Land use issue is an important constraining force for economic sustainable development of China. Urban and rural rapid expansion depletes valued land resources under the background of rapid urbanization. An extensive use pattern might cause a serious waste of land resources. The study on influencing mechanism of land intensive use (LIU) in China at the county level is an important tool for effective LIU practice and policy-making. This paper uses OLS model, Spatial Panel Lagged model and Spatial Panel Error model to characterize the influencing mechanisms of five class factors and 17 variables supported by GIS (Geographic Information System) and MATLAB. And a comprehensive data set, including physical geography attributes and socio-economic information with 2286 counties, was developed. Meanwhile, the spatiotemporal pattern of LIU has been discussed by means of GIS. The results show that Spatial Panel Data models are slightly superior to OLS model in terms of significance and confidence level. Regression results of these models indicate that industrialization, urbanization, economic development level, location, transportation and policy have significant impact on LIU of counties. The variables of physical geography are less significant than socio-economic variables. An ignored variable of historical factor, however, became the most significant factor. In the future, the LIU at the county level should enhance favorable factors and reduce disadvantageous ones, which can be acquired by improving the entire level and quality of industrialization and urbanization. We argued that an efficient and complete land market and operating system should be built to reflect market-oriented activities at the first place. Then, according to regional differences, differential LIU regulation policies and measurements should be optimized. Meanwhile, we should pay close attention to the carrying capacity of local resources and environments when conducting LIU practices.
Quantity and spatial pattern of farmland has changed, which leads to significant change of farmland potential productivity under the influence of national ecological environmental protection project and the rapidly increased economic growth during the last two decades. In this study, farmland potential productivity in China was calculated based on meteorological data, terrain elevation data, soil data and land use data in 1990, 2000 and 2010 by using the Globe Agricultural Ecology Zone model (GAEZ). Then, the changes in farmland potential productivity in response to farmland change from 1990 to 2000 were subsequently analyzed. (1) In 2010, total farmland potential productivity is 1.055 billion tons in China, and the average farmland potential productivity is 7614 kg/hm2, which shows tremendous heterogeneity in spatial pattern. The productivity in eastern China is high, while that of northwestern China is low. High value region of farmland potential productivity is mainly distributed in South China and the middle and lower reaches of the Yangtze River. (2) The obvious tempo-spatial heterogeneity of farmland change from 1990 to 2010 has a significant influence on the farmland potential productivity in China. The trend shows the farmland potential productivity decreased in southern China and increased in northern China. Furthermore, the gravity of the growth of farmland potential productivity moves gradually from northeastern to northwestern China. The net decrease of farmland potential productivity is 2.97 billion tons, which occupies 0.29% of the national total productivity. (3) There is a huge difference of the farmland potential productivity in response to farmland change between two periods from 1990 to 2000 and from 2000 to 2010. During the first decade, net increase in the cultivated land areas is 10.11 billion tons, which primarily spread across Northeast China Plain and arid and semiarid regions of North China. During the next decade, net decrease in the cultivated land areas is 13.08 billion tons, primarily distributed in the middle and lower Yangtze River region and the Huang-Huai-Hai Plain. In general, during the last two decades, the reason for the increase of the farmland potential productivity may contribute to the reclamation of grassland, woodland and unused land, and the reason for the decrease of the farmland potential productivity may result from the urbanization that occupies the cultivated land and Green for Grain Project that returns farmland to forests and grasslands.
Through an integration of exploratory spatial data analysis (ESDA) and confirmatory spatial data analysis (CSDA), this study examines the space-time dynamics of regional innovation at the provincial scale in China from 2000 to 2011. The results show that: firstly, since the implementation of national innovation strategy, the annual growth ratio of innovation outputs of the provinces in China has experienced a drastic process of acceleration, which suggests the overall improvement of regional innovation capabilities. However, an overwhelming status in growth rate still belongs to eastern region, leading to the rise of the coastal-interior division and the divergence among regions, and regional innovation in China may fall into the “Matthew Effect” that the strong will become stronger and the weak will be constantly weaker. Secondly, regional innovation outputs and inputs in China experience an increasing change of spatial clustering over time. Various types of hot spots are identified over time, revealing that innovation hot spots overlay well with other variables. Finally, the selected explanatory variables, such as GDP, RDE, RDP and PCH, have significant direct impacts on provincial innovation in China. There exist obvious spatial spillover effects in provincial innovation activities, and the geographic region of which has crossed the provincial border. The spatial dependence of innovation activities gives rise to the feedback among the provinces, and the acknowledge spillover of adjacent province have material influence on a specific province.
Studying the change of population distribution and density can provide important basis for regional development and planning. However, the spatial patterns and driving factors of the change of population density in China were not clear yet. Therefore, using the population census data in 2000 and 2010, this study first analyzed the change of population density in China and divided the changes in all 2353 counties into 4 types, consisting of rapid increase, slow increase, slow decrease and rapid decrease. Subsequently, based on the partial least square (PLS) regression method, we recognized the significant influencing factors of population density change among 11 natural and social-economic factors for the whole country and counties with different types of population change. The results showed that: (1) compared to the population density in 2000, the population density in most counties (over 60%) increased by 21 persons per km2 on average, while the population density in other counties decreased by 13 persons per km2 in 2010. Of all 2353 counties, 860 and 589 counties respectively show rapidly and slowly increasing population density, while 458 and 446 counties show slowly and rapidly decreasing population density, respectively. (2) Among the 11 factors, social-economic factors have impact on population density change more significantly than natural factors. The higher economic development level, better medical condition and stronger communication capability were main pull factors of population increases. The dense population density was the main push factor of population decreases. These conclusions generally clarified the spatial distribution pattern of population change and its influencing factors in China over the past 10 years and could provide reference for the future population planning.
China's rapid urbanization is accompanied by a continuous growth of economy and water use, and also a severe urban water crisis. However, the quantitative relationships and the interaction mechanisms among urbanization, economic growth and water use change are still unclear. To measure the exact driving effects of urbanization on economic growth and water use change, a complete decomposition model was established, and was applied in China and its 31 provincial administrative regions from 1997 to 2011. Results show that: (1) China's urbanization contributed about 30% of economic growth every year. More than 60% of economic growth relied on the increase of production efficiency. Therefore, such idea that urbanization is the engine or major driving force of economic growth may be properly weakened. (2) China's urbanization increased 2352×108βm3 of water use by intensifying the economic aggregate. However, it decreased 4530×108βm3 of water use by optimizing the industrial structure and improving the water use efficiency. Therefore, urbanization did not lead to water use growth. The cause for China's water use growth was the increase of population and economy. (3) In those provinces which are located in the eastern and central China, have large population and economy, and step into a period of accelerating urbanization, urbanization generally made great contribution to economic and water use growth. At the same time, it also had great contribution to industrial restructuring and water use efficiency improvement, and then largely decreased water use. In total, water use was decreased by urbanization in most provinces, and the spatio-temporal differences among them were lessened. (4) Although urbanization helps to decrease water use for China or a large region, it may cause water crisis in urban built-up areas or urban agglomerations. Therefore, the transfer and compensation mechanisms of water resoureces should be constructed as soon as possible between urban and rural areas, or low and high density urban areas.
Urban multi-center phenomenon is very common in many countries, which challenges urban models with the assumption of single center. Although there are literatures trying to explain the mechanism of multi-center urban system using models based on multi-center, the lack of empirical research makes the models being questioned. Under the pattern of multi-center, does the traditional classical geographic model like law of distance decay exist? What factors will disturb the model? This study aims to analyze and validate the spatio-temporal discipline of attration and mutual relationship between two commercial centers, based on spatio-temporal data mining of floating cars' GPS data and the recognition of two important commercial centers in Shenzhen City, China. The study reveals that the attraction between two commercial centers shows distinct power function relationship, which validates the law of geographic spatial decay. At the same time, the spatial decay's law shows some local disturbances due to a series of causes, such as the mutual attraction from other important and crowded areas, the influence of infrastructure to accessibility, urban spatial layout factor like landform and humanity factors like consumer behavior and preference etc.
For the first time in the examination of post-reform Chinese cities, this study uses the newly published 6th census data, at the microscopic level of residential committee, to examine the segregation of housing tenure in Guangzhou, the southern capital city. It first measures the housing tenure index for urban communities, and articulates the spatial pattern of housing tenure index across the city. More than that, it sheds light upon the mechanism of the differentiation of housing tenures through a series of regression models in terms of the variables of population, institution, market and space. In this vein, this paper contributes to the knowledge of the sociospatial morphology of post-reform urban China, with a particular attention paid to the dimension of housing tenure, so to fill the vacuum of our understanding about the pattern or dynamic mechanism of property right spatiality against the context of fast rising urbanism. There are three major findings. First, the average level of housing tenure index of Guangzhou is about 0.71, a high level, indicating its fast-speed privatization as well as de-collectivization of housing assets. Nevertheless, in the study we identify marked disparities across districts, as the index is the largest at the inner suburb, the smallest in the outer suburb, and the level of the central city is in-between. Thereby, the central city is featured by a mix of housing tenure, whilst that of the inner suburb is far more polarized, of which the tenure is dominated by private rental housing, especially those in "urban villages". Moreover, with regards to the spatiality of housing tenure within the central city, there is a "central-peripheral" pattern, as the highest index is found at Yuexiu, Liwan and Haizhu districts, the central area, whilst that of the surrounding districts is far smaller. Second, it is found that the segregation of housing tenure in Guangzhou is not very high, just 0.45, and the concentration index is about 0.68, which indicates that housing with different tenures in Guangzhou is largely spatially mixed, so that in general the segregation is by no means high. A close examination of districts indicates a complicated landscape: the tenure segregation in the inner suburbs, such as Haizhu, Tianhe, Baiyun and Huangpu, is pretty high, or even polarized, whilst the segregation index of outer suburban districts, such as Huadu, Conghua, and Zengcheng, is far smaller. The polarized housing tenure of inner suburbia indicates the assemblage of urban/migrant villages with commodity housing estates in the inner suburbia of Guangzhou. Such findings further highlight the impacts of urban villages and their private rental housing regime upon the sociospatial morphology of post-reform Chinese cities. Third, there are five factors we identify, through regression models, as the major factors of the sociospatial ecology of housing tenure: marriage status, age, educational attainment, hukou status and residential conditions; moreover, two variables, marriage and hukou status, are found to be the key determinants. In this sense, we argue that, differing to the situation in the West, it is the combined effect of family and institution, rather than market, that is driving the (re)structuring tenure landscape of post-reform urban China.
As a new mode of transportation, the rapid development of high-speed rail (HSR) will bring a leap in the history of transportation and have a comprehensive impact on the regional structure, population mobility, geographical division of labors, regional linkages, land use, and so on. Therefore, it is significantly important to study the impacts of HSR on regional spatial interactions, especially under the background of regional economic integration. The paper researches the impact of high speed rail on the reconstruction of spatial economic linkages. Based on the GIS network analysis tools, this paper first calculates the time cost matrix of 333 prefecture-level administrative units and four municipalities, and then uses the gravity model to calculate the interurban economic linkages, and lastly analyzes the distribution of the total economic linkage and the economic linkages between any two cities. In order to analyze the impact of HSR on regional spatial interaction, this paper resumes three scenarios: the current transport network in 2012 without the HSR network (scenario 1), the current transport network in 2012 (scenario 3), and the planning HSR network in 2020 (scenario 3) based on the current transport network, to calculate the time cost matrix of 337 cities. Results indicate that: (1) Cities in the east have the highest economic linkages, and cities with the highest increase of economic linkages are located along the HSR lines, which will lead to regional restructuring; (2) The development of HSR lines will improve the economic linkages between cities, and the increasing rate during the first period (comparing scenario 2 with scenario 1) is much higher than that during the second period (comparing scenario 3 with scenario 2); (3) From different perspectives and regional scales, the development of HSR has different impacts on spatial difference; (4) It is possible for cities in a long distance to have high economic linkages with the construction of HSR lines, which could also change the linkage directions.
Aviation hub-spoke structure is an important transportation network to achieve economies of scale development. As regards to its construction, most of methods are proposed by human geography scientists, whose efficiencies are affected by the authors' experience. In this paper, we present a novel graph method to extract hub-spoke structure from aviation network directly, which is more objective and efficient. Taking Chinese aviation network as a case study, we integrate a constraint distance into the conventional maximum leaf spanning tree algorithm to extract tree-shaped hub-spoke structure. The tree-shaped hub-spoke structure forms the branch airlines, and the top 10 degree nodes selected as aviation hubs are Beijing, Shanghai, Guangzhou, Chengdu, Urumqi, Kunming, Xi'an, Changsha, Harbin and Guiyang. The ten hubs dominate other non-hubs in different regions of China. For example, Urumqi dominates Northwest China and Shanghai dominates eastern China. The airlines among the hubs form the trunk airline network, which covers most of China's territory except the southwestern part because of lacking of a powerful hub. The aviation hub-spoke structure is generated by merging the branch airlines and the trunk airline network. Compared with the result of previous research, the hub selection of our method is more reasonable in some cases, such as selecting Harbin instead of Shenyang in Northeast China; the branch airlines and trunk airlines generated by our method have broader coverage; the division of branch and trunk airlines is more objective due to the use of constraint distance. In addition, our hub-spoke structure fits the real geographical situation better than the previous results. To sum up, the contributions of this paper are: (1) developing a novel maximum leaf spanning tree algorithm with distance constraint; (2) proposing a novel aviation hub-spoke structure construction method based on the algorithm; (3) applying the method to extract the hub-spoke structure of Chinese aviation in 2012, and it performs quite well.
Taking Nanjing as a case study, this paper calculates a matrix to describe the flows between scenic spots using data mining of tourism strategies and then systematically analyzes the structures, mechanisms and patterns of the flows. This study has drawn the following conclusions: (1) All the scenic spots form a hierarchy of several levels and the central ones are positioned as a core node on the flow network. Based on the quantity of inflows and outflows, Sun Yat-sen's Mausoleum is classified as a diffusion-type spot, Confucius Temple as a clustering-type one and Xinjiekou as a balance-type one. (2) The tourist flows have demonstrated a clear effect of distance decay. The scenic spots in inner city play a dominant role in influencing the overall flow. (3) The pattern of the flows is determined by the interactions between the intensities of inflows, outflows and the origin-destination distance. These flows follow the Wilson model represented as a power function. Compared with the inter-city and intra-city daily flows, the tourist flows between the inner city scenic spots are less sensitive to distance. (4) The primary scenic spots in Nanjing, encompassing the three systems (Sun Yat-sen's Mausoleum system, Confucius Temple system and central business district system), can be abstracted into three models: diffusion from a single center, clustering to a single center and balancing between multiple centers. The flow pattern is characterized by the primary flows between core nodes, secondary flows between the core and minor nodes and between the minor nodes, and the tertiary flows between the minor and normal moves and between the normal nodes.
Mr. Wang Yiming is a geographer working for the government over a long period of time, and he has been insisting on the combination of research in theory and practice. His academic thoughts focus on the geographical concept of time and space in developing regions under the theoretical framework of human-environmental interaction. And his academic thoughts would be of great significance in explaining and revealing the rules and structure changes of geographic process in developing regions (developing countries & regions, even microcosmic field, and the village for instance), and becomes a significant supplement to the current geographic theory. Mr. Wang has been striving for the research in the spatial and temporal views as well as for the application of geography in the aspects, including regional PRED system, regional land development and planning, regional historical geography, talent cultivation and academic activities of human geography. Furthermore, he has devoted himself to the service that Geography has offered for the national and regional development and decision making. Moreover, innovative research and practice that Mr. Wang has carried out have made outstanding contributions to the development of geography in China, particularly to the local economic and social development and environmental protection of the minority regions with the geography services. His academic thoughts deserve our inheritance and development, and the striking contributions he has made to the geography in China both in the theory and practice would surely be recorded in the history of the development of geography.
