Simulation of urban expansion via integrating artificial neural network with Markov chain – cellular automata     

Tingting Xu  Jay Gao  Giovanni Coco 《International journal of geographical information science》2019,33(10):1960-1983

Accurate simulations and predictions of urban expansion are critical to manage urbanization and explicitly address the spatiotemporal trends and distributions of urban expansion. Cellular Automata integrated Markov Chain (CA-MC) is one of the most frequently used models for this purpose. However, the urban suitability index (USI) map produced from the conventional CA-MC is either affected by human bias or cannot accurately reflect the possible nonlinear relations between driving factors and urban expansion. To overcome these limitations, a machine learning model (Artificial Neural Network, ANN) was integrated with CA-MC instead of the commonly used Analytical Hierarchy Process (AHP) and Logistic Regression (LR) CA-MC models. The ANN was optimized to create the USI map and then integrated with CA-MC to spatially allocate urban expansion cells. The validated results of kappa and fuzzy kappa simulation indicate that ANN-CA-MC outperformed other variously coupled CA-MC modelling approaches. Based on the ANN-CA-MC model, the urban area in South Auckland is predicted to expand to 1340.55 ha in 2026 at the expense of non-urban areas, mostly grassland and open-bare land. Most of the future expansion will take place within the planned new urban growth zone.  相似文献   

瓦氏黄颡鱼(Pelteobagrus vachellii)Toll样受体2(TLR2)基因克隆及免疫功能     

覃川杰  龚全  文正勇  袁登越  王均  贺扬  邵婷 《海洋与湖沼》2018,49(1):198-206

为探究Toll样受体2(Toll-like receptor 2,TLR2)及下游免疫分子对瓦氏黄颡鱼(Pelteobagrus vachellii)机体的保护作用,本研究采用RT-PCR及RACE法获得瓦氏黄颡鱼TLR2全长c DNA(2611bp),编码789个氨基酸残基,含有10个富含亮氨酸的重复序列(Leucine Rich Repeat,LRR)和Toll/IL-1R(Toll/IL-1 Receptor Domain,TIR)同源区结构域,属I型跨膜受体。序列同源性比对发现,瓦氏黄颡鱼TLR2 c DNA与斑点叉尾、鲤及虹鳟的同源性分别为78%、62%及49%。系统进化树分析表明,瓦氏黄颡鱼TLR2与斑点叉尾聚为一支。q RT-PCR分析表明,TLR2 m RNA在检测的组织中均有表达,且在头肾和脾脏中表达水平显著高于其他组织(P0.05)。嗜水气单胞菌感染能显著上调瓦氏黄颡鱼肝脏、头肾及脾脏中TLR2 m RNA表达(P0.05),分别在24h、48h及12h达到最大值。头肾中的TLR 2信号通路下游的髓样分化因子、半胱氨酸蛋白酶8、核转录因子kappa B、肿瘤坏死因子α、白细胞介素1βm RNA均显著上升(P0.05),分别在24h、12h、48h,48h和48h达到最大值。结果表明,嗜水气单胞菌感染激活了TLR2信号通路,通过上调表达,肿瘤坏死因子α,白细胞介素1β等。本研究表明,TLR2在瓦氏黄颡鱼抵御嗜水气单胞菌侵染的过程中发挥了重要的免疫作用。  相似文献   

顾及地类转换差异的城市空间扩展元胞自动机模型及应用研究     

于明明  曾永年 《地球信息科学学报》2018,20(1):48-56

元胞自动机模型已经成为城市空间扩展模拟研究的重要方法之一,并得到广泛应用。然而,现有的城市扩展元胞自动机模型仍存在不足。由于元胞状态设置较为简单,从而使模型转换规则中对不同用地类型向城市用地转换的差异与强度考虑不够。基于此本文在元胞自动机模型的框架下,设计了多元结构的元胞状态及转换规则,提出了顾及地类转换差异与强度的城市扩展元胞自动机模型。在计算非城市用地向城市用地转换的转换概率时,该模型考虑了3个方面的概率：① 地形地貌、经济发展等城市发展的驱动因素对城市用地扩展的影响概率,该概率采用logistics方法进行计算;② 邻域元胞的用地类型对中心元胞转换概率的影响,该概率采用扩展摩尔型方法进行计算;③ 不同类型的非城市用地（本研究中包括耕地、林地和裸地3种类型）向城市用地转换的强度,该概率由模拟基期土地利用数据与目标年份土地利用数据的叠加,得出不同类型的非城市用地在此时间段内向城市用地转换的规模,进而确定不同类型的非城市用地向城市用地转换的强度。最后,将以上3种概率的乘积作为元胞转换的概率。通过转换概率与转换阈值的对比判断中心元胞是否在下一个阶段转换为城市用地。经过迭代计算,不断增加城市用地元胞的数量。当模拟城市用地的结果与目标年份的城市用地规模差值在一定的范围内时停止模拟,得出最终结果。模型构建完成后,本文以长株潭城市群核心区为例进行了模拟实验。以2001年该地区的土地利用数据为基期数据,模拟2010年该地区的城市用地规模和空间分布。研究结果表明,根据本文提出的模型模拟的城市扩展结果与真实数据相比具有较高的一致性。模拟结果正确率达到68.66%,比基于传统logistics回归的元胞自动机模型的模拟精度提高了4.25%,Kappa系数为0.675。该模型较好地模拟了长株潭城市群核心区城市扩展,在城市空间扩展模拟中具有较好的适应性与有效性。  相似文献   

Modelling coastal land use change by incorporating spatial autocorrelation into cellular automata models   总被引：1，自引：0，他引：1  

Yongjiu Feng  Qianqian Yang  Zhonghua Hong  Li Cui 《国际地球制图》2018,33(5):470-488

This paper presents a spatial autoregressive (SAR) method-based cellular automata (termed SAR-CA) model to simulate coastal land use change, by incorporating spatial autocorrelation into transition rules. The model captures the spatial relationships between explained and explanatory variables and then integrates them into CA transition rules. A conventional CA model (LogCA) based on logistic regression (LR) was studied as a comparison. These two CA models were applied to simulate urban land use change of coastal regions in Ningbo of China from 2000 to 2015. Compared to the LR method, the SAR model yielded smaller accumulated residuals that showed a random distribution in fitting the CA transition rules. The better-fitting SAR model performed well in simulating urban land use change and scored an overall accuracy of 85.3%, improving on the LogCA model by 3.6%. Landscape metrics showed that the pattern generated by the SAR-CA model has less difference with the observed pattern.  相似文献   

Dynamic land use change simulation using cellular automata with spatially nonstationary transition rules   总被引：2，自引：0，他引：2  

Yongjiu Feng  Xiaohua Tong 《地理信息系统科学与遥感》2018,55(5):678-698

The dynamic relationships between land use change and its driving forces vary spatially and can be identified by geographically weighted regression (GWR). We present a novel cellular automata (GWR-CA) model that incorporates GWR-derived spatially varying relationships to simulate land use change. Our GWR-CA model is characterized by spatially nonstationary transition rules that fully address local interactions in land use change. More importantly, each driving factor in our GWR model contains effects that both promote and resist land use change. We applied GWR-CA to simulate rapid land use change in Suzhou City on the Yangtze River Delta from 2000 to 2015. The GWR coefficients were visualized to highlight their spatial patterns and local variation, which are closely associated with their effects on land use change. The transition rules indicate low land conversion potential in the city’s center and outer suburbs, but higher land conversion potential in the inner near suburbs along the belt expressway. Residual statistics show that GWR fits the input data better than logistic regression (LR). Compared with an LR-based CA model, GWR-CA improves overall accuracy by 4.1% and captures 5.5% more urban growth, suggesting that GWR-CA may be superior in modeling land use change. Our results demonstrate that the GWR-CA model is effective in capturing spatially varying land transition rules to produce more realistic results, and is suitable for simulating land use change and urban expansion in rapidly urbanizing regions.  相似文献   

基于影响因子动态更新的都市圈国土-人口协同模拟     

高位  涂伟  李明晓  方碧宸  陈栋胜  黄正东  贺彪 《地球信息科学学报》2022,24(8):1502-1511

都市圈作为典型的复杂巨系统,其国土、人口、交通等要素呈现出共同演化、协同发展的特征。现有基于元胞自动机的空间模拟方法通常分别进行国土或人口模拟,忽略了国土、人口之间的协同演化,从而限制了模拟性能。本文提出一种影响因子动态更新策略用以表征国土、人口两种要素间的相互作用,拓展经典元胞自动机模型构建协同模拟算法,实现了都市圈国土与人口空间分布态势的精准模拟。本文以深莞惠都市圈为例,对提出算法进行了实验验证。实验结果表明,本文提出协同模拟算法在深莞惠都市圈的国土模拟品质因素为0.274、人口模拟平均绝对百分比误差23.55%,分别优于传统基于随机森林的元胞自动机算法0.24和29.33%;相较于传统模型,在国土模拟中本模型在对于建设用地的模拟准确度提升了约3%,在人口模拟中本模型在对人口高密度的区域模拟误差降低了约6%。本文进一步预测了深莞惠都市圈2030年国土和人口发展空间态势。研究结果可为都市圈重大基础设施选址和发展情景推演提供技术支撑。  相似文献   

Simulation of landscape spatial layout evolution in rural-urban fringe areas: a case study of Ganjingzi District   总被引：2，自引：0，他引：2  

Jun Yang  Andong Guo  Yonghua Li  Yuqing Zhang  Xueming Li 《地理信息系统科学与遥感》2019,56(3):388-405

In recent years, the rapid expansion of urban spaces has accelerated the mutual evolution of landscape types. Analyzing and simulating spatio-temporal dynamic features of urban landscape can help to reveal its driving mechanisms and facilitate reasonable planning of urban land resources. The purpose of this study was to design a hybrid cellular automata model to simulate dynamic change in urban landscapes. The model consists of four parts: a geospatial partition, a Markov chain (MC), a multi-layer perceptron artificial neural network (MLP-ANN), and cellular automata (CA). This study employed multivariate land use data for the period 2000–2015 to conduct spatial clustering for the Ganjingzi District and to simulate landscape status evolution via a divisional composite cellular automaton model. During the period of 2000–2015, construction land and forest land areas in Ganjingzi District increased by 19.43% and 15.19%, respectively, whereas farmland, garden lands, and other land areas decreased by 43.42%, 52.14%, and 75.97%, respectively. Land use conversion potentials in different sub-regions show different characteristics in space. The overall land-change prediction accuracy for the subarea-composite model is 3% higher than that of the non-partitioned model, and misses are reduced by 3.1%. Therefore, by integrating geospatial zoning and the MLP-ANN hybrid method, the land type conversion rules of different zonings can be obtained, allowing for more effective simulations of future urban land use change. The hybrid cellular automata model developed here will provide a reference for urban planning and policy formulation.  相似文献   

Modelling controls on aeolian dune‐field pattern evolution     

ERIN EASTWOOD  JOANNA NIELD  ANDREAS BAAS  GARY KOCUREK 《Sedimentology》2011,58(6):1391-1406

A second‐generation, source‐to‐sink cellular automaton‐based model presented here captures and quantifies many of the factors controlling the evolution of aeolian dune‐field patterns by varying only a small number of parameters. The role of sediment supply, sediment availability and transport capacity (together defined as sediment state) in the development and evolution of an aeolian dune‐field pattern over long time scales is quantified from model simulations. Seven dune‐field patterns can be classified from simulation results varying the sediment supply and transport capacity that control the type and frequency of dune interactions, the sediment availability of the system and, ultimately, the development of dune‐field patterns. This model allows predictions to be made about the range of sediment supply and wind strengths required to produce the dune‐field patterns seen in the real world. A new clustered dune‐field pattern is identified from model results and used to propose an alternative mechanism for the formation of superimposed dunes. Bedforms are hypothesized to cluster together, simultaneously forming two spatial scales of bedforms without first developing a large basal dune with small superimposed dunes. Manipulation of boundary conditions produces evolving dune fields with different spatial configurations of sediment supply. Trends of spacing and crest length increase with decreasing variability as the dune field matures. This simple model is a valuable tool which can be used to elucidate the dominant control of aeolian sediment state on the construction and evolution of aeolian dune‐field patterns.  相似文献   

粗粒土三轴试验数值模拟与试样颗粒初始架构初探   总被引：4，自引：1，他引：3  

王光进  杨春和  张超  马洪岭  冒海军  侯克鹏 《岩土力学》2011,32(2):585-592

试样颗粒初始架构是粗粒土室内三轴试验中一个难以人为控制的因素。基于元胞自动机方法,结合粗粒土的室内三轴试验开发了能制备不同颗粒初始架构粗粒土试样的HHC-CA模型,该模型制备的粗粒土试样表征了粗粒土各粒组分布的不均匀性和随机性,再借助FLAC3D进行粗粒土三轴数值模拟试验,并探讨了试样剪切带内的砾石含量和试样砾石含量对内摩擦角的影响。数值模拟结果表明,同一粒径级配下,粗粒土的内摩擦角值与剪切带内的砾石含量呈增函数关系;试样砾石含量的增加可能会出现内摩擦角减小的现象,但同一粒径级配下的内摩擦角均值随试样砾石含量的增加而明显增大。  相似文献   

基于逻辑回归CA模型的溢油模拟与预测     

张亦汉  吴秉琦  吴青 《测绘与空间地理信息》2015,(6):10-12

结合逻辑回归方法和元胞自动机模型构建了逻辑回归CA模型,模型中的逻辑回归方法能够很方便地获取影响因子的权重,再设置起止条件等,便可以模拟出溢油的动态变化情况。把模型应用到Deep Spill项目的溢油模拟实验中,结果表明,从模型结果的形态看,模拟结果与检验结果吻合程度较高,能够很好地模拟出溢油扩散与漂移等重要的溢油特性。从统计分析中可知,模拟结果的总精度可达96.8%,Kappa系数达到0.834。  相似文献