Urban Land Use Dynamic Evolution Simulation And Optimization Based On GIS And Cellular Automata

Cellular Automata (CA) is a kind of discrete grid dynamic model, whose time, space and state are all discrete, and the spatial interaction and causality on time are completely specified in terms of a local relation. The traits of CA such as "from bottom to top" approach, strong complicated computing capability, inherent parallel computing capability, highly dynamic characteristic and spatial concept, etc., have made it very strong on spatial-temporal evolution modelling of the complex system. CA has shown thoroughly the essence of complexity science that "the complicated structure comes from the interaction of the simple subsystem". So CA is suitable to study complex spatial-temporal geographic system, especial for urban land use, and it has been an important tool and research focus for urban land use modeling.This thesis reviewed the literatures of CA model and progress on urban land use modeling thoroughly based on the previous researches. The theoretic framework about cellular automata on urban land use evolution simulation and optimization were analyzed, and the similarities and differences between the interrelated methods and theories with CA were discussed. This thesis mainly focused on the applications and extensions of CA in urban land use modeling and optimization. Firstly, two foreign classical CA models-SLEUTH and DUEM, were introduced with the principles and implementations, and applied with some proper revisions with the parameters. Secondly, tow extended CA models were designed and developed at the platform of MATLAB 7.2. The first CA model is named ULEM model (Urban Land-Use Evolution Model), integrating GIS, Artificial Neural Network (ANN) and CA to model urban land use dynamic evolution; the second CA model is named ULOM model (Urban Land-Use Optimization Model), integrating GIS, Genetic Algorithm (GA) and CA to optimize urban land use spatial structure. Lastly, all the four CA models were applied in the built-up of Lanzhou, China to test the respective suitability and capability. The main contents and conclusions of this thesis were illustrated as following:1 Analysis on characteristics and drive forces of land use dynamic evolution in LanzhouThe medium-resolution GIS database for urban expansion of 1949-2005 with eight different periods and high-resolution GIS database for land use evolution of 1976-2005 with four different periods were established with GIS and remote sensing. At the macro-level, the expansion of 1949-2005 presented obvious phased characteristics: the organic fast expansion period of 1949-1959; unordered high-speed expansion period of 1959-1976; recovery and adjustment period of 1976-1980; accelerated development period of 1993-2001 and new round fast expansion period of 2001-2005. At the micro-level, the characteristics of urban land use dynamic evolution of 1976-2005 in Lanzhou were illustrated as following: (1) The main fast growth of urban land use in 1976-1995 was Institutional and Green land use; (2) The fastest growth of urban land use in 1995-2001 was Commercial land use, then Residential, Industrial and Institutional land use; (3) The growth rate of 2001-2005 was both lower than those of the former two periods, with the main growth of Residential, Commercial and Industrial land use. Urban land use dynamic evolution in Lanzhou was mainly influenced by physical, economic, population, transportation, policy and historical factors, etc.2 Modeling urban land use spatial expansion in Lanzhou based on SLEUTH modelTo SLEUTH model, Monte Carlo iteration number, boom and bust parameters, threshold value of slope, calibration metrics were revised properly; and urban planning and policies influencing urban expansion were all considered synthetically. Urban expansion of 1949-2005 in Lanzhou was simulated with SLEUTH model and landscape spatial metrics, characterizing with diffusive growth in 1949-1978, coalescence growth in 1978-1993 and diffusive growth in 1993-2005. The calibration results under two different scenarios reflected two different urban growth forms, corresponding to the transformation of social-economic institution after the foundation of PRC. Predictions of 2006-2050 under two different scenarios were shown as following: (1) Urban spatial expansion tendency of the second scenario was faster than the first; (2) Coalescence infilling development, renewal and reconstruction were the main growth form for the first scenario, while the diffusive expansion was the main growth form for the second; (3) In the regard of land use restriction, the growth of the first scenario was more sustainable development, while that of the second was closer to the future urban growth; (4) Future urban development in Lanzhou should strengthen land use spatial optimization in the inner-city and control the fast expansion tendency; (5) SLEUTH model has high suitability to river-valley city.3 Modeling urban land use dynamic evolution in Lanzhou based on DUEM modelUrban land use dynamic evolution of 1995-2005 in Lanzhou was simulated with GISand DUEM model. Future evolution tendencies of 2006-2020 were predicted under two different scenarios and illustrated as following: (1) Future urban land use evolution will be mainly centralized in Yantan of Chengguan District, Matan and Cuijiadatan of Qilihe District, Anningbao, Shajingyi, Cuijiazhuang and Yingmentan of Anning District; (2) The growth of Residential and Commercial-Institutional land use for the second scenario will be obviously faster than the first, and the growth of Industrial land use for the second will be a little faster than the first; (3) Evolution tendency for the second will be closer to the future evolution tendency than the first; (4) DUUM model has high suitability to river-valley city.4 Urban land use evolution model (ULEM) integrating ANN and CAAn extended CA model integrating GIS, ANN and CA, named ULEM, was developed based on MATLAB7.2 for urban land use evolution modeling. To ULEM model, the spatial scale, land use criterion, spatial variables, development mode, random sample method of training and algorithm for ANN, calibration method and model developing platform were extended. And there were also some disadvantages for the model, such as time step, the control of model circle and calibration method, etc. Its application in Lanzhou was illustrated as following: (1) The accuracies under two different scenarios with five different parameter combinations were all very high; (1) The increase of random variable v could improve the accuracy of the model obviously, and the increase of the parameterαwould make the simulated spatial patterns of urban land use more scattering for the first scenario; while the changes of v andαhave almost no any influence on the accuracy and pattern for the second; (3) The prediction withα= 1.5 and T = 0.8 may be the best parameters'scenario to model future urban land use dynamic evolution tendency; (4) Urban planning influenced land use evolution in Lanzhou deeply.5 Urban land use optimization model (ULOM) integrating GA and CAAn extended CA model integrating GIS, GA and CA, named ULOM, was developed based on MATLAB7.2 for urban land use spatial optimization. This model was based on land use suitability and restriction, and considered with land use benefit optimization, land use amount optimization and land use spatial optimization with refined land use criterion at the micro-scale. Its application in Lanzhou was shown as following: (1) The industry in Chengguan District should be transferred out of the built-up area as soon as possible; (2) Commercial land use along Zhangye Road, Baiyin Road and Yantan Road, should be further to develop; (3) The growth of Institutional land use will be mainly centralized in Yingmentan of Anning District and Yantan of Chengguan District; (4) The growth of Residential land use will play the emphasis on developing non-urban land use, expect with the replacement from other land use in the inner-city; (5) Urban land use evolution tendency optimized by ULOM model is lined with urban planning, policy and the will of the government; (6) ULOM model has some sensitivity to the spatial scale, and its neighborhood extent will influence urban development pattern or growth form.The applications of SLEUTH and DUEM models, developments of ULEM and ULOM models in this thesis will be meaningful to explore and enrich the theories and methods for geographic system modeling; to enrich and promote the extended applied research of CA in urban modeling; to support and assist urban planning and land use planning in Lanzhou and supply a sound background for sustainable development in Lanzhou. In a world, there are certain innovations in theory and methodology, and applied value for real urban land use system modeling of this thesis. Simultaneously, the research of urban CA model in China is still at the rising stage, the theory, accuracy, spatial scale, facticity and calibration methods for CA model should be further explored and extended.