Search

This paper utilizes an improved undesirable output DEA model to measure the eco-efficiency of cities in five major urban agglomerations in China during 2006–2020. It employs the Theil Index and Geodetector to investigate the spatial-temporal distribution differentiation characteristics and driving factors of urban eco-efficiency. The main findings are as follows. Firstly, the eco-efficiency of all urban agglomerations showed a fluctuating upward trend, but the eco-efficiency performance of different urban agglomerations in China shows a stratification characteristic. Specifically, the Pearl River Delta urban agglomeration consistently ranks first in China, while the mean values of the Yangtze River Delta urban agglomeration, Beijing-Tianjin-Hebei urban agglomeration, and Chengdu-Chongqing urban agglomeration are lower than the national average. Secondly, the overall differences in the urban eco-efficiency of all sample cities show a consistently fluctuating downward trend. The factor that affects the level differences of eco-efficiency in different cities is the intra-regional differences. Last but not least, the top three factors affecting the spatial distribution difference of urban eco-efficiency in the whole sample are environmental pollution control investments, innovation level, and environmental infrastructure investments. In the end, this paper proposes that reducing the intra-regional differences is the primary task to achieve the coordinated improvement of urban eco-efficiency in urban agglomerations, and then puts forward some policy suggestions to improve eco-efficiency for the five major urban agglomerations. [ABSTRACT FROM AUTHOR]

With the advent of the era of Industry 4.0, big data and the Internet of Things came into being. The rise of big data and the Internet of Things has had an impact on all walks of life. The development of big data and the Internet of Things provides an opportunity for the evolution of street form. With the rapid development of smart cities, the street shape is also changing more and more towards the direction of intelligence. Taking Chunxi Road in Chengdu as an example, this paper studies the generation mechanism of street morphology. The factors influencing the generation of street form are divided into two categories: (1) legal factors. (2) Architectural design factors. By building a model, the article quantitatively analyzes the impact of these two types of factors on street form. At the same time, the article conducts an in-depth study on the evolution of ancient Chinese street morphology. The ancient Chinese street form is divided into four stages, namely the Tang and Song Dynasties, the Yuan, Ming and Qing Dynasties, the Late Qing Dynasty, and the founding of New China. The influencing factors of street shape are divided into four categories, namely, the influence of commodity economy, the influence of foreign culture, the influence of building materials, and the influence of traffic. This paper elaborates the influence mechanism of these four factors on the street form in China. The article finally puts forward the development trend of my country's future street form, and points out that the evolution of my country's street form will develop in the direction of intelligence, and intelligent transportation, intelligent garbage classification system, etc. will be applied. The number of brick-and-mortar stores in my country's street layout may decrease. [ABSTRACT FROM AUTHOR]

With the deepening of urbanization in China, the coordinated development of cities in different regions is an important part of the sustainable development of the country, and the reasonable quantification of the unbalanced development of cities in different regions is an important issue facing the society nowadays. Previous studies usually use population data to analyze the power-law distribution law to quantify the imbalance of urban development in different regions, but China's population data span a large number of years and numerous division criteria, and the results obtained from different population data are widely disparate and have obvious limitations. The paper starts from a fractal perspective and utilizes OpenStreetMap (OSM) data to extract national road intersections from 2015 to 2022, calculates critical distance thresholds for eight years using urban expansion curves, generates urban agglomerations in China, and quantifies the imbalance of urban development in different regions by calculating the urban agglomeration power-law index. The results indicate that (1) the critical distance threshold of urban expansion curves exhibits a slight overall increase and stabilizes within the range of 120–130 m, (2) the number of urban agglomerations in China has been increasing significantly year by year, but the power-law index has been decreasing from 1.49 in 2015 to 1.36 in 2022, and (3) the number of urban agglomerations and the power–law index of the Beijing–Tianjin–Hebei, Yangtze River Delta, Pearl River Delta, and Chengdu–Chongqing regions, which is consistent with the national scale trend, indicates that the scale distribution of urban agglomerations in China at this stage does not conform to Zipf's law, and there is a certain Matthew effect among cities in different geographic areas with a large unevenness. The results of the study can provide new ideas for assessing the coordinated development of cities in different regions. It compensates for the instability of population and economic data in traditional studies. [ABSTRACT FROM AUTHOR]

In daily operation, urban rail transit (URT) systems often experience disturbances that result in a partial reduction in transport capacity [partial disturbances (PDs)] rather than disturbances leading to a complete reduction in transport capacity. However, research that assesses the resilience of URT networks under PDs remains limited. This paper addresses this gap by proposing a passenger-oriented resilience assessment model for URT networks under PDs, considering the travel behaviors of passengers and different relations (i.e., linear, concave, and convex) between the velocity coefficient and failure severity. A simulation-based assessment approach was developed to solve the resilience assessment model. A numerical experiment was conducted on the Chengdu subway network in China. The results demonstrate that the performance indicator employed herein reflects the impact of passenger travel time distribution on network performance. Deliberate PDs cause more significant performance losses than random PDs. Moreover, the network is the least resilient under PDs considering the convex relation between the velocity coefficient and failure severity. The resilience-based critical link of each line is not fixed and varies with the failure severity and disturbance occurrence time. Increasing the failure severity of PDs results in more severe performance losses than increasing the number of PDs. Additionally, the passenger-oriented resilience of a URT network can be enhanced by improving the passengers’ tolerable delay time and disturbance duration. [ABSTRACT FROM AUTHOR]

Early work on China's Two-Child Policy identified cost as a major disincentive to having a second child, but financial constraints may work in tandem with cultural factors to shape childbearing desire. In addition, most research has excluded men from the sample. This paper develops Yan's (2003) concepts of 'new' and 'traditional' fertility cultures to childbearing desire, a key component of fertility decision-making that is poorly understood (Hayford & Agadjanian, 2017). In particular, we focus on how differing conceptions of children's needs relate to perceptions of cost. This paper reports on semi-structured interviews with 29 men and women in Chengdu, the capital of Sichuan province. We found that interviewees who espoused views consistent with a traditional fertility framework were more interested in having a second child, and were less concerned about cost. In addition, men were more likely to espouse views consistent with a traditional fertility cultural framework. [ABSTRACT FROM AUTHOR]

One of the most important archaeological finds excavated from the Tianhui Laoguanshan Han tombs in 2012–13 was a manuscript on horse medicine, dated around the third century BCE. Prior to the discovery of this highly specialized veterinary text, only a handful of horse recipes from the Qin and Han periods had been found, and a sixth-century CE agricultural treatise, Essential Techniques for the Common People , was generally regarded as the earliest surviving source of extensive veterinary material, including various medical treatments for horses. Although the Laoguanshan manuscript – given the modern title Book of Treating Horses by the Team for Collating the Medical Bamboo Slips Excavated from the Han Tombs in Tianhui Town, Chengdu – has suffered significant damage, it nevertheless gives us an insight into the knowledge and treatments for horses during the Qin and early Han periods. A variety of ways of treating horses are recorded in Treating Horses , including herbal remedies, piercing, cauterization, hot packs, bandages, massage, and bathing. The use of gold needles is also mentioned in this text, echoing the gold and silver sewing needles excavated from Liu Sheng's (d. 113 BCE) tomb in Mancheng, Hebei Province. This paper offers a short introduction to this valuable text on horse medicine by examining the content of its fragments, including names of ailments, symptoms of certain diseases, etiologies, and treatment methods. The discovery of Treating Horses challenges the established view that horse treatment methods in ancient China were predominantly herbal and that techniques of bleeding and cauterization recorded in Essential Techniques were brought to China from elsewhere, together with the introduction of Buddhism. The paper argues that the "foreign influence" had already occurred at a much earlier date, in the form of interactions with nomadic tribes such as the Scythians, the horsemen par excellence of classical antiquity. [ABSTRACT FROM AUTHOR]

• A non-linear programming model to design full-day demand-adapted timetables is proposed. • The time-dependent maximum sectional passenger flow is used as input data. • A new algorithm is proposed to match demand and services' supply. • The algorithm uses a rolling-horizon mechanism to iteratively compute departure times. • The effectiveness of the proposed algorithm is illustrated using real data of Chengdu Metro line 1. This paper focuses on the problem of designing the schedule of urban rail transit systems under dynamic passenger demand considering limited train capacity and congestion. From the point of view of operators, the goal of timetable optimization consists of using as few as possible service trains to transport the arriving passengers to their destinations securely and quickly. On the other hand, passengers want to spend the minimum time travelling to their destinations, including the time they wait on platforms until they board the first and successive trains in case of transferring between lines. Due to the variability of passenger flows and the difficulty in exactly solving full-day timetabling problems in short computation times, it is difficult in practice to use the approaches proposed in the literature. Moreover, when the capacity of trains is considered and oversaturation conditions emerge, the problem becomes even more complex, converting into a challenge the design of schedules from an operational point of view. By considering fixed train dwell times at stations and train running times between stations, we first propose a non-linear programming formulation to model the problem of determining the most convenient interdeparture times of services at the first station of a line, aiming at minimizing the waiting time of passengers. Since the dynamic behaviour of passenger demand and the maximum sectional passenger flow are approximately synchronous, an innovative method, the spatiotemporal synchronization coupling algorithm, based on working with the time-varying maximum sectional passenger flow instead of the demand patterns is proposed to quickly solve in an approximate way the demand-driven timetabling problem. The proposed approach is applied to a real case of Chengdu Metro Line 1 in China. The results show the effectiveness of the algorithm, both in terms of computational effort and in terms of reducing the waiting time currently experienced by passengers. [ABSTRACT FROM AUTHOR]

The Local Climate Zone (LCZ) classification scheme is a vital method of building a category dataset for high-resolution urban land. For the development of urban meteorology, air pollution and related disciplines, the high-resolution classification data of urban buildings are very important. This study aims to create LCZ datasets with detailed architectural characteristics for major cities and urban agglomerations in China, and obtain more accurate results. We constructed 120 m resolution land use datasets for 63 cities (mainly provincial capitals, municipalities directly under the Central Government, important prefecture-level cities and special administrative regions) and 4 urban agglomerations in China based on the local climate zone (LCZ) classification scheme using the World Urban Database and Access Portal Tools method (WUDAPT). Nearly 100,000 samples were used, of which 76,000 training samples were used to provide spectral signatures and 23,000 validation samples were used to ensure accuracy assessments. Compared with similar studies, the LCZ datasets in this paper were generally of good quality, with an overall accuracy of 71–93% (mean 82%), an accuracy for built classifications of 57–83% (mean 72%), and an accuracy for natural classifications of 70–99% (mean 90%). In addition, 35% of 63 Chinese cities have construction areas of more than 5%, and the plateaus northwest of Chengdu and Chongqing are covered with snow all year round. Therefore, based on the original LCZ classification system, the construction area (LZC H) and the snow cover (LCZ I) were newly added as the basic classifications of urban LCZ classification in China. Detailed architectural features of cities and urban agglomerations in China are provided by the LCZ datasets in this study. It can be applied to fine numerical models of the meteorological and atmospheric environment and improve the prediction accuracy. [ABSTRACT FROM AUTHOR]

The classical multi-period inventory routing problem (MIRP) combines inventory management and vehicle routing problems, attempting to maintain customer inventory levels via autonomous deliveries, with the assumption that stock-out never occurs at the supply side. While this is no more the truth when a common third-party logistics company operates a central warehouse for a group of small and medium sized retailing companies. Procurements have to be made to refill inventory at the central warehouse. This study thus extends the traditional MIRP by incorporating procurement decisions (MIRP-PD) and tries to minimize the total cost of procurement, inventory holding and transportation. To our knowledge, this paper is among the first to formally describe MIRP-PD and model it as a mixed integer linear program. A hybrid two-level heuristic is proposed to address large-scale instances. The upper level of the algorithm determines the visiting schedule while the lower level works out procurement and routing decisions accordingly. Components from tabu search and adaptive threshold acceptance are also embedded to help escape from local optima. Extensive numerical instances are generated from a real case in Chengdu (China), based on which the computational results reveal the effectiveness and efficiency of the proposed algorithm compared with the commercial solver CPLEX. The comparison between MIRP and MIRP-PD has demonstrated the cost advantage of incorporating procurement decisions into inventory and routing plans. Impacts on costs of key factors including delivery frequency and buffer size of stores have also been examined to provide managerial implications to practitioners. [ABSTRACT FROM AUTHOR]

This paper examines how the government harnesses the development of social enterprises. Drawing on an in-depth qualitative study in Chengdu City, China, we find that institution building, financial supporting, incubation developing, systematical cultivating and resource matchmaking are the main strategies employed by the municipal government to promote the development of social enterprises, whereupon we argue that besides the role as referee and sponsor which are the governments' traditional roles in western countries, the government in China also play a role of coach in harnessing the development of social enterprises. This paper contributes to the literature by theorizing how administrative forces affect the growth of hybrid organizations and also contributes to providing empirical evidence of the institutional environment of social enterprises in China. [ABSTRACT FROM AUTHOR]

In China, traditional food is a significant element of culture that affects human behaviors. The point of interest (POI) of traditional food restaurants' location and their volatile organic compounds (VOCs) emissions affect the urban ecology. Rather than examine potential urban development patch (PUDP) based on land use data, the perspective of this paper is to examine the PUDP, air quality, and food culture in urban ecology in Chengdu, China. Methods: First, the research identifies three types of PUDP models (open PUDP, landscape PUDP, and conflict PUDP) with the weighted overlay of land use data, then uses machine learning to examine the relationship between PUDP, POI of traditional food restaurant, and VOCs. Results: The study generates three types of PUDP which are open PUDP, landscape PUDP, and conflict PUDP. VOCs and POI of traditional restaurant have a strong correlation, and both have a significant negative correlation with open PUDP. However, the landscape PUDP and conflict PUDP do not show an obvious relationship with food POI and VOCs. Conclusion: The results indicate that the future urban ecology should consider restaurant location, VOCs from restaurants, and their relationship to urban land use data as they have a strong relationship. [ABSTRACT FROM AUTHOR]

As the passenger railway network is expanding and improving, the internal connections and interdependence in the network are rising. Once a sudden geological hazard occurs and damages the network structure, the train service is prone to large-scale halt or delay. A geographical railway network is modeled to analyze the spatial distribution characteristics of the railway network as well as its vulnerability under typical geological hazards, such as earthquakes, collapses, landslides and debris flows. First, this paper modeled the geographical railway network in China based on the complex network method and analyzed the spatial distribution characteristics of the railway network. Then, the data of geological hazards along the railway that occurred over the years were crawled through the Internet to construct the hazard database to analyze the time–space distribution characteristics. Finally, based on the data of geological hazards along the railway and results of the susceptibility to geological hazards, the vulnerability of the geographical railway network was evaluated. Among these geological hazards, the greatest impact on railway safety operation came from earthquakes (48%), followed by landslides (28%), debris flows (17%) and collapses (7%). About 30% of the lines of the geographical railway network were exposed in the susceptibility areas. The most vulnerable railway lines included Sichuan–Guizhou Railway, Chengdu–Kunming Railway and Chengdu–Guiyang high-speed Railway in Southwest China, Lanzhou–Urumqi Railway and Southern Xinjiang Railway in Northwest China, and Beijing–Harbin Railway and Harbin–Manzhouli Railway in Northeast China. Therefore, professional railway rescue materials should be arranged at key stations in the above sections, with a view to improving the capability to respond to sudden geological hazards. [ABSTRACT FROM AUTHOR]

Taking the Chengdu Municipal Solid Waste Incineration (MSWI) Plant in China as object, totally 100 ambient soil samples from 20 sampling points were taken for experiment. This paper analysed the characteristics of Cd in soil. By analyses, the distribution and health risk assessment were taken into consideration. The results demonstrated that the Cd value in soil in the surroundings of the MSWI plant was beyond the acceptable level according to standards (GB15618-2018). The risk assessment in this experiment showed that the carcinogenic and noncarcinogenic risks via inhalation exposure were in the accessible levels. [ABSTRACT FROM AUTHOR]

The high environmental pollution load caused by the massive pollutant emissions and the accumulation of endogenous and cross-regional pollution has become an important obstacle to the current ecological civilization construction in the Yangtze River Economic Belt (YREB) in China. Taking the YREB as an example, by using four environmental pollutant emission indicators, including chemical oxygen demand (COD), ammonia nitrogen (NH3-N), sulfur dioxide (SO2), and nitrogen oxides (NOx), this paper established an environmental pollution load index (EPLI) based on the entropy-based measurement. Moreover, the Spatial Durbin Model was used to quantitatively analyze the drivers and spatial effects of environmental pollution load. Finally, specific scientific references were provided for formulating environmental regulations of pollution source control in the YREB. The results showed that: 1) During 2011–2015, the EPLI in the YREB was reduced significantly and the environmental pollution load increased from upstream to downstream. Among them, the pollution load levels in the Upper Mainstream subbasin, Taihu Lake subbasin, and Lower Mainstream subbasin were the most prominent. 2) The environmental pollution load situation in the YREB was generally stable and partially improved. High load level areas were mainly concentrated in the Yangtze River Delta Region and the provincial borders in upstream, midstream, and downstream areas. The high load level areas already formed in Chengdu and Chongqing were also the key regulatory points in the future. 3) The degree of local environmental pollution load was apparently affected by the adjacent cities. The population size, industrialization level, and the fiscal decentralization not only drove the increase of the local environmental pollution load level, but also affected the adjacent areas through the spatial spillover effects. The land development intensity mainly drove the increase in the local EPLI in the YREB. While factors such as economic development level and agricultural economic share could only act on the environmental pollution load process in adjacent cities. 4) According to the differentiation characteristics of drivers of each city, the YREB was divided into seven zones based on k-medoids cluster method, and targeted zoning control policy recommendations for alleviating environmental pollution load in the YREB were proposed. [ABSTRACT FROM AUTHOR]

The business environment is becoming a yardstick for assessment of local governments in China, and thus the question of how to evaluate the business environment of urban agglomerations has become an important new issue. This paper proposes a quantitative method for the assessment of business environments in urban agglomerations for purposes of city ranking. First, a business environment evaluation index system for urban agglomerations, including the four dimensions of market, government, law, and humanistic, was established. Second, A hybrid model combined entropy weight method (EWM), genetic algorithm (GA), and back propagation (BP) neural network was constructed to quantise the business environment. Then, the Chengdu-Chongqing and Beibu Gulf urban agglomerations in China, the two most important urban agglomerations of the new western land-sea corridor, were selected as cast study. The results are as follows: (1) The business environments of the two most important urban agglomerations of the new western land-sea corridor have been improved, but the differences between them are significant. The level of development of the business environment of Chengdu-Chongqing is higher than that of Beibu Gulf; specifically, the biggest gap is of the rule of law environment. The gap in the governmental business environment is the smallest. (2) From 2015 to 2020, the difference in business environment between the two most important urban agglomerations in the new western land-sea corridor decreased. However, intra-group differences were the largest. (3) The spatial pattern of the business environment in the new western land-sea corridor shows a "northwest-southeast" distribution, with the center of gravity of the business environment moving to the southeast from 2015 to 2020. (4) Compared with focusing on the development of the business environment in large cities, promoting the business environment in small and medium-sized cities has a more significant effect on improving the business environment in urban agglomerations. • A quantification method is proposed. • Business environment in the corridor is uneven. • Small cities should develop firstly. [ABSTRACT FROM AUTHOR]

• Present a methodology for investigating ring road investment and cordon tolling problems in a congested ring-radial city. • Establish a two-dimensional urban system equilibrium for a ring-radial city. • Develop two social welfare maximization models (a short-sighted decision and a far-sighted decision) to optimize ring road investment and cordon tolling schemes. • Carry out a case study on the city network of Chengdu China. Ring roads, as candidate cordons, provide a convenient condition for implementing cordon tolling schemes. This paper presents a methodology for investigating the ring road investment and cordon tolling problems in a congested ring-radial city. A two-dimensional urban system equilibrium for a ring-radial city is first formulated, in which interrelated equilibria among stakeholders, including the authorities, property developers, households and commuters, are explicitly considered. Two social welfare maximization models for optimizing the ring road investment and cordon tolling schemes, a short-sighted and a far-sighted one, are then proposed. In the short-sighted model, the ring road investment decision is first made, and then the cordon tolling scheme is optimized based on the determined ring road locations as candidate cordons. However, in the far-sighted model, a simultaneous decision of the ring road investment and cordon tolling is made. The proposed models explicitly incorporate the estimation of the intra-area travel. A case study applied to the city network of Chengdu China shows that ring road investment and cordon tolling can reshape the urban spatial structure as a result of the tug-of-war between the dispersion effects due to ring road investment and the concentration effects due to cordon tolling. The far-sighted solution entails building more ring roads than the short-sighted solution, and is closer to the social optimum solution. Whether all ring roads are tolled, or just one, the far-sighted solution yields an appreciably higher welfare gain. The optimal single-cordon tolling scheme performs nearly as well as the optimal multi-cordon tolling scheme in terms of the social welfare. Ignoring the household residential relocation behavior leads to underestimates of total cordon toll revenue and welfare gain. [ABSTRACT FROM AUTHOR]

This paper explores the effect of government supervision on the development of FFBS by analyzing massive travel information data. Our identification strategy exploits a natural experiment focusing on Mobike in Chengdu. We find that supervision does not necessarily suppress the development of FFBS. It also allows FFBS to increase its focus on alleviating the pressure of public transport and reducing the consumption of public resources. Moreover, we identify that the impact of government supervision on weekends is considerably more significant than on weekdays given that government supervision has a significant suppression effect on the FFBS travel behavior of scattered parking, leisure, and long distance. In contrast, the effect of government supervision on the FFBS travel behavior of commuting and schooling is not significant. We finally present implications for government and operators of FFBS, especially in developing countries, on the sustainable development of FFBS. [ABSTRACT FROM AUTHOR]

Since the 2010s, two worldwide trends have reshaped the urban housing system and induced drastic neighborhood change: the financialization of rental housing and the rise of the platform economy. In China, with continued investment from speculative financial institutions, platform companies aggressively acquired rental houses from individual landlords to develop a platform-based housing rental economy. How does this new rental economy affect housing supply, rents and inequality? This research answers this question by taking Chengdu, China as a case study. A mixed method approach of big data analytics, hedonic pricing model, and field investigations were used to unpack: (a) the pattern of platform houses distribution and its indication of spatial strategies of the financialized platform economy to grab land rent; (b) the effect of such new housing rental economy on housing rents; (c) the effect of the degree of financialization on platform houses' rental prices. The results inform the debate on the disrupt effect of platform economy and housing financialization on equitable urban development, particularly the heterogeneity among cities and countries. This paper contributes to understanding financial investors' glocalization strategy and the state's territorialization strategy as two crucial factors for the variegation of rental housing financialization. • Houses with small living room and more bedrooms that can generate more rent. • Platform companies tend to choose houses nearby public transport services. • High concentration of platform houses increases rental price of surrounding normal houses. • Degree of financialization significantly increases the price premiums of platform houses. [ABSTRACT FROM AUTHOR]

• A hybrid deep learning model within decomposition-ensemble strategy named DEASeq2Seq is proposed for multistep metro passenger flow prediction. • DEASeq2Seq employs CEEMDAN and RQA to capture intrinsic dynamics. • An attention-based Seq2Seq model is developed to characterize temporal dependencies. • Real-world datasets to verify the proposed model and further model interpretation. Short-term passenger flow prediction has practical significance for metro management and operation. However, the complex nonlinear and non-stationary characteristics make it challenging to detect evolution characteristics of passenger flow. To address this problem, a hybrid short-term metro passenger flow prediction model named decomposition ensemble attention sequence to sequence (DEASeq2Seq) is proposed in this paper. The proposed DEASeq2Seq includes three phases: decomposition, ensemble, and prediction. First, complete empirical mode decomposition with adaptive noise (CEEMDAN) is utilized to decompose the original passenger flow data into several intrinsic mode functions (IMFs) and a residue. Second, recurrence quantification analysis (RQA) is performed to reconstruct the decomposed modes into a stochastic part, a deterministic part, and a trend part via determinism evaluation. Third, a Seq2Seq model with the attention mechanism is proposed to execute multistep prediction for short-term passenger flow and explore the influence mechanism of the reconstructed components on the prediction targets. The real dataset from Chengdu metro, China, is used to verify the proposed model. The experiment results show that the proposed DEASeq2Seq model outperforms the benchmark models. Further model interpretations are conducted to analyze the impacts of decomposition strategy, ensemble strategy, and attention mechanism. [ABSTRACT FROM AUTHOR]

One of the most important variables that leads to effective individual and group tours is the tourism route planning approach, which enables tourists to engage with tourism with ease, speed, and safety. However, current methods of designing tourist routes have some glitches, such as relying only on external objectives to find the best route. In this paper, a novel urban tourism path planning method based on a multiobjective genetic algorithm is proposed. The main goal of this paper is to enhance the accuracy of the genetic algorithm (GA) by adopting new parameters and selecting the optimal tourism path by combining external and internal tourist site potentials. Moreover, the GA and analytical hierarchy process (AHP) were used in our proposed approach to evaluate urban tourism route planning under multiple conflicting objectives. To visualize and execute the proposed approach, the geographic information system (GIS) environment was used. Our suggested approach has been applied to develop the tourist road network of Chengdu City in China. Compared with existing tourism path planning approaches, our proposed approach is more accurate and straightforward than other approaches used to choose routes. [ABSTRACT FROM AUTHOR]

This paper examines the recent green turn in China by investigating a large-scale urban greenway project. Using the perspective of the socio-ecological fix, we demonstrate that multi-scalar states strive to upgrade environmental quality. Specifically, the local state seizes the opportunity for 'ecological civilisation' envisioned by the central state to carry out green infrastructure development. We reveal complex motivations to incorporate ecological changes into entrepreneurial urban governance instead of encroaching greenspace for economic growth. Our state-centred analysis reveals that such an environmental strategy, the making of Chinese green urbanism, is promoted like a political mission, despite its operation by the development corporation. We argue that, while the socio-ecological fix facilitates capital accumulation, its deployment must be understood through state politics and actors. [ABSTRACT FROM AUTHOR]

• A spatial-temporal density-based clustering algorithm is proposed for trip end detection. • Three scenario optimization models are applied to improve the method capability. • A smartphone application is developed for GNSS data collection. • The potential of the method is demonstrated by comparing results with travel log. As a widespread portable probe, smartphone equipped with Global Navigation Satellite System (GNSS) can continuously track individual's travel trajectory, it is potential for trip end information identification. Existing studies mostly use rule-based methods with specific dwelling time and distance thresholds for trip end detection, these methods are highly dependent on expert experience and lack universality across different traffic environments. Some density-based spatial clustering methods also have issues in the case of GNSS signal missing, traffic congestion, short-time stays and repeat visits to the same place etc. Therefore, this paper proposes a two-step method for trip end identification by using smartphone GNSS positioning data. First, a spatial-temporal density-based clustering algorithm (ST-DBCA) is proposed for trip end identification, the method considers both spatial and temporal travel trajectory point density at the same time, and performs much better than traditional clustering methods. Second, three optimization models are further proposed to optimize the identification results, including 1) a short time stay optimization model, 2) a redundant stay optimization model, and 3) a traffic congestion stay optimization model. Field tests in Chengdu China are conducted to verify the feasibility and effectiveness of the proposed methods. Results show that the average trip end identification accuracy under different trip purposes reaches 92.8%, and the average errors of arrival and departure time are smaller than 150 s. [ABSTRACT FROM AUTHOR]

In recent years, haze pollution is frequent, which seriously affects daily life and production process. The main factors to measure the degree of smoke pollution are the concentrations of PM2.5 and PM10. Therefore, it is of great significance to study the prediction of PM2.5/PM10 concentration. Since PM2.5 and PM10 concentration data are time series, their time characteristics should be considered in their prediction. However, the traditional neural network is limited by its own structure and has some weakness in processing time related data. Recurrent neural network is a kind of network specially used for sequence data modeling, that is, the current output of the sequence is correlated with the historical output. In this paper, a haze prediction model is established based on a deep recurrent neural network. We obtained air pollution data in Chengdu from the China Air Quality Online Monitoring and Analysis Platform, and conducted experiments based on these data. The results show that the new method can predict smog more effectively and accurately, and can be used for social and economic purposes. [ABSTRACT FROM AUTHOR]

In the 2010s, China witnessed a return of the state in land acquisition and urban (re)development processes. This return of the state has resulted in a new type of neighborhood, namely displaced villagers' resettlement community (DVRC), which is well built by the government and located close to middle-income communities' amenities. The displaced villagers are entitled to full ownership and sale right of their resettlement houses. However, these houses in DVRCs are depreciated in the housing market. This study examines and explains the housing depreciation in DVRCs with a combination of quantitative hedonic models and qualitative field investigations. We explain the housing depreciation in DVRCs through the lens of territorial stigmatization theory. Based on the findings, we argue that the housing depreciation DVRCs is caused by the entrenched prejudice towards the peasantry in Chinese society. This prejudice has mutated into territorial stigmatization of DVRCs as uncivilized and poor neighborhoods. This paper innovatively bridges territorial stigmatization thesis and housing price research to provide a new method to reveal territorial stigmatization in the context of rising market approach to social housing. It contributes to the debate on whether social mix development can avoid the stigmatization of social housing communities. • China witnessed a return of the state in land acquisition and urban (re)development processes. • This return of the state has resulted in a new type of urban neighbourhood, namely displaced villagers' resettlement community (DVRC). • This study examines and explains the housing depreciation in DVRCs. • The depreciation phenomenon in DVRCs is caused by the entrenched prejudice towards the peasantry in Chinese society. • This prejudice has mutated into territorial stigmatisation of DVRCs as 'uncivilised and poor neighbourhoods' [ABSTRACT FROM AUTHOR]

Reducing car use is commonly considered as a potential strategy to reduce transport-related problems such as traffic congestion and air pollution. The increasing use of online shopping may potentially replace shopping trips, thus possibly reducing car use. However, car owners – compared to non-car owners – can more easily visit physical stores and transport goods. Therefore, it can be assumed that online shopping is less likely to reduce shopping trips for car owners. Using 653 structured face-to-face interviews in Chengdu (China) in 2016, an empirical study is conducted. The results show that 44.0% of respondents indicated a decrease in shopping trip frequency after they started to purchase online, while only 14.4% indicated an increase in the frequency. This confirms that online shopping tends to be a substitute for shopping trips. Applying a propensity score matching approach, this paper further compares the likelihoods of changes in shopping trips caused by online buying between car owners and non-car owners, while considering sociodemographic factors, internet experiences, spatial attributes, and online shopping attitudes as covariates. The results indicate that – due to online buying – shopping trip frequency is less likely to decrease for car owners compared to non-car owners, while there is no significant difference in the likelihood of increasing shopping trip frequency between owners and non-owners. These findings imply that online shopping may not effectively reduce driving, thus unlikely being a valid solution for transportation problems resulting from the increasing use of cars. • Propensity score matching is applied to infer causality; • Shopping trips can be partly replaced by e-shopping; • E-shopping is less likely to replace shopping trips for car owners; • E-shopping may not effectively reduce driving. [ABSTRACT FROM AUTHOR]