High accuracy surface modeling (HASM) is a new generation of surface simulation method. After 20 years of development, its theoretical basis has continuously improved, the algorithm is enriched, and the application field is expanding. However, a scientific classification system of HASM methods has not been established and this has prevented further application of HASM in various fields. To solve this problem, this article first summarizes the development process of HASM, then according to the nature of given research problems, HASM is divided into spatial interpolation and spatial data fusion methods based on the type of input data. The HASM spatial interpolation method generates target surface according to discrete sampling points. The HASM spatial data fusion method is the fusion of multi-source data that integrates the advantages of each data source to obtain a new surface. This classification provides a theoretical guidance for the further application of HASM. The article also introduces the general steps of solving spatial simulation problems using the two HASM methods, and the development prospect of the two methods is discussed.
With the globalization of services economy, services are becoming the core driving forces of metropolis development in different countries. Location choice of services is also the main factor that shapes the economic structure in metropolis. Therefore, this article examines progress of services location research in metropolis from three aspects: spatial pattern, location preference, and main influence factors. The main findings are as follows: (1) Discussion of services agglomeration and diffusion is often the most important topic. (2) Transportation factor is of high importance in the process of services agglomeration and diffusion. (3) The research perspective tends to be microscopic. (4) The influence of noneconomic factors such as urban amenity and local policy are being taken seriously. (5) Some researchers have focused on social equity and worked on the differentiation of services between different social groups. Finally, this article recommends further research on change analysis based on data of individual service companies, refocusing geospatial research on socioeconomic issues, and embedding services research into urban planning and management system.
Location-allocation model is one of the best methods to find the optimal location of public service facilities. Traditional p-median model takes efficiency as a major criterion and applies the adjacency rule—that is, allocating the residents of every demand site to the closest facility, neglecting difference in facilities’ capacity (scale). Hence it is difficult to adapt such model to certain distribution requirements of urban comprehensive hospitals that are moderate equilibrium—residents select comprehensive hospital stochastically with certain probability and location and capacity calculation of the facilities should be solved synchronously due to the spatial interaction between supply and demand. In order to address this type of location-allocation problem, we take the P-median model as the basic framework and discuss the development and applicability of the model, then construct a gravity P-median model based on the spatial interaction between the residents (demand) and urban comprehensive hospitals (supply). The new model makes some improvements in a number of aspects. First, spatial equality, that is, all residents can conveniently reach at least one comprehensive hospital, can be ensured by incorporating the highest travel cost (from the demand site to the adjacent hospital) factor. Second, spatial allocation efficiency is guaranteed through the pursuit of minimizing total weighted travel cost. Third, facility location decision and scale configuration are solved simultaneously by incorporating a facilities’ capacity factor. Fourth, facility scale efficiency and fairness of service quality are ensured by incorporating the minimum scale factor. Furthermore, through the empirical test in Wuxi City comprehensive hospital spatial configuration, the new model is validated and considered effective and practical. After optimization using the new model, compared with the current distribution the new spatial allocation of urban comprehensive hospitals is more equitable and more convenient for residents in the service areas to access; the collaborative distribution of comprehensive hospitals and community health service institutions can be achieved, and therefore the spatial distribution of the health facilities is more reasonable. Instead of practical applications, this study focused on the theoretical approach of model building, so some parameters need to be adjusted based on the supply and demand change when such model is applied to practical planning. It should be noted that such new model gives a relative optimal distribution result, which can support certain decision making for future public facility distribution adjustments or new town construction, meanwhile enrich research on public facility location allocation both in China and abroad.
Time is a sensitive factor in emergency medical service (EMS). The spatial and temporal differences of EMS accessibility are important for the assessment of siting of emergency facilities and the efficiency of emergency service dispatch. Traffic congestion is a common problem in the central areas of cities, and the impact of congestion on EMS accessibility cannot be ignored. In this study, the impact of traffic congestion on the temporal and spatial accessibility to EMS in the city of Guangzhou was analyzed by using the floating car data. The results show that: (1) During rush hours, the average and longest time between 120 hospitals and communities are 17% and 19% higher respectively than using standard road speed. (2) The accessibility of EMS to an emergency hospital as the center decays along the road network. The accessibility of EMS is high where the emergency hospital number is large and the road network is dense, and vice versa. The impact of traffic congestion on EMS accessibility is significant in areas where the road network and traffic rule are complex. (3) With the increase of time impedance, accessibility change slowed. This trend is more obvious in off-rush hours. Therefore, real-time traffic condition should be considered in research on EMS accessibility to optimize EMS scheduling and improve the efficiency.
Infrastructure development is an important part of urbanization and plays a fundamental role in supporting urban development. Using two kinds of statistical standards and by means of regression analysis, GIS analysis, and coefficient of variation calculation, this article analyzes the spatiotemporal pattern of infrastructure investment in China. The research found that: (1) Infrastructure investment in China has been growing at a high speed and has been an important driving force of urbanization. (2) Investment in economic infrastructure including electricity, transportation, water conservancy, is the main part of investment in infrastructure development, but the proportion of investment in medical and health care, education, social security, and other social infrastructure development has been gradually increasing. (3) Local government financial investment, bank loans, and land-transferring fees are the main sources of funds for infrastructure investment, and the government plays a leading role in such investment. (4) Infrastructure investment significantly differ between provinces and such difference is closely related to urbanization and economic development, but the gap tends to be closing. (5) There are differences between urban and rural infrastructure investment. The results not only can lay some foundation for further study including innovation and improvement of investment structure, but also provide some references for investment decisions of the government.
Infrastructure has positive spillover effects on economic development. This study took Beijing as a research area and measured the direct and indirect contribution of infrastructure on economic growth, input-output relationships between infrastructure sectors and other economic sectors, as well as the coordination degrees of infrastructure with socioeconomic development level. This study indicates that: (1) the average rate of contribution of infrastructure to economic growth during 1978-2014 was about 34.9% in Beijing. In 1985-1990, 1990-1995, and 1995-2000, the contribution rates reached 45%. With regard to direct contribution, that is, the share of value-added of infrastructure sector in GDP, the postal-telecommunication infrastructure had the highest direct contribution, which accounted for 9% of GDP. This was followed by transportation, energy, and water-related sectors; (2) transportation and energy sectors had relatively high induction coefficients, indicating that the growth of other economic sectors increased the demand for these two infrastructure sectors, and hence drove their growth. It also reflects that these two infrastructure sectors were mostly demanded by other economic sectors and tended to have restriction effects on economic development, thus required to be constructed in advance; (3) infrastructure development in Beijing lagged behind the city’s socioeconomic development, especially for the water-related infrastructure, which is still the weakest of all infrastructure sectors and has the lowest coordination degree with the socioeconomic development level, despite that it has gradually improved. On the other hand, transportation, energy, and postal-telecommunication sectors have recently reached a highly coordinated state with socioeconomic development. Among them, the postal-telecommunication sector has developed with the most impressive rate. To conclude, the coordination degree of infrastructure and socioeconomic development in Beijing has entered a moderately coordinated stage since 2010.
Residential space and employment space as two important components of urban structure can exert great impacts on overall urban structure and people’s livelihood. Internationally, research has mainly focused on the spatial organizational relationships between job and housing spaces, their spatial match, influence of mismatch between job and housing spaces on urban traffic, and other spatial mismatch issues. Similar studies began to be conducted in China since the late 1980s. The related literature mainly focused on introducing the theories and research progresses, impact of spatial matching between employment and housing spaces on traffic, spatial organization of job-housing, development patterns of urban land, and so on. The studies were mainly concentrated in the few largest cities but rarely involved the absolute majority of medium-sized cities in the central and western parts of China that are experiencing rapid growth. Urumqi City developed very quickly with industrialization and urbanization since the reform and opening up of China since the late 1970s. Meantime, the residential and employment spaces also started restructuring. This article presents a case study of the Urumqi area to explore the relationship between employment and residential locations. Based on various statistics and using the job-housing spatial bias index, kernel density estimation, and the geographically weighted regression (GWR) model, the authors examined the jobs-housing spatial matching issue and influencing factors of job-housing space relations. The study found that job-housing spatial separation is a prominent feature of urban spatial structure in Urumqi. The degree of job-housing spatial mismatching is relatively large—35 neighborhoods are mainly residential areas, which account for 44.3% of the total number of neighborhoods; 25 neighborhoods are mainly employment-oriented zones, which account for 31.65% of the total number of neighborhoods; and the number of neighborhoods where residential and employment functions largely match is only seven. Education, occupation, ownership of housing property, floating population, size of household living space, and other socioeconomic attributes have certain influence on the degree of separation of the two basic urban functions.
With the rapid development of information and communication technology (ICT), e-shopping has increasingly become a significant part of today’s social and economic life, deeply influencing residents’ shopping behavior and the development of traditional retail trade. Residents’ shopping behavior differs in different countries, among different groups of people, and with different types of goods. This article analyzes the characteristics of e-shopping behavior of Nanjing residents and compares residents’ e-shopping behavior by distinguishing product types based on a sample survey. The survey was conducted in Nanjing City from April to June 2015 by a research group at Nanjing University, which resulted in 963 valid samples that were later applied for analysis of variance. The study result has important implications for understanding the interactions between e-shopping and in-store shopping, as well as the influence of online shopping on transportation and urban retail space. By comparing two types of products—books and clothes, the article summarizes the general characteristics of Nanjing residents’ e-shopping behavior based on shopping frequency, distance of shopping trips, and shopping attitudes. The result of one-way ANOVA shows that residents’ e-shopping behavior is a complicated process. Considering the two types of products, residents with different e-shopping frequencies clearly differ in socioeconomic attributes, spatial locations, Internet use and shopping habits, and shopping attitudes. Residents with different frequencies of shopping clothes online have significantly more dissimilarities, which means experience goods response more strongly to the new shopping mode. Specifically, people with a high frequency of shopping books online are often older (with an average age of about 33), have higher level of education and household monthly income, are more likely to use online search to get product information and less sensitive to prices. People with a high frequency of shopping clothes online are often younger (with an average age of about 30.4), have higher level of education and household monthly income, and low shopping accessibility in place of residence with an average trip distance of 20 minutes, more likely have rich experiences in using the Internet and conduct unexpected consumption, value the recreational function of shopping, and pursue fashion. The results of this study may provide some references and basic data for dissecting the relationships between online shopping and in-store shopping from a geographic perspective and examining trends of retail sales in the city.
Facing the great challenge of climate change, carbon emission security-an important part of ecological security-has become a prominent issue. This study used the 1996-2012 statistics of 30 provinces (except Tibet) of the Chinese mainland to analyze the spatial and temporal differences of energy-related carbon emission security, with the aim to provide some guidance for regional carbon emission reduction strategy and sustainable development. The assessment indicator system of energy consumption-related carbon emission security was based on the pressure-response model, which consists of three main aspects: economic, social, and environmental. Then carbon emission security situation was projected for 2013 to 2020 by using the GM (1,1) method. The results show that: from 1996 to 2012, energy consumption-related carbon emission security of China was at a critical level (0.45-0.65) and showed a downward trend since 2000. The response system played an increasingly more important role in the security state of energy-related carbon emissions; carbon emission security of various provinces is very different, its spatial pattern underwent some changes, and the provinces of low security level shifted southward; most provinces face more pressure while the situation of the response system has improved; disparity of regional CO2 emission security gradually narrowed, provinces of high pressure and low response reduced substantially; energy intensity, per capita disposable income of urban residents, proportion of coal, per capita carbon emission, proportion of the secondary industry have great influence on carbon emission security in the majority of provinces. The forecasting results show that carbon emission security situation is not optimistic. Most provinces will be in the critical and unsafe state with regard to carbon emission.
Chinese high-speed railway entered a rapid development phase in recent years. One of the most important purposes of the construction of high-speed railway is to realize passenger and freight transport distributary. The construction of passenger train-dedicated high-speed railway has increased passenger transport capacity, thus releasing traditional train transport capacity for the usage of freight transport. But high-speed railway has higher ticket prices than traditional trains and the number of traditional trains in some cities has decreased, so people maybe have to pay much higher fare to take high-speed trains when traveling by railway. This phenomenon is called “involuntary high-speed railway travel”. In this article, we analyze this phenomenon based on the Beijing-Shanghai high-speed railway by comparing the monetary cost computed using the 2015 train timetable with hourly wage, and then estimate the possibility of “involuntary high-speed railway travel” of each city. The result shows that: (1) “involuntary high-speed railway travel” exists in many cities as monetary cost exceeds hourly wage in these cities; (2) the possibility of “involuntary high-speed railway travel” is around 50%; (3) the extent of “involuntary high-speed railway travel” varies in different cities—low at the endpoints, high in the middle, and relatively low in the Yangtze River Delta along the Beijing-Shanghai high-speed railway lines. Although traditional trains had not reduced too much along the Beijing-Shanghai high-speed railway lines, many low-income passengers may be forced to choose the high-speed railway once the number of traditional trains significantly declines, which may cause negative social impacts. This study can provide some references for the adjustment of the frequency of trains.
Using GIS technology, this article takes the 4A level and above attractions as the research objects to derive supply and demand market potential models by taking site accessibility as a starting point and based on the influencing factors of supply and demand. The study found that: (1) Harbin-Dalian high-speed rail improved Northeast China cities’ accessibility to tourism sites within the region by reducing average travel time by about 2.5 hours. The number of sites suitable for a one-day tour and a two-day tour increased, and a region tourism spatial structure formed along the high-speed railway, with center cities as the core, spreading from both sides of the high-speed railway and around the center cities, and characterized by one-day, two-day, and seven-day tours. (2) The potential of tourism supply and demand markets decreases when moving away from the high-speed railway lines, and the market concentrates along these lines, leading to the formation of a high-speed rail tourism economic zone and increasing the spatial concentration of tourism in the Northeast region. (3) High-speed rail stimulates short tours (day trips, two-day tours) more than seven-day tour. (4) According to accessibility and the core-periphery theory, we divided the tourism market in the Northeast region into four types: tourism market core area; tourism market peripheral area, tourism market transitional area, and tourism market margin area. It is necessary to rely on high-speed rail and other fast transportation mode and tourism hub cities to improve the transport network, and promote the optimization and coupling of the regional tourism supply and demand spatial networks.
This study constructed a self-organizing feature map (SOFM) clustering neural network model to evaluate economic-social-ecological poverty for 24 counties in three southern prefectures of Xinjiang Autonomous Region, constructed the evaluation model of regional tourism resources development, and analyzed the spatial distribution patterns of poverty and tourism resources development advantages in the study area with spatial data analysis method (ESDA). By matching the spatial patterns: (1) Factors of poverty-inducing set Matlab classification vector show that the type of southern counties under poverty can be divided into economic, social, and ecological poverty and there is a clear trend of spatial aggregation of poor counties. (2) Places with advanced tourism resources development are concentrated in areas where the geographical environment structure is complex and multiple ethnic communities reside, such as Kashi, Taxian County, Akto, and Hetian. Advanced tourism resources development areas show clear spatial autocorrelation and are distributed in clusters. (3) There is a significant spatial correlation between poverty and tourism resources development.
