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Tourist satisfaction has always been a crucial research issue in the tourism economy. This paper utilizes the Spatial Durbin Model (SDM) to analyze the impact of urban tourism satisfaction on urban macroeconomics from a macro perspective, using quarterly data on tourist satisfaction in 35 large and medium-sized cities along with major urban macroeconomic variables. This study is quite distinct from previous research that focused on constructing a tourist satisfaction index and analyzing the influence factors of tourism satisfaction from the perspective of the micro-level internal composition of tourism. The empirical results show: Firstly, in respect of the impact of urban tourists' satisfaction on the GDP income of cities, the SDM and the SDM with a lagged first-order dependent variable (SDM_dlag) show that the short-term and long-term indirect effects of log-tourist satisfaction are significantly positive, indicating that city satisfaction has a significant positive spatial spillover effect on GDP growth in other cities; Secondly, in respect of the influence of urban tourist satisfaction on the cost of urban life in the SDM, the long-term direct and indirect effects of logarithmic satisfaction are significantly positive, implying, in the long run, that tourist satisfaction has a positive intraregional spillover effect and spatial spillover effect on urban living costs; Finally, the SDM_dlag for the regression of urban tourist satisfaction on the cost of urban daily life shows that the short-run direct and indirect effects of city tourist satisfaction are significantly negative, indicating that tourist satisfaction has intra-regional and spatial spillover effects, and its rise will reduce the cost of living expenses in local and other cities in the short term. Overall, we have further elucidated the role of different levels of urban tourist satisfaction in city macroeconomics from the spatial dimension, thereby enriching the existing research on tourist satisfaction to some certain extent. [ABSTRACT FROM AUTHOR]

The deterioration of water quality has become a primary environmental concern worldwide. Understanding the status of water quality and identifying the influencing factors are important for water resources management. However, reported analyses have mostly been conducted in small and focused areas. It is still unclear if factors driving spatial variation in water quality would be different in extended spatial scales. In this paper, we analyzed spatial pattern of inland surface water quality in China using a dataset with four water quality parameters (i.e., pH, DO, NH4+-N and CODMn) and the water quality level. We tested the effects of anthropogenic (i.e., land use and socio-economic) and natural (i.e., climatic and topographic) factors on spatial variation in water quality. The study concluded that the overall inland surface water quality in China was at level III (fair). Water quality level was strongly correlated with CODMn and NH4+-N concentration. In contrast to reported studies that suggested land use patterns were the determinants of inland surface water quality, this study revealed that both anthropogenic and natural factors played important roles in explaining spatial variation of inland surface water quality in China. Among the tested explanatory variables, mean elevation within watershed appeared as the best predictor for pH, while annual precipitation and mean air temperature were the most important explanatory variables for CODMn and DO, respectively. NH4+-N concentration and water quality level were most strongly correlated with the percent of forest cover in watershed. Compared to studies at smaller spatial scales, this study found different influencing factors of surface water quality, suggesting that factors may play different roles at different spatial scales of consideration. Therefore management policies and measures in water quality control must be established and implemented accordingly. Since currently adopted parameters for monitoring of inland surface water quality in China are largely influenced by natural variables, additional physicochemical and biological indicators are needed for a robust assessment of human impacts on water quality. [ABSTRACT FROM AUTHOR]

Objective: The paper examines whether out-of-pocket health care expenditure also has regional discrepancies, comparing to the equity between urban and rural areas, and across households. Method: Sampled data were derived from Urban Household Survey and Rural Household Survey data for 2011/2012 for Anhui Province, and 11049 households were included in this study. The study compared differences in out-of-pocket expenditure on health care between regions (urban vs. rural areas) and years (2011 vs. 2012) using two-sample t-test, and also investigated the degree of inequality using Lorenz and concentration curves. Result: Approximately 5% and 8% of total household consumption expenditure was spent on health care for urban and rural populations, respectively. In 2012, the wealthiest 20% of urban and rural population contributed 49.7% and 55.8% of urban and rural total health expenditure respectively, while the poorest 20% took only 4.7% and 4.4%. The concentration curve for out-of-pocket expenditure in 2012 fell below the corresponding concentration curve for 2011 for both urban and rural areas, and the difference between curves for rural areas was greater than that for urban areas. Conclusion: A substantial and increasing gap in health care expenditures existed between urban and rural areas in Anhui. The health care financing inequality merits ample attention, with need for policymaking to focus on improving the accessibility to essential health care services, particularly for rural and poor residents. This study may provide useful information on low income areas of China. [ABSTRACT FROM AUTHOR]

Effective and timely quantification of the spatiotemporal pattern of urban expansion in China is important for the assessment of its environmental effects. However, the dynamics of the most recent urban expansions in China since 2012 have not yet been adequately explained due to a lack of current information. In this paper, our objective was to quantify spatiotemporal patterns of urban expansion in China between 1992 and 2015. First, we extracted information on urban expansion in China between 1992 and 2015 by integrating nighttime light data, vegetation index data, and land surface temperature data. Then we analyzed the spatiotemporal patterns of urban expansion at the national and regional scales, as well as at that of urban agglomerations. We found that China experienced a rapid and large-scale process of urban expansion between 1992 and 2015, with urban land increasing from 1.22 × 104 km2 to 7.29 × 104 km2, increasing in size nearly fivefold and with an average annual growth rate of 8.10%, almost 2.5 times as rapid as the global average. We also found that urban land in China expanded mainly by occupying 3.31 × 104 km2 of cropland, which comprised 54.67% of the total area of expanded urban land. Among the three modes of growth—infilling, edge expansion, and leapfrog—edge expansion was the main cause of cropland loss. Cropland loss resulting from edge expansion of urban land totalled 2.51 × 104 km2, accounting for over 75% of total cropland loss. We suggest that effective future management with respect to edge expansion of urban land is needed to protect cropland in China. [ABSTRACT FROM AUTHOR]

Nowhere has the scale and scope of urbanization been larger than in China over the last few decades. We analyze Chinese city development between the years 1996 and 2014 using data for the urbanized components of prefecture-level cities. We show that, despite much variability and fast economic and demographic change, China is undergoing transformations similar to the historical trajectory of other urban systems. We also show that the distinguishing signs of urban economies—superlinear scaling of agglomeration effects in economic productivity and economies of scale in land use—also characterize Chinese cities. We then analyze the structure of economic change in Chinese cities using a variety of metrics, characterizing employment, firms and households. Population size estimates remain a major challenge for Chinese cities, as official numbers are often reported based on the Hukou registration system. We use the information in the residuals to scaling relations for economic quantities to predict actual resident population and show that these estimates agree well with data for a subset of cities for which counts of total resident population exist. We conclude with a list of issues that must be better understood and measured to make sense of present urban development trajectories in China. [ABSTRACT FROM AUTHOR]

Bosten Lake is an important region of Northwest China that has transformed from a freshwater lake to a saltwater lake since the 1970s. The water quality in the Bosten Lake basin is important for social and economic development, and nitrogen (N) and phosphorus (P) are the key indicators of water quality. The land use data, precipitation data and Digital Elevation Model (DEM) data with the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model were used to simulate the N and P exports of the Bosten Lake basin. The spatial and temporal dynamics of nitrogen and phosphorus exports, and the response of nitrogen and phosphorus exports to land use change and precipitation change were analyzed between 2000 and 2015. The results show that the amount of N and P exports increased during 2000–2015, and the N and P exports are mainly distributed around Bosten Lake. The N and P exports are greatly affected by cultivated land, built-up areas and grassland, while they are less affected by other land use types. The high precipitation areas with small exports of N and P are mainly distributed in mountain areas, while small precipitation areas with large exports of N and P are distributed in plains where the cultivated land and built-up areas are concentrated. The InVEST model can be used in Northwest China, and the statistical downscaling of reanalysis precipitation data can be used in the InVEST model to improve the simulation accuracy in the data scarce regions of Northwest China. [ABSTRACT FROM AUTHOR]

Many studies have explored the relationship between housing prices and environmental characteristics using the hedonic price model (HPM). However, few studies have deeply examined the impact of scene perception near residential units on housing prices. This article used house purchasing records from and open access geolocation data (including massive street view pictures, point of interest (POI) data and road network data) and proposed a framework named “open-access-dataset-based hedonic price modeling (OADB-HPM)” for comprehensive analysis in Beijing and Shanghai, China. A state-of-the-art deep learning framework and massive Baidu street view panoramas were employed to visualize and quantify three major scene perception characteristics (greenery, sky and building view indexes, abbreviated GVI, SVI and BVI, respectively) at the street level. Then, the newly introduced scene perception characteristics were combined with other traditional characteristics in the HPM to calculate marginal prices, and the results for Beijing and Shanghai were explored and compared. The empirical results showed that the greenery and sky perceptual elements at the property level can significantly increase the housing price in Beijing (RMB 39,377 and 6011, respectively) and Shanghai (RMB 21,689 and 2763, respectively), indicating an objectively higher willingness by buyers to pay for houses that provide the ability to perceive natural elements in the surrounding environment. This study developed quantification tools to help decision makers and planners understand and analyze the interaction between residents and urban scene components. [ABSTRACT FROM AUTHOR]

Urban extent data play an important role in urban management and urban studies, such as monitoring the process of urbanization and changes in the spatial configuration of urban areas. Traditional methods of extracting urban-extent information are primarily based on manual investigations and classifications using remote sensing images, and these methods have such problems as large costs in labor and time and low precision. This study proposes an improved, simplified and flexible method for extracting urban extents over multiple scales and the construction of spatiotemporal models using DMSP/OLS nighttime light (NTL) for practical situations. This method eliminates the regional temporal and spatial inconsistency of thresholding NTL in large-scale and multi-temporal scenes. Using this method, we have extracted the urban extents and calculated the corresponding areas on the county, municipal and provincial scales in China from 2000 to 2012. In addition, validation with the data of reference data shows that the overall accuracy (OA), Kappa and F1 Scores were 0.996, 0.793, and 0.782, respectively. We increased the spatial resolution of the urban extent to 500 m (approximately four times finer than the results of previous studies). Based on the urban extent dataset proposed above, we analyzed changes in urban extents over time and observed that urban sprawl has grown in all of the counties of China. We also identified three patterns of urban sprawl: Early Urban Growth, Constant Urban Growth and Recent Urban Growth. In addition, these trends of urban sprawl are consistent with the western, eastern and central cities of China, respectively, in terms of their spatial distribution, socioeconomic characteristics and historical background. Additionally, the urban extents display the spatial configurations of urban areas intuitively. The proposed urban extent dataset is available for download and can provide reference data and support for future studies of urbanization and urban planning. [ABSTRACT FROM AUTHOR]

As a huge threat to the public health, China’s air pollution has attracted extensive attention and continues to grow in tandem with the economy. Although the real-time air quality report can be utilized to update our knowledge on air quality, questions about how pollutants evolve across time and how pollutants are spatially correlated still remain a puzzle. In view of this point, we adopt the PMFG network method to analyze the six pollutants’ hourly data in 350 Chinese cities in an attempt to find out how these pollutants are correlated temporally and spatially. In terms of time dimension, the results indicate that, except for O3, the pollutants have a common feature of the strong intraday patterns of which the daily variations are composed of two contraction periods and two expansion periods. Besides, all the time series of the six pollutants possess strong long-term correlations, and this temporal memory effect helps to explain why smoggy days are always followed by one after another. In terms of space dimension, the correlation structure shows that O3 is characterized by the highest spatial connections. The PMFGs reveal the relationship between this spatial correlation and provincial administrative divisions by filtering the hierarchical structure in the correlation matrix and refining the cliques as the tinny spatial clusters. Finally, we check the stability of the correlation structure and conclude that, except for PM10 and O3, the other pollutants have an overall stable correlation, and all pollutants have a slight trend to become more divergent in space. These results not only enhance our understanding of the air pollutants’ evolutionary process, but also shed lights on the application of complex network methods into geographic issues. [ABSTRACT FROM AUTHOR]

Extensive evidence has revealed that street greenery, as a quality-of-life component, is important for oxygen production, pollutant absorption, and urban heat island effect mitigation. Determining how green our streets are has always been difficult given the time and money consumed using conventional methods. This study proposes an automatic method using an emerging online street-view service to address this issue. This method was used to analyze street greenery in the central areas (28.3 km2 each) of 245 major Chinese cities; this differs from previous studies, which have investigated small areas in a given city. Such a city-system-level study enabled us to detect potential universal laws governing street greenery as well as the impact factors. We collected over one million Tencent Street View pictures and calculated the green view index for each picture. We found the following rules: (1) longer streets in more economically developed and highly administrated cities tended to be greener; (2) cities in western China tend to have greener streets; and (3) the aggregated green view indices at the municipal level match with the approved National Garden Cities of China. These findings can prove useful for drafting more appropriate policies regarding planning and engineering practices for street greenery. [ABSTRACT FROM AUTHOR]

The study of urban spatial interaction is closely linked to that of economic geography, urban planning, regional development, and so on. Currently, this topic is generating a great deal of interest among researchers who are striving to find accurate ways to measure urban spatial interaction. Classical spatial interaction models lack theoretical guidance and require complicated parameter-adjusting processes. The radiation model, however, as proposed by Simini et al. with rigorous formula derivation, can simulate directional urban spatial interaction. We applied the radiation model in China to simulate the directional migration number among 337 nationwide research units, comprising 4 municipalities and 333 prefecture-level cities. We then analyzed the overall situation in Chinese cities, the interaction intensity hierarchy, and the prime urban agglomerations from the perspective of migration. This was done to ascertain China’s urban spatial interaction and regional development from 2000 to 2010 to reveal ground realities. [ABSTRACT FROM AUTHOR]

In the Loess Hilly Region of China, the widespread conversion of cropland to forestland and grassland has resulted in great increased in organic carbon (C), nitrogen (N) and phosphorus (P) stocks in the shallow soil layers. However, knowledge regarding changes in C, N, and P in deep soil is still limited. To elucidate the responses of deep soil C, N, and P stocks and stoichiometry in response to changes in land use, the soil from a 0–200 cm soil profile was collected from the following three typical land use patterns in the heartland of the region: forestland, grassland, and cropland. Compared with cropland, forestland and grassland had improved soil organic carbon (SOC) and total nitrogen (TN) contents and stocks at most soil depths but decreased total phosphorus (TP) contents and stocks. At soil depths of 0–200 cm in the forestland and grassland, the cumulative SOC stocks were improved by 34.97% and 7.61%, respectively, and the TN stocks were improved by 54.54% and 12.47%, respectively. The forestland had higher SOC, TN and TP contents and stocks compared to the grassland in almost all soil layers. The soil depths of 100–200 cm contained the highest percentages of SOC, TN and TP stocks (47.80%–49.93%, 46.08%–50.05% and 49.09%–52.98%, respectively). Additionally, the forestland and grassland showed enhanced soil C:P, N:P and C:N:P ratios, and the forestland had higher C:P, N:P and C:N:P ratios compared to the grassland. Furthermore, the SOC and TN stocks had significant impacts on the soil C:N, C:P and N:P ratios. It was concluded that afforestation was the best choice for soil nutrient restoration of degraded land, and deep soil provided an extremely important resource for evaluating soil C, N and P pools and cycling. [ABSTRACT FROM AUTHOR]

Compared with CO2, methane (CH4) and nitrous oxide (N2O) are potent greenhouse gases in terms of their global warming potentials. Previous studies have indicated that land-use conversion has a significant impact on greenhouse gas emissions. However, little is known regarding the impact of converting rice (Oryza sativa L.) to vegetable fields, an increasing trend in land-use change in southern China, on CH4 and N2O fluxes. The effects of converting double rice cropping to vegetables on CH4 and N2O fluxes were examined using a static chamber method in southern China from July 2012 to July 2013. The results indicate that CH4 fluxes could reach 31.6 mg C m−2 h−1 under rice before land conversion. The cumulative CH4 emissions for fertilized and unfertilized rice were 348.9 and 321.0 kg C ha−1 yr−1, respectively. After the land conversion, the cumulative CH4 emissions were −0.4 and 1.4 kg C ha−1 yr−1 for the fertilized and unfertilized vegetable fields, respectively. Similarly, the cumulative N2O fluxes under rice were 1.27 and 0.56 kg N ha−1 yr−1 for the fertilized and unfertilized treatments before the land conversion and 19.2 and 8.5 kg N ha−1 yr−1, respectively, after the land conversion. By combining the global warming potentials (GWPs) of both gases, the overall land-use conversion effect was minor (P = 0.36) with fertilization, but the conversion reduced GWP by 63% when rice and vegetables were not fertilized. Increase in CH4 emissions increased GWP under rice compared with vegetables with non-fertilization, but increased N2O emissions compensated for similar GWPs with fertilization under rice and vegetables. [ABSTRACT FROM AUTHOR]

In the Loess Plateau, soil erosion has not only caused serious ecological and environmental problems but has also impacted downstream areas. Therefore, a model is needed to guide the comprehensive control of soil erosion. In this study, we introduced the WEPP model to simulate soil erosion both at the slope and watershed scales. Our analyses showed that: the simulated values at the slope scale were very close to the measured. However, both the runoff and soil erosion simulated values at the watershed scale were higher than the measured. At the slope scale, under different coverage, the simulated erosion was slightly higher than the measured. When the coverage is 40%, the simulated results of both runoff and erosion are the best. At the watershed scale, the actual annual runoff of the Liudaogou watershed is 83m3; sediment content is 0.097 t/m3, annual erosion sediment 8.057t and erosion intensity 0.288 t ha-1 yr-1. Both the simulated values of soil erosion and runoff are higher than the measured, especially the runoff. But the simulated erosion trend is relatively accurate after the farmland is returned to grassland. We concluded that the WEPP model can be used to establish a reasonable vegetation restoration model and guide the vegetation restoration of the Loess Plateau. [ABSTRACT FROM AUTHOR]

Analyzing spatiotemporal characteristics of the historical urbanization process is essential in understanding the dynamics of urbanization and scientifically planned urban development. Based on historical urban area maps and remote sensing images, this study examined the urban expansion of Shenyang from 1910 to 2010 using area statistics, typology identification, and landscape metrics approaches. The population and gross domestic product were analyzed as driving factors. The results showed that the urban area of Shenyang increased 43.39-fold during the study period and that the growth rate has accelerated since the 1980s. Three urban growth types were distinguished: infilling, edge-expansion, and spontaneous growth. Edge-expansion was the primary growth type. Infilling growth became the main growth type in the periods 1946–70, 1988–97, and 2004–10. Spontaneous growth was concentrated in the period of 1997 to 2000. The results of landscape metrics indicate that the urban landscape of Shenyang originally was highly aggregated, but has become increasingly fragmented. The urban fringe area was the traditional hot zone of urbanization. Shenyang was mainly located north of the Hun River before 1980; however, the south side of the river has been the hot zone of urbanization since the 1980s. The increase of urban area strongly correlated with the growth of GDP and population. Over a long time scale, the urbanization process has been affected by major historical events. [ABSTRACT FROM AUTHOR]