基于GIS的大连市沙河口区城市绿地公平性研究——以可持续人居环境为视角

我国快速城市化进程正在遭受着环境污染、交通拥挤、住房紧张等一系列的城市问题,城市生态环境质量持续下降。城市绿地对城市碳氧平衡的调节具有重要作用,大力发展城市绿化将有助于改善城市环境问题。但目前我国城市绿地建设缺乏具体的空间分布规划,只注重绿地覆盖率和人居绿地面积,绿地服务功能的公平性问题没有得到充分重视。本文利用ArcGIS对大连市沙河口区的绿地可达性进行了研究,通过对比绿地可达性与沙河口区人居环境类型发现,高收入社会群体拥有比低收入社会群体更高的绿地可达性。城市规划者应该注意到这些问题,并在今后的建设中关注社会各阶层对绿地的需要,使城市居民在享受公共服务资源上更为公平。     

Fine-scale simulation of spatial population distribution by coupling GA–ABM and big data: A case study of Dongguan,China

Capturing spatial population distribution can offer useful information for urban planning to promote reasonable population distribution and allocate urban resource. Agent-based model (ABM) based on the modeling idea of “bottom-up” can offer the ability to simulate the complex individual behaviors that generate spatial population distribution. Previous ABMs were unable to be extended for simulation of spatial population distribution at a fine scale due to the shortage of fine characterization of the urban environment and the calibration of agents' behavior. This study filled these gaps by proposing a genetic algorithm-ABM (GA–ABM) for fine-scale simulation of spatial population distribution in a manufacturing metropolis. In this model, the employment and residential choice behaviors of agents were defined by the labor economic theory and discrete selection model. Multisource geospatial big data such as enterprise points-of-interest big data and building footprints data were used to finely characterize the labor market and urban environment to reflect the impact of agents' employment choices on their residential decision. Furthermore, the grid-scale population investigation big data were combined with the GA to calibrate the agents' residential decision behaviors. The proposed model was used in Dongguan, the typical manufacturing metropolis in China. As a comparison, the expert-experience-based method-ABM (EEBM–ABM) was also conducted by using the same data set. Through the comparison of the results produced by these two models, it was demonstrated that the model coefficient calibrated by GA could effectively reflect the agents' residential decisions. The calibrated GA–ABM is more capable than EEBM–ABM in simulating spatial population distribution in a manufacturing metropolis. Hence, the proposed model can be used to simulate spatial population distribution in a manufacturing metropolis which helps the urban planner to conduct scientific urban planning.     

Geosimulation of urban growth and demographic decline in the Ruhr: a case study for 2025 using the artificial intelligence of cells and agents

The Ruhr is an “old acquaintance” in the discourse of urban decline in old industrialized cities. The agglomeration has to struggle with archetypical problems of former monofunctional manufacturing cities. Surprisingly, the image of a shrinking city has to be refuted if you shift the focus from socioeconomic wealth to its morphological extension. Thus, it is the objective of this study to meet the challenge of modeling urban sprawl and demographic decline by combining two artificial intelligent solutions: The popular urban cellular automaton SLEUTH simulates urban growth using four simple but effective growth rules. In order to improve its performance, SLEUTH has been modified among others by combining it with a robust probability map based on support vector machines. Additionally, a complex multi-agent system is developed to simulate residential mobility in a shrinking city agglomeration: residential mobility and the housing market of shrinking city systems focuses on the dynamic of interregional housing markets implying the development of potential dwelling areas. The multi-agent system comprises the simulation of population patterns, housing prices, and housing demand in shrinking city agglomerations. Both models are calibrated and validated regarding their localization and quantification performance. Subsequently, the urban landscape configuration and composition of the Ruhr 2025 are simulated. A simple spatial join is used to combine the results serving as valuable inputs for future regional planning in the context of multifarious demographic change and preceding urban growth.     

土地利用变化模拟模型及应用研究进展

元胞自动机CA(Cellular Automata)和多智能体ABM(Agent-Based Model)模型是土地利用格局和演化模拟的主流方法,两者在模拟自然因素影响和人文驱动机制方面具有突出优势,为LUCC研究提供了重要的工具。当前,ABM无论在模型构建还是应用研究方面,CA和ABM均取得了显著进展。论文从数据基础、模拟尺度、CA转换规则挖掘、ABM行为规则定义、CA和ABM的耦合4个方面梳理土地利用模拟模型和方法的研究进展。并总结这些模型在虚拟城市模拟与理论验证、真实城市模拟与规划预测以及多类用地模拟与辅助决策等方面的应用。最后,总结土地利用模拟模型在精细模拟和全球变化研究方面存在的局限性,认为未来发展将主要集中于解决从2维模型向3维模型发展、大数据与规则精细挖掘以及大尺度模拟与知识迁移等问题。     

浙江城市群人口与用地规模的时空分异结构演变研究

结合夜间灯光与城市统计数据,应用城市位序-规模法则及人地异速生长模型,初步分析了浙江人口分布及人地关系,考虑到人口增长的特征,提出了加入滞后效应的修正模型,对浙江城市群长期的发展展开了动态研究.研究结果表明,浙江城市群结构体系较为成熟,但是随着经济发展,城市首位度逐步提高,人口逐渐呈现聚集状态;浙江城市群中的杭州、宁波...     

Analyzing Urban Sprawl in Rethymno,Greece

Analysis of urban sprawl is an issue that has been continuously attracting attention in the planning and research community. Τhis paper presents the results of an analysis of the growth of the city of Rethymno during the 1997–2010 time period. Rethymno is a city in the island of Crete in Greece with population of about 35,000 people, in which developed land has expanded at a rate that is double the growth of the population during the study period. A qualitative analysis was first performed to identify growth patterns in the different parts of the city, how these are related to planning regulations and the extent of cohesiveness of the development. A logistic regression model was estimated using various variables influencing the expansion of the built up area. Variables such as slope, distance from main roads, distance from the University, distance from coastline, as well as variables describing the proximity to other developed areas were used as independent variables in the logistic regressions. Planning constraints with respect zoning were also considered. The accuracy/goodness of fit of the simulation results were also tested using Receiver Operating Characteristic (ROC) curve. The results revealed high (performance) accuracy, which can support the applicability of the proposed method in urban sprawl modeling. Once the equations were estimated they were applied using data from 2010 to identify future trends of urbanization. The methodology adopted in this study can result in a tool that can be of use to urban planning authorities in identifying areas of future urban growth and therefore, adopt zoning policies encouraging or discouraging growth in these areas according to the sustainability objectives of the local community.     

核密度估计法支持下的网络空间POI点可视化与分析

城市空间POI点的分布模式、分布密度在基础设施规划、城市空间分析中具有重要意义,表达该特征的核密度法(kernel density estimation)由于顾及了地理学第一定律的区位影响,比其他密度表达方法(如样方密度、基于Voronoi图密度)占优。然而,传统的核密度计算方法往往基于二维延展的欧氏空间,忽略了城市网络空间中设施点的服务功能及相互联系发生于网络路径距离而非欧氏距离的事实。本研究针对该缺陷,给出了网络空间核密度计算模型,分析了核密度方法在置入网络结构中受多种约束条件的扩展模式,讨论了衰减阈值及高度极值对核密度特征表达的影响。通过实际多种POI点分布模式(随机型、稀疏型、区域密集型、线状密集型)下的核密度分析试验,讨论了POI基础设施在城市区域中的分布特征、影响因素、服务功能。     

Study on forecast scenarios for simulation of future urban growth in Shenyang City based on SLEUTH model

The SLEUTH urban growth model was used to simulate future urban growth patterns and to explore potential environ-mental impacts of urban development under different conditions of development in Shenyang City, China. The SLEUTH model was calibrated with historical data (1988-2004) extracted from a time series of TM satellite images, and the future growth was pro-jected out to 2030 assuming three different policy scenarios: (1) current trends scenario (Scenario CT), (2) regional policy and ur-ban planning sce...     

城市人口时空分布估计研究进展EI北大核心CSCD

城市人口是构成城市的社会主体,是城市发展中最为活跃的因素。城市人口时空分布是城市管理需要掌握的重要信息。正确、精细化的城市人口分布数据对于城市运行与规划、城市经济发展和人民生活具有极为重要的意义,因此城市人口时空分布估计是城市地理学需要解决和研究的热点问题之一。本文以城市人口时空分布估计的关键点为核心,从以下几个方面展开综述:①空间分布单元划分方法,即城市人口分布的空间划分方式;②主要的模型和方法,从模型思想发展过程和估计对象的角度总结了6类方法并进行详细阐述;③估计结果在城市发展中的主要应用。在此基础上,本文指出了目前人口时空分布研究在空间单元构建、建模数据、建模思想和结果验证上存在的问题,同时探讨了未来的研究方向。     

Generating population census data through aerial remote sensing

For urban planning and decision making, exact information about population of a specific area is very important. In India, the population census is carried out after every decade by field survey. But to know the inter-censual population, field survey is not very appropriate method because it is not cost and time-effective. Remote sensing can help significantly in generating quick information about housing typology and housing stock, from which population data can be extracted with the help of limited field checks. Therefore, two techniques of estimation of population using remote sensing data have been employed for Saharanpur city as a case study and the results are very encouraging.     

Optimizing the spatial relocation of hospitals to reduce urban traffic congestion: A case study of Beijing

Traffic congestion represents an ongoing serious issue in many large cities. Many public facilities, such as hospitals, tend to be centrally located to ensure they are most accessible to local residents; as a result, they may contribute significantly to a city's traffic congestion. In this study, a multi‐objective spatial optimization model was provided to help formulate hospital relocation plans, taking into account both traffic congestion and hospital accessibility. Using intra‐urban movement data, we proposed a method to estimate the area‐wide traffic congestion caused by hospital visits and to identify potential hospitals to be relocated. An NSGA‐II (Non‐dominated Sorting Genetic Algorithm II) algorithm was applied to solve the hospital relocation optimization problem; we applied our model to study optimal hospital relocation plans in Beijing. Analysis results provide a tradeoff between traffic congestion relief and hospital accessibility. We discussed plans that significantly reduce traffic congestion while maintaining a high level of hospital accessibility. Our study has significant policy implications and provides insights for future facility planning and transportation planning.     

Assessing the effect of temporal dynamics on urban growth simulation: Towards an asynchronous cellular automata

Time is a fundamental dimension in urban dynamics, but the effect of various definitions of time on urban growth models has rarely been evaluated. In urban growth models such as cellular automata (CA), time has typically been defined as a sequence of discrete time steps. However, most urban growth processes such as land‐use changes are asynchronous. The aim of this study is to examine the effect of various temporal dynamics scenarios on urban growth simulation, in terms of urban land‐use planning, and to introduce an asynchronous parcel‐based cellular automata (AParCA) model. In this study, eight different scenarios were generated to investigate the impact of temporal dynamics on CA‐based urban growth models, and their outputs were evaluated using various urban planning indicators. The obtained results show that different degrees of temporal dynamics lead to various patterns appearing in urban growth CA models, and the application of asynchronous (event‐driven) CA models achieves better simulation results than synchronous models.     

基于介数中心性的交通拥堵指数计算

本文以北京城市交通为例,选取北京城市路网数据,计算城市路网介数中心性,以反映城市各道路路段的通达情况;并利用北京出租车GPS定点数据,计算实际的交通轨迹。传统的路网介数中心性主要依据各路段最短路径的比重评价理论上的道路通达性,而本文以网络介数中心性为基础,提出动态介数的方法,从城市各路段交通量比重的角度评价各道路实际拥堵情况。利用两个介数的对比能够全面客观地反映交通拥堵状况,提高交通拥堵指数的参考价值,并为城市建设规划决策及道路改建等方案提供依据,有利于缓解城市道路交通拥堵现状。     

Land Use/Cover Change Detection of Tiruchirapalli City, India, Using Integrated Remote Sensing and GIS Tools

The rapid growth of urban population in India is a cause of concern among country??s urban and town planners for efficient urban planning. The drastic growth of urban areas has resulted in sharp land use and land cover changes. In recent years, the significance of spatial data technologies, especially the application of remotely sensed data and geographical information systems (GIS) has been widely used. The present study investigates the urban growth of Tiruchirapalli city, Tamilnadu using IRS satellite data for the years 1989, 1992, 1995, 1998, 2001, 2004, 2007, and 2010. The eight satellite images are enhanced using convolution spatial enhancement method with Kernel (7?×?7) edge enhance function. Supervised classification method is used to classify the urban land use and land cover. The GIS is used to prepare the different layers belonging to various land uses identified from remotely sensed data. The analysis of the results show the drastic increase of built up area and reduced green cover within the city boundary limit.     

Understanding geographical patterns of a city’s diurnal rhythm from aggregate data of location‐aware services

Do collective behaviors of the daily routine of a city's inhabitants form the periodical cycling of human activity at the city level (here termed the “city's diurnal rhythm”)? If the answer is yes, do there exist geographical patterns in the city's diurnal rhythm? Using a nationwide dataset of observed uses of location‐aware services in the largest Chinese social media platform, we first confirm the significant periodicity in city‐level human activity from the perspective of the aggregate degree of social media uses over a day. We then investigate geographical changes in the diurnal rhythm of human activity and its local variations in different parts of the city, and between weekdays and weekend days, over 340 Chinese cities. Our results show that a city's diurnal rhythm across the whole country exhibits both regular, nationally conspicuous shifts along geographical gradients and locally distinct spatiotemporal changes within the city. Our findings could provide insights into the characterization of the daily routine of city‐level human activity and its geographical patterns, and have potential for several issues in terms of planning, management, and decision‐making related to human population dynamics.     

Mapping hourly dynamics of urban population using trajectories reconstructed from mobile phone records

Understanding the spatiotemporal dynamics of urban population is crucial for addressing a wide range of urban planning and management issues. Aggregated geospatial big data have been widely used to quantitatively estimate population distribution at fine spatial scales over a given time period. However, it is still a challenge to estimate population density at a fine temporal resolution over a large geographical space, mainly due to the temporal asynchrony of population movement and the challenges to acquiring a complete individual movement record. In this article, we propose a method to estimate hourly population density by examining the time‐series individual trajectories, which were reconstructed from call detail records using BP neural networks. We first used BP neural networks to predict the positions of mobile phone users at an hourly interval and then estimated the hourly population density using log‐linear regression at the cell tower level. The estimated population density is linearly correlated with population census data at the sub‐district level. Trajectory clustering results show five distinct diurnal dynamic patterns of population movement in the study area, revealing spatially explicit characteristics of the diurnal commuting flows, though the driving forces of the flows need further investigation.     

Quantification of Urban Landscape Dynamics Using Patch Parameters and Landscape Indices: An Analytical Study of Ranchi

Urbanization incepts serious challenges of growth and its management. The issues of urbanization manifest in the form of overcrowding, congestion, insufficient infrastructure, inadequate service provisioning, environmental degradation, pollution etc and affect the socioeconomic development of the city. Ranchi, the capital of newly formed state of Jharkhand (India) has been witnessing the same scenario; raising the question of its planning and management of growth to make it more efficient and sustainable. It hoists the necessity to study the pattern of urbanization and its impact on other landuse/landcover categories in Ranchi city. In order to assess the urbanization pattern and spatio-temporal dynamics in the study area, the changing pattern of the three significant patch parameters viz. patch frequency, largest patch size and average patch size of all affected landuse/landcover categories over a time gradient representing the pre-capital and post-capital formation phases of the Ranchi city have been analyzed. The two conventional landscape indices viz. Shannon’s diversity Index and Simpson’s diversity index and a newly developed index ‘Normalized Patch size Range Index’ have been employed in the analyses which not only ascertained the finding derived but also provided meaningful insights pertaining to the spatio-temporal urban landscape dynamics prevailing in the Ranchi city.     

Spatial pattern of urban functional landscapes along an urban–rural gradient: A case study in Xiamen City,China

Since there is an increasing demand for integrating landscape ecology and urban planning theories to study complex urban ecosystems and establish rational and ecological urban planning, we introduced a new concept-urban functional landscapes which can be reclassified based on detailed land use data to fulfill the various urban functions, such as residential, commercial, industrial, and infrastructure purposes. In this paper, urban functional landscapes were defined based on urban land use data produced from Pleiades images, and then landscape metrics and population density were combined to identify the urban functional zones along an urban–rural gradient. The features of urban functional landscape patterns and population density were also analyzed, and their relationship has been explored. The results showed that the pattern of urban functional landscapes and population density in the urban functional zones (Urban center, Urban peripheral area, Landscape barrier, Satellite city and Far-suburb) along the urban–rural gradient in Xiamen doesn't totally conform to the classical theories in spatial and social aspects. Urban functional landscapes is potential of acting as bridges between the landscape ecology and urban planning theories, providing scientific support for rational urban landscape planning and urban land use policy making.     

基于CA模型的城市空间扩展研究——义乌市为例

本文引入地理信息系统(GIS)和元胞自动机的有机集成而构筑的GeoCA-Urban模型模拟义乌市城市空间扩展的动态演化过程。结果表明:从发展速度分析,义乌市城市发展经历了一个起步—缓慢发展—爆炸发展的过程,而且爆炸式发展还在继续,从发展的空间布局上分析,义乌市在交通(主要是浙赣铁路和主要公路)、水系(义乌江)和城市中心辐射作用下,经历了带状(东北西南向)—椭圆—圆形的发展过程。通过设置转换规则、参数,真实直观地再现展示了城市空间系统的演化过程,为城市规划等提供了辅助决策。     

A Multi‐Objective,Multi‐Criteria Approach to Improve Situational Awareness in Emergency Evacuation Routing Using Mobile Phone Data

Emergency services personnel face risks and uncertainty as they respond to natural and anthropogenic events. Their primary goal is to minimize the loss of life and property, especially in neighborhoods with high population densities, where response time is of great importance. In recent years, mobile phones have become a primary communication device during emergencies. The portability of cell phones and ease of information storage and dissemination has enabled effective implementation of cell phones by first responders and one of the most viable means of communication with the population. Using cellular location data during evacuation planning and response also provides increased awareness to emergency personnel. This article introduces a multi‐objective, multi‐criteria approach to determining optimum evacuation routes in an urban setting. The first objective is to calculate evacuation routes for individual cell phone locations, minimizing the time it would take for a sample population to evacuate to designated safe zones based on both distance and congestion criteria. The second objective is to maximize coverage of individual cell phone locations, using the criteria of underlying geographic features, distance and congestion. In summary, this article presents a network‐based methodology for providing additional analytic support to emergency services personnel for evacuation planning.