Urbanization is essentially a geographical concentration of population and industry, and change of landscape patterns. The proportion of the urbanized population in China has increased to more than 50% during the recent decade. The rapid growth in such a short time period has not only led to an improvement of material wealth and a higher standard of living, but also caused severe environmental pollution, particularly the air pollution in many urbanized regions of China. In this research, multi-resolution remote sensing images, meteorological records, environmental monitoring data, and ground survey records were employed at multiple scales to understand the relationship between rapid urbanization and urban air quality, taking PM2.5 concentration as an indicator of air quality. The key findings are in the following three areas: (1) The spatial-temporal patterns of PM2.5 concentration in China; (2) The spatial-temporal patterns of the relationship between urban PM2.5 pollution and rural PM2.5 pollution in China's major cities; and (3) The linkage between urbanization and PM2.5 concentration at global, regional, city, and local scales. The results of this research also encourage different approaches to urbanization study in order to mitigate the negative impact caused by urban air pollution, both in China and in other rapidly developing mid- and low-income countries.
The framework of sustainable livelihoods analysis (SLA) can be used for semi-urbanized farmers working in cities in order to promote urbanization in China and is suitable for research at household scale in China's western regions for improving sustainable rural development. This article first summarizes the concept and analytic framework of sustainable livelihoods, and from the comprehensive perspective of geography, develops a theoretical and analytic framework that is applicable to China's empirical study, based on the sustainable livelihoods of semi-urbanized farmers and sustainable rural development. Second, based on the program "Assessment of livelihoods status of semi-urbanized farmers, and obstructive factors and policy intervention of the transformation to urban residents" supported by the National Natural Science Foundation of China, the international and Chinese research on sustainable livelihoods, and the empirical research progress on the transformation from semi-urbanized farmers to urban residents and sustainable rural development in China, are introduced. Finally, this article presents the key themes of future research including integrated study of the transformation from semi-urbanized farmers to urban residents and sustainable rural development; comprehensive research of willingness and obstructive factors of transforming semi-urbanized farmers to urban residents; interactions of semi-urbanized farmers and rural development and the effect of transformation to urban residents; and integrated research of sustainable livelihoods and sustainable rural development.
Vegetation phenology is an effective index that reflects the growth condition of vegetation and their response to climate change. Analyzing vegetation phenology at landscape or smaller scale will be a powerful supplement to remote-sensing based and artificial observed phenological studies. In this study, we applied the time series digital images from typical observation stations in camera-based phenology network (PhenoCam) to fit the seasonal growth curves at region of interest (ROI) and pixel scales. Key vegetation phenological parameters on the growth curve were extracted using multiple methods. First, we realized the custom definition of ROI by arbitrarily drawing polygons on the image and growth curve fitting based on the greenness index in the ROI. The results indicate that double logistic method is adapted for modeling the vegetation growing process at middle-high latitude that have a single growth peak. The spline method shows a good performance for fitting growth curves of vegetation that has multiple growth seasons. Second, based on the fitted curve, we used four models (Klosterman, Gu, TRS, and Derivatives) to derive the key phenological parameters for vegetation having single growth season. MODIS EVI-based phenological parameters were extracted as a comparison with camera based phenological parameters. We found that their capabilities in detecting phenological parameters in forest and cropland were consistent. For the vegetation with more than one growth season, the growth curve was fitted with spline method, then the change point detection method was applied to determine growth seasons on the curve and extract the key phenological parameters. The uncertainty of the fitting methods and phenology methods were estimated, with all of the RMSE less than 0.005. Klosterman method is identified as the most robust. Vegetation greenup date was extracted for each pixel in the ROI that can be useful for distinguishing the phonological diversity between different species. Pixel level vegetation phenology analysis could be used to identify biodiversity at landscape scale in the future.
With the rapid economic growth and the advancement of industrialization and urbanization, China has entered into a new stage of transformation and development since the economic reform and opening-up. However, due to the sectoral management by various planning departments, different planning system and technical standards present a phenomenon of boundary crossing and spatial overlap in the land space. How to solve the problem of boundary adjustment in conflict area caused by different planning and establish a scientific and orderly spatial planning system have become important and difficult issues. Because a large amount of complex spatial information is involved in spatial planning, we also need to consider the natural and socioeconomic attributes of land space. Therefore, spatial planning under such circumstances becomes a multi-objective optimization problem for nonlinear combinations. Traditional mathematical models such as linear programming and grey linear programming cannot meet this requirement. But the development of geographic information technology provides important support for spatial optimization. Scholars have combined mathematical models with the algorithm to explore the quantitative structure and spatial optimization of regional land space. Yet, these studies essentially take land use into consideration, ignoring the systematic and hierarchical nature of land space. In addition, they have mainly considered land use planning or master urban planning but not considered the optimization of various land spatial conflicts under different planning schemes. On the basis of existing spatial optimization models and intelligent algorithm, a model of land spatial optimization with both multi-objective programming and genetic algorithm has been constructed in this study. This model aims to improve the spatial value, reduce the degree of spatial fragmentation, and coordinate various kinds of space. In order to simulate different optimization results and provide solutions for decision makers, three scenarios were set up in this study. Taking Yantai City as the research area, the multi-objective programming model was chosen to carry out the study of land spatial optimization under three kinds of planning in 2020. By using the optimization model, land space efficiency has been significantly improved, with agricultural, urban, and ecological space values increased by 23.24%, 29.27%, and 6.30%. Agricultural, urban, and ecological space values have reached 1.17×109, 1.14×1010, and 6.44×107 yuan. After optimization, all kinds of spaces are reasonably distributed and spatial aggregation is increased. Spatial aggregation has reached the highest level with the value of 1.5876 in the ecological protection scenario, and the degree of spatial coordination reaches 2.5245 in the economic development scenario, which is the highest of all scenarios. The experimental results show that the optimization model in this study can effectively solve the problem of land space overlap and promote effective allocation of land space. Moreover, it can improve agricultural, urban, and ecological values in the land space and coordinate the development goals of different planning. It provides a technical support for land spatial optimization in the context of "multiple planning integration" in the future.
Although accessibility in terms of travel time has improved to a great extent under the construction of high-speed rail, people's consumption expectations of high-speed rail are limited by the raise of travel cost caused by the high ticket price of high-speed rail. From the perspective of cost accessibility and people's consumption capacity of high-speed rail, the level and change of inter-provincial cost accessibility, people's consumption capacity, and consumption expectations are calculated and analyzed by average travel cost, high-speed rail consumption capacity index, and high-speed rail consumption expectation index, based on the data of shortest travel time and corresponding railway fares between provincial capital cities, and per capita income of urban residents in 2008 and 2015. The results show that: (1) Travel cost accessibility has improved to different degrees under the construction of high-speed rail in china, and the spatial pattern of cost accessibility has been transformed from the "core-periphery" pattern with Zhengzhou-Jinan as the cores and other provinces as the peripheries to the "core-periphery" pattern with Hohehot-Taiyuan as the cores and other provinces as the peripheries; (2) People's consumption capacity of high-speed rail in the majority of provincial capital cities has increased to different degrees, while the level of consumption capacity and consumption expectation in central and eastern China is superior to the western and Northeast China. The research can provide some references for optimizing the service provision and improving the efficiency of the high-speed rail system.
Using the latest economic census and population census data as well as the transit-based travel time data obtained through the Baidu Map API, this study examines the job accessibility via transit in the Beijing metropolitan area and helps understand how well workers can access jobs by transit in Beijing and how it is different for various population groups and in different regions. Our results show that residents in the Beijing metropolitan area can reach 18.3% of metropolitan jobs within 60 minutes by transit, which is better than the average job accessibility via transit for 100 largest metropolitan areas in the United States, and similar to the New York metropolitan area. Due to the limited extent of job suburbanization as well as the hub-and-spoke pattern of the road and transit network in Beijing, there exist great regional disparities in the job accessibility by transit within the Beijing metropolitan area, with the job accessibility level significantly higher in the inner city than in the suburbs. Compared to jobs, population has suburbanized more extensively in Beijing, which has led to the great jobs-housing imbalance in the metropolitan area. With the increasingly more extensively decentralized spatial distribution of population, great challenges lie in further expanding the transit network to better serve the suburbs. Meanwhile, since most jobs in the inner city are oriented toward workers with higher levels of education, highly educated population is better served by the current transit system. Meanwhile, less educated population (without college degrees) and migrants reach less metropolitan jobs by transit because they are more extensively suburbanized due to their relatively low income and limited housing options. This raises a concern about the ability of suburbanizing disadvantaged populations to connect to job opportunities via transit. Therefore, multiple policies including affordable housing programs, transit investments, economic development initiatives, and appropriate land use planning should be coordinated to address the apparent spatial mismatch that disadvantaged population groups are facing.
Since the central government proposed "balancing basic public services" in 2006 and the 2009 World Bank Development Report advocated "equal coverage of residents' access to public services," improving facility accessibility and spatial distribution have increasingly become one of the development goals for regional governments and hot topics for academic research. In Shanghai Municipality, accessibility of medical facilities in different regions within the city needs to be examined urgently because it is closely related to people's livelihood, health, and social justice. Based on the accessibility of tertiary, secondary, and community hospitals in Shanghai, this study analyzed the accessibility of medical facilities in different areas of the city, and the variation between the registered and floating populations. Improved potential model and multivariate linear regression model are used accordingly. The study further explored the influencing mechanism of individual accessibility of medical treatment. The results are as follows. First, the inner city is characterized by the highest regional accessibility of medical facilities, and accessibility is gradually reduced from the inner city to the suburbs. The fluctuation of hospital accessibility is relatively clear in the suburban area. Anting Town, Huaxin Town, and some other towns in the west of Shanghai still lack of medical facilities. Second, registered population's accessibility of medical treatment is better than that of floating population, and the most obvious difference between the two groups is found in the fringe of the central urban area and the inner suburban areas. Compared to the Pudong area, floating population in the Puxi area is facing more difficulties in seeking medical care. Third, residential location significantly affects accessibility of medical treatment. For the registered population, community hospitals are more accessible in outer suburbs, and secondary hospitals are more accessible in the fringe of the central urban area compared with the inner suburbs. For the floating population, the above variation is not significant. No matter which regions they live, they are generally facing severe medical accessibility problems. Finally, socioeconomic and institutional factors also have impacts on accessibility to medical facilities. Middle-aged and elderly residents with higher education have better access to medical facilities. Housing property rights and medical insurance are much related to registered population's medical accessibility, while economic factors matter more for floating population. This study provides some suggestions for the relevant government departments to identify areas lacking medical facilities and improve the spatial distributions of medical and public transport facilities, thus helping to achieve the goal of equal access of health care. Future studies need to consider the integrated impact of spatial and institutional factors on residents' medical preferences and behaviors.
As the basic law of geography, the law of distance-decay is of great significance to the formation and evolution of spatial order. Using the data of Fujian expressway toll stations in October 2016, an expressway flow origin-destination matrix was identified with county areas as the basic unit. Cumulative proportion curve, spectrum analysis, and null model were used to simulate the distance-decay effect of expressway flow on the provincial and county scales. Then, combining spatial analysis and correlation analysis, the spatial differentiation characteristics and the distance-decay effect of expressway flow were discussed. The results show that: (1) The expressway flow is mainly concentrated in the 0~200 km and 0~200 min sections, which is in line with the economic radius of road transportation and the temporal and spatial fracture characteristics of traffic flow. (2) The expressway flow has a significant decreasing tendency on the provincial scale with the increase of distance. When using the road distance and power-law decay function, the distance decay coefficient is 2.674, which is significantly higher than the conventional value of 2. (3) The distance-decay rates of the expressway flow in different counties show a clear zonal pattern, corresponding well with the spatial distribution of expressway flow. (4) The law of distance-decay not only influences the evolution of spatial order, but also is influenced by the evolution of spatial order, and it is endogenous to the spatial patterns of socioeconomic activities. Under certain conditions, the strength of socioeconomic spatial connections will form a self accelerating feedback process with the increase of node size, population, and economic density, and the optimization of location conditions.
Urban network research based on a specific type of industry has unique value and is essential for understanding the industrial pattern and urban function. Using the data of headquarters and branches of the Chinese A-share listed medicine enterprises, this article analyzes the characteristics of urban networks shaped by these firms. The results show that: (1) Most of the headquarters of medicine enterprises are concentrated in the coastal economic regions, including the Yangtze River Delta, the Pearl River Delta, and the Beijing-Tianjin-Hebei Region. Wuhan, Beijing, and Hangzhou are the important nodes in the network. (2) Five urban clusters stand out in the urban networks shaped by Chinese medicine enterprises. Moreover, the connectivity values in urban networks are significantly different, which are mainly formed by hierarchical diffusion and proximity diffusion, with strong connections between the developed city pairs and their surrounding cities. (3) Developed cities generally have high power and influence in the network. Meanwhile, some small or medium-sized cities with abundant resources have also played an important role in the network. (4) China's medicine industry is still in the early stages of internationalization. Only a few cities, such as Hangzhou, Shenzhen, Kunming, and Tianjin, have strong international connections. (5) The spatial structures of urban networks vary greatly among different subsectors of medicine enterprises, while Beijing, Shanghai, Wuhan, and other major cities play a central role in all subnetworks.
As the development of economy and society enters into the "new normal" stage in China, urban planning is also gradually transformed from the traditional incremental planning to inventory planning. It is important to explore the urban spatial dynamic functional characteristics, and to optimize the use of urban activity space based on people's needs, which would enhance the quality of urban space. Advancements of information, communication, and location-aware technologies have made collections of various passively generated datasets possible. These datasets provide new opportunities to understand spatial dynamic characteristics at a low cost and large scale. This study explored the classification of urban space and spatial dynamic characteristics based on a large mobile phone location dataset from Shanghai Municipality, China. The results suggest that the geographical differences of spatial dynamic patterns in Shanghai are evident. The diurnal activity curve is consistent with the patterns of human activity. There were significant differences in intensity of day-to-day activity fluctuations and weekday activities between downtown, sub-centers, and major employment centers. Affinity propagation clustering was introduced to identify the characteristics of urban spatial structure and identify the characteristics of urban space structure of liquidity and viscosity. Several distinct patterns were extracted, and the spatial distributions of the derived clusters highlight distinct human mobility patterns in different areas of the city. We then discuss the socioeconomic and demographic characteristics of the regions covered by different cluster types to gain insights of human mobility patterns in the context of urban functional regions. The findings could offer useful information for policy and decision making.
As the result of a series of significant strategic decisions promulgated by the Chinese government, including Urban and Rural Harmonious Development, New Urbanization, New Rural Construction, and the government's focus on problems facing rural areas, rural population, and agriculture, rural settlements have become a research focus of contemporary geography in China. As a key area of rapid urbanization and agglomeration of production and living factors, the land use of rural settlements in metropolitan areas changes rapidly and complicatedly, which has become an important content of research. This study divided the rural settlements into five categories and then analyzed the spatial distribution of rural land non-agricultural degree in Guangzhou City in 2013 using correlated index and GIS. The results show that: (1) Rural land non-agricultural degree decreases with the distance between a rural settlement and the metropolitan area, and increases from the outer suburb to the inner suburb. (2) There is a significant correlation between the rural land non-agricultural degree and the development level of the district centers. The distribution of non-agriculture land in inner suburb areas is zonal spread while the distribution in outer suburb areas is along the main roads. (3) The level of rural development is generally higher where major infrastructure is developed. Finally, this study analyzed the mechanism of the spatial distribution of rural land non-agriculture degree in Guangzhou City by using multiple linear regression and geographical detector. This paper provides some reference for how to use rural non-agricultural process to promote urban development, optimize and regulate rural land use, and plan village development.
Crime is the product of a certain time and space. Research on crime cannot be separated from temporal and spatial analyses, as well as social, geographical, ecological, environmental, and other factors that generate crime. Risk terrain modeling technology was developed by American scholars for spatial risk assessment and predictive policing. It has been independently proven and tested in over 45 countries across six continents around the world and 35 states in the United States. It has been widely used in many fields such as predictive policing, homeland security, traffic accidents, public health, child abuse, environmental pollution, and urban development. It has achieved remarkable results in the crime research area of drug, arson, explosion, rape, robbery, and theft. This study adopted crime hotspot analysis and risk terrain modeling to analyze the risk factors, spatial blind spots, and risk terrain of narcotics crimes in 2015 in N City of the Yangtze River Delta region, explored the mechanism and evolution of drug crimes, and made a prediction on N City 2016 drug crime trend. The results show that N City drug crime presents obvious crime hotspots and crime cold spots. Rental housing, hotels, railway stations, banks, parking lots, entertainment venues, urban expressways, and Internet cafes are drug risk factors in the city. Risk terrain modeling is effective in predicting drug crimes. The narcotics departments of public security organs should put more police and energy to gradually limit and eliminate the hotspots that generate, attract, and promote crime.
Migrants' hukou transfer intention of the western ethnic minority regions has great implications not only for the overall urbanization level, but also for national unity and harmony in the society. Based on the dynamic monitoring data in 2012 from Xinjiang Autonomous Region and using a binary logistic regression model, this study analyzed the similarities and differences between the willingness of migrants to migrate in different regions and ethnic minority groups and their influential factors. According to the results, migrants' hukou transfer intention reached a high level, and more than half of respondents were willing to transfer their hukou to cities where they reside. This proportion is slightly higher in northern Xinjiang than in the south, and the related value is higher in ethnic minorities than Han nationality. The modeling result shows that Xinjiang barely had any attraction to highly educated and economically well-to-do migrants. Ethnic type, time of residence, and social integration degree are found to be the core factors in the dynamic system concerning migrants' hukou transfer intention. As well, there are different factors in different regions and ethnic groups in Xinjiang, when migrants make transfer decisions. But there is no regional or inter-group difference concerning social integration factors. Elevated social integration significantly helped to heighten transfer intention.
The problem of regional unbalanced development emerges while human well-being is improving. Using the Gini coefficient, Theil index, and regression analysis method, this study analyzed the regional difference in change and determinants of human well-being in China from 1995 to 2013. It revealed that: (1) The inter-provincial difference of human well-being shows a converging trend and is getting smaller in China from 1995 to 2013. In the 9th Five Year Plan period it kept narrowing and in the 10th Five Year Plan period it showed some fluctuations. In the 11th Five Year Plan period it decreased rapidly and in the 12th Five Year Plan period it had a development trend of convergence; (2) From 1995 to 2013, the difference between the four regions is the main difference of human well-being in China, but its contribution rate shows a decreasing trend as a whole. The contribution rate of inter-provincial difference of human well-being is increasing in the four regions. The west region had the biggest inter-provincial difference of human well-being but has decreased significantly. The inter-provincial difference of human well-being enlarged at first and then narrowed in the east region. The central and the Northeast region showed smaller inter-provincial differences of human well-being and had a narrowing trend; (3) Increasing economic development and educational expenditure can improve the provincial human well-being but also will expand the difference of human well-being. The growth of the ratio of health care expenditure in finance will decrease the human well-being, but can narrow the difference of human well-being. Social security expenditure and transfers per capita are effective ways to improve provincial human well-being, but also narrow the difference of human well-being.
