Case Study Of Kunming Research Articles

Resilience Levels of Natural–Social Security in Urbanization: A Case Study of Kunming, China

Resilience Levels of Natural–Social Security in Urbanization: A Case Study of Kunming, China

Differences in urban daytime and night block vitality based on mobile phone signaling data: A case study of Kunming’s urban district

Abstract Exploring the pattern of block vitality within cities and its influencing factors is an important topic in urban vitality research, which has great significance in promoting high-quality urban development. However, existing research has paid little attention to the spatial difference characteristics of daytime and night urban vitality and the differences in their influencing factors. Using the urban area of Kunming, China, as a case study, this study explores the differences in spatial patterns of daytime and night vitality at the intra-city block scale and analyses the differences in the main influencing factors of daytime and night block vitality using spatial regression models. The study obtains the following findings: (1) daytime block vitality in Kunming’s urban district (the urban Dist. of KM) is higher than night block vitality. The First Ring Area has the highest daytime block vitality, whereas the Second Ring Area has the highest night block vitality. (2) Block vitality in the urban Dist. of KM presents a polycentric structure. (3) There are obvious differences in the factors influencing urban vitality between daytime and night, with work accessibility, functional mixing, daily consumption accessibility, floor area ratio, and average building age, having different directions of influence on daytime and night urban vitality. (4) Daytime urban vitality in the urban Dist. of KM relies on work activities, while night urban vitality relies on residential activities. The results provide a scientific basis for urban land use layout, facility construction, and higher-quality urban planning and management, thus promoting sustainable urban development.

Spatial Accessibility of Urban Emergency Shelters Based on Ga2SFCA and Its Improved Method: A Case Study of Kunming, China

Emergency shelters are important public facilities for urban disaster prevention and mitigation. Measuring their spatial accessibility provides a valuable reference for urban modernization and a balanced layout of emergency shelters. In previous studies, the Gaussian two-step floating catchment area (Ga2SFCA) method has the shortcoming of ignoring the effect of a fixed search radius on accessibility. In this study, an improved Ga2SFCA method was proposed to evaluate emergency shelter accessibility in the main urban area of Kunming, China. The parameters of the serviceability of the shelters and the degree of population aggregation were introduced to calculate their effect on the search radius. The traditional Ga2SFCA method and the improved method were compared and analyzed. The results showed that the improved method is more reasonable and realistic in the search radius of densely populated areas and areas lacking shelters, thus providing highly objective and accurate accessibility to emergency shelters. Further, the spatial distribution of the emergency shelters in the main urban area of Kunming was unbalanced and did not match the population density distribution. The accessibility of shelters in parts of the northwestern, eastern, and central parts of the city was low. The method presented in this study could be used to provide reference and support for the government and planners to reasonably plan shelter facilities and promote equal access for all residents to shelter resources.

Spatial Characteristics of the Abandonment Degree of Residential Quarters Based on Data of the Housing Sales Ratio—A Case Study of Kunming, China

The abandonment degree of an urban residential building can reflect the popularity of residential areas. This study uses this idea as a basis for proposing the concept of using residential quarters’ abandonment rate to measure the abandonment degree of an area. The spatial pattern of the abandonment rate and its clustering characteristics were obtained by taking 2517 residential quarters in Kunming’s Main Urban District as research object, and using their listing for sale ratio data. Thereafter, curve estimation was used to explore the influencing factors of abandonment rate. The results are as follows. (1) The abandonment rate of the four circles in Kunming’s Main Urban District increases from inside to outside, showing the pattern of the core area–second ring area–third ring area–new urban district, with evident “core–edge” characteristics. (2) The relationship between distance from the city center, housing ages, and abandonment rate can be well fitted using a quadratic function and shows an inverted “U”-shaped “rising–declining” trend. The relationship between housing prices and abandonment rate is fitted by the inverse function, showing an evident “up” trend. This study is a reference for managers of relevant departments and urban planners in formulating reasonable urban housing development policies.

Relationship between Urban Three-Dimensional Spatial Structure and Population Distribution: A Case Study of Kunming’s Main Urban District, China

The three-dimensional (3D) spatial structure within cities can reveal more information about land development than the two-dimensional spatial structure. Studying the relationship between the urban 3D spatial structure and the population distribution is a crucial aspect of the relationship between people and land within cities. However, a few relevant studies focus on the differences between employment population and night population distribution in relation to urban 3D spatial structure. Therefore, this study proposes a new concept of 3D space-filling degree (3DSFD), which is applicable to evaluate the city’s 3D spatial structure. We took 439 blocks in Kunming’s Main Urban District as a sample and analyzed the 3D spatial structure based on geographic information data at the scale of a single building. The characteristics and differences of the daytime and night population distribution in Kunming’s Main Urban District were identified using cell phone signaling big data. Accordingly, a cross-sectional dataset of the relationship between the city’s 3D spatial structure and the population distribution was constructed, with the 3D space-filling degree of the block as the dependent variable, two indicators of population distribution (daytime and night population density) as the explanatory variables, and seven indicators of distance from the city center, and building, road, and functional place densities, proportion of undevelopable land area, housing prices, and land use type as the control variables. We used spatial regression models to explore the significance, strength, and direction of the relationship between urban 3D spatial structure and population distribution. We found that the spatial error model (SEM) was the most effective. The results show that only night population distribution is significantly and positively related to 3DSFD. Every 1% increase in night population density in a block will increase the value of 3DSFD by 2.8307%. The night population distribution is the core factor affecting the 3D spatial structure of Kunming’s Main Urban District. The correlation between daytime population distribution and 3DSFD is not significant. This variability has been ignored in previous studies. The findings are informative for further understanding of the relationship between urban 3D space and population distribution, especially the difference between night and daytime populations. This study can help city managers reasonably plan urban land development intensity and construction height, guide the population layout and formulate management policies to improve urban population and space matching, enhancing the livability and attractiveness of cities.

The Development Path of Smart Tourism in the Big Data Environment—A Case Study of Kunming, China

The Development Path of Smart Tourism in the Big Data Environment—A Case Study of Kunming, China

Construction of Urban Flooding Prevention System under “One City, One Executor, and One Network” Model: Case Study of Kunming, China

AbstractFlood disasters have plagued developing countries and impeded sustainable city development as a result of global climate change and economic development. Chaotic urban flooding prevention s...

Suitability of Underground Space Development in Plateau Cities Based on Geological Environment Analysis: Case Study in Kunming, China

Geology forms the basis for underground space development. In mountainous plateau areas, developing underground spaces requires detailed analyses and appraisal. This study used the index scale analytic hierarchy process (AHP) to analyze the geological conditions and to propose an evaluation system suitable for Kunming, China. An evaluation model was established using mathematical principles, and a geological suitability evaluation of Kunming was conducted using GIS. According to the evaluation, underground space in Kunming considered suitable, medium suitable, unsuitable, and forbidden for development accounts for 37.81%, 20.38%, 17.61%, and 24.2% of its total area, respectively. Soft soil and karst topographies are the primary disqualifying factors, followed by groundwater and geological fault zones. Our results reveal that most of the underground spaces in the plateau area are suitable for development. However, there are areas where construction should be strictly regulated, such as those adjacent to geological fault zones. With this study, the superiority of the index scale method was demonstrated, and the consideration criteria of the evaluation system and indexes in plateau cities were proposed.

The Extraction of Urban Built-Up Areas by Integrating Night-Time Light and POI Data—A Case Study of Kunming, China

With the urban built-up area becoming one of the most prominent forms of urban expansion, accurately extracting the urban built-up area is becoming more and more important to judge the urbanization process and evaluate the urban environment. Since it is difficult to significantly improve the accuracy of single satellite data in the extraction of urban built-up areas, this study proposes a method integrating POI (Point of Interest) data and Luojia-1A data to improve the extraction accuracy of urban built-up areas. In this study, integrated Density Graph, OSTU and geometric mean are used to extract urban built-up areas respectively. The highest precision of urban built-up areas extracted before data integration is 74.3% with the highest Kappa value of 0.54; while the highest precision of urban built-up area extracted after data integration is 91.4%, with the highest Kappa value of 0.91. Therefore, it can be concluded that compared with the existing widely used night-light-based methods, this method can integrate the advantages of POI data and Luojia-1A data, that is, it can not only solve the long-term oversaturation phenomenon of night light data, but also can extract urban built-up areas in a more refined way. The method used in this study, which integrates POI data and Luojia-1A data, can not only provide a new method for urban built-up area extraction, but also can play an active guiding role in urban planning and construction.

A Tabu Search-Based Algorithm for Airport Gate Assignment: A Case Study in Kunming, China

An airport gate is the core resource of an airport operation, which is an important place for passengers to get on and off the aircraft and for maintaining aircraft. It is the prerequisite for other related dispatch. Effective and reasonable allocation of gates can reduce airport operating costs and increase passenger satisfaction. Therefore, an airport gate assignment problem (AGAP) needs to be urgently solved in the actual operation of the airport. In this paper, considering the actual operation of the airport, we formulate an integer programming model for AGAP by considering multiple constraints. The model aims to maximize the number of passengers on flights parked at the gate. A tabu search-based algorithm is designed to solve the problem. In the process of algorithm design, an effective initial solution is obtained. A unique neighborhood structure and search strategy for tabu search are designed. The algorithm can adapt to the dynamic scheduling of airports. Finally, tests are performed using actual airport data selected from Kunming Changshui International Airport in China. The experimental results indicate that the proposed method can enhance the local search ability and global search ability and get satisfactory results in a limited time. These results provide an effective support for the actual gate assignment in airport operations.

Exploring differences within the low‐income population in urban China: A case study in Kunming, Yunnan Province

This study focuses on differences between people in Kunming, China who are categorised as low income. Whereas in the existing literature low‐income people in urban China are generally described as comprising heterogeneous groups based on case studies of coastal megacities, this study offers a much‐needed comprehensive, micro‐level analysis to identify and differentiate low‐income groups from each other, based on the case of an inland megacity. A population sample from a number of low‐income neighbourhoods is used to analyse the differentiation among the urban low‐income population. According to the results from a latent class cluster analysis, low‐income urban people can be divided into five groups: low‐income locals with some employment‐relevant abilities; low‐income migrants; low‐income locals with limited employment‐relevant abilities; inherited socialist low income; and low‐income with high mobility. Of these groups, the inherited socialist low‐income group and the low‐income locals with limited employment‐relevant abilities were found to be the most vulnerable, given that the people in these two groups were the poorest and had few abilities pertinent to improving their ability to make a living and, therefore, few prospects of improving their standard of living. The low‐income locals with some employment‐relevant abilities had the potential to gain employment, yet evinced the lowest labour participation rate. The members of the low‐income migrant group had limited skills and most were excluded from city welfare and formal employment systems. The low‐income with high mobility had weak competitive abilities in the labour market and experienced difficulty obtaining stable employment. The study clearly shows that there is an urgent need to adopt different measures for the distinct groups of urban low‐income thus identified.

Multi-Objective Optimal Allocation of Urban Water Resources While Considering Conflict Resolution Based on the PSO Algorithm: A Case Study of Kunming, China

With the rapid increase of water demand in urban life, ecology and production sectors, the problem of water resources allocation has become increasingly prominent. It has hindered the sustainable development of urban areas. Based on the supply of various water sources and the water demand of different water users, a multi-objective optimal allocation model for urban water resources was proposed. The model was solved using the algorithm of particle swarm optimization (PSO). The algorithm has a fast convergence and is both simple and efficient. In this paper, the conflict over Kunming’s water resources allocation was taken as an example. The PSO algorithm was used to obtain optimized water resources allocation plans in the year 2020 and 2030, under the circumstances of a dry year (inflow guarantee rate p = 0.825) and an unusually dry year (inflow guarantee rate p = 0.885), respectively. The results showed that those allocation plans can lower the future potential water shortage rates of Kunming. At the same time, the interests of different sectors can all be satisfied. Therefore, conflicts over urban water use can be effectively alleviated.

An integrated approach to investigate the relationship of coupling coordination between social economy and water environment on urban scale - A case study of Kunming

With a rapid economic growth and social development in China, the associated problems of water pollution and shortage of water resources would limit the sustainable and coordinated development of socioeconomic and water environmental systems of urban cities. To investigate the relationship of coupling coordination between social economy and water environment on urban scale, we introduced an integrated approach that enables the dynamic evaluation of coupling coordination degree (CCD), which consists of a system dynamics model and a coupling coordination degree model; and applied it to a case study in Kunming in 2016–2025. The business-as-usual (BAU) scenario and five alternative regulating scenarios are simulated to evaluate the effectiveness exerted by various socioeconomic development patterns and water protection efforts in improving CCD. We found that the improvement of CCD could attribute to both the sufficient water protection efforts and the maintaining sustainable speed and scale of socioeconomic development patterns. Under BAU scenario, Kunming would maintain the current state of barely balanced development with CCD at 0.5–0.8, predominantly due to substantial water consumption and pollution. Through the comparison of dynamic evolutions of system indicators and CCD under five alternative regulating scenarios, it is realistic for Kunming to plan its future development in accordance to M-H scenario (Medium-speed socioeconomic development pattern; High-intensity water protection effort). Following this scenario, Kunming's CCD would conform to a steadily increasing trend in 2016–2025 and remain above 0.8 in 2022–2025, tracing a shift in the development stage of that coupling coordination from “barely balanced development” to “highly balanced development” despite the difficulty to cut NH3-N emission significantly. The effective and feasible regulatory measures such as reducing productive or domestic water pollutants and consumptions; improving collection and reuse rates of wastewater, should be prioritized when adjusting coordination development during decision-making.

Research of the distribution of tourists’ attributes based on internet data: A case study of Kunming

With the development of the era of big data, the ever-growing user trajectory provides the basis for studying multi-scale tourist activity law. This paper selected 17 famous tourist attractions in Kunming. Sina Microblog, Ctrip Travel, Lvmama Travel Network and other platforms were used to extract 139727 records between Oct. 2015 and Sep. 2016. The methods of data mining and clustering analysis were used to explore the activity characteristics of tourists with different attributes in scenic spot and the activity differences of different age tourists in different scenic spots affected by season, not only considered gender, geographical, check-in time and other factors, but also the introduced age attributes. At the same time, the scenic area is divided into “Adolescent active pattern”, “Young and middle-aged women active pattern”, “Middle-aged and old men active pattern” and “General active pattern” according to different tourists’ activities law of different gender and age in spatial perspective. Research shows that female tourists are mainly distributed in the Green Lake Park, Nanping Street, Dounan Flower Market and other attractions, elderly male tourists are mainly distributed in Expo Park, Jindian area. Foreign tourists accounted for 86.32% of the total tourists, reflecting the rapid development of tourism in Kunming. The spatial distribution of tourist attractions has an impact on the distribution of tourists’ attributes. The number of tourists of Shilin, Jiuxiang, Guandu Ancient Town are accounted for 36.38% of the total tourists, which shows that the spatial distribution of tourist attributes is consistent with the development of key tourist areas in Kunming.

Enhancing future resilience in urban drainage system: Green versus grey infrastructure

In recent years, the concept transition from fail-safe to safe-to-fail makes the application of resilience analysis popular in urban drainage systems (UDSs) with various implications and quantifications. However, most existing definitions of UDSs resilience are confined to the severity of flooding, while uncertainties from climate change and urbanization are not considered. In this research, we take into account the functional variety, topological complexity, and disturbance randomness of UDSs and define a new formula of resilience based on three parts of system severity, i.e. social severity affected by urban flooding, environmental severity caused by sewer overflow, and technological severity considering the safe operation of downstream facilities. A case study in Kunming, China is designed to compare the effect of green and grey infrastructure strategies on the enhancement of system resilience together with their costs. Different system configurations with green roofs, permeable pavement and storage tanks are compared by scenario analysis with full consideration of future uncertainties induced by urbanization and climate change. The research contributes to the development of sustainability assessment of urban drainage system with consideration of the resilience of green and grey infrastructure under future change. Finding the response measures with high adaptation across a variety of future scenarios is crucial to establish sustainable urban drainage system in a long term.

Government-Nonprofit Collaboration: Social Enterprise Participates in Drug Addicts’ Social Integration

As a special community, the drug addicts cannot integrate into the society easily. In the case study of Kunming Q social enterprise, the author found out that it was effective to help drug addicts integrate into the society, combining government investment with social enterprise operation and the social participation. But this government-nonprofit collaboration was not successful at last. The failure was originated from these factors, which included market competition, social entrepreneur, inner-governance and participators’ congruent goals, and the last was more important.

Investigating Electric Bicycles as a Travel Mode Choice for Escorting Children to School: A Case Study in Kunming, China

To encourage low-carbon travel, reduce car trips, and improve the urban traffic system, an understanding of travel mode choice for escorting children to and from school is important. Previous studies have focused mostly on walking and bicycling. However, the electric bicycle (e-bike—a mainstream escorting mode in China) rarely has been investigated. The factors that affect travel mode choice (walking, e-bike, or car) for escorting children to and from school are explored at the household level in a case study from Kunming, China. Intrahousehold interactions and parental space–time constraints are represented by the comparative working hours of the parents and space–time coordination in joint parent–child trips, respectively. A multinomial logit model was applied in mode analysis. The results reveal interesting phenomena in travel mode choices for escorting children to school. When the mother’s working hours are longer than the father’s, the travel mode choice for escorting a child to and from school is less likely to be walking or e-bike; in other words, a car is the preferred choice in mother-dominated households. The distance deviation between parents and children is a significant factor in choosing between a car or an e-bike. Children are more likely to be escorted by e-bikes as a result of distance deviations, and walking or e-bike is less likely to be chosen when the school is far from home. Results could be valuable for traffic demand management to reduce car use for trips to and from school. In addition, e-bike development should be considered seriously for the future development of China.

A New Hybrid Model FPA-SVM Considering Cointegration for Particular Matter Concentration Forecasting: A Case Study of Kunming and Yuxi, China.

Air pollution in China is becoming more serious especially for the particular matter (PM) because of rapid economic growth and fast expansion of urbanization. To solve the growing environment problems, daily PM2.5 and PM10 concentration data form January 1, 2015, to August 23, 2016, in Kunming and Yuxi (two important cities in Yunnan Province, China) are used to present a new hybrid model CI-FPA-SVM to forecast air PM2.5 and PM10 concentration in this paper. The proposed model involves two parts. Firstly, due to its deficiency to assess the possible correlation between different variables, the cointegration theory is introduced to get the input-output relationship and then obtain the nonlinear dynamical system with support vector machine (SVM), in which the parameters c and g are optimized by flower pollination algorithm (FPA). Six benchmark models, including FPA-SVM, CI-SVM, CI-GA-SVM, CI-PSO-SVM, CI-FPA-NN, and multiple linear regression model, are considered to verify the superiority of the proposed hybrid model. The empirical study results demonstrate that the proposed model CI-FPA-SVM is remarkably superior to all considered benchmark models for its high prediction accuracy, and the application of the model for forecasting can give effective monitoring and management of further air quality.

Elasticity of Demand for Urban Housing in Western China Based on Micro-data - A Case Study of Kunming

Elasticity of Demand for Urban Housing in Western China Based on Micro-data - A Case Study of Kunming

Drivers’ Information Behavior Analysis with ATIS Equipment: A Case Study of Kunming in China

Advanced travel information system (ATIS) gives assistance to a better decision-making of trip makers. Including vehicle navigation system, mobile phone application, variable message sign (VMS), traffic radio, a series of information delivery equipment which can meet real demand in information services, are used to support travel decision making of destinations, departure time, routes and travel mode. Along with the development of information technology which can release plenty of travel information, it will be a considerable challenge to department who furnish the travel information service that requires them to choose which service to provide. To reach that goal, it is fundamental to acquaint themselves to understand market penetration of ATIS equipment and information behavior of traveller. Through the data of drivers’ information behavior of ATIS equipment in Kunming based on tracking survey, this paper reveal that Chinese drivers have a sustainable increased willingness to pay for personalized information service. Market penetration of vehicle navigation, as the most well-used ATIS equipment, is climbing. Satisfaction to vehicle navigation is closely related to utilization frequency, willingness to pay for the map upgrade and utilization load. Furthermore, although users have a distinguished dependency to vehicle navigation, query level is still high.