Multi-source Data-driven Identification of Urban Functional Areas:A Case of Shenyang,China

Urban functional area(UFA)is a core scientific issue affecting urban sustainability.The current knowledge gap is mainly reflected in the lack of multi-scale quantitative interpretation methods from the perspective of human-land interaction.In this paper,based on multi-source big data include 250 m×250 m resolution cell phone data,1.81×105 Points of Interest(POI)data and administrative boundary data,we built a UFA identification method and demonstrated empirically in Shenyang City,China.We argue that the method we built can effectively identify multi-scale multi-type UFAs based on human activity and further reveal the spatial correlation between urban facilities and human activity.The empirical study suggests that the employment functional zones in Shenyang City are more concentrated in central cities than other single functional zones.There are more mix functional areas in the central city areas,while the planned industrial new cities need to develop comprehensive functions in Shenyang.UFAs have scale effects and human-land interaction patterns.We suggest that city decision makers should apply multi-sources big data to measure urban functional service in a more refined manner from a supply-demand perspective.

Recognizing mixed urban functions from human activities using representation learning methods

When various urban functions are integrated into one location,they form a mixture of functions.The emerging big data promote an alternative way to identify mixed functions.However,current methods are largely unable to extract deep features in these data,resulting in low accuracy.In this study,we focused on recognizing mixed urban functions from the perspective of human activities,which are essential indicators of functional areas in a city.We proposed a framework to comprehensively extract deep features of human activities in big data,including activity dynamics,mobility interactions,and activity semantics,through representation learning methods.Then,integrating these features,we employed fuzzy clustering to identify the mixture of urban functions.We conducted a case study using taxiflow and social media data in Beijing,China,in whichfive urban functions and their correlations with land use were recognized.The mixture degree of urban functions in each location was revealed,which had a negative correlation with taxi trip distance.The results confirmed the advantages of our method in understanding mixed urban functions by employing various representation learning methods to comprehensively depict human activities.This study has important implications for urban planners in understanding urban systems and developing better strategies.

Exploring spatiotemporal patterns of geosocial media data for urban functional zone identification

Urban Functional Zones(UFZs)can be identified by measuring the spatiotemporal patterns of activities that occur within them.Geosocial media data possesses abundant spatial and temporal information for activity mining.Identifying UFZs from geosocial media data aids urban planning,infrastructure,resource allocation,and transportation modernization in the complex urban system.In this work,we proposed an integrated approach by combining the spatiotemporal clustering method with a machine learning classifier.The spatiotemporal clustering method was used to mine the spatiotemporal patterns of activities,of which the distinctive features were extracted as inputs into a machine learning classifier for UFZ identification.The results show that more than 80%of the UFZs can be correctly identified by our proposed method.It reveals that this work serves as a functional groundwork for future studies,facilitating the understanding of urban systems as well as promoting sustainable urban development.

Identifying urban functional zones by capturing multi-spatial distribution patterns of points of interest

Urban Functional Zone(UFZ)identification is vital for urban planning,renewal,and development.Point of Interest(POI),as one of the most popular data in UFZ studies,is transformed into a geo-corpus under specific sampling strategies,which can be used with Natural Language Processing(NLP)technology to extract geo-semantic features and identify UFZs.However,existing studies only capture a single spatial distribution pattern of POIs,while ignoring the other spatial distribution information.In this paper,we developed an integrated geo-corpus construction approach to capture multi-spatial distribution patterns of POIs that were represented by different modal POI embeddings.Subsequently,random forest model was leveraged to classify UFZs based on those embeddings.A set of combination experiments were designed for performance validation.The results show that our proposed method can effectively identify UFZs with an accuracy of 72.9%,with an improvement of 8.5%compared to the baseline methods.The outcome of this study will help urban planners to better understand UFZs through investigating the integrated spatial distribution patterns of POIs embedded in UFZs.

Integrating urban morphology and land surface temperature characteristics for urban functional area classification

The classification of urban functional areas plays an important role in urban planning and resource management.Although previous studies have confirmed that different urban func-tional areas have different morphological structures and Land Surface Temperature(LST)characteristics,these two types of characteristics have rarely been fully integrated and used for functional area classification.In this paper,a new framework for classifying urban functional areas is proposed by combining urban morphological features and LST features.First,metrics are constructed from three levels,namely,building,road and region,which are used to portray urban morphology;LST is retrieved using thermal infrared remote sensing to reflect LST features with four metrics:the average temperature,maximum temperature,temperature difference and standard deviation of temperature.Then,the functional areas are classified into four categories:service/public land,commercial land,residential land and industrial land.A random forest algorithm is used to effectively fuse the features of these two categories and classify the functional areas.The effectiveness of the proposed framework is tested in the study area of Shenzhen City,Guangdong Province.The results show that the combined classification accuracy of the proposed classification method is 0.85,which is 0.26 higher than that of the classification model based on urban morphology and 0.1 higher than that of the classification model based on LST features.The proposed framework verifies that the integration of LST features into urban functional area classification is reliable and effectively combines urban morphology and LST features for functional area classification.

Functional Characteristics of Beijing Subway Stations Based on POI Data:Taking Beijing Metro Line 6 as An Example

Urban subway station is a key node related to urban social,political,economic and cultural activities.There are some differences in the location,function orientation,land use and flow characteristics of different types of stations in the city.This paper mainly used Tyson’s edge,kernel density analysis,chart analysis and other methods to classify the functional types of 412,393 POI data of 26 stations along Metro he results showed that the spatial distribution of Beijing Metro Line 6 was mainly divided into 3 categories,subway stations were divided into 4 categories.Among them,type A sites were divided into composite and single types,and the distribution characteristics of the 6 types of sites were quite different.Based on the qualitative and quantitative analysis of POI point data,this method can quickly classify and analyze the characteristics of stations along Line 6 in Beijing,which also has theoretical and practical value for the planning of urban subway lines.

Functional Characteristics of the Surrounding Area of Beijing Metro Line 5 Based on POI Data

As an important urban infrastructure,rail transit not only has transportation function,but also has a close connection and harmonious development with the surrounding urban space.Taking Beijing Metro Line 5 as an example,each station of Beijing Metro Line 5 was analyzed by GIS software and Echarts chart based on POI data.The functions of subway site type were divided into main function,secondary function and no significant function,and various types of sites within the main functional characteristics of urban functions were discussed in details.The paper presents a new method for identifying urban functional features,which can be applied to not only other metro stations in Beijing but also the same type of cities.Moreover,it lays a foundation for the research of rail transit subway stations and their related researches.

Application of Spatial and Temporal Entropy Based on Multivariate Data for Measuring the Degree of Urban Function Mix

Quantifying the degree of urban function mix has great signifi cance to both urban planning practices and studies. This paper, fi rst of all, based on the data of points of interest(POIs), analyzes the spatial distribution patterns of urban functions in Beijing. Then according to the taxi GPS data with the origin and destination points(taxi-ODs), we identify the spatial and temporal pattern of the degree of urban function mix in Beijing. Finally, based on the information entropy model of the POIs and taxi-ODs, we establish a spatial entropy and a temporal entropy to quantitatively assess the degree of urban function mix, confirming by virtue of correlation analysis and regression analysis that the spatial entropy of POIs is closely associated with the temporal entropy of taxi-ODs, which proves that it is reasonable to assess the degree of urban function mix via these two entropies. As a result, the degree of urban function mix in Beijing is characterized by slowly decreasing from its core area along the 3rd and 4th Ring Roads to its periphery. In detail, there is the highest degree of urban function mix in Beijing's traditional core areas, including Zhongguancun, CBD(Central Business District), the Old Dongcheng District, the Old Xicheng District, and the area within the 2nd Ring Road; a higher degree in Wangjing area; and a low degree in Tiantongyuan and Huilongguan communities. The analytical results have initially achieved a more accurate identifi cation and quantitative evaluation on the degree of urban function mix, and can be taken as a supporting tool to analyze the comprehensiveness of urban functions.

Spatial Identification of Urban Ecological Function on the North Slope of Qinling Mountains Based on Ecological Sensitivity—A Case Study in Baoji, China

Since the 17th National Congress of the Communist Party of China, ecological civilization has been the key construction goal in China, which has a profound impact on the process of urbanization. In recent years, with the rapid development of urbanization and unreasonable land development and utilization, the ecological environment has deteriorated sharply, and the stability of ecological environment has always been a difficult problem in the process of regional development. The spatial division of urban ecological function can be divided into different types of spatial utilization according to the fragile state of ecological environment, which not only guarantees urban construction but also maintains the ecological environment health, and has great economic benefits and ecological value in formulating regional development strategies and ecological protection. In this paper, from four perspectives of “land, water, human and forest”, eight factors affecting ecological sensitivity were selected, and GIS spatial superposition method was used to conduct qualitative and quantitative analysis on the ecological sensitivity of Baoji City, and the evaluation results of single factor ecological sensitivity and comprehensive ecological sensitivity were obtained. The areas with different ecological sensitivity are divided into extremely sensitive areas, highly sensitive areas, moderately sensitive areas, slightly sensitive areas and non-sensitive areas. The research shows that the proportion of extreme, high, moderate, mild and insensitive areas in Baoji City is 7.32%, 10.57%, 22.25%, 42.91% and 16.95% respectively. Finally, the areas with different sensitivity grades are identified as three types of urban ecological function areas: ecological conservation area, ecological coordinated moderate utilization area and ecological suitable construction area, so as to provide scientific theoretical basis for urban construction and land use optimization in Baoji City.

Function of Agricultural Land Use and Its Evolvement in Peri-urban Area: A Case Study of Beijing

Rapid urbanization in Beijing stimulates the urban land expansion and diminishes available agricultural land. Monofunctional agricultural land use can not meet the demand of the devel- opment of the multifunctional agriculture and urbanization any more, so multifunctional agricultural land use is going to be promoted in the city. This article proposes the evolvement of the land use change from 1992 to 2004 and discusses some evolvement views.

An integrated approach to evaluation on ecological service functions for urban green space and its application

This methodological investigation deals with measurement and valuation of ecological service functions for urban green space. Social, economic and ecological dimensions for such types of function were analyzed and a concept “integrated ecological service functions” (IESF) was put forward for evaluation. Based upon this conceptual approach, an index system for measuring IESF for urban green space was established. With a methodological integration of fuzzy mathematics, decision making analysis and Delphi method, an AHP fuzzy evaluation techniques for IESF for urban green space, called AFIFUG method, was developed. Such a method has been directly applied to the land use strategic planning of Tianjin out ring green belt(TOGB), and its analysis results have been successfully put into operation.

Characteristics and Influencing Factors of Microplastics in Snow in the Inner Mongolia Plateau, China

Microplastics(MPs;<5 mm)have become one of the most prominent global environmental pollution problems.MPs can spread to high altitudes through atmospheric transport and can be deposited by rainfall or snowfall,potentially threatening the structure and function of natural ecosystems.MPs in terrestrial and aquatic ecosystems alter the growth and functional characteristics of organisms.However,little attention has been given to the possible harm associated with MPs deposited in snow,particularly in the context of global climate warming.MPs collected from surface snow in the Inner Mongolia Plateau,China,were used for quantitative analysis and identification.The results showed that MPs were easily detected,and the related concentration was approximately(68±10)–(199±22)MPsL1 in snow samples.Fibers were the most common morphology,the polymer composition was largely varied,and the abundance and composition of MPs were linked to human activity to a great extent.High-throughput sequencing results showed that the composition and abundance of microorganisms also differed in snow samples from areas with different MP pollution characteristics,indicating a considerable difference in microbial functional diversity.MPs may have an interference effect on the individual growth and functional expression of microorganisms in snow.In addition,the results showed that functional living areas(e.g.,landfills and suburban areas)in cities play an important role in the properties of MPs.For instance,the highest abundance of MPs was found in thermal power plants,whereas the abundance of polymers per sample was significantly lower in the suburban area.The MP contaminants hidden in snow can alter microbial structure and function and are therefore a potential threat to ecosystem health.

城市功能区识别研究进展与趋势

随着经济社会的快速发展,城市开发边界迅速由中心向外蔓延,识别城市功能区可为城市建设与规划提供参考依据,且对城市空间和资源合理配置利用具有重要意义。本文在梳理有关城市功能区划分与识别的国内外文献基础上,对城市功能区识别的研究现状进行综述。首先,介绍了用于城市功能区识别的多种数据源,并分析比较其优缺点;然后,总结了城市功能区识别的4类方法,重点分析了深度学习方法在城市功能区识别中的应用,并展开实例分析对比,说明不同数据源和方法对城市功能区识别的有效性;最后,指出了城市功能区划分识别研究领域存在的问题和研究趋势。

Empirical Study of China's Rural Consumption Function from the Perspective of Balancing Urban and Rural Development

From the perspective of balancing urban and rural development,this article researches the factors influencing the consumption level of rural residents in China.I select the relevant data concerning per capita net income of rural households and annual per capita consumer spending of rural residents for living in the period 1985-2008,establish the regression model of per capita net income of rural households and per capita consumer spending of rural residents for living,and conduct regression analysis and error correction model test using the measurement software.The analysis results show that there is not only long-term equilibrium relationship between rural residents' current consumption and rural residents' current income,between rural residents' consumption in lag period 1 and rural residents' income in lag period 1,but also short-term equilibrium relationship;current income is the main reason for determining the current consumption).Corresponding proposals are put forward to promote the level of rural consumption in China as follows:propel agricultural modernization;actively develop specialized cooperative organizations of rural residents;improve rural land transfer mechanism;promote the level of public services in rural areas;accelerate the transfer of rural surplus labor.

资源枯竭型城市生态质量时空格局与驱动力研究--以阜新市中心城区为例

为评价资源枯竭型城市转型期的生态质量时空演变特征,本文以阜新市中心城区为研究区域,基于Landsat遥感影像构建遥感生态指数(RSEI),以OSM数据和POI数据为基础识别城市功能区,借助参数最优地理探测器模型探究城市生态质量与城市功能区之间的复杂性关系。结果表明:①2004—2022年阜新市中心城区生态质量整体呈略微下降趋势、波动相对稳定,形成四周好、中间差的盆地状格局;②Hurst指数均值为0.67,强持续性最近邻指数值为146.53,生态质量未来变化趋势呈现均匀持续性,大部分区域变化趋势与过去相同,但局部地区有反持续性趋势;③识别出“31+1”类城市功能区,功能区生态质量由高到低依次为绿地、公共服务、工业、交通、居住、商业、矿区,且不同因子交互作用均会增强对生态质量的解释力。研究结果可为资源枯竭型城市转型期针对不同功能区的生态保护和恢复工作提供科学参考。

多源大数据支撑下的城镇职能类型结构测度——从乡镇尺度的视角

城镇职能类型结构是在特定区域范围内,城镇职能互动关系的布局总况。针对当前乡镇职能多以定性判断的现实问题,基于手机信令、企查查、POI等大数据与职能特性的关联,建立了针对各类职能的定量测度方法,并据此构建了适用于乡镇尺度的城镇职能类型结构定量测度框架。以宁波市乡镇为单元展开测度,定量识别出宁波市发挥工业、交通、商业、科教、旅游5类职能优势的城镇单元,且识别结果与该市的规划发展模式基本吻合,验证了框架的可行性。该框架不仅弥补了城镇职能类型定量测度在乡镇尺度的空白,亦能够助力城镇职能类型结构的合理配置。

“一带一路”高质量建设中我国内陆节点城市功能响应评价与展望

“一带一路”倡议的提出对我国内陆地区开放发展产生了深远影响。为了更好地融入和服务“一带一路”建设,我国内陆节点城市需要在城市功能方面做出积极响应。通过构建城市功能响应指数,对我国内陆节点城市功能响应状况进行评价分析发现,功能响应状况特征明显:一是响应程度总体不高;二是在城市和区域间存在明显分化。从城市来看,在10个内陆节点城市中,成都和重庆的城市功能响应程度最强,其次为武汉、西安、郑州,西宁垫底。从区域来看,西南地区整体较强,西北地区偏弱,中部地区中等;三是五大城市功能子系统的响应程度存在较大差异。站在“一带一路”十周年的新起点,我国内陆节点城市要积极主动作为,在推动“一带一路”高质量发展中融入全球开放大局,重塑区域经济发展格局,在推动丝绸之路数字化、绿色化和创新发展中提升节点城市功能。

城市功能区夜间光环境差异性分析

由于城市环境的复杂性,城市内的各功能区在环境、需求等方面存在着显著差异。夜间光环境在城市环境中占据重要地位,其特征对城市空间的规划、设计和管理至关重要。深入研究不同功能区夜间光环境的特点有助于全面了解城市在夜晚的特征与需求,为提升城市整体质量和可持续性提供了重要的参考依据。本研究针对六个具有代表性的城市功能区展开了夜间光环境的实地测量。通过绘制各功能区的夜间照明分布图,并对不同参数和多视角的照明数据进行了综合分析比较,揭示了这些功能区在夜间照明方面的显著差异。通过深入研究夜间照明特征,不仅为城市规划和设计提供了具体的数据支持,也为夜间照明管理策略的制定提供了理论依据。

面向城乡融合的都市农业功能转型研究进展及其关键科学问题

面向城乡融合和乡村振兴等国家重大战略,聚焦于都市农业发展的功能演化与空间重组机制具有重要的理论和现实意义。文章系统梳理了都市农业功能转型的研究进展,提出了未来亟需关注的关键科学问题。研究发现:1)都市农业功能转型研究的主要议题包括都市农业发展转型评价及类型划分、都市农业多功能转型及可持续发展、都市农业空间组织与生产组织方式、都市农业发展中土地利用及竞租机制、都市农业发展问题及其多维效应等5个方面。2)都市农业地域系统与城乡地域系统间的要素流动、物质循环,以及两者间的内在作用逻辑是都市农业发展的理论基石。都市农业地域系统功能演化和空间重组的动力机制有待深入探索,亟待强化基于地域系统视角的都市农业发展中的土地竞租、土地权属和相关利益主体等研究。3)聚焦于都市农业地域系统功能演变的关键科学问题,未来亟待开展的研究包括3个方面:其一,基于城乡连续体的视角,厘清都市农业系统地域功能演化的内源性和外部性驱动力间的交互联动和耦合作用机制;其二,揭示都市农业地域系统空间重组的核心机理,以及利益主体的作用关系与土地竞租的内在逻辑;其三,探索都市农业地域系统功能演化带来的生态环境效应,以及对生态环境的影响机制。

北京市轨道交通线网规划探索与实践

作为超大城市的北京市进入新发展阶段,面临新发展要求,其轨道交通线网规划也需要进行适应性转变。为充分发挥轨道交通线网规划对于北京城市高质量发展的服务和引领作用,文章针对北京市轨道交通线网规划所面临的主要问题和新发展要求,在分析和总结轨道交通线网在规划对象、手段和范畴方面转型特征的基础上,从服务首都、城市协同、多网融合、精细服务、创新实施5方面探索北京市轨道交通线网规划新理念,并据此有针对性地提出相关实践建议,以期为进一步优化完善北京市轨道交通线网规划工作、推动轨道交通与城市的高质量融合发展提供参考和借鉴。