Firms spatial expansion is of great significance to enterprise efficiency and regional coordinated development. Based on the data of listed manufacturing firms in Beijing and their subsidiaries from 2009 to 2018, this study examined the enterprise spatial expansion model through the changes of spatial distribution of subsidiaries, and analyzed the change of the distance between headquarters and subsidiaries brought by expansion. Furthermore, the dynamic panel measurement method was used to empirically test the impact of the change of geographical distance and economic distance between headquarters and subsidiaries on the efficiency of manufacturing enterprises with different expansion modes. The study found that: First, during the study period, the scale of expansion of the sample listed manufacturing firms in Beijing was relatively large, and the spatial expansion mode has changed from hierarchical diffusion to a combination of hierarchical diffusion and contagious diffusion, with contagious diffusion as the dominant mode. The geographical distance between headquarters and subsidiaries showed an upward trend, and the economic distance first decreased and then increased. Among these firms, technology-intensive firms and non-state-owned firms tend to experience hierarchical diffusion, while non-technology-intensive firms and state-owned firms tend to undergo contagious diffusion. Second, for the firms with contagious diffusion as the main expansion mode, geographical distance between headquarters and subsidiaries was negatively correlated with firm efficiency, but the efficiency of firms that did not take contagious diffusion as the main mode of expansion was not affected by geographical distance. Third, regardless of firm expansion mode, economic distance between headquarters and subsidiaries was positively correlated with firm efficiency. Therefore, different types of manufacturing firms should choose different expansion strategies.
Based on the 41692 venture capital investment events in China's mainland from 2001 to 2017, the impact of high-speed railway on the agglomeration, radiation, and intermediary powers of Chinese venture capital network was studied by using the social network analysis model, as well as the heterogeneity of the effect of different city types, radiation radius of the central cities, and four investment stages, in order to research the impact of high-speed railway on Chinese urban venture capital network. The analysis of the time-varying Difference-in-Differences (DID) model shows that high-speed railway can improve the accessibility of cities, reduce the transaction cost of venture capital activities, promote the cross-regional flow of innovation resources, and enhance the abundance of urban innovation elements, thus having a positive impact on the venture capital network development. High-speed railways have a significant promoting effect on the city network of venture capital in both non-central cities and central cities, and the positive effect is stronger in central cities. The impact of high-speed railway on venture capital network is different under different distance scales: the influence is significantly weaker in areas within a radius of 100 km and beyond 200 km than that between 100 km and 200 km. The impact of high-speed railway on the agglomeration power, radiation power, and intermediary power of venture capital network in the expansion and maturity stages (with lower risk, stable return, and higher marketization degree) is clearly more significant than in the seed stage and initial stage.
High-speed rail affects the structure, function, and relationship of urban network by changing the connectivity and connection strength between cities. With the extension and upgrading of China's high-speed rail network, understanding and interpreting urban network based on high-speed rail flow has become one of the important ways of research. Starting from the high-speed rail flow, this study analyzed the characteristics and process of change of China's county network structure with the help of the 2008-2018 high-speed rail passenger transport data and social network analysis method. The results show that: 1) the density of high-speed railway network is increasing year by year. The centrality values of the eastern and central regions are high, and the hub position is obvious. The core intersection of multiple high-speed railway trunk lines is likely to generate high and medium intermediate nodes. 2) The hierarchical structure of multiple networks identifies the hierarchical characteristics with evolutionary differentiation and complex and diverse connection patterns. The node effect of the first and second levels is significant and the location advantage is obvious, and the third level is the extension and refinement of the network. 3) The composition of agglomerating subgroups is determined by regional proximity and spatial connection strength. Affected by the layout of high-speed railway lines, the subgroups present a trend of "multi-cores", which is manifested in three types of change: extension, merger, and addition.
In recent years, the spatiotemporal distribution and its hazards to republic health of air pollution in China have shown new characteristics. Using hourly air quality monitoring data for five years (2015-2019) in 332 Chinese cities, this study analyzed the spatiotemporal distribution characteristics of air quality and urban population exposure risks by different methods. The results suggest that: 1) Air quality in Chinese urban areas has improved in recent years. Ambient Air Quality Index (AQI) decreased in 303 cities (91.3%). The concentrations of PM2.5, PM10, SO2, and CO declined while the concentrations of NO2 and O3 increased. 2) The hotspots of PM2.5, PM10, SO2, and CO concentration change rates were distributed in Xinjiang and Yunnan-South China. The hotspots of NO2 concentration change rate were in the Xinjiang area and the Hetao Plain. The hotspots of O3 concentration change rate were from the North China Plain to the middle and lower reaches of the Yangtze River. The trends of air quality change in the Northwest and South China were relatively slow. 3) Nine cities were exposed to PM2.5, PM10, SO2, NO2, O3, and CO pollution, which were located in Shanxi, Hebei, and Shandong provinces; 12 cities had no exposure risks to these six pollutants, which were distributed in Xinjiang, Yunnan, Guizhou, Sichuan, Guangdong, Fujian, and Heilongjiang provinces. These conclusions are of important reference value for collaborative treatment of cross-regional air pollution and formulating spatially diffenrentiated population flow management policies in China.
Characterizing the spatial distribution of urban residential land prices (RLPs) is essential for timely improving urban planning and management, as well as for effectively realizing urban smart growth. However, mapping urban RLPs at a fine scale remains challenging, due to the complex nonlinear relationship between RLPs and their potential determinants. This study developed a grid-level urban RLP mapping method based on big geo-data and ensemble learning technology to meet the needs of rapid and accurate monitoring of urban RLP dynamics. Using ensemble learning technology, combined with predictor variables extracted from points of interest (POIs) and NPP-VIIRS nighttime light images, the fine-scale RLPs in Wuhan City in 2018 were mapped through the following steps. First, the kernel density of POIs and the intensity of nighttime lights were extracted and aggregated at the 500 m×500 m grid level as the predictor variables of RLPs. Second, several RLP prediction models were established using four individual machine learning algorithms (MLAs) and bagging and stacking ensemble methods. Finally, the prediction accuracy or errors of different models were evaluated and compared, and the best performing model was selected to estimate the RLPs of the grids with no observations in Wuhan City. The results show that: 1) Among all the individual MLAs, the support vector regression (SVR) algorithm has the best prediction performance, followed by the k-nearest neighbor algorithm (k-NN), Gaussian process regression (GPR), and back propagation neural network (BP-NN) algorithms. 2) In terms of improving the prediction accuracy of individual MLAs, the performance of the stacking method is better than that of the bagging method. The stacking #1 model that integrates the SVR and k-NN algorithms has the smallest prediction error, with %MAE of 8.29%, and R2 of 0.814. 3) The RLP map generated by the proposed methodological framework can effectively reveal the circular characteristics and local singularity of the RLP distribution. This study provides new ideas, methods, and technical means for rapidly and accurately mapping urban RLPs, which is conducive to the improvement of urban RLP monitoring systems in the era of big data.
Institutional change is a major driving force for urban spatial evolution. As a special and important type of town, farm towns are more affected by institutional factors. Given that existing research is less involved in the evolution of farm towns under institutional changes, this study first systematically reviewed the overall situation of the changes in the farm system. Then taking the Wusan Farm, a state-owned farm in Hubei Province, as an example and using a comprehensive research approach including text analysis, non-participatory observation, and in-depth interviews, this study examined the spatial evolution of farm towns and its dynamic mechanism under institutional changes since the founding of the People's Republic of China. The results reveal that: 1) The spatial evolution of farm towns is mainly reflected in three aspects: spatial form, spatial relationship, and spatial function. The spatial form has undergone a process from slow change to drastic change. Spatial relationship has shifted from the production collaboration relationship to the rural-urban relationship. Spatial function changed from public operation to private operation, production-oriented to consumption-oriented, and single function to diversification. 2) Institutional change promotes the spatial evolution of farm towns by changing the role of the farm, interest relationships, and resource allocation. The change of farm identities directly affects the development direction of farm towns. As a result, the farms' corporate identity is becoming more prominent. Changes in the interest relations promote the industrialization and marketization of farm town space. Therefore, industrial parks, commercial streets, and industrial clusters have emerged and developed rapidly. Changes in resource allocation affect the spatial evolution of farm towns by changing the subject, type, scale, and speed of resource allocation. Through this research, we hope to be able to guide the development of farm towns in the new era. For example, we believe that clarifying the relationship between the institutional changes at the national level and the institutional changes at the reclamation administration level can guide the development of farm towns. Likewise, the development of farm towns must pursue quality and efficiency rather than the simple expansion of built-up areas, because farm towns do not have enough land to support extensive development. We also hope that this study can enrich the theoretical research of urban spatial evolution.
The low-altitude air route environment in the Beijing-Tianjin-Hebei region is complex and unstable. The safety of low-altitude flight is mostly affected by meteorological factors such as thunderstorms, wind shear, low visibility, and extreme temperature and humidity. It is difficult to accurately simulate and forecast the meteorological elements on the low-altitude air route of the unmanned aerial vehicle (UAV). Based on the mesoscale Weather Research and Forecasting (WRF) model and its advanced three-dimensional variational assimilation system (3D-Var), we took the "7·20" heavy rainfall of North China in 2016 as a study case. The temperature field, humidity field, and wind field of the UAV low-altitude air route in the Beijing-Tianjin-Hebei region were simulated, and the ground observation data and numerical simulation results were compared and analyzed. The aim was to provide a reference for the flight safety of UAVs in the Beijing-Tianjin-Hebei region. The conclusion is as follows: WRF model can better simulate the daily variation trend of near-surface temperature, humidity, and wind speed in this area. The root mean square error (RMSE) and the bais between the simulated values and the observed values of the plain sites (Tianjin and Miyun) is lower, the wind speed simulations in mountainous areas is higher, and the simulation effect in plain areas is better than that in the northern and western mountainous areas. When heavy rainfall occurs, the temperature difference between the plain areas and the mountainous areas is about 15 ℃, the relative humidity is above 95%, and the boundary layer height is less than 500 m. The strong temperature difference, higher humidity, and lower boundary layer will affect UAV flying performance. At an altitude of 900 hPa along the 117°E longitude line, a wind speed of more than 10 m·s-1 appeared in Langfang-Hengshui in Hebei Province, forming a strong northeast wind. The northern part of the region (39°N-40.5°N) has a clear updraft. The vertical wind speed at a height of 1000 m also exceeds 2 m·s-1. The strong updraft is extremely unfavorable to the flight of the UAV, and will have a significant impact on the flight attitude and flying height of the UAV, causing potential safety hazards.
Karst dissolution is one of the most fundamental processes in the karst area, which is closely related to water and extremely prone to the impact of drought. Previous studies have shown that drought has a significant impact on karst dissolution. However, the magnitude of drought impact is unclear, especially the karst dissolution loss caused by different intensities of drought. The present study used a field control test to quantify the effects of 12 different drought durations on karst dissolution for the forest, shrub grassland, and cropland in central Guizhou Province using the standard carbonate tablets method. We also analyzed the drought influence mechanism of karst dissolution. The results show that drought has caused enormous karst dissolution loss and the loss percentage ranges from 30.61% to 83.33% for the forest area, 38.45% to 88.82% for shrub grassland, and 66.76% to 95.14% for cropland, respectively. According to the loss data of different soil layers, the deeper soil layers have higher karst dissolution loss under the impact of shorter duration drought, while the surface soil layers have lower karst dissolution loss. However, under the influence of more prolonged drought, the karst dissolution loss of surface soil layers is higher than the deeper soil layers. The mechanism of influence of drought indicates that soil moisture was the leading cause of karst dissolution loss, which plays a crucial role in karst dissolution loss caused by drought.
Explaining how offenders choose a crime location is one of the central themes of crime geography. However, previous research on offenders' crime location choice mostly considers the impact of the built environment and social environment, without considering the impact of ambient population and surveillance cameras on street robbery and its temporal difference. To fill this gap, this study integrated ambient population and surveillance cameras in assessing street robbers' decision making and its time effects in ZG City of China, by using the discrete spatial choice modeling. The results demonstrate that ambient population and surveillance cameras have a significant negative impact on street robbers' crime location choice, and they play a protective role in preventing street robbers' criminal activities. Interestingly, we found that the protective effect of ambient population is greater than that of surveillance cameras. The protective role of ambient population and surveillance cameras is stable daily through the week, but diurnally, the influence of ambient population shows temporal fluctuation, while the impact of surveillance cameras is temporally stable. These findings can be of some reference for police control and crime geography research by: 1) Carrying out the experimental evaluation of surveillance camera system's prevention and control effect, and dynamic optimization and adjustment of surveillance cameralocations. 2) Arranging a suitable amount of mixed functional land in urban planning or urban renewal to strengthen the moderation of ambient population through planning or management. 3) Focusing on diurnal variability in future studies of the time effects.
With the further development of new urbanization and implementation of the rural revitalization strategy, spatial governance in metropolitan fringe is worthy of attention. As the metropolitan fringe is located at the junction of urban and rural areas, population, society, resources, and other issues in metropolitan fringe reflect the urban-rural conflicts. Therefore, the spatial governance in metropolitan fringe is of great significance for the balanced development of urban and rural areas. As collaborative governance of multi-subjects is a clear requirement for the improvement of national governance system and governance capacity, it is important to examine how to realize the spatial governance of multi-subjects coordination in metropolitan fringe. Based on the perspective of multi-subjects, this study examined the theoretical framework, structure, issues, mechanisms, and paths of spatial governance in metropolitan fringe, and drew the following conclusions. First, through the literature and theoretical analysis of the relationship between the governance subjects and the spatial characteristics of metropolitan fringe, this article summarized the theoretical framework of spatial governance in metropolitan fringe from the perspective of multiple subjects. It showed that with the transformation of governance subject in metropolitan fringe from single subject to multi-subjects coordination, urban and rural spaces gradually develop to a balanced state. Second, by exploring the historical development of metropolitan fringe, this study concluded that the spatial governance structure of metropolitan fringe has gradually transformed from single center structure to multi-centric network structure. Third, in the process of spatial development in metropolitan fringe, the multi-subjects follow the principle of maximizing their own interests to compete for resources. The competition for spatial resources causes three problems of spatial governance, which are the diversification of material space, the differentiation of social space, and the imbalance of spatial power. Fourth, the multiple subjects follow their own spatial governance needs and logic to implement the corresponding governance mechanism for the urban fringe. Finally, based on the cooperation of multi-subjects, the optimized path of spatial governance in metropolitan fringe is concluded. Based on the above conclusions, this article summarized and constructed the progressive research framework of "governance structure-governance issues-governance mechanism-path optimization". At present, the research of spatial governance still needs to be improved. In order to promote the institutional turn of human geography and constantly expand the research field, it is vital to strengthen the research on the spatial relationship, governance mechanism, and path optimization of multi-subjects and metropolitan fringe.
The increasing trend of extreme precipitation has become stronger globally, and is expected to have detrimental impact on agricultural ecosystems. Rice is one of the staple foods, and the inter-annual fluctuation of rice yield is highly affected by extreme precipitation. However, the mechanisms and spatiotemporal sensitivity of rice yield to extreme precipitation have not been clarified. This review summarized the temporal and spatial patterns of extreme precipitation in the main rice-producing regions of the world and its impact on rice yield, and explored the mechanism of extreme precipitation impact on rice growth and yield from the perspective of physiological, chemical, and physical processes. The input data and advantages and disadvantages in application of the main research methods, including statistical model and crop model, were evaluated and compared. The results indicate that an increase of 1% in extreme precipitation led to a decrease in rice yield by 0.02%-0.5%, mainly through increased nutrient loss and flooding. Yet, large uncertainties still exist in rice yield prediction of current studies, because it is difficult to clarify how rice yield responds to different characteristics (intensity, frequency, and duration) of extreme precipitation and its spatiotemporal sensitivity, and the mechanisms of extreme precipitation affecting rice yield components are not well understood. In addition, lacking the integration of crop models and statistical models also introduces uncertainties. We recommend to promote the integration of multi-methods, especially field observation, controlled experiment, and model improvement, to quantitatively analyze the mechanism of extreme precipitation impact on yield components, and to improve data accuracy to better simulate rice yields under extreme precipitation events in the future. Achieving these progresses will lay a foundation for optimizing the current rice cropping system and agricultural management to mitigate the impact of extreme precipitation.
Air transport has played a critical role worldwide for human mobility and trade. Airport agglomeration, usually located in urban agglomerations or metropolitan regions, are developing globally, and are estimated to handle most global passenger traffic. Multiple airport systems have long received attention from researchers. Meanwhile, airport agglomeration, as a new concept appeared in China's airport planning, has gradually grown into an emerging hot research field for air transport geography. This article reviewed related research on airport agglomeration as well as multiple airport system, defined the concept, and then discussed related research topics. It classified relevant research on airport agglomeration in China into three stages: 1) The embryonic stage before 2008; 2) the initial development stage between 2008 and 2016; and (3) the prosperous development stage since 2017. The research topics on airport agglomeration mainly involve six aspects: 1) Identification of developmental processes and organizational patterns. 2) Airports' catchment area and ground transport access. 3) Characteristics of air transport connectivity and optimization of air route network. 4) Passengers' travel behavior and airport choice. 5) Airport layout planning and evaluation. 6) Competition and cooperation of airports and their regional coordination. For the first time, this study distinguished multi-airport system, regional airport system, and airport agglomeration from a spatial view. From the perspective of geography, future research of airport agglomeration should focus on the following three aspects: 1) To clarify the conceptual connotation of airport agglomeration, strengthen empirical research and analysis, and establish a theory and methodology for the identification of the spatial organization pattern of airport agglomeration. 2) To build the airport-hinterland (or city) "spatial flow" big data system on the basis of urban agglomerations, and to explore the spatiotemporal pattern and development mechanism of airport agglomeration. 3) To explore practical solutions that can guide the resource development and optimization of an airport agglomeration and its coordination area.
High quality public compulsory education resources have a strong capitalization effect on urban housing prices, which leads to the unique urban residential landscape and residential clustering. Such issue has become the focus in the field of public service provision. In the existing review studies, there is a lack of systematic discussion on the capitalization of educational resources. Based on the analysis of the concept and formation mechanism of the educational resources capitalization, we focused on the impact of school education quality and accessibility on housing prices, the measurement of educational resources capitalization, the residential clustering (segregation) caused by unbalanced distribution of educational resources, and coping strategies. First, from the perspective of the measurement of the quality of school education and its impact on housing prices and the measurement of the accessibility from dwelling places to schools and impact on housing prices, we summarized the relevant research on the impact of educational resources on housing prices. We introduced the mainstream methods to quantify the quality of school education and the impact of school education quality on housing prices. Then we commented on the limitations of traditional accessibility measurement methods, the advantages of the new comprehensive measurement methods, and the impact of school accessibility on housing prices. Second, we reviewed the four typical research methods (hedonic price method, fixed boundary method, instrumental variable approach, difference-in-difference method), some typical spatial econometric models, and geographically weighted regression model and their related applications, to examine the relevant literature on the measurement methods for educational resources capitalization. Finally, we summarized the research progress of educational clustering and coping strategies concerning the phenomenon of educational clustering (segregation) caused by school selection or school district policies and the policies on alleviating the problem. The following topics may be the direction of further discussion: tracking and evaluating the effect of enrollment policy, constructing a systematic research framework to alleviate the problem of education clustering, measuring the capitalization of educational resources covering the whole schooling period, designing more effective accessibility measurement methods for schools in each schooling period, assessing the impact of school accessibility on housing prices (especially rental prices) under the background of "school choice" policies, and following the dynamic changes of capitalization of educational resources under the policy of the same right of renters and owners in China.
Energy is one of the core topics of geographic research. As a typical activity involving regional human-land relationship, household energy consumption is a major trend in the refined research of energy geography. Based on the spatial scale perspective of geography, we reviewed the origins of energy geography research, the spatial characteristics of household energy consumption, formation mechanism, and data sources. Three main conclusions are drawn: 1) Constructing a panoramic survey framework of household energy data, including the geographical type, energy type, quantity, and use in the scope of the survey. 2) Meso-scale research needs to be strengthened. Coordination through the micro-medium-macro-scale relationship is conducive to understanding and grasping the characteristics and patterns of household energy consumption from a nested structure as a whole. 3) Constructing a comprehensive analysis framework of multi-factors such as household attributes, geographic factors, and lifestyles, and analyzing the dynamic drivers for the formation of spatial characteristics of household energy consumption, to realize the essential understanding of the spatial differentiation process of household energy consumption. This study contributes to the internationalization of energy-related spatial research and practice in the field of geography, and has positive significance for supplementing the theoretical perspective of Chinese household energy consumption research.
