Main Urban Area Of Chongqing Research Articles

Integrated Evaluation Method of Bus Lane Traffic Benefit Based on Multi-Source Data

Bus lanes are an important measure for improving the quality of bus service and the efficiency of transportation systems. A scientific and reasonable evaluation of the overall traffic operation efficiency of the bus priority road section is helpful to fully understand the improvement effect of the introduction of bus lanes on traffic operation. To comprehensively and objectively evaluate the traffic benefits of bus lanes, the Delphi and grey correlation methods were used to construct a comprehensive weight calculation model of the indicators. The weights of eight traffic benefit evaluation indicators at the two levels of buses and general traffic were calculated, and the weights were then optimized using the target optimization model. Combined with different weight indexes, the evaluation of the traffic benefit level of the bus lane was realized using the matter-element extension model based on the improvement in the sticking progress. The bus lanes of the Daping-Yangjiaping, Huanghuayuan interchange-Luneng turntable, and Dashiba-Hongqihegou routes in the main urban area of Chongqing were used for verification. The results show that the traffic benefits of the three case areas have been improved to a certain extent after the construction of bus lanes, but the benefit level has not changed. Through the analysis of various operating indicators, the weaknesses that affect the traffic efficiency can be obtained, and then the decision-making basis for the implementation and improvement of the bus lane optimization scheme can be provided.

A study of prehospital EMS response time and influencing factors in the main urban area of Chongqing, China.

Shortening the prehospital emergency medical service (EMS) response time is crucial for saving lives and lowering mortality and disability rates in patients with sudden illnesses. Descriptive analyses of prehospital EMS response time and each component were conducted separately using ambulance trip data from the 120 Dispatch Command Centre in the main urban area of Chongqing in 2021, and then, logistic regression analyses were used to explore the influencing factors. The median prehospital EMS response time in the main urban area of Chongqing was 14.52 min and the mean was 16.14 min. A 44.89% of prehospital EMS response time exceeded 15 min. Response time was more likely to surpass this threshold during peak hours and in high population density areas. Conversely, lower probabilities exceeding 15 min were observed during the night shift, summer, and autumn seasons, and areas with a high density of emergency station. 33.28% of preparation time was >3 min, with the night shift and high population density areas more likely to be >3 min, while for the summer and autumn seasons, high Gross National Product (GDP) per capita areas had a lower likelihood of having preparation time >3 min. 45.52% of travel time was >11 min, with peak hours, summer and autumn, and high GDP per capita areas more likely to have had a travel time >11 min, while night shift and high emergency station density areas had a lower likelihood of travel time >11 min. The primary factors influencing prehospital EMS response time were shifts, traffic scenarios, seasons, GDP per capita, emergency station density, and population density. Relevant departments can devise effective interventions to reduce response time through resource allocation and department coordination, staff training and work arrangement optimisation, as well as public participation and education, thereby enhancing the efficiency of prehospital emergency medical services.

About Community Health Centers in the Main District of Chongqing Municipality Current Situation and Measures of Infectious Disease Prevention and Control Introduction

With the acceleration of urbanization and the increase of population mobility, the public health and safety situation in the main urban area of Chongqing, as a modern metropolis with rapid economic development and dense population, has become increasingly complex and severe. The outbreak and spread of infectious diseases pose a serious threat to the lives and health of community residents and social stability, so it is crucial to strengthen the research on the prevention and control system of infectious diseases in grassroots community health service centers. Grassroots community health service centers in the main urban areas of Chongqing are the foundation and frontier of the entire public health prevention and control system, which is directly related to the health level of community residents and community public health safety. In the current global context of multiple, new, and frequent outbreaks of infectious diseases, it has become imperative to strengthen the construction of the infectious disease prevention and control system of grassroots community health service centers to improve the effectiveness and level of infectious disease prevention and control. This study will focus on the infectious disease prevention and control system of grassroots community health centers in the main urban areas of Chongqing, aiming to deeply analyze its composition structure, functional positioning, operation mechanism, personnel quality and facilities and equipment. Through the study and analysis of the infectious disease prevention and control system, existing problems and bottlenecks will be identified, and feasible and operable optimization suggestions will be made to promote the improvement and enhancement of the infectious disease prevention and control system. The significance of this study is not only to provide scientific basis and practical guidance for the improvement of the infectious disease prevention and control system in the main urban area of Chongqing, but also to provide reference and experience sharing for similar problems in other cities and regions, so as to jointly promote the modernization and standardization of the infectious disease prevention and control system of China's grassroots community health service centers, in order to ensure the health and safety of the community residents.

Evaluation of existing underground public space supply based on the Node-Place-Experience model

The development of underground public space is considered to be a major contributor to urban sustainability. However due to the lack of customized tools for identification and assessment the effective or ineffective supply of existing underground public space has yet to receive sufficient attention resulting in frequent problems such as its undersupply and underutilization of space. Therefore this study proposes three assessment frameworks for existing underground public spaces namely traffic supply (Node) land use and activity diversity (Place) and user experience (Experience) to judge the effectiveness of the supply in 13 cases in the main urban area of Chongqing by the degree of balance of the three dimensions, and to categorize the results of the evaluation through hierarchical clustering. The study confirms that except for Nanping the other cases suffer from under-provision especially in terms of transport provision such as the low connectivity of the existing underground public space to other urban spaces. Afterward we classified the evaluated cases into four clusters: “unsustainable place with potential to be balanced,” “developing balanced with promising potential to be balanced,” “developing balanced with potential to be balanced,” “developing balanced with lower potential to be balanced” and proposed corresponding optimization paths. Our method can be used as an effective tool to identify and measure the effectiveness of existing underground public space supply and to provide a database and decision support for the optimization of future renovation of the project.

Cascading failure mechanism of major drainage system in mountainous city: Taking the basin of the main urban area of Chongqing as an example, China

Failure of major drainage systems is almost always accompanied by waterlogging. Understanding the operation and failure mechanism of major drainage systems is an important prerequisite for understanding and managing waterlogging. The natural and artificial environments in mountainous cities are more complex, and the major drainage system, as an open system for excessive surface runoff discharge and storage, is more prone to local overload and cascading failure. Existing theories and methods are difficult to explain and analyze the cascading failure characteristics and principles of major drainage systems in mountainous cities. Based on the complex network technology and the principle of runoff balance, the cascade failure model of major drainage system was constructed, and the characteristics and laws of cascade failure under six kinds of terrain, six kinds of short duration rainstorm and two kinds of surface environments were quantitatively analyzed. Research has found that the cascading failure of major drainage systems and waterlogging in mountainous cities should be the same phenomenon from different perspectives, and the simulated matching degree between the two can reach 79.5%. Meanwhile, 456 potential waterlogging locations were discovered in the study area, which is much larger than the actual 73 locations. When urban construction and rainfall conditions change, these unstable potential waterlogging locations are easily apparent. Among them, terrain is the main factor restricting the cascading failure of major drainage systems. Low lying valley areas often quickly accumulate a large amount of overflow, while flat areas are prone to overflow spreading to the surrounding areas; Slope areas are not prone to overflow, but are prone to local flooding. The change of short duration rainstorm and the difference of surface environmental openness will further interfere with the cascade failure of the major drainage system. The longer the return period of the short duration rainstorm or the increase of the peak value of the rainfall pattern, the greater the discharge and storage pressure of the major drainage system per unit time, resulting in intensified waterlogging. The open and unobstructed surface environment will lead to the small-scale spread of waterlogging, but this will significantly reduce the overall degree of waterlogging in the late rainstorm. The study revealed the spatiotemporal principles and basic laws of cascading failure of major drainage systems in mountainous cities. The conclusion is helpful for mountainous cities to formulate urban construction management strategies and climate change adaptation strategies, and to cope with current and future potential waterlogging disasters.

CO and CH4 atmospheric trends from dense multi-point forest fires around the city of Chongqing using spaceborne spectrometer data

Forest fires greatly impact the global terrestrial ecology and atmospheric environment. It is important to improve fire prediction mechanisms and track fire trends. This study evaluates using spaceborne spectrometers (Sentinel-5P TROPOMI and Aqua AIRS) to track atmospheric CO and CH4 changes caused by more than a dozen forest fires around the main urban area of Chongqing, China. These forest fires consisted of dense, multi-point, small-scale outbreaks over a short period (August 17–26, 2022). All the fires were near human living areas, leading to relatively complex atmospheric trends. We obtained the spatial distribution of CO and CH4 and analysed the forest fires' exact occurrence and quenching time at each fire location. Concentration gradients of the CO column are consistent with the rise and fall of the fires observed at all fire points. Large CO plumes from different fire locations observed on August 21, and 22 have concentrations exceeding 0.07 molecules/m2. The average CO concentration data at nine ignition points are summed to reflect the temporal trend of CO in the atmosphere over the entire region. The CO2 column range estimated from the CO column was 0.16–0.63 molecules/m2 on August 22. We also tracked and analysed the atmospheric trend of methane concentration during the fire. Consequently, based on satellite data, tracking the temporal trends of CO and CH4 in the atmosphere caused by dense forest fires in a complex environment is feasible.

Influences of Spatial Accessibility and Service Capacity on the Utilization of Elderly-Care Facilities: A Case Study of the Main Urban Area of Chongqing

With the unprecedented growth of the elderly population in China, elderly-care facilities (ECFs) are in a fast expansion process. However, limited attention has been paid to the imbalance at the actual utilization level of ECFs. This research aims to reveal the spatial inequity of ECFs and to quantitatively examine the effect of accessibility and institutional service capacity on utilization. Taking Chongqing, China, as the study area, we measured the spatial accessibility of different travel modes by the Gaussian Two-Step Floating Catchment Area (G2SFCA) method and investigated distribution differences in spatial accessibility, service capacity, and utilization of ECFs by the Dagum Gini Coefficient and its decomposition. Then, the impact of spatial accessibility and service capacity on the utilization of regional ECFs was quantified by multiscale geographically weighted regression (MGWR). The study findings can be summarized as follows. (1) Walking accessibility has the most significant impact on the utilization of ECFs and shows geographic heterogeneity. Developing a pedestrian-oriented network of pathways is essential to enhance the utilization of ECFs. (2) Accessibility by driving and bus-riding does not correlate with regional ECFs utilization, and relevant studies cannot rely on them alone for assessing the equity of ECFs. (3) In the utilization of ECFs, since the inter-regional difference is more significant than the intra-regional difference, efforts to reduce the overall imbalance should be oriented toward inter-regional variation. The study's findings will assist national policymakers in developing EFCs to enhance health indicators and quality of life for older adults by prioritizing financing for shortage areas, coordinating ECFs services, and optimizing road systems.

Ecological network analysis of the carbon metabolism system in mountainous cities based on the land-carbon nexus: a case study of the main urban area of Chongqing, China.

The analysis of urban carbon metabolism will help to mitigate global warming and achieve China's "Dual Carbon" targets. Taking the main urban area of Chongqing (MUAC) as an example, this study accounted for the carbon release and carbon absorption in MUAC, constructed an urban carbon flow model based on the land-carbon nexus, and evaluated the urban carbon metabolic system from 2000 to 2020 by using the ecological network analysis method. The results show that MUAC is dominated by a "carbon source" effect, and the net carbon flow is always negative. The negative carbon flow mainly comes from the conversion of cultivated land to construction land, and the positive carbon flow mainly comes from the conversion of construction land to cultivated land and woodland. The ecological relationship of carbon metabolism in MUAC is dominated by exploitation and control relationships, which mainly exist in the ecological relationship between construction land and cultivated land, and the spatial distribution is concentrated in the central and western areas of MUAC. Our research results can provide a reference for Chongqing's green and low-carbon sustainable development as a means toward the realization of the "Dual Carbon" targets and provide a reference for other similar mountainous cities in western China.

Spatiotemporal Dynamic Evolution and Gravity Center Migration of Carbon Emissions in the Main Urban Area of Chongqing over the Past 20 Years

Global warming caused by carbon emissions is an environmental issue that is of great concern to all walks of life. Dynamic monitoring of the spatiotemporal evolution of urban carbon emissions is an important part of achieving the regional double-carbon goals. Taking the main urban area of Chongqing as an example, based on the data of land use and energy consumption, this study estimated the carbon emissions of 153 townships and streets in the main urban area of Chongqing from 2000 to 2020 by using the carbon emission coefficient method. Additionally, using the ESTDA framework to pass the LISA time path, spatiotemporal transition, and the standard deviation ellipse model from the perspective of spatiotemporal interaction, the spatiotemporal dynamic evolution of carbon emissions in the main urban area and the shift in the center of gravity over the past 20 years were analyzed. The results showed that: ① in the past 20 years, the carbon emissions in the main urban and rural areas have had a significant positive spatial correlation, and the spatial convergence showed a trend of first decreasing and then increasing. ② In the past 20 years, there were 126 township streets with low and medium relative lengths (accounting for 82%), indicating that the local spatial structure of township carbon emissions in the main urban area had strong stability; the total number of township streets with low and medium curvatures was 138 (accounting for 90%), indicating that the volatility of the main urban and rural carbon emissions in the direction of spatial dependence was relatively stable; there were 113 township streets (accounting for 74%) of the synergistic growth type, indicating that the main urban and rural carbon emissions were relatively stable. The emission pattern had strong spatial integration. ③ In the past 20 years, the spatiotemporal agglomeration index was greater than 70%, indicating that the local spatial correlation pattern and agglomeration characteristics of carbon emissions in the main urban and rural areas had strong stability. 4 In the past 20 years, the center of carbon emission in the main urban area had been distributed between 106°30'43″-106°32'42″E, 29°33'34″-29°35'56″N, and the center of gravity shifted to the northeast as a whole. The spatial distribution changed from the "northwest-southeast" pattern to the "northeast-southwest" pattern. These results can provide reference for the green and low-carbon sustainable development of Chongqing and the formulation of differentiated emission reduction policies, as well as provide reference for other similar mountain cities in western China.

Establishment of Inland Ship Air Pollution Emission Inventory Based on Power Method Correction Model

The atmospheric pollutants and greenhouse gases emitted by ships have a significant impact on the air quality of the cities around the port and the physical and mental health of the residents. In order to promote the low-carbon, green, and sustainable development of the region, it is urgent to conduct comprehensive research and control the air pollution emissions from ships in the region. In this paper, the traditional power-based emission inventory calculation model is improved through field tests, and the engine propeller matching coefficient is proposed. Combined with the actual situation of local ships, the parameters suitable for the air pollution emission inventory of ships in the region are comprehensively selected. In the case of statistical comparison of the air pollutant emissions of the main and auxiliary engines under different navigation conditions, the uncertainty analysis was carried out, and the AIS (Automatic Identification System) combined with the power method was used to obtain the air pollution emission inventory of ships in the main urban area of Chongqing. The research in this paper can improve the calculation model of the power method emission inventory according to the situation of ships in the inland river area, which provides a reference for the development and improvement of the emission inventory in the inland river area, and also provides suggestions and thinking for the government to formulate energy saving and emission reduction measures in the inland river area.

Retention Effect of Heavy Metals in Rivers of a Typical Mountainous City by Cascade Weirs: A Case Study of Liangtan River in Chongqing

Contaminants such as heavy metals in rivers are partially retained in the sediments at the bottom as a result of the altered water regime within the cascade weirs. The associated heavy metals in the sediments can affect surface water quality and ecology for a long period. In May 2020, sediments were collected in a typical mountainous river (Liangtan River) with cascade weirs in the main urban area of Chongqing. The accumulation of sediments in each river section, the content of heavy metals, and other basic physicochemical indicators in the samples were monitored. The results showed that the average ω(As), ω(Cd), ω(Cu), ω(Hg), ω(Ni), and ω(Pb) in the sediments of the main stream of Liangtan River were (4.66±4.78), (0.361±0.256), (32.30±14.38), (0.069±0.039), (33.47±15.37), and (26.34±11.52) mg·kg-1, respectively. A large coefficient of spatial variation regarding the content of heavy metals in the sediments across the sampling sites was observed owing to the uneven spatial distribution of pollution sources and the destruction of river connectivity by cascade weirs. The modified geoaccumulation index (Im) showed that Cd was the most polluted heavy metal element in the sediments. Of the monitored river sections, 12.50% approached or were at moderate pollution levels, and these sections were mainly found in the upstream and downstream reaches of Liangtan River with relatively concentrated construction lands. The potential ecological risk assessment index method (RI) and the sediment quality guideline method (SQGs) showed that, in addition to Cd and Hg with a high pollution level and strong toxicity, Ni in the sediments also posed a potential threat to the ecological safety of surface water due to its high background content in the watershed. The total amounts of As, Cd, Cu, Hg, Ni, and Pb retained in the sediments by cascade weirs were estimated to be 446.10, 47.28, 4997.80, 10.81, 5135.68, and 4048.16 kg, respectively, in which Cd, Ni, and Pb were identified to be the major threats to the ecological safety of surface water over a long period. The upper reaches prior to the weirs with the most retained heavy metals and the easier formation of an anaerobic environment are suggested to be the key areas for investigation of the endogenous release of heavy metals. Source apportionment of heavy metals in river sediments through the combination of principal component analysis and cluster analysis revealed that Cd, Cu, and Pb mainly originated from residential/industrial point source pollution. Hg mainly originated from agricultural non-point source pollution, whereas As and Ni mainly originated from natural soil erosion.

Response and multi-scenario prediction of carbon storage to land use/cover change in the main urban area of Chongqing, China

Carbon storage services play an important role in maintaining ecosystem stability. Land use/cover change (LUCC) is the dominant factor generating changes in the ecosystem carbon storage. Demonstrating the impact of LUCC on regional carbon storage changes and predicting future carbon storage under different land use scenarios is of great significance for promoting regional carbon peak and carbon neutrality goals. Taking the main urban area of Chongqing as an example, this study analyzes carbon storage changes from 2000 to 2020 and the response to LUCC. The Markov-FLUS model is employed to predict the land use pattern of the main urban area in 2035 under four scenarios, and the InVEST model is used to assess carbon storage in 2035 under different scenarios. The results can be summarized as follows: 1) In the past 20 years, the area of cultivated land in the main urban areas of Chongqing decreased by 743.29 km2, and the area of construction land increased by 773.48 km2. About 18.8 % of the main urban area of Chongqing was transferred, the conversion of cultivated land to construction land being the most important type of transfer. 2) In 2000, 2005, 2010, 2015, and 2020, the carbon storage in the main urban area was 59.85, 59.29, 57.90, 56.95, and 54.07 Tg, respectively, showing an annually decreasing trend with a cumulative decrease of 5.78 Tg. The cultivated land occupation by construction land is the leading factor for the rapid decrease of carbon storage. The spatial distribution of carbon storage in the main urban area differs significantly, exhibiting a low in the middle and high in the surrounding areas. 3) In 2035, the carbon storage in the main urban area shows different degrees of decline in the Natural Trend Scenario (NTS), the Food Security Scenario (FSS) and the High Urbanization Scenario (HUS), decreasing by 3.37, 0.59, and 5.25 Tg, respectively. The only increase by 1.51 Tg is found in the Ecological Security Scenario (ESS). Therefore, under the background of the “Dual Carbon” targets and the important positioning of Chongqing as an important ecological barrier in the Yangtze River Basin, the ESS can be considered in the future development planning of the main urban area of Chongqing, which can both increase carbon sink and ensure ecological security.

Nonlinear Effects of Community Built Environment on Car Usage Behavior: A Machine Learning Approach

This study aims to guide the community life circle to create a green, travel-supportive built environment. It quantitatively analyzes the variations in car usage behavior based on the level of the built environment of the community and objectively reflects the car usage behavior based on the parking space utilization rate (PSUR). Ordinary least squares (OLS) and gradient boosting decision tree (GBDT) models were developed to describe the impact of the built environment on this utilization rate. An empirical analysis of the model was also conducted using the multisource, heterogeneous parking data of commercial parking facilities in the main urban area of Chongqing, China; the data include records of parking survey, points of interest, and road networks. The results showed that the GBDT model had a better fitting degree than the OLS model considering nonlinear effects. In terms of the contribution of community-built environment variables, distance to business center (14.30%), population density (14.20%), and land use mix (12.60%) considerably affect the PSUR, indicating that these variables have an important influence on the use of private cars. All built environment variables have nonlinear relationships, and the threshold effects reflect a complex relationship between the built environment and car usage behavior. This study provides refined suggestions for the spatial design and transformation of the community life circle.

Identification and Evaluation of Water Pollution Risk in the Chongqing Section of the Three Gorges Reservoir Area in China

The Three Gorges Reservoir is the largest freshwater resource reservoir in China. The water environment security in the Three Gorges Reservoir area has a prominent position in the major national strategy for the protection of the Yangtze River. Based on the pressure–state–response (PSR) model, this study comprehensively considers the dangerousness of risk source, the sensitivity of risk receptors, and the acceptable level of regional environmental risk to construct the grading evaluation index system of water environment pollution risk. By using spatial statistical methods, including the variation coefficient method and cold–hot spot pattern analysis, the risk distribution of water environment pollution in the Chongqing section of the Three Gorges Reservoir area was comprehensively identified and evaluated by administrative units. The results showed that: (1) the number of risk sources was largest in Yunyang County and the number of risk receptors was largest in Wanzhou District. However, the distribution of high-risk pollution sources and high-sensitivity receptors was most intensive in the main urban area and surrounding areas of Chongqing, and the regional environmental risk acceptance level was the lowest. (2) The statistical results of risk source dangerousness and the risk receptor sensitivity index at the county level in the study area showed an aggregated distribution pattern, with hotspot areas concentrated in the main urban area of Chongqing and the surrounding area in the upper reaches of the reservoir area. Moreover, the acceptable level of risk in this area showed a cold spot area, while other regions basically showed a balanced distribution pattern without forming significant hot spot or cold spot areas. (3) The high-risk river section of water pollution in the reservoir area comprised five counties, including Jiulongpo District, Yubei District, Shapingba District, Yuzhong District and Nanan District; the middle-risk river section comprised six counties, including Changshou District, Beipei District, Jiangbei District, Dadukou District, Fuling District and Shizhu County; and the low-risk river sections were mainly distributed in the Jiangjin District in the upper reaches of the reservoir area and the middle and lower reaches of the northeast ecological area of Chongqing. Therefore, the acceptable levels of water pollution risk sources, receptors and regional environmental risks in the Chongqing section of the Three Gorges Reservoir area are unevenly distributed, showing an aggregated distribution pattern. The spatial distribution of water environment pollution risk is uneven, and the significant potential risk area is the functional core area of Chongqing, which is the critical area of water environment risk management in the future.

Research on the Influence Mechanism of Street Vitality in Mountainous Cities Based on a Bayesian Network: A Case Study of the Main Urban Area of Chongqing

As the main spatial carrier for people’s social activities, street space occupies an important position in the urban space. However, under the direction of traffic-driven urban planning, the social function of street space has been neglected, resulting in the gradual loss of vitality. In mountainous cities with rugged terrain, the factors influencing the vitality of streets may be different compared to those in plain areas. In order to explore the influence mechanism of street vitality in mountainous cities, a new quantitative research method based on the new data environment and a Bayesian network is proposed. In this study, Python and GIS are used to obtain spatial data of streets, and Bayesian networks are used to construct street vitality models to identify important influencing factors and causal relationships between influencing factors. The results demonstrate strong causal dependencies between the factors influencing street vitality in mountainous cities. The mechanism of influence of street vitality revolves around functionality and street texture in terms of its own environment and external environment, respectively. The combination of factor group with functional density as the root node achieved the maximum probability of high vitality of the street. The results of this study have implications for community or urban planners with respect to urban regeneration and street vitality promotion.

Spatial Distribution and Influential Factors of Nutrients in Rivers of a Typical Mountainous City: A Case Study of the Qingshuixi River in Chongqing

Surface water pollution seriously restricts the development of the city and results in the citizens yearning for a better life. Mountainous cities have their own characteristics in surface water environment and pollution compared with those of plain cities due to their unique topography. In August and October 2019, surface water and sediments were collected in a typical river (Qingshuixi River) in the main urban area of Chongqing. These samples were analyzed for nutrients such as carbon, nitrogen, and phosphorus as well as other basic physicochemical indicators. The results showed that the surface water of the Qingshuixi River was inferior to Category V at present, and it was also at a serious pollution level according to the comprehensive pollution index evaluation system. Among all the water quality indices, NH4+ and TP showed the most serious pollution. The tributaries of the Qingshuixi River exhibited higher surface water quality than that of the main stream, and the water quality during the rainfall season was better than that during the non-rainy season. Pollution sources, tailwater/tributary inflow, and river self-purification capacity determined the spatial distribution of nutrients in the surface water of the mainstream of the Qingshuixi River. Point sources such as the direct discharge of source sewage and pollution overflow in the middle and lower reaches were the most important sources of surface water pollution in the mainstream of the Qingshuixi River. Non-point source pollution had a limited impact on water quality. The "sink" or "source" role transformation of river sediments would occur under different water volume conditions in the river, reflecting the complexity of endogenous pollution. Surface water quality of the main stream showed a gradual improvement tendency along the downstream due to the dilution of the tail water/tributary inflow and the increased self-purification capability of the surface water in the mountainous rivers due to the increased DO content. To summarize, this study suggests that the water environment of the Qingshuixi River should be improved in comprehensive ways, which might be reducing the input of point source pollution by the deployment of the municipal pipe network in key areas, upgrading the sewage treatment plants to decrease pollutant concentrations or fluxes or channel dredging at the reaches with low DO content, etc.

Research on urban spatial structure based on the dual constraints of geographic environment and POI big data

A large number of cities in China have proposed the spatial development strategy of polycentric in their planning, but whether the evolution of polycentric structure meets the planning expectation and whether the polycentric structure and function can be identified through effective ways has become a hot topic of academic research at present. Compared with the traditional survey and identification methods of population, land use and industry, the emergence of urban big data provides an opportunity for polycentric identification, especially the analysis based on POI (Point of Interest) big data is more accurate and efficient than the traditional methods. Chongqing, as a typical representative of mountainous cities, has chosen the development model of polycentric clusters at an early stage and strengthened it in the planning, forming a real polycentric city with both form and function, which makes it typical and representative among polycentric cities in China. Based on the POI data of Chongqing's main urban area, the paper identifies the polycentric structure of the city as a whole and different functions and its influence range based on the spatial distribution characteristics and aggregation degree of the overall and different types of POI data. The results show that Chongqing, as a mountainous city, exhibits an obvious “polycentric and clustered” structure under natural constraints and planning guidance. The study of Chongqing can reveal the differences between the polycentric characteristics of mountain cities and plain cities, summarize the effectiveness and shortcomings of polycentric development, and provide useful reference for urban planning. This paper collects all kinds of geospatial data, network big data and all kinds of historical statistical yearbook data in the main urban area of Chongqing. The experimental results show that by using the double constraints of POI big data and geographical environment, Chongqing is in urban polycentric structure, different functional types of urban centers, and employment function space and leisure and recreation function space have many advantages.

How can the landscape ecological security pattern be quantitatively optimized and effectively evaluated? An integrated analysis with the granularity inverse method and landscape indicators.

The optimization of the landscape ecological security pattern aims to construct a suitable ecological environment and promote the harmonious development between humans and nature. The optimization model of the ecological security pattern for the main urban area of Chongqing was constructed with the granularity inverse method, minimum cumulative resistance model, and spatial network analysis method. We used ecological nodes to optimize the landscape ecological security pattern by organically combining the landscape quantity and spatial structure, and analyzed the effectiveness of the optimized pattern. The results were as follows: (1) The optimal granularity for selecting the ecological source in the study area was 500 m. There were 220 ecological sources with a total area of 188691.03 hm2 and a minimum area of 75.15 hm2. (2) The ecological buffer zone, protection and utilization zone, key development zone, coordinated control zone, and restricted development zone accounted for 57.78%, 20.87%, 12.36%, 6.48%, and 2.50%, respectively, of the total area. (3) The construction of the landscape ecological security pattern contained 70 ecological corridors with a total length of 415.89 km. The longest and shortest ecological corridors had lengths of 20.33 km and 1153.23 m, respectively. There were 17 ecological nodes of corridor-resistance and 27 ecological nodes of corridor-corridor. (4) 41 ecological node service areas were constructed, with a total area of approximately 236.0723 hm2, accounting for 0.04% of the total study area, and the largest and smallest ecological node areas were 6.0744 hm2 and 0.0057 hm2, respectively. (5) The optimized result of the landscape ecological security pattern converted 209.1384 hm2 of nonecological land into ecological land.

Variation of spatio-temporal distribution of on-road vehicle emissions based on real-time RFID data

High-resolution vehicular emissions inventories are important for managing vehicular pollution and improving urban air quality. This study developed a vehicular emission inventory with high spatio-temporal resolution in the main urban area of Chongqing, based on real-time traffic data from 820 RFID detectors covering 454 roads, and the differences in spatio-temporal emission characteristics between inner and outer districts were analysed. The result showed that the daily vehicular emission intensities of CO, hydrocarbons, PM2.5, PM10, and NOx were 30.24, 3.83, 0.18, 0.20, and 8.65 kg/km per day, respectively, in the study area during 2018. The pollutants emission intensities in inner district were higher than those in outer district. Light passenger cars (LPCs) were the main contributors of all-day CO emissions in the inner and outer districts, from which the contributors of NOx emissions were different. Diesel and natural gas buses were major contributors of daytime NOx emissions in inner districts, accounting for 40.40%, but buses and heavy duty trucks (HDTs) were major contributors in outer districts. At nighttime, due to the lifting of truck restrictions and suspension of buses, HDTs become the main NOx contributor in both inner and outer districts, and its three NOx emission peak hours were found, which are different to the peak hours of total NOx emission by all vehicles. Unlike most other cities, bridges and connecting channels are always emission hotspots due to long-time traffic congestion. This knowledge will help fully understand vehicular emissions characteristics and is useful for policymakers to design precise prevention and control measures.

Research on the Application of Deep Learning Technology Oriented to the Construction and Innovation of Smart City Image Cognition

City image is the observer’s subjective impression of the city image. It is an important content of urban geography and planning research and has important guiding significance for shaping a unique urban space. Cognitive research on traditional urban imagery is mainly by means of questionnaires and image sketches. It has problems such as high cost, low update frequency, and limited data coverage, which cannot meet the needs of quantitative research on smart cities and urban economic development in the information age. With the advent of the era of big data and the development of Internet technology, there are more and more quantitative research results on smart city image cognition with the help of big data and deep learning technology. It will be a feasible way to apply it to urban image research. This article combines the development and transformation of smart cities with the transformation of urban planning and leads to an innovation in the construction of urban image cognition based on urban image, active representation data as the data source, and deep learning as the core technology. The theoretical connotation and cognitive dimension of urban imagery are expanded to establish a cognitive model of urban imagery. The city image is cognitively analyzed from three dimensions: image structure, image type, and image evaluation. Specific cities are taken as examples to verify the applicability and scientificity of the cognitive methods and models, so as to enhance the practicality and applicability of urban imagery in urban planning. At the same time, this research is used to answer the development dilemma of big data, summarize the development trend of big data, and explore the new changes that artificial intelligence brings to urban planning. The experimental results show that the model we designed efficiently evaluates the image of the city and can also effectively recognize the image of the city in the main urban area of Chongqing.