Development trends among Moscow Oblast cities and some issues in the regulation of the growth of Moscow

Reasons for the continuing growth of central Moscow in comparison with little growth in subsidiary cities in the surrounding Moscow Oblast are examined. The author attributes this uneven growth to the concentration of shopping facilities in central Moscow. It is noted that past attempts to slow the growth of central Moscow have failed and that the only strategy likely to succeed in the future would involve developing the infrastructure of the surrounding subcenters.     

Use of the population potential model for predicting the growth of cities in a region (with reference to Moscow Oblast)

"A modification of the population potential model is used to analyze the structure of the potential of population for cities of the Moscow region, to develop a relationship between population potential and city size, and to use this procedure to forecast future population change in Moscow Oblast cities." Cities in the region with a population of 50,000 or more at the censuses of 1959, 1970, and 1979 are included.     

新重力P中值模型及其在城市综合医院区位决策中的实证检验——以无锡市为例

区位—分配模型是实现公共服务设施最适配置的有效方法之一。传统的P中值模型以效率作为导向,采用“邻近分配”规则,不考虑设施容量(规模),难以适应城市综合医院供需之间相互作用规律下适度均衡、居民随机概率式选择和区位与规模同步求解的布局要求。本文尝试以P中值模型为基础框架,在对P中值模型来源及其适用性进行分析的基础上,构建出基于供需双方(居民—综合医院)空间相互作用的重力P中值模型。新模型通过纳入“邻近就医”最大出行成本因子,确保居民至少邻近1所综合医院(保障空间公平);通过追求总加权出行成本最小化,确保设施空间配置效率;通过纳入设施容量规模因子实现设施区位和规模同时求解;通过纳入最小规模因子,保障设施规模效率和服务质量公平。进一步通过无锡市区综合医院空间配置进行实证检验发现：采用新模型优化后,综合医院空间配置更加公平、居民邻近就医更加便捷,且能够实现与社区卫生设施协同布局,使整个医疗设施体系空间布局更加合理。本文构建的新重力P中值模型(模型的变量参数可作适当调整)可用于竞争型公共设施区位决策,为相关设施布局调整或者规划提供决策依据。     

Planning for growth in a natural resource boomtown: challenges for urban planners in Fort McMurray,Alberta

Between 2000 and 2010, the population of the city of Fort McMurray, Alberta increased by 80%, mainly due to the expansion of oil extraction projects and subsidiary industries. Population growth of this magnitude has significant consequences for city planning. While Fort McMurray struggles to keep up with enormous numbers of in-migrants, the cost of living in the city has skyrocketed. Using interviews with city planners and field experience in the city, in this paper I examine the current challenges faced by urban planners in Fort McMurray against the backdrop of global economic decision-making, corporate influence, and commodity dynamics. While the recession of 2008 gave city planners some breathing room, they still struggle with gathering accurate census information and predicting population growth, providing affordable housing, and balancing short-range planning with their long-term goals. Attempts by city planners to address these challenges could provide a contemporary model for urban planning in rapidly growing, resource-dependent communities.     

Differential urban growth as a process of redistribution of population: a case study of Sao Paulo state,Brazil

"This paper identifies the process of the differential concentration of population in urban areas....[Data for the state of Sao Paulo, Brazil, have] been subjected to an ambiguous model of development. This model is reflected in the pattern of population distribution."     

城市交通效率的多目标评价方法研究——以北京市城六区为例

高速城镇化和机动化阶段,面临与日剧增的环境压力,城市交通的多目标发展成为交通可持续发展的关键。在提升居民出行满意度的同时,降低交通碳排放是目前及未来城市交通可持续发展关注的核心目标,是城市交通效率的主要内涵。由此,本文从交通出行便捷与交通碳减排双目标综合评估的角度,提出基于中观尺度的城市交通出行满意度和交通碳排放的定量测算方法;并利用数据包络分析(Data Envelopment Analysis, DEA)法探讨城市交通综合效率评价方法。对北京市城六区的实证结果显示,在三环以内地区,城市交通综合效率较高,五环以外大部分地区较差。交通综合效率较高的地区集中分布于：①西三环至西四环万寿路街道的公主坟-五棵松地区。②北三环和平里街道安贞桥附近地区。③东北三环的三里屯地区。而综合效率较差的地区大多位于城市外围,例如西北六环周边,西南五环至西南六环部分地区,以及东五环外常营地区等,交通碳排放较高是这些地区交通效率较差的主要原因。此外,交通效率的空间差异与地理空间环境的差异性呈现高度的相关。例如,交通效率较差的地区大多是高档别墅区集聚的地区,以及城市五环周边公共交通不完善的部分居住区。通勤中机动化比例较高和通勤距离较长是碳排放强度较高的主要原因。     

Simulating artificial cities in a GIS environment: urban growth under alternative regulation regimes

This paper reports on an attempt to combine neo-classical urban economic theory with complex systems methods. The innovative feature of our model from the point of view of conventional economic theory lies in its explicit treatment of spatial relationships and time sequence. From the perspective of raster or cellular GIS models of urban processes, the work is innovative in that it replaces the more usual heuristic cell-transition rules with micro-economic theory. The mix of modelling paradigms is not unproblematic, however, and we discuss the challenges encountered at this research frontier. These notwithstanding, our hybrid model has the potential to be used as a GIS-based laboratory for exploring micro-economic propositions, particularly those relating to urban processes that are path dependent. The version of the model reported simulates spatially equilibriated path dependent futures of a city governed by local development decisions that are at partial equilibria in the neo-classical sense. Two simulations are described which permit visual and economic exploration of (a) an explicitly spatial version of the economic theory of externalities and (b) a new theory of densification. The dual paradigm (Cellular Automata-neo-classical economics) leads to an interesting class of simulations in terms of stability. Economically our simulated cities become increasingly efficient, in terms of private and social product. The long-run economic equilibrium is achieved by many individually efficient negotiations based only on local information. There is no parallel long-run spatial equilibrium however. The spatial configuration of land uses is constantly shifting as a result of randomness in the land use bidding process. The spatial instability is, however, limited by the self-organised drive for greater overall economic efficiency. In economic terms, the model's spatial instability represents random re-allocation of land-use within a set of Pareto-efficient spatial configurations - an intriguing result that we intend to follow up in future work.     

The case of urban sprawl in Spain as an active and irreversible driving force for desertification

The United Nations Convention to Combat Desertification (UNCCD) does not distinguish between natural and human drivers, and between active and inherited desertification. Partly as a result of these ambiguities the UNCCD has attracted a low level of international attention. As the Spanish case study shows, this vagueness hinders the implementation of effective strategies to combat this global challenge. Unsustainable agricultural land management is the most blamed desertification agent in Spain but as land use changes trends demonstrate, desertification phenomena are fueled by a push–pull dynamics. Our data indicate that agriculture, rather than being a desertification agent, is a victim of a set of social and economic conditions leading to its abandonment and/or transformation in urban land, becoming irreversibly degraded by soil sealing. From 1975 to 2008, half a million ha of former agricultural land has been made available for development. Urban sprawl has become the most active desertification agent in Spain.     

Factors controlling carbonate dissolution rates quantified in a field test in the Austrian alps

Carbonate dissolution rates were investigated by measuring the mass difference of carbonate tablets exposed to natural dissolution for 1 year. 70 tablets were distributed over 13 test sites on the north slope of the Hochschwab Massif in the Austrian Alps. The influences of altitude, subsoil vs. sub-aerial exposure, vegetation, karst morphology, soil humidity, sample lithology, and sample surface morphology were investigated. The observed dissolution rates varied between 13 and 40 μm/a for subcutaneous samples and about 11 μm/a for sub-aerial exposure. Outstandingly high rates of 48 μm/a were observed in a doline and nearly zero rates were measured at a site influenced by seeping spring water.A mass balance, using high-resolution hydrological data, was calculated for the Kläffer Spring, which has an average outflow of 4.8 m³/s. It indicated a loss of 21×10⁶ kg of carbonate rock per year which gives an average dissolution rate of 95 μm/a for the catchment area of 83 km². The dissolution rates of 10 μm/a from the sub-aerially exposed samples are comparable to values from limestone pedestals, which were protected from dissolution by glacial erratics for the past 15 ka.     

Simulating urban growth in a metropolitan area based on weighted urban flows by using web search engine

As a consequence of rapid and immoderate urbanization, simulating urban growth in metropolitan areas effectively becomes a crucial and yet difficult task. Cellular automata (CA) model is an attractive tool for understanding complex geographical phenomena. Although intercity urban flows, the key factors in metropolitan development, have already been taken into consideration in CA models, there is still room for improvement because the influences of urban flows may not necessarily follow the distance decay relationship and may change over time. A feasible solution is to define the weights of intercity urban flows. Therefore, this study presents a novel method based on weighted urban flows (CA_WeightedFlow) with the support of web search engine. The relatedness measured by the co-occurrences of the cities’ names (toponyms) on massive web pages can be deemed as the weights of intercity urban flows. After applying the weights, the gravitational field model is integrated with Logistic-CA to fulfill the modeling task. This method is employed to the urban growth simulation in the Pearl River Delta, one of the most urbanized metropolitan areas in China, from 2005 to 2008. The results indicate that our method outperforms traditional methods with respect to two measures of calibration goodness-of-fit. For example, CA_WeightedFlow can yield the best value of ‘figure of merit’. Moreover, the proposed method can be further used to explore various development possibilities by simply changing the weights.     

Food gardens as important elements of urban agriculture: Spatio-developmental trends and future prospects for urban gardening in Czechia

The main research goals of the article are to explain the historical context of urban food gardens in Czechia, to describe the current spatial pattern of allotment gardens, and to introduce and analyse recent trends in urban gardening. The main method for achieving the first goal was a literature study. For the second goal, geographical mapping and analysis of data relating to the spatial distribution of allotment gardens were used. For the third goal, mapping together with analysis of semi-structured interviews carried out in community gardens in Prague were used. The analysis showed a strong tradition of urban agriculture and urban food gardening activities in Czechia. Both allotment gardens and newly emerged community gardens were concentrated mainly in the biggest cities and in areas with a rich industrial and mining tradition. This finding supports the significance of gardening as an important element of urban agriculture. However, uncertainty regarding land tenure and long-term sustainability were among the greatest obstacles for the future of allotment and community gardens. The authors’ main recommendations are that urban agriculture should be included as primary land use in sustainable planning and there should be broader community involvement in planning and decision-making processes.     

城市物流企业区位分布的空间格局及其演化——以苏州市为例

通过建立苏州市1990～2007年的物流企业空间与属性数据库,借助GIS空间分析模块,采用样方、空间自相关以及热点区分析方法,对城市物流企业空间分布及其演化进行探究。研究表明：（1）近20年来,物流企业区位分布总体处于集聚状态,但BPI呈减小趋势,显示集聚强度减弱;物流空间分布从少数高强度中心向多集聚中心扩散,缺乏全局...     

Developing a multi-network urbanization model: A case study of urban growth in Denver,Colorado

Urbanization is an important issue concerning diverse scientific and policy communities. Computational models quantifying locations and quantities of urban growth offer numerous environmental and socioeconomic benefits. Traditional urban growth models are based on a single-algorithm fitting procedure and thus restricted on their ability to capture spatial heterogeneity. Accordingly, a GIS-based modeling framework titled multi-network urbanization (MuNU) model is developed that integrates multiple neural networks. The MuNU model enables a filtering approach where input data patterns are automatically reallocated into appropriate neural networks with targeted accuracies. We hypothesize that observations classified by individual neural networks share greater homogeneity, and thus modeling accuracy will increase with the integration of multiple targeted algorithms. Land use and land cover data sets of two time snapshots (1977 and 1997) covering the Denver Metropolitan Area are used for model training and validation. Compared to a single-step algorithm – either a stepwise logistic regression or a single neural network – several improvements are evident in the visual output of the MuNU model. Statistical validations further quantify the superiority of the MuNU model and support our hypothesis of effective incorporation of spatial heterogeneity.     

The impact of Hurricane Katrina on urban growth in Louisiana: an analysis using data mining and simulation approaches

ABSTRACT

Understanding human dynamics after a major disaster is important to the region’s sustainable development. This study utilized land cover data to examine how Hurricane Katrina has affected the urban growth pattern in the Mississippi Delta in Louisiana. The study analyzed land cover changes from non-urban to urban in three metropolitan areas, Baton Rouge, New Orleans-Metairie, and Hammond, for two time periods, pre-Katrina (2001–2006) and post-Katrina (2006–2010). The study first applied a focal filter to extract continuous urban areas from the scattered urban pixels in the original remote sensing images. Statistical analyses were applied to develop initial functions between urban growth probability and several driving factors. A genetic algorithm was then used to calibrate the transition function, and cellular automata simulation based on the transition function was conducted to evaluate future urban growth patterns with and without the impact of Hurricane Katrina. The results show that elevation has become a much more important factor after Hurricane Katrina, and urban growth has shifted to higher elevation regions. The elevation most probable for new urban growth increased from 10.84 to 11.90 meters. Moreover, simulated future urban growth in this region indicates a decentralized trend, with more growth occurring in more distant regions with higher elevation. In the New Orleans metropolitan area, urban growth will continue to spill across Lake Pontchartrain to the satellite towns that are more than 50 minutes away by driving from the city center.     

Rediscovering the anatomy of urban growth: The spatio-temporal evolution of building activity in a Mediterranean city

ABSTRACT

The impact of building cycles on recent expansions of Athens was assessed under the hypothesis that non-linear paths of urban growth result from sequential phases of economic growth and decline. Changes over time in building activity were examined by considering indicators derived from a local-scale analysis of building permits issued by Greek municipalities between 1990 and 2016. Relevant socioeconomic forces shaping spatio-temporal variability in building activity were identified by analyzing contextual indicators through inferential techniques and multivariate analysis. The results showed distinctive responses of real-estate local markets to economic cycles at the local scale in Athens, allowing for identification of short-term and long-term urban dynamics characteristic of expansion and recession waves. The most sensitive indicators to economic cycles in Athens were density of new buildings, average floors per new building, density of building additions, and number of building permits per inhabitant. Infrastructure-driven development, as a result of the 2004 Olympic Games, has produced relevant alterations in short-term patterns in the construction market, resulting in spatially-complex urbanization trends. The author concludes that local-scale indicators derived from building permit data provide insights into progressively complex dynamics of urban growth, with implications for regional planning and the design of sustainable development practices.     

中国城市群土地利用互补性比较研究——以14个城市群为例

互补性指基于区域间禀赋差异,借助“流”要素促进区域间优势互补,使得总体效益大于个体之和。从互补性概念出发,以中国14个城市群为案例研究区,借助SPSS对应分析及ArcGIS平台,结合能够反映互补性的统计量指标总惯量,对中国城市群土地利用互补性进行时空分析。结果表明：① 中国城市群土地利用互补性差异较大,以长江经济带为轴,向北向南土地利用互补性增加;② 中国超大型城市群城市用地类型综合化特征显著,土地利用互补性低于全国重要地区城市群;③ 大多数城市群5年间互补性呈现下降趋势,城市间产业同构,缺乏特色。未来在合理的城市群规划基础上,加快相关民生政策跨行政区合作,打破行政壁垒,协调区域间土地供求关系,明确城市功能定位,形成协调互补的城市发展格局。     

Ranking spaces for predicting human movement in an urban environment

A city can be topologically represented as a connectivity graph, consisting of nodes representing individual spaces and links if the corresponding spaces are intersected. It turns out in the space syntax literature that some defined topological metrics can capture human movement rates in individual spaces. In other words, the topological metrics are significantly correlated to human movement rates, and individual spaces can be ranked by the metrics for predicting human movement. However, this correlation has never been well justified. In this paper, we study the same issue by applying the weighted PageRank algorithm to the connectivity graph or space–space topology for ranking the individual spaces, and find surprisingly that: (1) the PageRank scores are better correlated to human movement rates than the space syntax metrics, and (2) the underlying space–space topology demonstrates small world and scale free properties. The findings provide a novel justification as to why space syntax, or topological analysis in general, can be used to predict human movement. We further conjecture that this kind of analysis is no more than predicting a drunkard's walking on a small world and scale free network.     

Modelling sustainable urban growth in a rapidly urbanising region using a fuzzy-constrained cellular automata approach

This article presents an application of a fuzzy-constrained cellular automata model to simulate the spatio-temporal processes of urban growth in the rapidly growing Gold Coast City in Southeast Queensland, Australia. Urban growth has been captured in the model as a continuous process in space and over time, which has been affected by a set of primary and secondary transition rules. The primary transition rules deal with the propensity of a local area for development and the impact of its neighbouring cells on such development, while the secondary transition rules reflect the influences of environmental and institutional factors on urban growth. Application of the model demonstrates its re-applicability to different regions and the effectiveness of the cellular automata technique in studying urban dynamics. It also provides tools to explore sustainable urban growth options under different socio-environmental and planning control factors. A sustainable urban future of the region is achievable if development is managed to maintain a balance amongst ecological conservation, economic growth and the contemporary Australian lifestyle.     

基于空间句法理论的城市群核心区发展边界识别

准确识别当前城市群建设进程中核心区发展边界是研究城市群的一项重要内容。本文提出一种研究思路：采用空间句法分析城市群道路网,将得到的4个分析指标融合成新指标——“城市群集群度”,并提取“城市群集群度”等值线和“城市群集群度”曲线,通过计算找到最佳阈值从而提取出城市群核心区发展边界。以长株潭城市群为例,将基于空间句法的研究结果与基于Densi-Graph方法的研究结果进行对比,在除去数据质量因素后,城市群核心区发展边界识别差异有望控制在10%以内。研究表明：基于空间句法理论的城市群核心区发展边界识别方法容易获取计算数据,适用范围广,可靠性强。