This page has only limited features, please log in for full access.
Taking the main district in Lanzhou city of China as an example, the questionnaires were designed and distributed, and then the effects of five factors, i.e., behavioral attitude, subjective norm, perceived behavioral control, perceived ease of use and perceived usefulness, on the behavioral intention of dockless bike-sharing (DBS) use were empirically analyzed based on the integrated model of technology acceptance model (TAM) and the theory of planned behavior (TPB) as well as the structural equation model. Results show that the five factors all impose significantly positive effects on the public’s behavioral intention of DBS use but differ in influencing degrees. Behavioral attitude, subjective norm and perceived behavioral control can all directly affect the public’s behavioral intention of DBS use, with direct influence coefficients of 0.691, 0.257 and 0.198, while perceived ease of use and perceived usefulness impose indirectly effects on behavioral intention, with indirect influence coefficients of 0.372 and 0.396. Overall, behavioral attitude imposes the most significant effect, followed by perceived ease of use, perceived usefulness and subjective norm, and finally perceived behavioral control. This indicates that the public’s behavioral intention of DBS use depends heavily on their behavioral attitude towards the shared bikes. In view of the limited open space of the main district in Lanzhou, the explosive growth of shared bikes, oversaturated arrangements, disordered competition, unclear and unscientific divisions of parking regions, and hindrance of traffic, this study proposes a lot of policy suggestions from the research results. A series of supporting service systems related to DBS should be formulated. The shared bikes with different characteristics should be launched for different age groups, gender groups and work groups. The corresponding feedback platform for realtime acquisition, organization, analysis and solution of data information, as well as the adequate platform feedback mechanism, should be established.
Wei Ji; Chengpeng Lu; Jinhuang Mao; Yiping Liu; Muchen Hou; Xiaoli Pan. Public’s Intention and Influencing Factors of Dockless Bike-Sharing in Central Urban Areas: A Case Study of Lanzhou City, China. Sustainability 2021, 13, 9265 .
AMA StyleWei Ji, Chengpeng Lu, Jinhuang Mao, Yiping Liu, Muchen Hou, Xiaoli Pan. Public’s Intention and Influencing Factors of Dockless Bike-Sharing in Central Urban Areas: A Case Study of Lanzhou City, China. Sustainability. 2021; 13 (16):9265.
Chicago/Turabian StyleWei Ji; Chengpeng Lu; Jinhuang Mao; Yiping Liu; Muchen Hou; Xiaoli Pan. 2021. "Public’s Intention and Influencing Factors of Dockless Bike-Sharing in Central Urban Areas: A Case Study of Lanzhou City, China." Sustainability 13, no. 16: 9265.
Automobile traffic has shifted the use of bicycles in many developed regions to being mainly for sport, recreation and commuting. Due to the desire to mitigate the impacts of climate change and alleviate traffic jams, bicycle sharing is booming in China. Governmental public bicycles and dockless bicycles are the main types of bicycle sharing in China, each with different types of management and pricing. Field research has found that many bicycle sharing networks are idle and wasteful, and thus we investigated which type is more popular and suitable for Chinese cities. This research comparatively analyzes the application of governmental public bicycles and dockless bicycles, mainly focusing on the cycling destination, cycling frequency, and cycling factors, taking Linfen City as an example. The results show that: (1) The purpose is different between governmental public bicycles and dockless bicycles. On the one hand, the aim of riding a governmental public bicycle to work represents the largest proportion at about 29%, mainly because of the fixed route of travel, and the fact that the fixed placement of governmental public bicycles makes them more available compared to the random arbitrariness of dockless bicycles. On the other hand, the aim of riding a dockless bicycle for entertainment accounts for the largest proportion, at about 34%, mainly due to the ease of borrowing and returning a bike, and mobile payment. (2) In terms of frequency, the public’s choice of riding a dockless bicycle or a governmental public bicycle has no essential difference, given that there are only two options for citizens in Linfen. (3) The response to the two kinds of bicycle sharing is different; the governmental public bicycle has the advantage of lower cost, but the dockless bicycle has more advantages in the procedure of borrowing and returning the bicycle.
Xiaojia Guo; Chengpeng Lu; Dongqi Sun; Yexin Gao; Bing Xue. Comparison of Usage and Influencing Factors between Governmental Public Bicycles and Dockless Bicycles in Linfen City, China. Sustainability 2021, 13, 6890 .
AMA StyleXiaojia Guo, Chengpeng Lu, Dongqi Sun, Yexin Gao, Bing Xue. Comparison of Usage and Influencing Factors between Governmental Public Bicycles and Dockless Bicycles in Linfen City, China. Sustainability. 2021; 13 (12):6890.
Chicago/Turabian StyleXiaojia Guo; Chengpeng Lu; Dongqi Sun; Yexin Gao; Bing Xue. 2021. "Comparison of Usage and Influencing Factors between Governmental Public Bicycles and Dockless Bicycles in Linfen City, China." Sustainability 13, no. 12: 6890.
Tourism efficiency is an effective index of measuring the development quality of the tourism industry. In this study, the tourism efficiency of 30 provinces in China during the period from 2006 to 2018 was measured with the SBM model and Malmquist index. On the basis of ESDA and GWR models, we explored the spatial pattern of China’s tourism efficiency and the spatial heterogeneity of the influencing factors in depth. The results revealed that China’s tourism efficiency has been constantly enhanced with an increasingly balanced pattern. Meanwhile, the utilization degrees of various input factors have constantly been improving. Both technological efficiency and technological progress jointly promote rapid growth of total-factor productivity. Accompanied with constant enhancement of the spatial agglomeration effect, the local spatial pattern also showed obvious differentiation. In general, low-efficiency regions were mainly concentrated in northern China, while high-efficiency regions were concentrated in southern China. The distinct spatial–temporal differentiation characteristics of tourist economic efficiency can be attributed to different influencing strengths of various factors in various regions and different action tendencies. The level of economic development, traffic conditions, the professional level of tourism, and openness degree can significantly promote tourism efficiency. Tourism resource endowment and environmental cost impose slight effects and differ in action direction, thereby inhibiting the tourism efficiency of many regions.
Zhiliang Liu; Chengpeng Lu; Jinhuang Mao; Dongqi Sun; Hengji Li; Chenyu Lu. Spatial–Temporal Heterogeneity and the Related Influencing Factors of Tourism Efficiency in China. Sustainability 2021, 13, 5825 .
AMA StyleZhiliang Liu, Chengpeng Lu, Jinhuang Mao, Dongqi Sun, Hengji Li, Chenyu Lu. Spatial–Temporal Heterogeneity and the Related Influencing Factors of Tourism Efficiency in China. Sustainability. 2021; 13 (11):5825.
Chicago/Turabian StyleZhiliang Liu; Chengpeng Lu; Jinhuang Mao; Dongqi Sun; Hengji Li; Chenyu Lu. 2021. "Spatial–Temporal Heterogeneity and the Related Influencing Factors of Tourism Efficiency in China." Sustainability 13, no. 11: 5825.
The COVID-19 epidemic has become a Public Health Emergency of International Concern. Thus, this sudden health incident has brought great risk and pressure to the city with dense population flow. A deep understanding of the migration characteristics and laws of the urban population in China will play a very positive role in the prevention and control of the epidemic situation. Based on Baidu location-based service (LBS) big data, using complex networks method and geographic visualization tools, this paper explores the spatial structure evolution of population flow network (PFN) in 368 cities of China under different traffic control situations. Effective distance models and linear regression models were established to analyze how the population flow across cities affects the spread of the epidemic. Our findings show that: (1) the scope of population flow is closely related to the administrative level of the city and the traffic control policies in various cities which adjust with the epidemic situation; The PFN mainly presents the hierarchical structure dominated by the urban hierarchy and the regional isolation structure adjacent to the geographical location.(2) through the analysis network topology structure of PFN, it is found that only the first stage has a large clustering coefficient and a relatively short average path length, which conforms to the characteristics of small world network. The epidemic situation has a great impact on the network topology in other stages, and the network structure tends to be centralized. (3) The overall migration scale of the whole country decreased by 36.85% compared with the same period of last year’s lunar calendar, and a further reduction of 78.52% in the nationwide traffic control stage after the festival. (4) Finally, based on the comparison of the effective distance and the spatial distance from the Wuhan to other destination cities, it is demonstrated that there is a higher correlation between the effective distance and the epidemic spread both in Hubei province and the whole country.
Xiaorong Jiang; Wei Wei; Shenglan Wang; Tao Zhang; Chengpeng Lu. Effects of COVID-19 on Urban Population Flow in China. International Journal of Environmental Research and Public Health 2021, 18, 1617 .
AMA StyleXiaorong Jiang, Wei Wei, Shenglan Wang, Tao Zhang, Chengpeng Lu. Effects of COVID-19 on Urban Population Flow in China. International Journal of Environmental Research and Public Health. 2021; 18 (4):1617.
Chicago/Turabian StyleXiaorong Jiang; Wei Wei; Shenglan Wang; Tao Zhang; Chengpeng Lu. 2021. "Effects of COVID-19 on Urban Population Flow in China." International Journal of Environmental Research and Public Health 18, no. 4: 1617.
Waste is increasingly used as a renewable resource. Industrial symbiosis is an innovative concept for more efficient use of waste streams within industrial complexes, with the aim of reducing the overall environmental impact of the complex. Industrial symbiosis plays a more important role in promoting green economic growth and building low-carbon cities. Based on the ecological theoretical framework, combined with Waste Flow Analysis (WFA), the material flow analysis (MFA) and production matrix methods were used as the core to construct the Industrial Symbiosis System Waste Flow Metabolism Analysis (ISSWFMA) model. In addition, taking the “Jinchang Model” as an example, a typical case selected by the National Development and Reform Commission of China’s regional circular economy development model, we conducted a refined quantitative study on the flow and metabolism of waste flow in the regional industrial symbiosis system at the City-Region level using the circulation degree index. The following conclusions were obtained from the study: The ISSWFMA model can better describe the flow and metabolism of waste streams in the industrial symbiosis system at the City-Region Level and can provide data and methods for storage management. As the internal industrial chain and the correlation between various departments continuously improved, the Circulation Index (CI) of solid waste, wastewater, and exhaust gas in the industrial symbiosis system of Jinchang City showed an overall increasing trend, the degree of recycling was continuously increasing, the industrial symbiosis ability was continuously enhanced, and the system structure was more complete. At the same time, based on the analysis of different wastes, the industrial symbiosis is developed at different stages; based on the analysis of solid wastes, the industrial symbiosis ability of Jinchang’s Industrial Symbiosis System has strengthened and accelerated the fastest from 2005 to 2010; based on the analysis of wastewater, the industrial symbiosis ability of the system strengthened slowly during the whole study period; and based on the analysis of exhaust gas, the industrial symbiosis ability of the system continued to strengthen rapidly during the whole study period. Finally, on the basis of further discussion on the selection of waste recycling paths, we proposed to give full play to the role of market mechanisms, and to build recycling areas and ecological areas by strengthening industrial symbiosis and its derived urban symbiosis to achieve the goals of natural resource conservation, ecological environment protection, and harmonious coexistence between human and nature.
Chengpeng Lu; Xiaoli Pan; Xingpeng Chen; Jinhuang Mao; Jiaxing Pang; Bing Xue. Modeling of Waste Flow in Industrial Symbiosis System at City-Region Level: A Case Study of Jinchang, China. Sustainability 2021, 13, 466 .
AMA StyleChengpeng Lu, Xiaoli Pan, Xingpeng Chen, Jinhuang Mao, Jiaxing Pang, Bing Xue. Modeling of Waste Flow in Industrial Symbiosis System at City-Region Level: A Case Study of Jinchang, China. Sustainability. 2021; 13 (2):466.
Chicago/Turabian StyleChengpeng Lu; Xiaoli Pan; Xingpeng Chen; Jinhuang Mao; Jiaxing Pang; Bing Xue. 2021. "Modeling of Waste Flow in Industrial Symbiosis System at City-Region Level: A Case Study of Jinchang, China." Sustainability 13, no. 2: 466.
The study of the carbon emission intensity of agricultural production is of great significance for the formulation of a rational agricultural carbon reduction policy. This paper examines the regional differences, spatial–temporal pattern and dynamic evolution of the carbon emission intensity of agriculture production from 1991 to 2018 through the Theil index and spatial data analysis. The results are shown as follows: The overall differences in carbon emission intensity of agriculture production presents a slightly enlarging trend, while the inter-regional differences in carbon emissions intensity is decreasing, but the intra-regional difference of carbon emissions intensity presented an expanding trend. The difference in carbon emission intensity between the eastern and central regions is not obvious, and the difference in carbon emission intensity in the western region shows a fluctuating and increasing trend. The overall differences caused by intra-regional differences; the average annual contribution of intra-regional differences is 67.84%, of which the average annual contribution of western region differences is 64.24%. The carbon emission intensity of agricultural production in China shows a downward trend, with provinces with high carbon emission intensity remaining stable, while provinces with low intensity are expanding. The Global Moran’s I index indicates that China’s carbon emission intensity of agricultural production shows a clear trend of spatial aggregation. The agglomeration trend of high agricultural carbon emission remains stable, and the overall pattern of agricultural carbon emission intensity shows a pattern of increasing differentiation from east to west.
Jiaxing Pang; Hengji Li; Chengpeng Lu; Chenyu Lu; Xingpeng Chen. Regional Differences and Dynamic Evolution of Carbon Emission Intensity of Agriculture Production in China. International Journal of Environmental Research and Public Health 2020, 17, 7541 .
AMA StyleJiaxing Pang, Hengji Li, Chengpeng Lu, Chenyu Lu, Xingpeng Chen. Regional Differences and Dynamic Evolution of Carbon Emission Intensity of Agriculture Production in China. International Journal of Environmental Research and Public Health. 2020; 17 (20):7541.
Chicago/Turabian StyleJiaxing Pang; Hengji Li; Chengpeng Lu; Chenyu Lu; Xingpeng Chen. 2020. "Regional Differences and Dynamic Evolution of Carbon Emission Intensity of Agriculture Production in China." International Journal of Environmental Research and Public Health 17, no. 20: 7541.
Based on the measurement of producer service industry agglomeration and export technological complexity of manufactured products in 288 Chinese cities from 2000 to 2015, this paper illustrates the evolvement and spatial characteristics of the two factors through visualization figures, and discusses the effects of producer services agglomeration on export technological complexity of manufacturing through robust panel data models. The findings are as follows: as with the influence of industrial connection, empirical outcomes indicate that urban producer service agglomeration can promote technological complexity of export manufacturing on the full-sample level. Visualization analysis shows that the scale of producer service industry agglomeration and the export technological complexity of manufactured products around Chinese cities kept rising constantly during the study period. However, although the export technological complexity displayed a trickle-down effect, the producer service industry agglomeration experienced continuous polarization both on the national and the regional levels. Accordingly, as is shown in the empirical analysis by areas, regions with strong support from producer service industry saw a remarkable promotion in the export manufacturing technology, while the northwest and the northeast gradually lagged behind. Such results sufficiently prove that heterogeneity does exist in the performances of industrial connection between producer service industry and export manufacturing in cities of different regions in China.
Xinyu Gao; Chengpeng Lu; Jinhuang Mao. Effects of Urban Producer Service Industry Agglomeration on Export Technological Complexity of Manufacturing in China. Entropy 2020, 22, 1108 .
AMA StyleXinyu Gao, Chengpeng Lu, Jinhuang Mao. Effects of Urban Producer Service Industry Agglomeration on Export Technological Complexity of Manufacturing in China. Entropy. 2020; 22 (10):1108.
Chicago/Turabian StyleXinyu Gao; Chengpeng Lu; Jinhuang Mao. 2020. "Effects of Urban Producer Service Industry Agglomeration on Export Technological Complexity of Manufacturing in China." Entropy 22, no. 10: 1108.
Health is the basis of a good life and a guarantee of a high quality of life. Furthermore, it is a symbol of social development and progress. How to further improve the health levels of citizens and reduce regional differences in citizens’ health status has become a research topic of great interest that is attracting attention globally. This study takes 31 provinces (municipalities and autonomous regions) of China as the research object. Through using GIS (Geographic Information System) technology, the entropy method, spatial autocorrelation, stepwise regression, and other quantitative analysis methods, measurement models and index systems are developed in order to perform an analysis of the spatio-temporal comprehensive measurements of Chinese citizens’ health levels. Furthermore, the associated influencing factors are analyzed. It has important theoretical and practical significance. The conclusions are as follows: (1) Between 2002 and 2018, the overall health levels of Chinese citizens have generally exhibited an upward trend. Moreover, for most provinces, the health levels of their citizens have improved dramatically, although some provinces, such as Tianjin and Henan, showed a fluctuating downward trend, suggesting that the health levels of citizens in these regions displayed a tendency to deteriorate. (2) The health levels of citizens from China’s various provinces showed clear spatial distribution characteristics of clustering, as well as an obvious spatial dependence and spatial heterogeneity. As time goes by, the degree of spatial clustering with regard to citizens’ health levels tends to weaken. The health levels of Chinese citizens have developed a certain temporal stability, the overall health status of Chinese citizens shows a spatial differentiation of a northeast–southwest distribution pattern. (3) The average years of education and urbanization rate have a significant positive effect on the improvement of citizens’ health levels. The increase of average years of education and urbanization rate can promote the per capita income, which certainly could help improve citizens’ health status. The Engel coefficient, urban–rural income ratio, and amount of wastewater discharge all pose a significant negative effect on the improvement of citizens’ health levels, these three factors have played important roles in hindering the improvements of citizen health.
Chenyu Lu; Shulei Jin; Xianglong Tang; Chengpeng Lu; Hengji Li; Jiaxing Pang. Spatio-Temporal Comprehensive Measurements of Chinese Citizens’ Health Levels and Associated Influencing Factors. Healthcare 2020, 8, 231 .
AMA StyleChenyu Lu, Shulei Jin, Xianglong Tang, Chengpeng Lu, Hengji Li, Jiaxing Pang. Spatio-Temporal Comprehensive Measurements of Chinese Citizens’ Health Levels and Associated Influencing Factors. Healthcare. 2020; 8 (3):231.
Chicago/Turabian StyleChenyu Lu; Shulei Jin; Xianglong Tang; Chengpeng Lu; Hengji Li; Jiaxing Pang. 2020. "Spatio-Temporal Comprehensive Measurements of Chinese Citizens’ Health Levels and Associated Influencing Factors." Healthcare 8, no. 3: 231.
Industrial ecology is an advanced form and ideal model of modern industrial development, in which the industrial ecosystem is the core. Based on the PSR model, this paper builds a comprehensive evaluation index system for urban industrial ecosystem development and selects 14 prefecture-level cities in Liaoning Province of the traditional industrial area in Northeastern China as cases to calculate the development level of its industrial ecosystem during 2000–2018 using an improved Topsis method and then to conduct a spatial visualization analysis. Finally, based on the “stress-state-response” subsystem, this paper diagnoses the constraints for industrial ecosystem development, which can provide a reference basis for decision-making in industrial ecology of traditional industrial area represented by those in Northeast China. The results show the following: (1) From 2000 to 2018, the industrial ecology of the 14 cities in Liaoning Province was at a medium level. Except for Shenyang and Dalian with the rapid development, the difference of industrial ecosystem development for other cities was relatively small. (2) From 2000 to 2018, the industrial ecosystem development of each city was in a status of “either increasing, or decreasing, or fluctuating,” which generally raised first and then decreased. Regarding spatial difference, the development exhibited a “center-periphery” pattern, with Shenyang and Dalian as the “dual-core” that were increasingly strengthened with significantly high-level industrial ecology. (3) At system level, PSR constraint grades for the industrial ecosystem development in the 14 cities of Liaoning Province were different. Constraint grades in the pressure subsystem, the state subsystem, and the response subsystem for the industrial ecosystem of Liaoning were 45.73%, 20.01%, and 34.34%, respectively, indicating that the lack of human response to the ecological environment and the pressure of human activities on the ecological environment during the industrial economy development were the main constraints affecting the process of industrial ecology in these cities. (4) Due to the differences in geographical environments, economic bases, industrial structures, and local development contexts, the major constraint factors of industrial ecosystem development in different cities are significantly different and complicated; however, there are five factors that are generally considered as major constraint factors in all cities, i.e., regional GDP, number of labor force employed in the secondary industrial sector, gross investment in fixed assets, amount of industrial sulfur dioxide removal, and production value from “three-wastes” comprehensive utilization. At last, this paper puts forward some recommendations and suggestions for providing scientific support for industrial ecosystem construction in the traditional industrial area of Northeastern China.
Chengpeng Lu; Wei Ji; Zhiliang Liu; Shuheng Dong; Bing Xue. Synergistic Evaluation and Constraint Factor Analysis on Urban Industrial Ecosystems of Traditional Industrial Area in China. Complexity 2020, 2020, 1 -16.
AMA StyleChengpeng Lu, Wei Ji, Zhiliang Liu, Shuheng Dong, Bing Xue. Synergistic Evaluation and Constraint Factor Analysis on Urban Industrial Ecosystems of Traditional Industrial Area in China. Complexity. 2020; 2020 ():1-16.
Chicago/Turabian StyleChengpeng Lu; Wei Ji; Zhiliang Liu; Shuheng Dong; Bing Xue. 2020. "Synergistic Evaluation and Constraint Factor Analysis on Urban Industrial Ecosystems of Traditional Industrial Area in China." Complexity 2020, no. : 1-16.
To better understand the agricultural resources and environmental problems of the provinces along The Belt and Road in China, it is critical to investigate their agricultural carbon emission efficiency and evolutionary trends. Based on the panel data of 18 key provinces and cities between 2006 and 2015, this paper evaluated the agricultural carbon emission efficiency with the data envelopment analysis–Malmquist model and further explored their dynamic evolutionary trends. There were several main findings. First, the efficiency levels of agricultural carbon emissions showed significant regional differentiation among the areas, with that along the 21st-Century Maritime Silk Road being much higher than that along the Silk Road Economic Belt. Second, technical efficiency was the key factor that restricted the improvement of the comprehensive efficiency of agricultural carbon. Third, most provinces invested in too many redundant and unreasonably allocated resources, showing a trend of diminishing returns to scale. Last, According to dynamic evolution analysis, the total productivity still demonstrated a diminishing trend. This paper provides some suggestions for effectively improve the efficiency of agricultural carbon emissions in China, such as optimize the agricultural industrial structure, increasing the investment of carbon emission reduction technology, and implementing a carbon emission quota clearing system. This paper contributes to the improvement of the environment in China.
Hua Zhang; Sidai Guo; Yubing Qian; Yan Liu; Chengpeng Lu. Dynamic analysis of agricultural carbon emissions efficiency in Chinese provinces along the Belt and Road. PLoS ONE 2020, 15, e0228223 .
AMA StyleHua Zhang, Sidai Guo, Yubing Qian, Yan Liu, Chengpeng Lu. Dynamic analysis of agricultural carbon emissions efficiency in Chinese provinces along the Belt and Road. PLoS ONE. 2020; 15 (2):e0228223.
Chicago/Turabian StyleHua Zhang; Sidai Guo; Yubing Qian; Yan Liu; Chengpeng Lu. 2020. "Dynamic analysis of agricultural carbon emissions efficiency in Chinese provinces along the Belt and Road." PLoS ONE 15, no. 2: e0228223.
The study of urban spatial structure is currently one of the most popular research fields in urban geography. This study uses Lanzhou, one of the major cities in Northwest China, as a case area. Using the industry classification of POI data, the nearest-neighbor index, kernel density estimation, and location entropy are adopted to analyze the spatial clustering-discrete distribution characteristics of the overall economic geographical elements of the city center, the spatial distribution characteristics of the various industry elements, and the overall spatial structure characteristics of the city. All of these can provide a scientific reference for the sustainable optimization of urban space. The urban economic geographical elements generally present the distribution trend of center agglomeration. In respect of spatial distribution, the economic geographical elements in the central urban area of Lanzhou have obvious characteristics of central agglomeration. Many industrial elements have large-scale agglomeration centers, which have formed specialized functional areas. There is a clear “central–peripheral” difference distribution in space, with an obvious circular structure. Generally, tertiary industry is distributed in the central area, and secondary industry is distributed in the peripheral areas. In general, a strip-shaped urban spatial structure with a strong main center, weak subcenter and multiple groups is present. Improving the complexity of urban functional space is an important goal of spatial structure optimization.
Chenyu Lu; Min Pang; Yang Zhang; Hengji Li; Chengpeng Lu; Xianglong Tang; Wei Cheng. Mapping Urban Spatial Structure Based on POI (Point of Interest) Data: A Case Study of the Central City of Lanzhou, China. ISPRS International Journal of Geo-Information 2020, 9, 92 .
AMA StyleChenyu Lu, Min Pang, Yang Zhang, Hengji Li, Chengpeng Lu, Xianglong Tang, Wei Cheng. Mapping Urban Spatial Structure Based on POI (Point of Interest) Data: A Case Study of the Central City of Lanzhou, China. ISPRS International Journal of Geo-Information. 2020; 9 (2):92.
Chicago/Turabian StyleChenyu Lu; Min Pang; Yang Zhang; Hengji Li; Chengpeng Lu; Xianglong Tang; Wei Cheng. 2020. "Mapping Urban Spatial Structure Based on POI (Point of Interest) Data: A Case Study of the Central City of Lanzhou, China." ISPRS International Journal of Geo-Information 9, no. 2: 92.
The issue of how to realize the coordinated development of various elements in human–land systems, or, in other words, how to achieve the coordinated development of population-economy-society-resource-environment (PESRE) systems, has become an important topic, which has received global attention. This study takes 31 provinces in China as the research objects, and carries out the research on the spatial–temporal synthetic measurement of the coordinated development of PESRE systems. The conclusions are as follows. From 1995 to 2015, the process of change of coupling coordination degree of China’s PESRE systems can be divided into two types: Rising first and then declining, and fluctuant continuously. The number of provinces of the first type was higher, and most provinces were on the verge of uncoordinated development status or in a weakly coordinated development status. The coupling degree of PESRE systems at the provincial level in China generally shows some positive spatial correlations, and the level of coordinated development displays some obvious spatial aggregation patterns. Moreover, the degree of such aggregation first increases and then weakens. The eastern parts of China represent the main “high-high” type aggregation regions. The central and western parts of China represent the main “low-low” types, account for the largest proportion, and display obvious aggregation characteristics.
Chenyu Lu; Jiaqi Yang; Hengji Li; Shulei Jin; Min Pang; Chengpeng Lu. Research on the Spatial–Temporal Synthetic Measurement of the Coordinated Development of Population-Economy-Society-Resource-Environment (PESRE) Systems in China Based on Geographic Information Systems (GIS). Sustainability 2019, 11, 2877 .
AMA StyleChenyu Lu, Jiaqi Yang, Hengji Li, Shulei Jin, Min Pang, Chengpeng Lu. Research on the Spatial–Temporal Synthetic Measurement of the Coordinated Development of Population-Economy-Society-Resource-Environment (PESRE) Systems in China Based on Geographic Information Systems (GIS). Sustainability. 2019; 11 (10):2877.
Chicago/Turabian StyleChenyu Lu; Jiaqi Yang; Hengji Li; Shulei Jin; Min Pang; Chengpeng Lu. 2019. "Research on the Spatial–Temporal Synthetic Measurement of the Coordinated Development of Population-Economy-Society-Resource-Environment (PESRE) Systems in China Based on Geographic Information Systems (GIS)." Sustainability 11, no. 10: 2877.
Chengpeng Lu; WanXia Ren; Lu Jiang; Bing Xue. Modelling impact of climate change and air pollution in cities. Proceedings of the Institution of Civil Engineers - Engineering Sustainability 2017, 170, 133 -140.
AMA StyleChengpeng Lu, WanXia Ren, Lu Jiang, Bing Xue. Modelling impact of climate change and air pollution in cities. Proceedings of the Institution of Civil Engineers - Engineering Sustainability. 2017; 170 (3):133-140.
Chicago/Turabian StyleChengpeng Lu; WanXia Ren; Lu Jiang; Bing Xue. 2017. "Modelling impact of climate change and air pollution in cities." Proceedings of the Institution of Civil Engineers - Engineering Sustainability 170, no. 3: 133-140.
Improving the sustainability of traditional resource-based cities in China has been a core issue and policy-priority for Chinese government to establish long-term ecological civilization, particularly for northeastern China which is recognized as a typical agglomeration area of resources cities. In this study, we establish a three-layer index system consisting of a comprehensive layer, systemic layer, and variable layer, and including 22 indicators which are grouped into economic, social and environmental subsystems. After that, the TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) method was applied to measure and rank the sustainability of the selected 15 typical resource-based cities in northeast China, and then a GIS (Geographical Information System) technique based on the software of SuperMap was applied to map the sustainability in terms of the spatial effects among these cities. The results reveal that a unilateral improvement of a subsystem did not mean an improvement or contribution to whole system. In detail, during the past 15 years from 2000 to 2015, the comprehensive sustainability of resource-based cities in Northeastern China shows a declining trend in the mass, and the sustainability of the economic subsystem shows increase; the sustainability of the social system remains stable, while the environmental subsystem shows decrease. These situations might result from policy interventions during the past 15 years, therefore, promoting the sustainability of resource-based cities needs a historical approach, which should focus on the coordinated development of its economic, social, and environmental subsystems.
Chengpeng Lu; Bing Xue; Chenyu Lu; Ting Wang; Lu Jiang; Zilong Zhang; WanXia Ren. Sustainability Investigation of Resource-Based Cities in Northeastern China. Sustainability 2016, 8, 1058 .
AMA StyleChengpeng Lu, Bing Xue, Chenyu Lu, Ting Wang, Lu Jiang, Zilong Zhang, WanXia Ren. Sustainability Investigation of Resource-Based Cities in Northeastern China. Sustainability. 2016; 8 (10):1058.
Chicago/Turabian StyleChengpeng Lu; Bing Xue; Chenyu Lu; Ting Wang; Lu Jiang; Zilong Zhang; WanXia Ren. 2016. "Sustainability Investigation of Resource-Based Cities in Northeastern China." Sustainability 8, no. 10: 1058.