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.

Remote Sensing Data and SLEUTH Urban Growth Model:As Decision Support Tools for Urban Planning

Sri Lanka is experiencing speedy urbanization by converting the agriculture land and other natural land cover into built-up land. The urban population of Sri Lanka is expected to reach to 60% by 2030 from 14% in 2010. The rapid growth in urban population and urban areas in Sri Lanka may cause serious socioeconomic disparities, if they are not handled properly. Thus, planners in Sri Lanka are in need of information about past and future urban growth patterns to plan a better and sustainable urban future for Sri Lanka. In this paper, we analyzed the characteristics of past land use and land cover trends in Matara City of Sri Lanka from 1980 to 2010 to assess the historic urban dynamics. The land use change detection analysis based on remote sensing datasets reveal that the conversion of homestead/garden and paddy into urban land is evident in Matara City. The historic urban trends are projected into the near future by using SLEUTH urban growth model to identify the hot spots of future urbanization and as well as the urban growth patterns in Matara City up to the basic administrative level, i.e., Grama Niladari Divisions(GND). The urban growth simulations for the year 2030 reveal that 29 GNDs out of 66 GNDs in Matara City will be totally converted into urban land. Whereas, 28 GNDs will have urban land cover from 75% to 99% by 2030. The urban growth simulations are further analyzed with respect to the proposed Matara city development plan by the Urban Development Authority(UDA) of Sri Lanka. The results show that the UDA's city development plan of Matara will soon be outpaced by rapid urbanization. Based on the calibration and validation results, the SLEUTH model proved to be a useful planning tool to understand the near future urbanization of Sri Lankan cities.

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.

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.

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.

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.

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。

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。

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。

计及区域建筑群生长特性的动态冷热负荷预测

考虑区域建筑群的动态生长特性,结合负荷计算理论、灰色Verhulst模型及等维新息灰色理论,采用MATLAB构建完整的区域动态冷热负荷预测方法,以常州高铁新城2017—2022年的建筑面积为历史数据,对区域未来10年的冷热负荷进行预测.结果表明,采用基于等维新息灰色理论的Verhulst灰色模型建立的3种业态面积预测方程拟合精度均达到一级.高铁新城未来10年冷热负荷先快速增长后缓慢增长直至饱和,达到饱和的时间约为2030年,冷、热负荷饱和规模分别为436、228 MW,与采用面积指标法的计算结果(冷负荷为472 MW、热负荷为285 MW)相比,分别降低了约7.52%、19.86%.

Cassini Growth of Population Between Two Metropolitan Cities——A Case Study of Beijing-Tianjin Region,China

The existing models of population distribution often focus on the region with a single city or even multiple centers,and lack the detailed explorations of the common and special type of urbanization areas with two centers Taking Beijing-Tia njin region of China,which is a distinct dual-nuclei metropolitan area in the world,as an example and choosing Landsat-5 TM image in 2005,population,etc.as the data,this paper devotes to comprehending and illustrating a model of Cassini growth of population between the two metropolitan cities through the research of spatial population distribution pattern,aided with RS and GIS techniques.Main technical processes include Kriging interpolation of the population data and character simulation of the Cassini ovals.According to the calculation of a/b,a key characteristic index ofCassini growth model,the spatial structures ofpopulation distribution were given.When a/b<1, it is a curve with two separated loops with a population density more than 3000 persons/km2.When a/b=1,it is a lem- niscate curve with a population density about 3000 persons/km2.When 1<a/b<2～(1/2),it is a dog-bone shaped concave curve with a population density between 500-3000 persons/km2.Whena/b=2～(1/2),it is an oblate curve with a population density about 500 persons/km2.Whena/b>2～(1/2),there is an oval-shaped convex curve with a population density less than 500 persons/km2. The results show that owing to the combined action and influence of the regional dual-nuclei,the population distribution of Beijing-Tianjin region is in accord with Cassini model significantly.Therefore,there is Cassini growth of population between the two metropolitan cities in Beijing-Tianjin region.In addition, the process of Cassini growth has extraordinarily instructive significance for judging the development stages of the dual-nuclei metropolitan areas.

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.

基于PSR模型的城市生态韧性成长力评价指标体系构建及应用

加强城市生态韧性建设是提高城市生态安全、改善城市生态环境、增加生态效益、实现城市可持续发展的重要举措。为克服静态分析的局限性,结合三螺旋理论,采用压力-状态-响应(PSR)模型构建了包含16个评价指标的城市生态韧性成长力评价指标体系,并采用主成分分析法和熵值法确定指标综合权重,评估了2017—2020年中国31个城市的生态韧性成长力,进一步引入耦合度及耦合协调度对评估结果进行了分析。结果表明:除乌鲁木齐外其他省会城市的生态韧性成长力水平都呈现先上升后下降再平稳的趋势,城市生态韧性的总体水平螺旋上升;城市生态韧性成长力的耦合协调度呈先升后降、先降后升、不断上升3种情况,且多数城市生态韧性成长力耦合协调度符合先升后降的变化趋势。依据评价结果,为推进城市生态韧性建设提出对策建议。

基于随机森林模型的辽宁省收缩城市未来发展趋势探究

由于城镇水平的高速发展,如何快速有效地遏制收缩城市的进程已然成为人们关注的重点。该文针对收缩城市的分类、影响收缩城市的重要因素和收缩城市未来发展趋势进行分析与讨论。通过对常住人口增长率、随机森林模型的计算,筛选出了2009—2020年辽宁省30个城市中的收缩城市与影响收缩的较大因素,将数据绘制成城市发展指数变化折线图,针对曲线的趋势,对各个收缩城市的未来发展进行合理的分析与预测。

企业异地投资视角下长三角城市经济增长的网络外部性研究

基于企业异地投资数据构建2003—2018年全球、全国及区域3个空间尺度的长三角城市网络,利用空间面板计量模型从分尺度、分时段、分区域等角度分析城市网络对城市经济增长的影响,揭示长三角存在的城市网络外部性特征。结果表明:(1)长三角各尺度城市网络均在持续扩张,且呈现典型的核心-边缘结构特征。(2)各尺度城市网络对城市经济增长均产生积极的影响,但影响程度呈现出全球>全国>区域的尺度差异。(3)随着时间的推移,嵌入全国和区域城市网络所带来的经济效益逐渐超过全球城市网络的影响,这从城市网络的角度证实了长三角地区转向内循环为主,既是现实表现,也是必然选择。(4)城市网络外部性存在明显的区域异质性,位于核心区域的城市在网络中获益较多,但城市网络对位于外围区域的城市影响逐渐增强。(5)与集聚外部性相比,网络外部性的重要性越来越突出,城市发展愈发依赖于建立和维持与其他城市之间联系的能力。

中国地级及以上城市人口与公园面积的非线性增长效应分析

【目的】探究城市人口增长与公园面积扩张之间的响应关系,是“公园城市”理念实施背景下协调二者高质量发展的理论基础。【方法】采用平滑转换回归(smooth transition regression,STR)模型,从全国及不同规模城市尺度,分析1997—2020年城市人口增量与公园面积增量的作用机制及动态演变趋势。【结果】1)全国尺度层面,城市人口增量对公园面积增量的影响关系呈现分段特征,且二者间的线性关系始终存在;当人口增量越过门限参数时,对公园面积增长的非线性影响显现,此时人口增量每增加1%,公园面积增量会正向变动2.90773%;2)城市尺度层面,中、小城市非线性占比较高,对城市人口增量、公园面积增量的贡献率远低于特大、大城市。【结论】研究将城市人口与公园面积增长的线性、非线性关系同步考虑,揭示了二者间的阈值效应及增长变动规律,为优化人口与公园供给关系提供科学依据。