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Economic development and fast growing urbanization in China have caused severe air pollution, with frequent pollution episodes endangering the health of inhabitants and disturbing social activities, and as an expanding metropolis, Chengdu has suffered ever since. The concentration variations of main air pollutants, such as PM10, PM2.5 and NO2, often show periodicity because of meteorological impact and anthropic activities, and display orientation discrepancies due to influences of wind speed (WS), frequency and pollutant sources. These features have complicated the mechanisms of pollution episodes and deepened the difficulty in pollution control evaluation. The WS has significant influences on the periodicity and orientation variations in pollutant concentrations, and quantifying the influence of which is of high significance and provides sustainable foundations for pollution alleviation strategies. Different time-scale cycles (i.e., Diurnal, weekly, seasonal and annual), along with the WS, wind frequency, wind and spatial orientations in urban areas, were analyzed in this paper. Results show that the periodicity of diurnal, seasonal and annual cycles is remarkable, and weekly cycle is obvious by adding the influence of the WS in 16 orientations. The WS has direct impacts on pollutants varying in the range of 1.5–2.5 m/s, and has a remarkable diffusion effect on pollutants once above 2.5 m/s. Over heavy pollution hours in diurnal, weekly, annual cycles and transitional seasons, the WS had more significant influences on pollutants, and whereas the wind frequency is not the main impact factor for orientation variations. For Chengdu, the northeast orientation is suitable to construct a wind panel with a remarkable diffusion effect on pollutants, while air pollutions in the northwest and southwest orientations were severe with the WS below 1.5 m/s, and pollution diffusion in the north-northwest orientation was the worst. This work can provide guidance and reference for urban planning optimization and air environment protection in cities with air quality control considerations impacted by city wind. [ABSTRACT FROM AUTHOR]

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As low and lower-middle social groups account for a great proportion of the total population in China and their status in society is special, it is of great social and practical significance to study their housing conditions and characteristics. Based on research at home and abroad, this paper defines the basic characteristics of low and lower-middle social groups in China, and elaborates the definition and connotation of housing marginalization, thereby proposing that these residents in the Chinese city are facing a problem of housing marginalization. According to data from the fifth and sixth population census and statistical yearbooks of Chengdu, it reveals changes in housing location, housing tenure structure, and housing quality of the study group between 2000 to 2010 by means of spatial and statistical analysis, which indicates that the low and lower-middle social groups are facing the three trends of "living in outskirts," "predicament in tenure selectivity of housing," and "impoverishment of housing quality." In response to these trends, three planning suggestions are proposed: 1 to establish "housing policy areas" suitable for the group of residents to reside and work; 2 to innovate policy measures to support the low and lower-middle social groups to rent and purchase houses within these areas; 3 to guide the residents to integrate into the community life circle in these areas so as to avoid poverty concentration. [ABSTRACT FROM AUTHOR]

In this paper, the LSTM model is used to predict the PM2.5 concentrations in five representative Chinese cities with the GDP exceeding 1 trillion Yuan, including Beijing, Chengdu, Shanghai, Shenzhen and Wuhan. The PM2.5 concentration data in 2015-2017 are selected for training, and the results are optimized to achieve an efficient solution by adjusting the parameters. Based on the optimized solution, a test is carried out to predict the PM2.5 concentration in 2018, and the results are compared with the real value obtained from the monitoring centre. According to the comparison results, the correlation coefficient of Wuhan and Chengdu is 0.86724 and 0.80070, which are the highest in these five cities. While the correlation coefficient of Shenzhen and Shanghai, are 0.78225, 0.72147, Beijing, as the capital city of China achieved the lowest correlation coefficient which is 0.64118. The LSTM-based predictive model has relatively good reliability and transferability. More effective predictive results can be achieved by implementing deep learning to analyse PM2.5 concentration. [ABSTRACT FROM AUTHOR]

Copyright of Transactions of the Chinese Society of Agricultural Engineering is the property of Chinese Society of Agricultural Engineering and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The concept of neoliberalisation is increasingly applied to China to explain its unprecedented urban transformation. This paper argues against fitting China into a prototype neoliberal model. Instead it proposes a fresh interpretation of its urban planning particularities within a continuity-contestation framework, embodied in the context, governance and practice of planning. Chengdu, the gateway in West China, is chosen as a case study to illustrate this framework. Analysing the successive city Master Plans of Chengdu, it was found that there was a strong path dependency in Chengdu's plan-making process. Yet contestations from the planning context and planning practice pressured for planning transformation. Interestingly, inconsistencies within its Master Plans sometimes worked in line with the market and mediated the conflicts between plan-led and market-led development logics. [ABSTRACT FROM AUTHOR]

Street quality plays a crucial role in promoting urban development. There is still no consensus on how to quantify human street quality perception on a large scale or explore the relationship between street quality and street composition elements. This study investigates a new approach for evaluating and comparing street quality perception and accessibility in Shanghai and Chengdu, two megacities with distinct geographic characteristics, using street-view images, deep learning, and space syntax. The result indicates significant differences in street quality perception between Shanghai and Chengdu. In Chengdu, there is a curvilinear distribution of the highest positive perceptions along the riverfront space and a radioactive spatial distribution of the highest negative perceptions along the ring road and main roads. Shanghai displays a fragmented cross-aggregation and polycentric distribution of the streets with the highest positive and negative perceptions. Thus, it is reasonable to hypothesize that street quality perception closely correlates with the urban planning and construction process of streets. Moreover, we used multiple linear regression to explain the relationship between street quality perception and street elements. The results show that buildings in Shanghai and trees, pavement, and grass in Chengdu were positively associated with positive perceptions. Walls in both Shanghai and Chengdu show a consistent positive correlation with negative perceptions and a consistent negative correlation with other positive perceptions, and are most likely to contribute to the perception of low street quality. Ceilings were positively associated with negative perceptions in Shanghai but are not the major street elements in Chengdu, while the grass is the opposite of the above results. Our research can provide a cost-effective and rapid solution for large-scale, highly detailed urban street quality perception assessments to inform human-scale urban planning. [ABSTRACT FROM AUTHOR]

The study of urban functional zoning is not only important for analyzing urban spatial structure but also for optimizing urban management and promoting scientific urban planning. Different areas undertaking different urban functions correspond to different traffic patterns and specific cycles. Here, a method named Urban Functional Zoning based on the Spatial Specificity (UFZ-SS) is proposed. The core of this method is to obtain urban spatial zoning through the specific cycles of traffic flows. First, UFZ-SS uses the Ensemble Empirical Modal Decomposition (EEMD) method to extract the specific periodic signal characteristics of traffic flows. Second, UFZ-SS calculates the contribution of online car-hailing traffic of different cycles in each zone. Then, the Gaussian Mixture Model (GMM) is utilized to classify all spatial zones into different spatial partitions based on the contribution of each periodic signal. Finally, this study validates UFZ-SS with the online car-hailing traffic volume in northeast Chengdu, China. The results show that the periodic characteristics of traffic can be effectively extracted and analyzed by the EEMD method, and highly distinct and accurate urban spatial partitioning results can be derived by spatial clustering based on the measures of specific cycles. Moreover, with the assistance of Point of Interest (POI) data, we verify the functional zones and structural patterns, which further demonstrates the validity and rationality of urban functional zones identified by UFZ-SS. This study provides a new potential perspective for the identification of urban functional zones, which may lead to a better understanding of the urban spatial structure and even urban planning. [ABSTRACT FROM AUTHOR]

The subway stations of urban community type are not only main nodes in the urban traffic network, but also important places for people's daily life. With the rapid development of urban metro and urban economy, the commercial space near the subway station has become the focus of urban planning and urban spatial development, and commercial self-organization plays an important role in the development of commercial operations, commercial structures, and commercial scales, so how to make effective use of the inherent laws of the commercial space evolution, and further guide the rational development of community businesses needs more attention and research. This paper takes Chengdu Wannianchang Subway Station as an example to study the evolution stage, influencing factors, evolution characteristics and laws of the nearby commercial space. Moreover, suggestions were put forward such as coordinating competition and collaboration, optimizing space design and management, co-directional self-organization and heter-organizations, in order to provide a new reference for the healthy and orderly development of the neighboring commercial space near the subway stations of community type. [ABSTRACT FROM AUTHOR]

Cities are currently confronted with many urban problems, such as water shortages, water quality pollution, floods, and the loss of habitats of aquatic organisms, and badly in need of a more comprehensive solution. In this context, the concept of "sponge city" is proposed. This paper, based on the theory of sponge city and low impact development, elaborated the origin, development, connotation, and construction method of "sponge city" concept. In this paper, the urban design scheme of Renbei District in Chengdu was taken for example to analyze the geographical environment and climate characteristics of Chengdu and explain the formation and verification of the scheme. It is considered that the "sponge city" is different from the traditional urban infrastructure. It is essentially an ecological approach. It's core is to build a cross-scale urban water ecological infrastructure to comprehensively solve the prominent water-related problems of urban and rural areas in China. [ABSTRACT FROM AUTHOR]

Understanding urban human mobility, particularly trip purposes, is essential for optimizing traffic management, personalized recommendations, and urban planning. However, in real-world scenarios, trip purposes cannot be directly extracted from the trajectory data. To address this issue, we propose a geometry-driven neural topic model for trip purpose inference. We integrate trajectory data with nearby POI data using a geometry-driven technique to enhance the interpretability of the results. Furthermore, our model captures the semantics and relationships of the data in a high-dimensional space and identifies latent topics representing distinct trip purposes. These learned topics are analyzed using clustering algorithms to group similar trips, enabling trip purpose inference. And we evaluate our model using the trajectory data of Shenzhen and Chengdu, and compare it with baseline models. The results demonstrate that our model performs well. Furthermore, we analyze trajectory data containing trip purpose information to gain insight into human mobility patterns and the influence of trip purposes, paving the way for potential implications and future research directions. [ABSTRACT FROM AUTHOR]

Urban areas with an imbalanced vulnerability to disasters have garnered attention. Building an urban resilience index helps to develop a progressively favored instrument for tracking progress toward disaster-resilient cities. However, there remains a lack of empirical studies on measuring urban resilience, with limited focus on the spatial-temporal characteristics of urban resilience to disasters, particularly relevant in developing nations like China. Thus, a refined urban resilience index to disasters based on the subcomponents of infrastructure, environment, socio-economy, and institution is suggested in this study. This index-based assessment framework is applied and validated to measure the spatial-temporal resilience using a real-world case study in Chengdu, China. The main findings of this study indicate that: (1) the overall urban resilience of Chengdu has been growing toward better conditions, with infrastructural resilience accounting for the majority of this growth. (2) The distribution of urban resilience exhibits a regional disparity and a spatially polarized pattern. (3) The agglomeration characteristics of urban resilience are significant. (4) There is a clear regional mismatch in the distribution of urban resilience to disaster risk. The validated model offers a comprehensive and replicable approach for urban resilience assessment and planning, especially for disaster-frequent regions. [ABSTRACT FROM AUTHOR]

PM2.5 particles with an aerodynamic diameter of less than 2.5 μm are receiving increasing attention in China. Understanding how complex factors affect PM2.5 particles is crucial for the prevention of air pollution. This study investigated the influence of meteorological factors and land use on the dynamics of PM2.5 concentrations in four urban agglomerations of China at different scales from 2010 to 2020, using the Durbin spatial domain model (SDM) at five different grid scales. The results showed that the average annual PM2.5 concentration in four core urban agglomerations in China generally had a downward trend, and the meteorological factors and land use types were closely related to the PM2.5 concentration. The impact of temperature on PM2.5 changed significantly with an increase in grid scale, while other factors did not lead to obvious changes. The direct and spillover effects of different factors on PM2.5 in inland and coastal urban agglomerations were not entirely consistent. The influence of wind speed on coastal urban clusters (the Pearl River urban agglomeration (PRD) and Yangtze River urban agglomeration (YRD)) was not significant among the meteorological factors, but it had a significant impact on inland urban clusters (the Beijing–Tianjin–Hebei urban agglomeration (BTH) and Chengdu–Chongqing urban agglomeration (CC)). The direct effect of land use type factors showed an obvious U-shaped change with an increase in the research scale in the YRD, and the direct effect of land use type factors was almost twice as large as the spillover effect. Among land use type factors, human factors (impermeable surfaces) were found to have a greater impact in inland urban agglomerations, while natural factors (forests) had a greater impact in coastal urban agglomerations. Therefore, targeted policies to alleviate PM2.5 should be formulated in inland and coastal urban agglomerations, combined with local climate measures such as artificial precipitation, and urban land planning should be carried out under the consideration of known impacts. [ABSTRACT FROM AUTHOR]

The design and optimization of urban form has always been a hot topic in urban planning and development research. Besides, the creation of continuous vitality in urban areas is of critical importance in the development of urbanization. However, due to the lack of data, it is difficult to measure the effects of urban form on neighborhood vibrancy. Additionally, no uniform conclusion has been drawn regarding to what degree urban form can contribute to neighborhood vibrancy. Taking advantage of emerging new data sources, the depth and breadth of related research can now be improved. Therefore, this paper uses high-precision positioning social media check-in data to approximate the vibrancy of 658 neighborhoods, and uses a geographical information system (GIS) to quantitatively measure the urban form indicators in the central area of Chengdu City, China. A quantitative exploration and analysis of the relationships between neighborhood vibrancy and urban form is conducted. The results of three regression models considering different explanatory variables show that socio-economic factors account for approximately 23% of neighborhood vibrancy. In addition, the correlation between the shape characteristics of a neighborhood and the vibrancy is weak. However, when the inner urban form indicators of neighborhoods are introduced into the regression model, the goodness of fit (R2) is nearly doubled. This finding indicates that strong associations exist between urban form and neighborhood vibrancy. Specifically, building density and functional diversity are positively correlated with neighborhood vibrancy. Unlike existing studies, this study finds that the road network within the neighborhood plays a positive role in the creation of neighborhood vibrancy. However, the impact of a road density indicator is not as powerful as the impacts of building density and functional diversity. This research can help urban designers to better design urban environments. [ABSTRACT FROM AUTHOR]

Accessibility-oriented development (AOD) strategies are the extension of transit-oriented development (TOD) strategies but focus more on access to destinations. Adopting AOD strategies can help identify and improve the defects of imperfect TOD construction. Based on AOD strategies, this paper evaluated the comprehensive accessibility to multiple public facilities with the Gaussian-based two-step floating catchment area method (G2SFCA) in the heart area of Chengdu City and further analyzed its equity issues. The comprehensive accessibility analysis proved the efficiency of AOD-based analysis in public resources shortage area determination and TOD level evaluation. The equity analysis indicated that the improvement of equity could not reflect the progress on total accessibility but only rationalize the allocation structure of public resources. Based on the case study, several suggestions for policy-making are given, including the construction of the non-motorized transportation system, adjustment of supply allocation, and comprehensive consideration of equity and accessibility in urban planning. [ABSTRACT FROM AUTHOR]

Public transportation infrastructure is a typical, complex, coupled network that is usually composed of connected bus lines and subway networks. This study proposes an entropy-based node importance identification method for this type of coupled network that is helpful for the integrated planning of urban public transport and traffic flows, as well as enhancing network information dissemination and maintaining network resilience. The proposed method develops a systematic entropy-based metric based on five centrality metrics, namely the degree centrality (DC), betweenness centrality (BC), closeness centrality (CC), eigenvector centrality (EC), and clustering coefficient (CCO). It then identifies the most important nodes in the coupled networks by considering the information entropy of the nodes and their neighboring ones. To evaluate the performance of the proposed method, a bus–subway coupled network in Chengdu, containing 10,652 nodes and 15,476 edges, is employed as a case study. Four network resilience assessment metrics, namely the maximum connectivity coefficient (MCC), network efficiency (NE), susceptibility (S), and natural connectivity (NC), were used to conduct group experiments. The experimental results demonstrate the following: (1) the multi-functional fitting analysis improves the analytical accuracy by 30% as compared to fitting with power law functions only; (2) for both CC and CCO, the improved metric's performance in important node identification is greatly improved, and it demonstrates good network resilience. [ABSTRACT FROM AUTHOR]

Overall scientific planning of urbanization layout is an important component of the new period of land spatial planning policies. Defining the main functions of different spaces and dividing urban functional areas are of great significance for optimizing the land development pattern. This article identifies and analyses urban functional areas from the perspective of data mining. The results of this method are consistent with the actual situation. In this paper, representative taxi trajectory data are selected as the research basis of urban functional areas. First, based on trajectory data from Didi Chuxing within the high-speed road surrounding Chengdu, we generated trajectory time sequence data and used the dynamic time warping (DTW) algorithm to generate a time series similarity matrix. Second, we utilized the K-medoid clustering algorithm to generate preliminary results of land clustering and selected the results with high classification accuracy as the training samples. Then, the k-nearest neighbour (KNN) classification algorithm based on DTW was performed to classify and identify the urban functional areas. Finally, with the help of point-of-interest (POI) auxiliary analysis, the final functional layout in Chengdu was obtained. The results show that the spatial structure of Chengdu is complex and that the urban functions are interlaced, but there are still rules that are followed. Moreover, traffic volume and inflow data can better reflect the travel rules of residents than simple taxi on–off data. The original DTW calculation method has high temporal complexity, which can be improved by normalization and the reduction of time series dimensionality. The semi-supervised learning classification method is also applicable to trajectory data, and it is best to select training samples from unsupervised learning. This method can provide a theoretical basis for urban land planning and has auxiliary and guiding value for urbanization layout in the context of land spatial planning policies in the new era. [ABSTRACT FROM AUTHOR]

Surface urban heat islands (SUHIs) are mostly an urban ecological issue. There is a growing demand for the quantification of the SUHI effect, and for its optimization to mitigate the increasing possible hazards caused by SUHI. Satellite-derived land surface temperature (LST) is an important indicator for quantifying SUHIs with frequent coverage. Current LST data with high spatiotemporal resolution is still lacking due to no single satellite sensor that can resolve the trade-off between spatial and temporal resolutions and this greatly limits its applications. To address this issue, we propose a multiscale geographically weighted regression (MGWR) coupling the comprehensive, flexible, spatiotemporal data fusion (CFSDAF) method to generate a high-spatiotemporal-resolution LST dataset. We then analyzed the SUHI intensity (SUHII) in Chengdu City, a typical cloudy and rainy city in China, from 2002 to 2022. Finally, we selected thirteen potential driving factors of SUHIs and analyzed the relation between these thirteen influential drivers and SUHIIs. Results show that: (1) an MGWR outperforms classic methods for downscaling LST, namely geographically weighted regression (GWR) and thermal image sharpening (TsHARP); (2) compared to classic spatiotemporal fusion methods, our method produces more accurate predicted LST images (R2, RMSE, AAD values were in the range of 0.8103 to 0.9476, 1.0601 to 1.4974, 0.8455 to 1.3380); (3) the average summer daytime SUHII increased form 2.08 °C (suburban area as 50% of the urban area) and 2.32 °C (suburban area as 100% of the urban area) in 2002 to 4.93 °C and 5.07 °C, respectively, in 2022 over Chengdu City; and (4) the anthropogenic activity drivers have a higher relative influence on SUHII than other drivers. Therefore, anthropogenic activity driving factors should be considered with CO2 emissions and land use changes for urban planning to mitigate the SUHI effect. [ABSTRACT FROM AUTHOR]

Five national urban agglomerations are selected according to the Fourteenth Five-Year Plan, namely the Yangtze River Delta, the Pearl River Delta, Beijing-Tianjin-Hebei, the Middle reaches of the Yangtze River, and Chengdu-Chongqing. The study on synergistic effects of such national strategic planning urban agglomerations, defined as coordinated degrees, and their time-series trends from 2016 to 2021 is significant for the practice of the national "double carbon" goal. Spatial differentiation of coordinated degree in five agglomerations is analyzed based on the Theil Index, along with regional linkage strength of coordinated degree under the gravity model. Conclusions include: (1) a downward trend is shown from 2016 to 2021 for the coordinated degree, along with the Pearl River Delta is the best among the five agglomerations; (2) the Middle reaches of the Yangtze River is the highest, followed by the Pearl River Delta and the Yangtze River Delta of coordinated degree in 2021; (3) the main cause of downwards in coordinated degree combined by a stable decline in carbon emissions and fluctuating increase in pollutants; (4) intra-regional differences in the Yangtze River Delta and the Middle reaches of the Yangtze River are relatively large, compared with the smallest in the Pearl River Delta measured by Theil Index; (5) coefficients of variation are relatively higher in the Middle reaches of the Yangtze River and the Yangtze River Delta, followed by the Beijing-Tianjin-Hebei, the Pearl River Delta and Sichuan-Chongqing urban. Consequently, countermeasures are proposed from the perspective of government, including technology and regional cooperation, policy innovation by overall coordination, synergy promotion by technological innovation, and regional synergy by win-win cooperation. [ABSTRACT FROM AUTHOR]

The majority of studies on Chinese urbanization have been focused on coastal areas, with little attention given to urban centers in the west. Western provinces, however, will unquestionably undergo significant urban change in the future as a result of the 'Go West' policy initiated in the 1990s. In this paper the authors examine the relationship between drivers of urban growth and land- use outcomes in Chengdu, capital of the western province of Sichuan, China. In the first part of this research, remotely sensed data are used to map changes in land cover in the greater Chengdu area and to investigate the spatial distribution of development with use of landscape metrics along seven urban-to-rural transects identified as key corridors of growth. Results indicate that the urbanized area increased by more than 350% between 1978 and 2002 in three distinct spatial trends: (a) near the urban fringe in all directions prior to 1990, (b) along transportation corridors, ring roads, and near satellite cities after 1990, and, finally, (c) infilling in southern and western areas (connecting satellite cities to the urban core) in the late 1990s. In the second part of this paper the authors connect patterns of growth with economic, land, and housing market reforms, which are explored in the context of urban planning initiatives. The results reveal that, physically, Chengdu is following trends witnessed in coastal cities of China, although the importance of various land-use drivers differs from that in the east (for example, in the low level of foreign direct investment to date). The information provided by the land-use analysis ultimately helped tailor policies and plans for better land management and reduced fragmentation of new development in the municipality. [ABSTRACT FROM AUTHOR]

Introduction: Nature-based solutions (NBS) have been used to address a wide range of urban environmental challenges, an important aspect of which is to improve human health and well-being. However, most relevant studies focus either on what positive influences nature may have or on identifying what natural factors can have these benefits. Few have investigated the sensory composition of nature and the effects of nature in different sensory aspects on human health. Setting out from the multi-sensory perspective, this study aims to explore human behavior and emotional response from visual and aural contact with urban nature. Methods: Taking Jiangjia Art Garden in Chengdu as an example, natural attributes such as its visual (landscape) and aural (sound source) characteristics as well as people’s activities (behavioral responses) were measured by on-site mapping analysis. This was done while a questionnaire-based survey was conducted to investigate people’s emotional responses regarding their overall satisfaction, pleasantness, calm, and agreeableness. Results: The results indicated that nature-dominated visual landscapes such as grassland, waterscapes, and woodlands, as well as natural sounds such as bird sounds, chirp sounds, and wind sounds were found to be positively correlated to the vitality of activities and people’s emotional status. Regarding behavioral responses, it was shown that grasslands and woodlands are more likely to be attractive places for recreation, and the vitality measured became extremely high when these two were paired with lakes. As for the emotional responses, people’s perceived overall satisfaction, calm, and agreeableness were equally reflected in their behavioral patterns, suggesting a strong relationship with natural factors. Discussion: The research findings were visually presented in behavior and emotional maps to provide direct cues of informing the future design of highquality urban green spaces and promoting the application of aural-visual experience in the design of urban nature areas. [ABSTRACT FROM AUTHOR]

Quantitative research on the impact weight and impact of regional heterogeneity of urban spatial structure elements on carbon emissions efficiency can provide a scientific basis and practical guidance for low-carbon and sustainable urban development. This study uses the megacity of Chengdu as an example to measure and analyze the spatial carbon emission efficiency and multidimensional spatial structure elements by building a high-resolution grid and identifying the main spatial structure elements that affect urban carbon emissions and their impact weights via the Ordinary Least Squares regression (OLS) and Geographically Weighted Regression (GWR). The spatial heterogeneity of the impact of each element is also explored. The results show that the overall carbon emission efficiency of Chengdu is high in the center and low on the sides, which is related to urban density, functional mix, land use, and traffic structure. However, the influence of each spatial structure element is different in the developed central areas, developing areas of the plain, mountainous developing areas, underdeveloped areas of the plain, and mountainous underdeveloped areas. Thus, it is appropriate to form differentiated urban planning strategies based on the characteristics of the development of each zone. The findings provide inspiration and a scientific basis for formulating policies and practice to the future low-carbon development of Chengdu, while provide a reference for other growing megacities. [ABSTRACT FROM AUTHOR]

Rapid urbanization has brought along with it many environmental and social problems such as ecosystem damage and traffic congestion. Therefore, forecasting the trend of urban expansion and providing a reasonable urban planning basis for government departments have become the focus of researchers. An artificial neural network (ANN) can be used to consider spatial nonstationarity when obtaining the changing characteristics of urban land types. Therefore, in this study, we use cellular automata (CA) based on ANN (ANN-CA) to simulate and forecast urban expansion and discuss the parameter sensitivity of the model in detail. In addition, we propose a new Urban Expansion Early Warning Indicator system to warn about the deterioration of future land distribution patterns. Chengdu is selected as the study area, and the study period is from 2000 to 2020. The results showed the following: (1) The best accuracy was achieved when the neighborhood size is 7 × 7 and the number of model iterations is 250, and overall accuracy (OA), Kappa coefficient, and figure of merit (FOM) are 91.47%, 0.855, and 0.354, respectively; (2) ANN-CA is more suitable for predicting the urban expansion of Chengdu than CA based on logistic regression (LR-CA) and CA based on decision tree (DT-CA). Compared with the worst performance model, the score of OA increased by 6.23%, that of kappa increased by 0.062, and that of FOM increased by 0.056. (3) According to the current development trend, artificial built-up areas will increase substantially. The comprehensive evaluation results of the morphology effect, ecological effect, and intensity effect of urban expansion predict severe early warning for Jinniu District, Qingyang District, and Wuhou District by 2030. [ABSTRACT FROM AUTHOR]

Transport data are important for understanding human mobility and urban interactions within a city. As China's transportation infrastructure continues to grow, more research is needed to analyse the spatial patterns of travel flows and to understand how these patterns change over time. With the development of online car-hailing and ride sharing services, floating car data have become a new resource to facilitate the analysis of human mobility patterns and the interactions of urban mobility within a city. The detection of urban communities based on urban networks is a helpful way to represent urban interactions. However, understanding community changes using online car-hailing data remains an underexplored topic. To this end, this study applies a community detection method to explore community changes over time based on the newly available floating car data (DiDi Chuxing ('DiDi')) in Chengdu, China. We applied undirected graphs to examine the spatial distribution of DiDi usage and the spatial patterns of travel distance. In addition, we explored the spatial-temporal variations of the communities at the taxi zone level using Blondel's iterative algorithm, a modularity optimization approach. Results suggest that: 1) taxi zones on the south and west sides of Chengdu have more average daily trips compared to those in other areas; 2) residential taxi zones in the northeast area have a long median travel distance, indicating people living in those areas travel longer distances; and 3) the detected community structures change at different times. These findings provide valuable information for urban planning and location-based services in Chengdu. [ABSTRACT FROM AUTHOR]

This paper, based on the literature review and field investigation, studied the status quo of maker spaces in main urban district of Chengdu at a time when the development of the maker spaces has received strong support from national and local governments. In addition to introducing the related concepts and policy support of the maker space, it summarized its distribution characteristics, audience characteristics and status quo as well as problems and presented the direction for the development of the maker space in main urban area of Chengdu grounded on a survey of the status quo of national maker spaces in main urban area of Chengdu. [ABSTRACT FROM AUTHOR]

This paper introduced basic situation and challenges of Block 9, Dongdajie, Chengdu City, expounded basic definition and design concept of "place making", briefed the design scheme from three aspects, namely planning layout, space environment and architectural style, and concluded the application of the idea of "place making" in Block 9 design scheme in view of the multi-functional urban complex with high plot ratio. [ABSTRACT FROM AUTHOR]

The expansion of urban areas and the increase in the number of buildings and urbanization characteristics, such as roads, affect the meteorological environment in urban areas, resulting in weakened pollutant dispersion. First, this paper uses GIS (geographic information system) spatial analysis technology and landscape ecology analysis methods to analyze the dynamic changes in land cover and landscape patterns in Chengdu as a result of urban development. Second, the most appropriate WRF (Weather Research and Forecasting) model parameterization scheme is selected and screened. Land-use data from different development stages in the city are included in the model, and the wind speed and temperature results simulated using new and old land-use data (1980 and 2015) are evaluated and compared. Finally, the results of the numerical simulations by the WRF-Chem air quality model using new and old land-use data are coupled with 0.25° × 0.25°-resolution MEIC (Multi-resolution Emission Inventory for China) emission source data from Tsinghua University. The results of the sensitivity experiments using the WRF-Chem model for the city under different development conditions and during different periods are discussed. The meteorological conditions and pollution sources remained unchanged as the land-use data changed, which revealed the impact of urban land-use changes on the simulation results of PM2.5 atmospheric pollutants. The results show the following. (1) From 1980 to 2015, the land-use changes in Chengdu were obvious, and cultivated land exhibited the greatest changes, followed by forestland. Under the influence of urban land-use dynamics and human activities, both the richness and evenness of the landscape in Chengdu increased. (2) The microphysical scheme WSM3 (WRF Single–Moment 3 class) and land-surface scheme SLAB (5-layer diffusion scheme) were the most suitable for simulating temperatures and wind speeds in the WRF model. The wind speed and temperature simulation results using the 2015 land-use data were better than those using the 1980 land-use data when assessed according to the coincidence index and correlation coefficient. (3) The WRF-Chem simulation results obtained for PM2.5 using the 2015 land-use data were better than those obtained using the 1980 land-use data in terms of the correlation coefficient and standard deviation. The concentration of PM2.5 in urban areas was higher than that in the suburbs, and the concentration of PM2.5 was lower on Longquan Mountain in Chengdu than in the surrounding areas. [ABSTRACT FROM AUTHOR]

Recent advances in the fusion technology of remotely sensed data have led to an increased availability of extracted urban information from multiple spatial resolutions and multi-temporal acquisitions. Despite the existing extraction methods, there remains the challenging task of fully exploiting the characteristics of multisource remote sensing data, each of which has its own advantages. In this paper, a new fusion approach for accurately extracting urban built-up areas based on the use of multisource remotely sensed data, i.e., the DMSP-OLS nighttime light data, the MODIS land cover product (MCD12Q1) and Landsat 7 ETM+ images, was proposed. The proposed method mainly consists of two components: (1) the multi-level data fusion, including the initial sample selection, unified pixel resolution and feature weighted calculation at the feature level, as well as pixel attribution determination at decision level; and (2) the optimized sample selection with multi-factor constraints, which indicates that an iterative optimization with the normalized difference vegetation index (NDVI), the modified normalized difference water index (MNDWI), and the bare soil index (BSI), along with the sample training of the support vector machine (SVM) and the extraction of urban built-up areas, produces results with high credibility. Nine Chinese provincial capitals along the Silk Road Economic Belt, such as Chengdu, Chongqing, Kunming, Xining, and Nanning, were selected to test the proposed method with data from 2001 to 2010. Compared with the results obtained by the traditional threshold dichotomy and the improved neighborhood focal statistics (NFS) method, the following could be concluded. (1) The proposed approach achieved high accuracy and eliminated natural elements to a great extent while obtaining extraction results very consistent to those of the more precise improved NFS approach at a fine scale. The average overall accuracy (OA) and average Kappa values of the extracted urban built-up areas were 95% and 0.83, respectively. (2) The proposed method not only identified the characteristics of the urban built-up area from the nighttime light data and other daylight images at the feature level but also optimized the samples of the urban built-up area category at the decision level, making it possible to provide valuable information for urban planning, construction, and management with high accuracy. [ABSTRACT FROM AUTHOR]

The construction of urban rail transit (URT) guides and promotes urban development. Different URT line construction schedule, including construction sequence (priority order of line construction) and construction timing (when to build), will have different effects on urban traffic and development. Therefore, the planning of construction schedule is an important part of URT network planning. At present, the determination of construction schedule is mainly based on qualitative analysis methods (i.e., experience, comparisons with other cities, and expert opinion) in engineering practice. In this study, based on an analysis of the main factors affecting the construction sequence and the construction timing data of existing URT lines, a quantitative double-level model of a construction schedule is proposed. The model consists of construction sequence and construction timing sub-models. The construction sequence sub-model employs an improved Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) with Rough Set method; the construction timing sub-model takes the results of the construction sequence model and the factors associated with urban development characteristics into account and presents an improved Logistic-β method. The model is verified using the Chengdu rail transit network as the case study. The results of the study show that the double-level calculation model could provide quantitative theoretical support for the construction schedule planning of URT network. [ABSTRACT FROM AUTHOR]

Located in the mountainous area of southwest China, the Chengdu–Chongqing urban agglomeration (CCUA) has been rapidly urbanized in the last 4 decades, which has led to a 3-fold urban area expansion, thereby affecting the weather and climate. To investigate the urbanization effects on the thermal environment in the CCUA under complex terrain, we conducted simulations using the advanced Weather Research and Forecasting (WRF V4.1.5) model together with combined land use scenarios and terrain conditions. We observed that the WRF model reproduces the general synoptic summer weather pattern, particularly for the thermal environment. It was shown that the expansion of the urban area changed the underlying surface's thermal properties, leading to the urban heat island effect, enhanced further by the complex terrain. The simulation with the future scenario shows that the implementation of idealized measures including returning farmland to forests and expanding rivers and lakes can reduce the urban heat island effect and regulate the urban ecosystem. Therefore, urban planning policy has the potential to provide feasible suggestions to best manage the thermal environment of the future city toward improving the livelihood of the people in the environment. [ABSTRACT FROM AUTHOR]

The transport system in the traditional integrated planning theory focuses on road transport, takes vehicle travelers as the main service object, and lacks the research on the integrated planning of public transport system and land use system. Evaluating the joint development effect of P&R (Park and Ride) and TOD (Transit-Oriented Development) is one of the bases of integrated planning of transport system and land use system near metro stations; however, it remains difficult to come up with an evaluation indicator system and calculating methods reflecting the characteristics of transport systems and land use systems. Aiming at the joint development issue of P&R and TOD near metro stations in the urban planning field, 24 indicators are selected and three comprehensive evaluation methods are proposed to judge the joint development level of metro stations from two dimensions: P&R characteristics and TOD characteristics, followed by entropy wright method and expert scoring method being combined to obtain the comprehensive weight values, P&R characteristics being subdivided into P&R facility service level, and metro service level. TOD characteristics consisting of density level, diversity level, and refinement level. Through field investigation, API interface, and APP data acquisition, the characteristic datasets of P&R and TOD near metro stations are obtained in one megacity (Chengdu, China), and then three combined models are tested. Furthermore, four category results of joint development are analyzed and sorted: A-class, B-class, C-class, and D-class near metro stations. Development characteristic and environment features of each category stations are summarized to provide theoretical and practical guidance for the joint development of P&R and TOD near metro stations in other similar megacities. [ABSTRACT FROM AUTHOR]

Enhancing urban development vitality and optimizing the allocation of regional industrial factors require a comprehensive analysis of listed companies, such as the overall distribution network, agglomeration evolution trend, industrialization layout, and driving mechanism. Using 1,624 A-share listed companies in China's Yangtze River Economic Belt as research area, this study integrated trend surface analysis (TSA), exploratory spatial data analysis (ESDA), standard deviation ellipse (SDE), and spatial regression model methods. The main results are as follows: (1) The overall quantity scale of the listed companies in the Yangtze River Economic Belt has achieved significant growth, but the spatial difference of location selection persists. The spatial configuration formed a hierarchical urban distribution pattern with the Yangtze River Delta region as the agglomeration core and the provincial capitals as the fulcrum. (2) Listed companies accelerate the expansion of the Yangtze River Delta region. Chengdu, Wuhan, Changsha, and other central-western provincial capitals gradually increased the region's attractiveness. High-high and low-low agglomerations remain the main forms of agglomeration. (3) There are significant differences in the location selection of listed companies with varying specialization levels, forming a relatively different alienated high-value distribution structure among various industry types. (4) The levels of knowledge spillover, city scale, and policy support level are major factors affecting the location selection process of listed companies in the Yangtze River Economic Belt. For low-level city network with few listed companies, city scale and knowledge spillover levels are significant determinants for the development of headquarters' economy. For high-level city network, along with the level of knowledge spillovers and policy support, globalization level has an important contribution to the shaping of the location advantages of attracting the layout of listed companies. [ABSTRACT FROM AUTHOR]

ABSTRACT More than one hundred million people will settle in the peri-urban areas surrounding the urban areas of city regions in the developing countries of East Asia in the next decade. These areas are the epicenter of world urbanization where the greatest opportunities and most pressing problems coexist. Yet no East Asian city-region has a peri-urban plan. This article describes the nature of East Asian peri-urban areas and the peri-urbanization process occurring there today. It describes typical sites in peri-urban areas requiring remediation and which present potential problems and opportunities in the future. Drawing on the authors' research in Chengdu, China and the Yogyakarta/Kartamantul region of Indonesia, the article describes how innovative decision-making and governance and coordinated regional plans and policies can remediate and prevent problems and capitalize on opportunities in peri-urban areas. [ABSTRACT FROM AUTHOR]

Urban vitality is a key indicator for measuring urban development. This topic has been trending in urban planning and sustainable development, and significant progress has been made in measuring single indicators of urban vitality based on parcel or block units. With the continuous development of smart sensing technology, multisource urban data are becoming increasingly abundant. The application of such data to measure the multidimensional urban vitality of street space, reflecting multiple functions of an urban space, can significantly improve the accuracy of urban vitality analyses and promote the construction of people-oriented healthy cities. In this study, streets were taken as the analysis unit, and multisource data such as the trajectories of taxies and shared bicycles, user reviews and cultural facility points of interest (POIs) in Chengdu, a city in southwestern China, were used to identify spatial patterns of urban vitality on streets across social, economic and cultural dimensions. The correlation between the built environment factors and the multidimensional urban vitality on the street was analyzed using a multiple regression model. The spatial distribution of the different dimensions of urban vitality of the street space in Chengdu varies to a certain extent. It is common for areas with high social vitality to have production and life centers nearby. High economic vitality centers are typically found along busy streets with a high concentration of businesses. Areas with high cultural vitality centers tend to be concentrated on the city's central streets. Land use, transportation, external environment, population and employment are all closely linked to urban vitality on streets. The crowd counting and POI density have the greatest impact on multidimensional urban vitality. The crowd and the level of service facilities profoundly affect social interaction, trade activities and cultural communication. The goodness of fit (R2) of the regression models for social, economic and cultural vitality are 0.590, 0.423 and 0.409, respectively. Using multisource urban data, our findings can help stakeholders better understand the spatial patterns and influencing factors of multidimensional urban vitality on streets and provide sustainable urban planning and development strategies for the future. [ABSTRACT FROM AUTHOR]

Urban land use mapping is critical to understanding human activities in space. The first national mapping result of essential urban land use categories of China (EULUC-China) was released in 2019. However, the overall accuracies in some of the plain cities such as Beijing, Chengdu, and Zhengzhou were lower than 50% because many parcel-based mapping units are large with mixed land uses. To address this shortcoming, we proposed an area of interest (AOI)-based mapping approach, choosing Beijing as our study area. The mapping process includes two major steps. First, grids with different sizes (i.e., 300 m, 200 m, and 100 m) were derived from original land parcels to obtain classification units with a suitable size. Then, features within these grids were extracted from Sentinel-2 spectral data, point of interest (POI), and Tencent Easygo crowdedness data. These features were classified using a random forest (RF) classifier with AOI data, resulting in a 10-category map of EULUC. Second, we superimposed the AOIs layer on classified units to do some rectification and offer more details at the building scale. The overall accuracy of the AOI layer reached 98%, and the overall accuracy of the mapping results reached 77%. This study provides a fast method for accurate geographic sample collection, which substantially reduces the amount of fieldwork for sample collection and improves the classification accuracy compared to previous EULUC mapping. The detailed urban land use map could offer more support for urban planning and environmental policymaking. [ABSTRACT FROM AUTHOR]