A REVIEW ON ACCURACY AND UNCERTAINTY OF SPATIAL DATA AND ANALYSES WITH SPECIAL REFERENCE TO URBAN AND HYDROLOGICAL MODELLING <s> URBAN LAND USE SIMULATION MODELS <s> Since mathematical models came to be applied to problems of architectural and urban form, new concepts based on predicting large-scale structure from local rules have emerged through insights originating in computation and biology. The clearest of these are computer models based on cellular automata (CA) and their recent generalization in evolutionary biology and artificial life. Here we show how such models can be used to simulate urban growth and form, thus linking our exposition to the longer tradition of ideas in studies of built form emanating from the â€˜Cambridge Schoolâ€™. We first review developments of CA in general and then in urban systems in particular. We propose a general class of CA models for urban simulation and illustrate two simple applications, the first a simulation of the development of the historical â€˜cellâ€™ city of Savannah, Georgia, the second, a generic hypothetical application. We then show how this generic model can be used to simulate the growth dynamics of a suburban area of a mid-sized North American city, thus illustrating how this approach provides insights into the way microprocesses lead to aggregate development patterns. <s> BIB001 </s> A REVIEW ON ACCURACY AND UNCERTAINTY OF SPATIAL DATA AND ANALYSES WITH SPECIAL REFERENCE TO URBAN AND HYDROLOGICAL MODELLING <s> URBAN LAND USE SIMULATION MODELS <s> Most desktop mapping and GIS applications have focused on mapping and spatial data management for viewing and geo-query of mapped data. However, in many ways geographic information systems (GIS) technology is as different from as it is similar to traditional map processing. Map analysis and GIS modeling involve entirely new spatial reasoning concepts and procedures that are not reflected in our paper map legacy. <s> BIB002 </s> A REVIEW ON ACCURACY AND UNCERTAINTY OF SPATIAL DATA AND ANALYSES WITH SPECIAL REFERENCE TO URBAN AND HYDROLOGICAL MODELLING <s> URBAN LAND USE SIMULATION MODELS <s> Several lessons about the process of calibration were learned during development of a self-modifying cellular automaton model to predict urban growth. This model, part of a global change research project on human-induced land transformations, was used to predict the spatial extent of urban growth 100 years into the future. The context of the prediction was to evaluate urban environmental disturbances such as land use conversion, urban heat island intensification, and greenhouse gas generation. Using data for the San Francisco Bay area as a test case, methods were developed, including interactive and statistical versions of the model, animation and visualization tools, automated testing methods, and Monte Carlo simulations. This presentation will enumerate, analyze, and discuss the lessons learned during the extensive process of model calibration. Experience with the methods developed may have broader use in assisting the rigorous calibration for other CA models, and perhaps those coupled environmental models with an extensive spatial data component. These methods are now under test as the project moves to a new data set for the Washington, D.C.-Baltimore area. <s> BIB003 </s> A REVIEW ON ACCURACY AND UNCERTAINTY OF SPATIAL DATA AND ANALYSES WITH SPECIAL REFERENCE TO URBAN AND HYDROLOGICAL MODELLING <s> URBAN LAND USE SIMULATION MODELS <s> Cellular Automata (CA) have attracted growing attention in urban simulation because their capability in spatial modelling is not fully developed in GIS. This paper discusses how cellular automata (CA) can be extended and integrated with GIS to help planners to search for better urban forms for sustainable development. The cellular automata model is built within a grid-GIS system to facilitate easy access to GIS databases for constructing the constraints. The essence of the model is that constraint space is used to regulate cellular space. Local, regional and global constraints play important roles in affecting modelling results. In addition, 'grey' cells are defined to represent the degrees or percentages of urban land development during the iterations of modelling for more accurate results. The model can be easily controlled by the parameter k using a power transformation function for calculating the constraint scores. It can be used as a useful planning tool to test the effects of different urban develo... <s> BIB004 </s> A REVIEW ON ACCURACY AND UNCERTAINTY OF SPATIAL DATA AND ANALYSES WITH SPECIAL REFERENCE TO URBAN AND HYDROLOGICAL MODELLING <s> URBAN LAND USE SIMULATION MODELS <s> The SLEUTH model (slope, landuse, exclusion, urban extent, transportation and hillshade), formerly called the Clarke Cellular Automaton Urban Growth Model, was developed for and tested on various cities in North America, including Washington, DC, and San Francisco. In contrast, this research calibrated the SLEUTH model for two European cities, the Portuguese metropolitan areas of Lisbon and Porto. The SLEUTH model is a cellular automaton model, developed with predefined growth rules applied spatially to gridded maps of the cities in a set of nested loops, and was designed to be both scaleable and universally applicable. Urban expansion is modeled in a modified two-dimensional regular grid. Maps of topographic slope, land use, exclusions, urban extents, road transportation, and a graphic hillshade layer form the model input. This paper examines differences in the model’s behavior when the obviously different environment of a European city is captured in the data and modeled. Calibration results are included and interpreted in the context of the two cities, and an evaluation of the model’s portability and universality of application is made. Questions such as scalability, sequential multistage optimization by automated exploration of model parameter space, the problem of equifinality, and parameter sensitivity to local conditions are explored. The metropolitan areas present very different spatial and developmental characteristics. The Lisbon Metropolitan Area (the capital of Portugal) has a mix of north Atlantic and south Mediterranean influences. Property is organized in large patches of extensive farmland comprised of olive and corkorchards. The urban pattern of Lisbon and its environs is characterized by rapid urban sprawl, focused in the urban centers of Lisbon, Oeiras, Cascais <s> BIB005
A model is a simplified representation of reality in either material form or symbolic form for purposes of description, explanation and forecasting of planning. GIS modelling involves symbolic representation of locational properties as well as thematic and temporal attributed describing characteristics and conditions of space and time BIB002 . Urban models help scientists to analyse the form, speed and impact of urban growth in the past to assess current trends and to simulate scenarios of future development. A model maybe suitable for one area in terms of parameters and it has to be localized in another research area since the underlying factors of growth are different. An urban model has to be calibrated so as to 'learn' the endogenous characteristics of the particular environment that they explain and simulate BIB005 . However, in order to model urbanisation processes across different areas, it is vital to test the efficiency of the model's algorithms at capturing and simulating the land transformations that are specific to a place BIB001 BIB003 BIB004 . Cellular Automata (CA) models are ideal for modelling land use in areas where data is unavailable and experiencing rapid urban growth  .