Modeling urban expansion scenarios by coupling cellular automata model and system dynamic model in Beijing, China

Spatially explicit urban expansion models that can trace urban development in the past and predict the expansion scenarios in the future are indispensable for examining urban planning policies. This paper demonstrates a new urban expansion scenario (UES) model by coupling one “bottom-up” cellular automata (CA)-based model and one “top-down” system dynamics (SD)-based model. By implementing the UES model in Beijing, the urban evolution from 1991 to 2004 was simulated and the UESs from 2004 to 2020 were predicted. The results suggest that a dilemma of urban expansion versus limited water resource and environment deterioration exists. Dealing with such a dilemma remains a challenge for the local government.     

A partitioned and asynchronous cellular automata model for urban growth simulation

Cellular automata (CA) models are used to analyze and simulate the global phenomenon of urban growth. However, these models are characterized by ignoring spatially heterogeneous transition rules and asynchronous evolving rates, which make it difficult to improve urban growth simulations. In this paper, a partitioned and asynchronous cellular automata (PACA) model was developed by implementing the spatial heterogeneity of both transition rules and evolving rates in urban growth simulations. After dividing the study area into several subregions by k-means and knn-cluster algorithms, a C5.0 decision tree algorithm was employed to identify the transition rules in each subregion. The evolving rates for cells in each regularly divided grid were calculated by the rate of changed cells. The proposed PACA model was implemented to simulate urban growth in Wuhan, a large city in central China. The results showed that PACA performed better than traditional CA models in both a cell-to-cell accuracy assessment and a shape dimension accuracy assessment. Figure of merit of PACA is 0.368 in this research, which is significantly higher than that of partitioned CA (0.327) and traditional CA (0.247). As for the shape dimension accuracy, PACA has a fractal dimension of 1.542, which is the closest to that of the actual land use (1.535). However, fractal dimension of traditional CA (1.548) is closer to that of the actual land use than that of partitioned CA (1.285). It indicates that partitioned transition rules play an important role in the cell-to-cell accuracy of CA models, whereas the combination of partitioned transition rules and asynchronous evolving rates results in improved cell-to-cell accuracy and shape dimension accuracy. Thus, implementing partitioned transition rules and asynchronous evolving rates yields better CA model performance in urban growth simulations due to its accordance with actual urban growth processes.     

论地理信息科学的发展

该文阐述 1995年以来 ,中国地理学界关于 3S(RemoteSensing ,GlobalPositioningSystemandGeographicalIn formationSystem)的研究与应用 ;1998年以来 ,对数字地球有所介绍与了解 ;2 0 0 0年以来 ,对对地观测系统给予充分的关注。国外有“地理信息科学”的杂志 ,国外也有将 3S称为空间信息技术 (SpatialInformationTechnique )的。该文作者长期以来研究并讲授地理信息科学、地理信息系统、地理信息系统工程、全球定位系统等课程 ,提出航天信息与地理信息一体化网络系统 ,是一个开放的、复杂的信息巨系统 ,进而提出了新一代的地理信息系统 ;以天地信息一体化网络系统为基础 ,提出了天地人机关系 ,发展了地理学中的人地关系 ;并且论述了地理信息科学是可持续发展信息社会的重要支柱 ;指出地理信息科学研究的方向与前景。     

A travel time-based variable grid approach for an activity-based cellular automata model

Urban growth and population growth are used in numerous models to determine their potential impacts on both the natural and the socio-economic systems. Cellular automata (CA) land-use models became popular for urban growth modelling since they predict spatial interactions between different land uses in an explicit and straightforward manner. A common deficiency of land-use models is that they only deal with abstract categories, while in reality, several activities are often hosted at one location (e.g. population, employment, agricultural yield, nature…). Recently, a multiple activity-based variable grid CA model was proposed to represent several urban activities (population and economic activities) within single model cells. The distance-decay influence rules of the model included both short- and long-distance interactions, but all distances between cells were simply Euclidean distances. The geometry of the real transportation system, as well as its interrelations with the evolving activities, were therefore not taken into account. To improve this particular model, we make the influence rules functions of time travelled on the transportation system. Specifically, the new algorithm computes and stores all travel times needed for the variable grid CA. This approach provides fast run times, and it has a higher resolution and more easily modified parameters than the alternative approach of coupling the activity-based CA model to an external transportation model. This paper presents results from one Euclidean scenario and four different transport network scenarios to show the effects on land-use and activity change in an application to Belgium. The approach can add value to urban scenario analysis and the development of transport- and activity-related spatial indicators, and constitutes a general improvement of the activity-based CA model.     

论地理信息系统在考古学中的应用

回顾了地理信息系统(GIS)在考古学中应用的发展历程和实例,分析了GIS与考古学之间的内在关系.GIS的各种功能可以用于考古研究的各个环节和许多分支,在考古学中应用GIS不仅具有可能性,而且具有必要性或必然性,这有利于提高考古学的工作效率和研究水平.因此,应当给GIS在考古学中以适当的定位,不应该看作是可有可无的.此外,作者讨论了应用中存在的限制和问题,对GIS在考古学中的应用提出了一些看法和建议:应当结合中国的特点,把GIS应用于解决中国考古研究中的具体问题;为了把GIS的空间分析功能应用于考古学,非常需要培养既懂考古也懂GIS的复合型人才.     

Social Applications of Geographical Information Systems: technical tools for social innovation

ABSTRACT

The establishment of the National Key Centre for Social Applications of Geographical Information Systems (GIS) in 1995, under the directorship of Professor Graeme Hugo, was a turning point in the use of GIS in Australia. The field of GIS, previously dominated by environmental applications, now broadened its focus to include populations, services and the interactions between people and the environment. Social applications of GIS offered a unique opportunity to make service planning, reporting, funding allocations and research both smarter and fairer. Geography and geographic relationships as implemented in GIS became the integrating platform for social spatial information, invigorating social research, planning and policy. A key strength of this approach, recognised by Professor Hugo, was the ability to ‘put people back into the planning process’. Further to being an integrating platform, GIS also offered the ability to generate new information and knowledge, which could facilitate evidence-based decision making. This paper focuses in particular on providing a written record of the development of the Accessibility/Remoteness Index of Australia (ARIA) suite of spatial accessibility indices. The lasting legacy and continued relevance of this work in social applications of GIS is also reviewed in this paper, with reference to key examples of how social research and planning in Australia have been made both smarter and fairer through the contributions of Professor Hugo and his team.     

基于局部化转换规则的元胞自动机土地利用模型

传统土地利用元胞自动机(Cellular automata,CA)模型基于空间同质性假设,使用全局性模型建立元胞转换规则,忽略了土地利用变化驱动因素的驱动作用在空间上的变化。以美国佛罗里达州的橙县(Orange County)2003-2009年土地利用变化为例,提出了基于局部化转化规则的CA土地利用模型,其中元胞的土地利用类型适宜性由地理加权多项logit模型(Geographically weighted multinomial logit,GWML)获得。结果表明:GWML模型较传统全局性多项logit(Multinomial logit,MNL)模型有更高的数据解释能力。基于GWML模型的土地利用CA模型能反映局部土地利用变化模式,因而较基于MNL模型的CA模型具有更高的模拟精度。所得结论对未来国内地区的研究有借鉴意义。     

Exploring the performance of spatio-temporal assimilation in an urban cellular automata model

Urban cellular automata (CA) models propagate and accumulate errors during the modeling process due to the model structure or stochastic processes involved. It is feasible to assimilate real-time observations into an urban CA model to reduce model uncertainties. However, the assimilation performance is sensitive to the spatio-temporal units in the assimilation algorithm, that is, spatial block size and window length (temporal interval). In this study, we coupled an assimilation model, an ensemble Kalman filter (EnKF) and a Logistic-CA model to simulate the urban dynamic in Beijing over a period of two decades. Our results indicate that the coupled EnKF-CA model outperforms the CA-alone counterpart by about 10% in terms of the figure of merit, which reflects the agreement of modeled pixels. We also find that the assimilation performance using a finer block (1 km) is better than that using a coarser block (5 km and 10 km) because of the better depiction of spatial heterogeneity using a finer block. Moreover, the improvement of intermediate outputs using the coupled EnKF-CA model is effective for a certain period (e.g. 5 years). This implies that a high-frequency assimilation may not significantly improve the model performance. The sensitivity analyses of spatio-temporal assimilation in the EnKF-CA model provide a better understanding of the assimilation mechanism that couples with land-use change models.     

Modeling dynamic urban land-use change with geographical cellular automata and generalized pattern search-optimized rules

A novel generalized pattern search (GPS)-based cellular automata (GPS-CA) model was developed to simulate urban land-use change in a GIS environment. The model is built on a fitness function that computes the difference between the observed results produced from remote-sensing images and the simulated results produced by a general CA model. GPS optimization incorporating genetic algorithms (GAs) searches for the minimum difference, i.e. the smallest accumulated residuals, in fitting the CA transition rules. The CA coefficients captured by the GPS method have clear physical meanings that are closely associated with the dynamic mechanisms of land-use change. The GPS-CA model was applied to simulate urban land-use change in Kunshan City in the Yangtze River Delta from 2000 to 2015. The results show that the GPS method had a smaller root mean squared error (0.2821) than a logistic regression (LR) method (0.5256) in fitting the CA transition rules. The GPS-CA model thus outperformed the LR-CA model, with an overall accuracy improvement of 4.7%. As a result, the GPS-CA model should be a superior tool for modeling land-use change as well as predicting future scenarios in response to different conditions to support the sustainable urban development.     

基于Web Service的分布式互操作的GIS

分布式、可互操作的Web GlS一直是人们追求的目标，传统的Web GIS建立于B／S结构之上，该文介绍一种新型的Web GIS，即基于Web Service的GIS。Web Service是近几年发展起来的基于网络的新技术，基于Web Ser—vice的地理信息系统具有分布式、可互操作、方便集成现有GIS资源的特点并具有良好的扩展性，是Web GIS自勺发展趋势。该文介绍了基于Web Service的分布式互操作的GIS的特点、提出了其系统框架，并阐述了其关键技术，包括：地理对象在Web Service中的表达，服务的描述、发现、注册，以及用Web Serivce集成现有的GIS系统等。     

Characterization of neighborhood sensitivity of an irregular cellular automata model of urban growth

The neighborhood definition, which determines the influence on a cell from its nearby cells within a localized region, plays a critical role in the performance of a cellular automaton (CA) model. Raster CA models use a cellular grid to represent geographic space, and are sensitive to the cell size and neighborhood configuration. However, the sensitivity of vector-based CAs, an alternative to the raster-based counterpart, to neighborhood type and size remains uninvestigated. The present article reports the results of a detailed sensitivity analysis of an irregular CA model of urban land use dynamics. The model uses parcel data at the cadastral scale to represent geographic space, and was implemented to simulate urban growth in Central Texas, USA. Thirty neighborhood configurations defined by types and sizes were considered in order to examine the variability in the model outcome. Results from accuracy assessments and landscape metrics confirmed the model’s sensitivity to neighborhood configurations. Furthermore, the centroid intercepted neighborhood with a buffer of 120 m produced the most accurate simulation result. This neighborhood produced scattered development while the centroid extent-wide neighborhood resulted in a clustered development predominantly near the city center.     

Constructing Interfaces between (and within) Geographical Information Systems

Abstract

An interface is a software package used, alone or in conjunction with other interfaces, to transfer data from one geographical information system to another, or between different representations within a single GIS. The aim in this paper is to extend the traditional view of an interface to include interfaces that use communication networks to move data between (and within) GIS. We suggest that, to exchange data across a network, the best solution may be to construct a set of communicating interfaces, each able to send data to, and receive data from, other communicating interfaces. We describe a working set of communicating interfaces that transfer data between a number of GIS data representations.     

A high-performance cellular automata model for urban simulation based on vectorization and parallel computing technology

Cellular automata (CA) models can simulate complex urban systems through simple rules and have become important tools for studying the spatio-temporal evolution of urban land use. However, the multiple and large-volume data layers, massive geospatial processing and complicated algorithms for automatic calibration in the urban CA models require a high level of computational capability. Unfortunately, the limited performance of sequential computation on a single computing unit (i.e. a central processing unit (CPU) or a graphics processing unit (GPU)) and the high cost of parallel design and programming make it difficult to establish a high-performance urban CA model. As a result of its powerful computational ability and scalability, the vectorization paradigm is becoming increasingly important and has received wide attention with regard to this kind of computational problem. This paper presents a high-performance CA model using vectorization and parallel computing technology for the computation-intensive and data-intensive geospatial processing in urban simulation. To transfer the original algorithm to a vectorized algorithm, we define the neighborhood set of the cell space and improve the operation paradigm of neighborhood computation, transition probability calculation, and cell state transition. The experiments undertaken in this study demonstrate that the vectorized algorithm can greatly reduce the computation time, especially in the environment of a vector programming language, and it is possible to parallelize the algorithm as the data volume increases. The execution time for the simulation of 5-m resolution and 3 × 3 neighborhood decreased from 38,220.43 s to 803.36 s with the vectorized algorithm and was further shortened to 476.54 s by dividing the domain into four computing units. The experiments also indicated that the computational efficiency of the vectorized algorithm is closely related to the neighborhood size and configuration, as well as the shape of the research domain. We can conclude that the combination of vectorization and parallel computing technology can provide scalable solutions to significantly improve the applicability of urban CA.     

A hybrid parallel cellular automata model for urban growth simulation over GPU/CPU heterogeneous architectures

As an important spatiotemporal simulation approach and an effective tool for developing and examining spatial optimization strategies (e.g., land allocation and planning), geospatial cellular automata (CA) models often require multiple data layers and consist of complicated algorithms in order to deal with the complex dynamic processes of interest and the intricate relationships and interactions between the processes and their driving factors. Also, massive amount of data may be used in CA simulations as high-resolution geospatial and non-spatial data are widely available. Thus, geospatial CA models can be both computationally intensive and data intensive, demanding extensive length of computing time and vast memory space. Based on a hybrid parallelism that combines processes with discrete memory and threads with global memory, we developed a parallel geospatial CA model for urban growth simulation over the heterogeneous computer architecture composed of multiple central processing units (CPUs) and graphics processing units (GPUs). Experiments with the datasets of California showed that the overall computing time for a 50-year simulation dropped from 13,647 seconds on a single CPU to 32 seconds using 64 GPU/CPU nodes. We conclude that the hybrid parallelism of geospatial CA over the emerging heterogeneous computer architectures provides scalable solutions to enabling complex simulations and optimizations with massive amount of data that were previously infeasible, sometimes impossible, using individual computing approaches.     

A complete classification of spatial relations using the Voronoi-based nine-intersection model

In this article we show that the Voronoi-based nine-intersection (V9I) model proposed by Chen et al. (2001, A Voronoi-based 9-intersection model for spatial relations. International Journal of Geographical Information Science, 15 (3), 201–220) is more expressive than what has been believed before. Given any two spatial entities A and B, the V9I relation between A and B is represented as a 3 × 3 Boolean matrix. For each pair of types of spatial entities that is, points, lines, and regions, we first show that most Boolean matrices do not represent a V9I relation by using topological constraints and the definition of Voronoi regions. Then, we provide illustrations for all the remaining matrices. This guarantees that our method is sound and complete. In particular, we show that there are 18 V9I relations between two areas with connected interior, while there are only nine four-intersection relations. Our investigations also show that, unlike many other spatial relation models, V9I relations are context or shape sensitive. That is, the existence of other entities or the shape of the entities may affect the validity of certain relations.     

An intelligent expert system shell for knowledge-based Geographical Information Systems: 1. The tools

Abstract

An intelligent expert system shell for the development of knowledge-based geographical information systems (GIS) is examined in this two-part article. Basic concepts and the overall architecture of the shell are discussed in the present part. Fuzzy logic and expert systems technology are demonstrated to be appropriate methods for approximating human reasoning and enhancing the level of intelligence in GIS. The shell can be employed as an effective and efficient tool for developing knowledge-based GIS.     

Parallel cellular automata for large-scale urban simulation using load-balancing techniques

Cellular automata (CA), which are a kind of bottom-up approaches, can be used to simulate urban dynamics and land use changes effectively. Urban simulation usually involves a large set of GIS data in terms of the extent of the study area and the number of spatial factors. The computation capability becomes a bottleneck of implementing CA for simulating large regions. Parallel computing techniques can be applied to CA for solving this kind of hard computation problem. This paper demonstrates that the performance of large-scale urban simulation can be significantly improved by using parallel computation techniques. The proposed urban CA is implemented in a parallel framework that runs on a cluster of PCs. A large region usually consists of heterogeneous or polarized development patterns. This study proposes a line-scanning method of load balance to reduce waiting time between parallel processors. This proposed method has been tested in a fast-growing region, the Pearl River Delta. The experiments indicate that parallel computation techniques with load balance can significantly improve the applicability of CA for simulating the urban development in this large complex region.