A Spatially Heterogeneous Expert Based (SHEB) Urban Growth Model using Model Regionalization

Urbanization changes have been widely examined and numerous urban growth models have been proposed. We introduce an alternative urban growth model specifically designed to incorporate spatial heterogeneity in urban growth models. Instead of applying a single method to the entire study area, we segment the study area into different regions and apply targeted algorithms in each subregion. The working hypothesis is that the integration of appropriately selected region-specific models will outperform a globally applied model as it will incorporate further spatial heterogeneity. We examine urban land use changes in Denver, Colorado. Two land use maps from different time snapshots (1977 and 1997) are used to detect the urban land use changes, and 23 explanatory factors are produced to model urbanization. The proposed Spatially Heterogeneous Expert Based (SHEB) model tested decision trees as the underlying modeling algorithm, applying them in different subregions. In this paper the segmentation tested is the division of the entire area into interior and exterior urban areas. Interior urban areas are those situated within dense urbanized structures, while exterior urban areas are outside of these structures. Obtained results on this model regionalization technique indicate that targeted local models produce improved results in terms of Kappa, accuracy percentage and multi-scale performance. The model superiority is also confirmed by model pairwise comparisons using t-tests. The segmentation criterion of interior/exterior selection may not only capture specific characteristics on spatial and morphological properties, but also socioeconomic factors which may implicitly be present in these spatial representations. The usage of interior and exterior subregions in the present study acts as a proof of concept. Other spatial heterogeneity indicators, for example landscape, socioeconomic and political boundaries could act as the basis for improved local segmentations.

Spatial Effects of Varying Model Coefficients in Urban Growth Modeling in Nairobi, Kenya

Urban land-use modeling has gained increased attention as a research topic over the last decade. This has been attributed to advances in remote sensing and computing technology that now can process several models simultaneously at regional and local levels. In this research we implemented a cellular automata (CA) urban growth model (UGM) integrated in the XULU modeling frame-work (eXtendable Unified Land Use Modeling Platform). We used multi-temporal Landsat satellite image sets for 1986, 2000 and 2010 to map urban land-use in Nairobi. We also tested the spatial effects of varying model coefficients. This approach improved model performance and aided in understanding the particular urban land-use system dynamics operating in our Nairobi study area. The UGM was calibrated for Nairobi and predicted development was derived for the city for the year 2030 when Kenya plans to attain Vision 2030. Observed land-use changes in urban areas were compared to the results of UGM modeling for the year 2010. The results indicate that varying the UGM model coefficients simulates urban growth in different directions and magnitudes. This approach is useful to planners and policy makers because the model outputs can identify specific areas within the urban complex which will require infrastructure and amenities in order to realize sustainable development.

Urban Growth Modelling Using Determinism and Stochasticity in a Touristic Village in Western Greece

Urban development has acquired an important magnitude in touristic places in Greece. Many villages, especially in seaside areas have adapted to touristic requirements by the necessary infrastructures and activities. Pogonia, located in Vonitsa Etoloakarnanias, is a village which has welcomed the opportunity of touristic development. As a result, the house settlements increased 57.5% during the last 8 years. Urban growth modelling using Artificial Neural Networks (ANNs) was applied in order to simulate the urban development in Pogonia village using two methods: determinism and stochasticity. The variables used for deterministic simulation were: distances to roads, urban areas and coastline, slope and elevation. It was found that urban development can be better described using the network of distances between all urban settlements (stochastic approach) rather than using determinism. This can be explained by the importance of the neighbourhood relationships and the interaction between urban settlements, occurred within the interconnected network of the self-organized urban system.

Cointegration Analysis on the Relation between Urbanization and Economic Growth in China

This paper utilizes cointegration theory,error correcting model and Granger causality testing theory to make an empirical research on the relation between urbanization and GDP in China,and also implements a comparative analysis to the relation between three industries and degree of urbanization,the related coeffecient is 0.97,0.95,0.97,0.97.And the result shows a long-term balance between these two factors,and the promoting effect to tertiary industry by urbanization is more obvious.Urbanization and economic growth are the long-term balanced relations.In the long-term balance,every 1% increment of urbanization can make 4.82% increment of GDP;In short-term balance,if the balance depart from the long-term balance at the i-th term,the model will take automatic reversal adjustment with-0.06 adjusting strength at the(i+1)th term,to make it move to the long-term balance.The economic growth onto urbanization is one-way causality relationship,the primary and secondary industry onto urbanization is also one-way causality relationship.However,the tertiary industry onto urbanization is both-way causality relationship.

A Century of Monitoring Urban Growth in Menofya Governorate, Egypt, Using Remote Sensing and Geographic Information Analysis

Urban growth is a global phenomenon mainly driven by the overpopulation growth particularly in developing countries like Egypt. Pattern and extent of urban growth could be monitored and modelled on a spatial and temporal dimension. GIS and remote sensing data along with other thematic maps were used to analyze the urban growth, pattern and extent in the last century in one of the biggest governorates at the heart of the Nile Delta of Egypt. Both spatial and temporal analyses enabled to identify the pattern of urban growth and subsequently project the nature of future growth. However, the overall urban growth in the last century was 12 times the original built up areas in 1910;the third stage from 1950 to 1972 was the highest stage of urban growth with 124% increase of the built-up area. The dominant pattern of urban growth was linear along highways and railways with majority to the North, North East and North West directions. The study developed a spatial model to project urban growth by 2027, indicating that urban growth in the Menofya Governorate would be continued at the same directions with the same pattern with an estimated increase of 33%. The study provided an understanding of the controlling factors which drove the urban growth along this long time.

Modeling urban land use dynamics using Markov-chain and cellular automata in Gondar City,Northwest Ethiopia

Modeling urban land-use dynamics is critical for urban experts’and infrastructure managers’planning.This study attempts to explore the land-use/land-cover(LULC)dynamics of Gondar using satellite images from 1984 to 2020.Markov-Chain and Cellular Automata(MC-CA)models have been recognized as performing well in predicting urban land-use change.However,only a few models work in Ethiopia in general,and no study in Gondar has applied this approach to study urban land-use patterns.Therefore,Gondar land-use/land cover changes of Gondar were predicted using the MC-CA model in IDRISI.The built-up area in Gondar city covered 1413 ha(3%of the total area)in 1984 and increased to 2380 ha(5%)in 1994;21153 ha(45.5%)in 2004;22622 ha(48.7%)in 2014;and 23427 ha(50.5%)in 2020.The area has been predicted to reach 57.5%in the 2050s,showing a faster increase that will cause a very vast loss of farmland.This will increase urban sprawl challenges as well as overall environmental disequilibrium in the preceding decade.Thus,innovative and careful structures and systems in urban planning are required to secure a sustainable urban future and to make our cities livable and competitive in the paradigm of sustainable cities.

The Chinese Urban-rural Dual Economic Structure Model and Analysis

Based on the characteristics of urban-rural dual economic structure in China,we build a dynamic endogenous urban-rural dual economic model closely linked to China's reality,and carry out mathematical economics analysis of optimized conditions for urban and rural sectors. The main results show that:(i) The labor growth rate of urban-rural sectors must be greater than the time discount rate,or else there would be a vicious cycle of diminishing returns in the sectors;(ii) The accumulation rate of physical capital and human capital of urban-rural sectors,and the rate of technological progress,need to be greater than the corresponding depreciation rate plus the time discount rate,otherwise there would be a vicious cycle of diminishing returns in the sectors;(iii) The low accumulation rate in the rural sector,and the occurrence of labor outflow,human capital loss and lack of investment,will expand income gap between urban and rural areas,which is a reason for solidification of urban-rural dual economic structure.

GeoCA-Urban模型在城市增长与土地增值研究中的应用

城市增长与土地增值规律的研究是城市规划中的关键问题,二者的相互影响是一个时空动态变化过程,现有的地理信息系统由于缺乏对时空分析和动态模拟的能力而无法完整地表达这一地理现象。本文提出将地理信息系统技术与城市动态模拟GeoCA-Urban模型有效集成,动态模拟城市增长与土地增值过程,并在分析二者关系规律的基础上进行预测。

Detection on Resources Consumption Drag of Urbanization in China

A unique model of resources consumption drag of urbanization is developed by employing the neo-classical production model and the urbanization relation model. By using this model, it is viable to estimate the resources consumption drag, measured as the reduced speed of urbanization from resources consumption and environmental services. In terms of reduced urbanization process, the aggregated and disaggregated effects from some crucial resources, such as energy, land and water, are calculated and presented. The results show that the drags from energy consumption, land and water in process of China’s urbanization are 0.1061, 0.0036 and 0.1914 percent point respectively and the aggregate drag arrives 0.3010 percent point. With the increasing population and the developing urbanization process in China, the constraints of resources, water and energy in particular cannot be eliminated and the drags will be enhanced and hence the pressure of further urbanization process is still a relatively serious problem.

旅游发展影响经济增长的动态新型城镇化门限效应

将新型城镇化纳入旅游业导向型经济增长研究框架,能够有效拓展对经济增长决定因素的认识视域。文章在量化测度旅游业与新型城镇化综合指数基础上,基于中国2004—2019年省际面板数据,通过构建能够捕捉非线性不对称动态因素的面板门限回归模型,并使用允许门限变量和解释变量同时内生的一阶差分矩估计法,实证检验旅游业对经济增长的新型城镇化门限效应。结果表明,中国旅游业与经济增长之间因新型城镇化水平不同而呈现具有显著双重门限特征的非线性关系,并且旅游业对经济增长的影响随新型城镇化跨越门限值而具备边际效用递增特性。因此,文章认为,增进旅游业与新型城镇化耦合协同,充分发挥新型城镇化在旅游业影响经济增长过程中的渠道作用,能够显著提升旅游业的经济增长效应。

协调发展视角下大南昌都市圈城市增长边界的划定

科学划定城市增长边界(UGB)能合理引导城市发展方向,有效抑制无序蔓延。基于协调发展视角,结合多目标土地利用适宜性评价方法与PLUS模型划定大南昌都市圈刚性UGB及自然增长、政策约束、协调发展3种情景下的弹性UGB。结果表明:①多目标土地利用适宜性呈现空间差异且存在重叠和交叉,协调发展最适宜区与农业生产最适宜区、生态保护最重要区重叠面积相比城镇建设最适宜区均有所下降;②刚性UGB面积占研究区总面积的76.11%,保障大南昌都市圈城市扩张严格遵循生态保护红线和粮食安全底线;③PLUS模型模拟结果总体呈耕地、林地、草地、未利用地减少以及水域和建设用地增加的趋势,其中建设用地扩张最显著,但协调发展情景下城市扩张得到有效约束,且该情景下弹性UGB能有效减缓城市扩张占用农业或生态价值最高区域,更能优化城市景观格局。研究结果有利于引导和实现大南昌都市圈城市可持续发展,也可为其他城市三生空间协调发展提供参考。

基于“双评价”约束和PLUS模型的三重城镇开发边界划定

为解决城镇快速发展带来的用地矛盾和建设用地无序蔓延等问题,该研究以咸阳市为例,基于“双评价”技术方法划定城镇建设适宜区与不适宜区作为约束条件,在此基础上,引入PLUS模型模拟咸阳市2040年土地利用变化情况,最终划定并修正相对应的三重城镇开发边界。结果表明:1)咸阳市南部以城镇发展和农业生产为主,北部以生态保护为主,城镇建设适宜区面积为1368.98 km^(2),不适宜区面积为3853.04 km^(2)。2)PLUS模型模拟得到2040年城镇建设用地面积为133.86 km^(2),与未加约束的自然发展情景相比,未利用地面积明显减少,耕地、林地、建设用地等面积均有增加,有利于实现土地的高效利用。3)划定除城镇建设不适宜区外的底线城镇开发边界、由城镇建设适宜区构成的备用城镇开发边界、以及将2040年城镇建设用地作为范围的优先城镇开发边界面积分别为3863.39、852.28和134.84 km^(2)。该方法划定的城镇开发边界能够满足城镇动态发展的需要,有利于解决城镇发展、耕地保护、生态保护之间的矛盾,并为规划实践提供方法参考和决策依据。

西部地区城市群空间结构调整的经济增长效应:基于动态空间计量模型的检验

城市群已成为中国西部地区经济发展的重要增长极与核心区,其合理有序的空间结构是经济增长的重要源泉。文章基于西部地区八大城市群2004—2020年面板数据,利用动态空间杜宾模型检验西部地区城市群空间结构调整对经济增长的作用效果与作用机制。研究发现:西部地区城市群的人口、产业和土地利用空间结构调整主要表现为空间集聚并显著促进了城市群经济增长;进一步的检验发现,这三类空间结构集聚对经济增长的促进作用在不断增强,且由短期促进演变为短期促进与长期促进并存。在影响机制方面,西部地区城市群人口空间集聚因加重环境污染而抑制了经济增长,但抑制作用明显弱于正向促进作用;产业空间集聚通过促进技术进步推动了经济增长;土地利用空间集聚通过加快产业结构升级促进了经济增长。最后,文章提出了提升城市群中心城市人口承载能力、提高城市群第二产业和第三产业空间集聚度、提高建设用地空间集聚度等政策建议。

江苏省城市建设用地增长贡献及其驱动机理研究

合理有序的城市建设用地增长对促进区域高质量发展具有重要意义。运用城市建设用地增长率、贡献率和LMDI模型,揭示了2012-2017年江苏省城市建设用地增长贡献和增长动因。结果表明:①2012-2017年江苏省城市建设用地增长729.86km^(2),增长率为19.72%,工业用地、道路交通设施用地和居住用地是城市建设用地增长的主要来源,三者的贡献率分别为30.86%、28.55%和22.45%,三者贡献之和高达81.87%;②对城市建设用地增长类型进行划分,连云港、盐城、无锡和常州属于超速增长型,泰州、南通和苏州属于滞后增长型,其余地级市属于同步增长型;③人口、人均GDP和二三产值比重对江苏省及13个地级市的城市建设用地增长具有正向驱动作用,地耗强度对其则具有负向驱动作用,人均GDP是驱动江苏省及13个地级市城市建设用地增长的主导因子,其正向驱动作用明显大于地耗强度的负向驱动作用。

城市内湖藻源污染及生态风险控制研究

针对城市内湖富营养化频发,导致水体生态安全遭到严重危害的问题,以西安市汉城湖为例,通过水动力和富营养化模型,借助边界条件的情景模拟,分析水质恶化原因并提出水质改善方案。结果表明:参数率定后模型拟合度高于0.8,较好地模拟了湖体水质的演变规律,湖体藻类生长受外界环境和营养物质影响,且无机磷对其生长起到重要作用;对水质改善措施效果较好的分别为净化补水水质、加大补水量、增加大型植物种植和浮游动物对藻类的捕获。结合实际情况,可通过调节补水水量、采取引水渠道的生态净化措施和生物操纵组合方案,保障汉城湖水质目标。当补水量不充足时,可将其水力停留时间控制在35 d为最优。

网络基础设施建设、知识流动与城市包容性绿色增长——基于调节中介与链式中介的综合分析框架

网络基础设施作为数字经济发展的“中枢节点”和“传输纽带”,对激活城市包容性增长与绿色偏向发挥着重要作用。本文将宽带中国战略视为网络基础设施的外生政策冲击,并利用修正后的引力模型、非期望产出的Super-EBM模型,对知识流动与包容性绿色增长效率进行测算。在此基础上,从知识流动视角对网络基础设施建设与城市包容性绿色增长的关系进行深入探索。研究发现,第一,网络基础设施建设对城市包容性绿色增长具有显著促进作用,且该作用在非资源型城市更为明显;第二,知识流动是网络基础设施促进城市包容性绿色增长的重要中介机制,该中介机制通过地形起伏度、方言多样性指数等工具变量系统识别后仍然成立;第三,绿色创新与创业活力是网络基础设施驱动城市包容性绿色增长的调节中介机制,两者均能够强化知识流动对城市包容性绿色增长的促进作用;第四,城市间知识流动能够进一步推进市场有效整合,使得网络基础设施对城市包容性绿色增长的机制影响存在明显的链式传导作用。上述结论更深层次地打开了知识流动传导机制黑箱,能够为网络基建规划与城市转型方案提供重要借鉴和政策启示。

城市户籍人口规模增长预测及其对地区GDP的影响——以南京市为例

以南京市为例,探讨城市户籍人口规模增长对地区生产总值的影响。采用线性回归模型、Holt’s线性趋势模型、ARIMA模型、Logistic增长模型、多元线性回归与BP神经网络等多种计量经济学方法预测南京市户籍人口增长趋势,分析其对经济发展的作用。研究结果表明,人口增长与GDP增长呈正相关性,人口增长对经济发展具有推动作用,多种模型的综合应用提升了预测结果的稳定性与准确性。考虑人口增长的质量与结构变化对经济的影响,强调人口特征在经济发展过程中的重要性,可以为城市规划与区域经济战略制定提供理论与实践参考。

城市扩展模型在土地供应空间决策中的应用——以深圳市龙岗区为例

土地供应在城市化进程中起着重要的指导作用,充足而稳定的土地供应是城市发展的必要保障,而其定位的合理也是提升城市健康的重要前提。本文针对当前土地供应科学性不足、缺乏时序性及与相关部门工作无法衔接等问题,选择典型的快速城市化地区深圳市龙岗区为例,整合卫星影像、数字地形、地籍、交通以及各类社会经济统计数据,建立城市用地空间扩展模型,并利用人口预测为基础的城市用地类型增长预测,构建土地供应决策支持系统。结果可得龙岗区近期(2003～2005)和中期(2006～2008)可供应土地的类型、数量和空间分布,以提供龙岗区未来土地供应决策参考。

中国城镇化进程与经济增长关系的实证研究

以我国1978—2009年城镇化率和人均GDP年度时间序列数据为基础,建立反映城镇化水平和经济增长动态关系的向量自回归(VAR)模型;在VAR模型的基础上,运用脉冲响应函数和方差分解分析了城镇化进程与经济增长之间的动态影响。为了弥补时间序列数据只包含时间和指标两维信息的缺陷,进一步采用2000—2009年我国31个省市的城镇化率和人均GDP的面板数据,利用横截面、时间和指标三维信息对两者之间的关系进行分析。通过运用面板数据的单位根检验和面板数据协整检验,得出我国城镇化进程与经济发展水平之间存在长期稳定的均衡关系。在此基础上,建立面板数据固定效应变系数模型,从弹性角度分析,认为我国城镇化率每提高一个百分点,可以维持7.1%的经济增长。

基于水文效应的城市增长边界的确定——以镇江新民洲为例

城市增长边界(UGB)是城市增长管理、控制城市无序蔓延的重要工具,但如何科学定量划定城市增长边界一直是一个技术难题。针对目前城市增长边界定量划定研究的不足,提出一种基于城市水文效应,适用于城市内涝易发区的城市增长边界划定方法。该方法整合了元胞自动机(CA)模型与区域水文模型(SCS),通过CA模型预测城市不透水面积的扩张范围与形态,并以此作为城市水文模型的参数,评估城市淹水面积的比例及风险,最后根据风险水平确定城市增长边界。以镇江新民洲为例,实证研究了该地区的城市增长边界的合理划定,研究发现该区域城市扩张规模控制500 hm2之内,城市在最大降雨条件下城市积水面积的风险水平能有效降低。研究结果可为新民洲的水文风险控制及城市规划提供依据,同时可为其他城市增长边界划定提供方法参考。