood diffusion, and administrative constraint characteristics. The provincial capitals Nanjing and Hangzhou of Jiangsu and Zhejiang provinces became major investment stronghold only after Shanghai. Nanjing's network centrality was higher than Suzhou because of its higher administrative status; (4) In the background of the Yangtze River Delta economic integration, cross-regional linkages has been strengthened, especially the diffusion of companies from Shanghai and Southern Jiangsu to Central and Northern Jiangsu was very clear. Centrality of Southwest Zhejiang was relatively low. The area was still relatively isolated within the network; (5) Administrative status and divisions and market scale were the main factors affecting the spatial structure of urban network in the Yangtze River Delta. The impact of temporal distance to Shanghai by express way, labor costs, and land costs were not statistically significant.
The regional disparity and determining factors of foreign direct investment (FDI) locations are influenced by industrial characteristics, corporate attributes, and the social and economic environments of the home country and receiving country. Changes in the location choice of FDI and influencing factors have occurred under the background of global financial crisis. Based on the theory of path dependence, we choose the Pan-Yangtze River Delta area as an example to study such change. First, we analyzed the process of spatiotemporal evolution of FDI in terms of total amount, target industry, and location choice before and after the global financial crisis. Then we explored the change in the determining factors of FDI locations and their influences through a panel data analysis model. Our study suggests that the evolution of the location choice of FDI and its influencing factors in the Pan-Yangtze River Delta area followed the path dependence model. The original evolution path of FDI was shocked by the global financial crisis, and with the dynamic change of internal and external factors such as market circumstances, factor cost, innovative milieu, agglomeration economies, suck cost, and institutional environment and their influences, the trends of total amount, target industry, and location choice of FDI showed high complexity and diversity. Specifically, the total amount of FDI experienced negative growth under the economic crisis, but along with the resuscitation of the world economy, its growth has recovered. Although the regional difference of target industry is huge, services will become the largest business for FDI in China. Moreover, because of the transformation of factor cost, policy environment, among others, it is an inevitable trend that FDI of labor/resource/pollution-intensive industries will shift from coastal areas to central and western China. However, on account of the market circumstances, innovative milieu, agglomeration economies, and so on, FDI in high-end manufacturing and service sectors will continue to gather towards urban areas.
Foreign direct investment (FDI) technology spillover is an important topic in China and abroad, but most research do not address the temporal change of such effects. This paper argues that there is a temporal dimension of the effect of FDI technology spillover. FDI effects on domestic enterprises change between spillover and crowding out over time. Using a prefecture level city panel dataset of the communication equipment, computer, and other electronic equipment manufacturing industry from 2003 to 2007, we made an empirical study on the dynamic process of FDI technology spillover and found that the process is a lying S curve: at the initial stage of FDI entering the host country, there was a significant crowding out effect. In 3 to 4 years after the initial stage, the effect gradual shifted to spillover. With time, spillover slowed and declined, eventually reached a point where there was no significant spillover or crowding out. In addition, the process of FDI technology spillover varied for domestic enterprises of different ownership types.
Simulation and quantitative analysis of urban land-use change dynamics are an effective way to understand the evolution of spatial structure in urban systems. Cellular automata (CA) has drawn continuous and increasing interest of researchers in the field of land use and land cover change simulation. Neighborhood rules are a core component of the urban CA model, with varied neighborhood effects among different land use combinations. Most urban CA models constructed with neighborhood rules consider only a small neighborhood scope under a specific spatial resolution. However, the extended enrichment factor indicates that there are still obvious neighborhood effects in large neighborhoods with a particularly long distance to the central cell. Based on a measured extended enrichment factor for a large neighborhood, we applied particle swarm optimization (PSO) to obtain the parameter settings of neighborhood rules, including various sub-neighborhoods at different distances within the large neighborhood. The extracted neighborhood rules were integrated into a widely used logistic regression urban CA model, Logistic-CA (LNCA), and a large neighborhood urban land use model, PSO-LNCA, was developed. Using Xiamen City as a study case, the PSO-LNCA model was implemented to simulate urban growth during the period between 1995 and 2010. The accuracy of simulated results by the model was evaluated with confusion matrix and Kappa coefficient. Accuracies for built-up land and non-built land and overall accuracy for 2010 are 83.9%, 91.7%, and 89.6%, respectively, and the Kappa coefficient for 2010 is 74.5%. The results show that the PSO-LNCA model achieved significantly higher simulation accuracy for built-up land and Kappa coefficient than the traditional urban CA model with a 3×3 kernel neighborhood (3.2% higher accuracy for built-up land and 4.5% higher for Kappa coefficient, respectively), and also generated relatively higher overall accuracy (1.8% higher). By integrating the extended neighborhood module, the simulation result generated by the PSO-LNCA model is closer to the actual space morphology and structure, compared with the traditional 3×3 kernel Logistic-CA model.
Flow of migrant workers in large scale is one of the most important social and economic phenomena in China. Choice of migrant destinations is a critical aspect of such movement. On the basis of a field investigation of 1091 sample migrant workers' in 33 villages in Henan Province, this study examines the choice of migrant destinations and influencing factors at a micro scale. The research found that, the flow direction and choice of destination of the migrant workers showed both a decentralized and a centralized characteristic. Distance from home area determined the density of social network and cost of household management, and the level of economic growth in destination areas affected the salary level and employment opportunities. These two factors determined the overall direction of flow of migrant workers. Other significant factors that influenced the choice of migrant workers of migrant destination were age, education level, marital status, number of family laborers, per capita average area of farmland, and economic development of the home villages. The migrant workers who were younger, with lower level of education, married, with more family laborers, and from villages with lower level of economic development had a higher probability to work outside of Henan Province and in more distant places, and vice versa. In addition, migrant workers from households with larger per capita average area of farmland were more likely to work in places further away from the home areas. Household management is an important mechanism for the choice of the migrant destination.
Determining the appropriate number of civil airports is an important topic in Chinese civil airport planning and development. Qualitative estimation of the number of airports cannot meet the requirement of future planning, thus appropriate quantitative methods are needed for providing sound support for decision making. According to the different accessibility requirements of various demand points, this paper defines different accessibility thresholds for different levels of airports, sets the minimum number of population that an airport should serve, and utilizes the revised Location Set Covering Problem (LSCP) and Maximal Covering Location Problem (MCLP) models for the stratified estimation of the total number and location of Chinese civil airports. The result reveals that to cover 95% of the total population within 100 km rectilinear distance, the required number of airports is 370~385. In the central and western regions, city-and county-level airports are all required. City-level airports need to be constructed in northeast China and there should be a number of new county-level airports in Heilongjiang Province. In the eastern region, seldom any city-level airports but some county-level airports are demanded. The result that some cities do not need new airports in the city-level estimation but the counties under these cities need one or more new airports in the county-level estimation may seem counter intuitive, but this research found that this result is reasonable. The result is heuristic for future civil airport planning.
In the past ten years, high-speed railway has rapidly developed in China and its effect on urban development is gradually revealed. This paper explores the impact of high-speed railway on market potential of 268 Chinese cites at the prefecture level or above in 2012. First, market potential function is redefined based on the average travel time and train frequency between 268 cities obtained from the railway train schedules. Second, to examine the high-speed railway effect this research compares market potential of cities with and without high-speed railway. Existing studies of high-speed railway effect have primarily focused on its contribution to time saving and paid little attention to increased train frequency. In this paper, both travel time and train frequency are analyzed. The results show that: (1) Market potential of Chinese cities without high-speed railway exhibits a multi-center and corridor structure. Cities with high values of market potential are mainly located in the Yangtze River Delta Region, Pearl River Delta Region, Beijing-Tianjin-Hebei Region, and along some major railway lines such as the Beijing-Guangzhou Railway Line, Beijing-Shanghai Railway Line, and Beijing-Harbin Railway Line; (2) Market potential with high-speed railway also presents a multi-center and corridor structure, but has higher densities around the centers; (3) the high-speed railway effect of cities along the Beijing-Shanghai Railway Line, Shanghai-Hangzhou Railway Line, and Ningbo-Xiamen Special Railway Line is most pronounced, which significantly facilitates the growth of market potential in these cities; (4) The average value of the time-saving effect of 109 cities connected by high-speed railway is 31.3% and the average value of frequency effect is 68.7%, which is the most significant part of the high-speed railway effect.
As a useful spatial interaction modeling method, gravity models have been widely applied in geographic research. The results of gravity models are sensitive to model parameters, which may lead to significant variation in modeling results when different sets of parameters are used. Therefore accurate parameters are essential to the application of gravity models. Although there have been various studies on the calibration of gravity model parameters, spatial heterogeneity of model parameters has not been carefully considered due to the lack of necessary data for such analysis. In this study we took the volume of China's railway passengers between city pairs in 2010 as the indicator of the magnitude of spatial interaction between cities. Nodal attraction of cities was depicted by the total disposable income of residents in the city areas, which represents the attraction of a city. Compared to the existing literature, this study modified the basic form of gravity model and introduced frequency of trains as a variable into the model, representing the spatial separation between city pairs along with travel time. This adjustment produced improved goodness-of-fit result. Three parameters in the modified gravity model were tested: nodal attraction, α; travel time, β; and frequency, γ. Spatial heterogeneity of each parameter was analyzed by means of regression analysis and GIS. The results show that β has the largest range, followed by α and γ. The research indicates that remarkable spatial heterogeneity exists and cannot be overlooked. Using a single set of parameters of gravity model for different regions may not be appropriate.
Measuring and analyzing the time-space compression phenomenon caused by improved road network accessibility in geographical space have been a major challenge for transport researchers. Current attempts of comparing accessibility pattern maps only describe centrality of nodes, and the isochrone approach is capable of analyzing individual cities but fails to provide a complete picture of regions of concern. This study developed an analytical model using time-space map to visualize time-space compression phenomenon, based on a synergy of current big-data available on the internet and statistical and 3D-visualization technologies. OD (Origin and Destination) data matrix (travel distance and duration by cities) was generated from web-map-server's direction API using web-crawling programs. Multidimensional scaling method was then applied to find the best-fit configuration space, which redraw the map by replacing the euclidean distance with network distance or duration. The scale and distribution of errors were statistically tested to verify the validity and reliability of the results. Finally, 3D time-space maps were visualized and overlapped with the geographical map to observe stretching, shrinking, and wrinkling effects of space caused by uneven transportation accessibility improvements. Using Hunan Province as a case, this study produced two time-space maps of travel distance and duration between cities, and analyzed the errors on these maps. The case study supports the view that time-space analysis is a valid method to visualize time-space compression and a useful tool to generate policy recommendations for building a more balanced road network with higher accessibility of regions.
Urban traffic condition is a fundamental aspect of city operation and development, also determines the operational efficiency of cities and the optimization of urban spatial structure. The ring and dispersal pattern of urban road network in Beijing influences the internal structure and form of the urban space, also affects the spatial accessibility of different functional districts. Based on the sampling data of a questionnaire survey, this paper examines accessibility of 10 office clusters of Beijing. By multidimensional scaling analysis, we evaluate the respondents' subjective perception of accessibility in the research areas. Meanwhile, using ArcGIS spatial analysis tools, we analyze the actual accessibility of office clusters and classify the evaluation results of accessibility. Through a comparison of the subjective perception based on the questionnaire survey data and the objective assessment result, we analyze the accessibility in different office clusters of the inner city. The result shows that, first, in different office clusters, there is no obvious difference in the selection of transportation means, but non-motor vehicles and private cars were used frequently in certain areas. Ground transportation and rail transportation as leading public transport tools are the main transport methods that urban residents in Beijing choose to use in commuting. Nearly 50% of people preferred to walk 5~10 minutes to public transportation sites and entertainment facilities. Second, there are significant differences between commuters' subjective perception of accessibility and objective assessment result in different office clusters of the inner city. Respondents had different perception of accessibility in different office clusters. Third, the difference between subjective and objective accessibility assessments indicates that transport accessibility assessment should not only focus on the distance to public transport sites, but also on travelers' psychological perception and the convenience of transfer between different lines and transport means, especially the connection of "the last kilometer" between public transportation sites and workplace. Fourth, 5~10 minutes walking distance is the basic space of activities for city residents. This not only provide the basis for the planning and design of public transportation sites and supporting facilities, but also make constructing the "5~10 minutes walking circle" an important tool for improving the spatial accessibility in Beijing's urban area. These results can be useful for optimizing the location of office spaces in the city of Beijing.
In recent years, with the construction of high-speed railway network, regional economic development in China has entered into an "era of high-speed rail". High-speed trains have become an important part of people's travel choices. To examine the scope and structure of high-speed rail influences, this study selected 14 stations along the Beijing-Guangzhou High-Speed Railway as the research objects. It introduced the concept of "passenger-flow hinterland" and "business passenger-flow hinterland" and analyzed the scope and structure of influence of these stations in terms of total and business travelers respectively. Influencing factors are discussed using the central place theory, market area theory, rational decision theory, and so on. The results show that the average radius of passenger-flow hinterland is 151 km, while the average radius of business passenger-flow hinterland is 139 km which is more limited than that of the passenger-flow hinterland. The scope of the passenger-flow hinterland is positively correlated with the scale of the station and the distance of travel outside of the hinterland area, and negatively correlated with the cost of travel within the area. Similarly, the scope of the business passenger-flow hinterland is positively correlated with the scale of the station and the distance of travel of business travelers outside of the hinterland area, and negatively correlated with the cost of travel of business travelers within the area. The "core-periphery" hinterland structure of high-speed railway station is clear. The "core-periphery" structure of passenger-flow hinterland is positively correlated with population distribution, and negatively correlated with the structure of the travel time within the hinterland area. Similarly, the "core-periphery" structure of business passenger-flow hinterland is positively correlated with the spatial structure of GDP, and negatively correlated with travel time of business travelers within the area. This paper explores a new field of the study of high-speed railway and provides a basis for high-speed rail planning and urban development planning in the future. Major drawbacks of this study include that the combined effect of influencing factors on hinterland scope is not modeled, which requires further research.
In order to study coastal flooding in Shanghai caused by typhoons following typical paths, the possible effects of the six severe typhoon storm surges were analyzed using MIKE21 Flow Model. Based on the probable maximum intensity of tropical cyclones and by taking into consideration sea level rise, topographic change, and seawalls subsidence, 12 scenarios were analyzed for potential storm surge impacts. The results show that, because of the high standard protective seawalls, the possibility of overtopping inundation resulting from storm surges is extremely low under the present condition. However, as the strength of influencing factors increases over time, overtopping inundation becomes more likely. In 2040, the inundation caused by a tropical cyclone landing in Shanghai can be very large, and water depth can reach 3.0 meters or more in some local areas. About 25% of seawalls would be at risk of flooding , and the inundation area of the storm surges can reach 910 km2 under the proposed scenarios. Storm surge disaster prevention measures include protecting the source areas of water supply to the city, creating urban flood retention space, increasing the protection standard of seawalls, enhancing the drainage capability of the city, and optimizing the distribution of the emergency shelters.
The extensive planting of single crop for extended time periods in agricultural landscapes has led to a decrease in species diversity. Natural and semi-natural habitats within agricultural landscapes, as well as the associated plant and small animal (especially ground arthropod) communities, are of vital importance for preserving biodiversity in agro-ecosystems. It is crucial to study the relationship of regional agricultural landscape heterogeneity and biodiversity for maintaining ecosystem services and stability. In this study, Fengqiu County of Henan Province, a typical agricultural region in the lower reaches of the Yellow River, was taken as the study area for investigating the diversity of semi-natural habitat plants in agricultural landscape and ground arthropods in comparison to cropland of this agricultural ecosystem. The analysis of the relationship between plant diversity in semi-natural habitat and landscape variables was repeated for four different spatial scales (100 m, 250 m, 400 m, 550 m) and for artificial forest, hedgerow, and ditch environments to determine the optimal spatial scale of analysis for plant diversity in agricultural landscape. The relationship between ground arthropods diversity and semi-natural habitat variables was also analyzed at the local habitat scale. All analyses were conducted using generalized linear models (GLM) in R statistical software. The results show that: (1) Plant diversity was highest in artificial forest. The abundance and species richness of ground arthropods in semi-natural habitats were significantly higher than that in farmland; (2) The relationships between richness of plant species and diversity in semi-natural small habitat and landscape heterogeneity were strongest at a spatial scale up to 250 m radius around the sampling point. But the relationship between ground arthropod species and diversity in semi-natural small habitat and landscape heterogeneity was strongest at a spatial scale up to 250 m radius around sampling points in artificial forest and cropland; (3) Results of GLM regression on plant species diversity and landscape variables at the scale up to 250 m radius around sampling points confirmed that vegetation richness (Sveg) was negatively correlated to interspersion and juxtaposition index (IJI) in artificial forest and hedgerows; In ditches, vegetation richness (Sveg) had a negative effect on edge density (ED) and aggregation index (AI) but a positive effect on Shannon's diversity (SHDI); (4) Results of GLM regression on ground arthropod species diversity and landscape variables confirmed that at the range of 250 m radius around sampling points, abundance was negatively related to Shannon's diversity (SHDI) and land use richness, and was only significantly negatively related to Shannon's diversity (SHDI) in cropland fields. Generally speaking, the semi-natural habitat elements in intensively farmed agricultural landscapes may function as refugia and sources of dispersal or stepping stone habitats. It will play an increasingly important role in regional biodiversity conservation and improvement by connecting these scattered semi-natural habitat elements in agricultural landscape into networks. However, attributes of semi-natural habitats, such as area, quantity, type, and spatial distribution, are among the important research topics in urgent need of study and consideration.
