土地利用总体规划中心城区建设用地布局研究
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摘要
当前我国经济正处于快速增长阶段,工业化、城市化水平不断提高,一个显著特征就是对土地的需求日益膨胀,建设用地总量频频突破规划。而土地资源的稀缺性和不可再生性,再加上中国人多地少的现实,导致建设用地日趋紧张,已经成为目前经济发展中最主要的限制瓶颈之一。另一方面,在国家不断加强耕地保护,保证国家粮食安全的大背景下,要求在土地利用总体规划中,落实上级规划确定的各类用地控制指标和空间布局要求,做到图数一致。因此,如何将有限的建设用地资源落实到空间上,实现建设用地的合理布局,发挥建设用地的最大效益,保障社会经济又好又快发展,已经成为了现阶段我国土地利用总体规划编制的重要任务。同时,中心城区建设用地是区域经济发展的核心与载体,其布局优化直接关系到整个区域社会经济的可持续发展和生态环境的保护,对于引导和控制未来的土地利用有着重要意义。
     目前,城市的发展过程,被普遍认为是一个复杂系统,具有动态性、开放性、自组织性和非平衡性等耗散结构特征。同时,城市也存在着他组织,其发展过程受到人为意志的宏观干预,需要通过规划协调各子系统、各行为主体多元目标间产生的矛盾,弥补城市自组织过程中存在的自发性、盲目性和滞后性的缺陷。因此,本文基于城市复杂系统的视角,对土地利用总体规划中心城区建设用地优化布局进行理论与实证的研究,试图实现城市用地规划的他组织作用与城市发展自组织规律的协调发展。主要研究结论如下:
     (1)通过计算机仿真模拟发现:当规划与城市发展的自组织规律相协调时,不论是经济效益还是社会效益和生态效益,都将有所提高。冒险的决策主体偏好经济效益,而谨慎的决策主体相对来说偏好社会效益和生态效益。所以对于冒险的决策主体,只有当规划符合城市发展的自组织规律时,其用地开发才会更好的符合规划,也才能避免蔓延式、跳跃式的开发;对于谨慎的决策主体,只有当规划符合城市发展的自组织规律时,才能提高城市开发的经济价值。另外,当规划符合城市发展的自组织规律时,提高规划执行力度对于促进城市开发的社会效益和生态效益大有裨益。为了使提高规划执行力度变得更有价值,必须确保规划布局符合城市发展的自组织规律。
     (2)基于适宜性评价的中心城区建设用地布局可以有效确定未来城市发展的优势区位,引导城市紧凑化发展,抑制城市沿主干道蔓延式发展,而代之以沿城市主干道填充式开发。其不足之处是,基于适宜性评价的中心城区建设用地布局是一种自上而下的布局方式,难以体现邻域的动态影响、局部规则的交互作用所导致的空间格局,不足以区分较小范围内不同空间之间的异质性,所以倾向于集中式的布局。然而现实情况是任何区域的城市开发主体都有着追求经济利益的动机,已有建城区周边具有较好区位条件的地块都有可能被开发,城市集中式开发过程中始终伴随着分散式的开发。因此,自上而下的建设用地布局方法由于未考虑城市发展自下而上的自组织规律,容易导致布局结果与城市实际发展的偏离。
     (3)1996年之前,杭州市城市发展相对缓慢,市场经济还不很发达,城市开发仍以单一主体、确定的城市开发模式为主,城市增长的驱动因素较为简单,道路和已有城市建设用地是城市扩展的最主要因素,城市扩展以边缘增长为主,沿道路和已有建成区周边向外扩散。1996年之后,杭州城市化的速度明显加快,计划经济体制下的单一主体、确定的城市开发模式逐渐被以多元开发主体和普遍的偶发性开发为代表的新城市发展模式所取代,城市开发变得越来越复杂,影响因素越来越多,迫切需要在土地利用总体规划中心城区建设用地布局中考虑城市发展的复杂性。
     (4)基于元胞自动机模型的建设用地布局方法在预测城市未来近郊区可能的发展区域时具有优势,通过布局引导可以防止该区域内用地随机散乱地开发。与基于适宜性评价的建设用地布局方法相比,虽然建设用地布局要相对分散,但是与城市实际发展情况具有较高的吻合度,更有现实指导意义。同时,如此布局往往连接了城市近郊区相邻破碎的斑块,能有效提高城市建设用地的紧凑程度。到2010年其建设用地斑块数量降低为998,集聚度指数增加到92.57,到2020年其建设用地斑块数量降低为875,集聚度指数增加到93.80,城市格局趋于紧凑。通过与城市规划范围的对比,该布局方法在对于中心城区用地的控制上与城市规划相衔接,衔接度达到了82.35%。另外,在中心城区建设用地布局过程中采用凸壳理论来控制城市发展的形态,引导凸壳内的用地优先开发,能有效促进城市往紧凑化方向发展。
With the rapid growth of economy, industrialization and urbanization in China have been expanding continuously. One notable feature of modern society is the increasing demand for land, and the amount of construction land developed during the planning period always exceed the limited amount in planning. Land resources are scarce and non-renewable. Besides, there are more people and less land in China leading to the rising lack of construction land, which has become the main limitation for economic development. On the other hand, in the context of enhancing protection of farmland and ensuring national food security, governments need to implement various control targets and distribution requirements in land use planning to achieve the consistence of diagram and number. Therefore, how to put limited construction land resources into space, fulfill its rational distribution, achieve its maximum effectiveness, and ensure the development of social economy has become the most important task of land use planning. In addition, the land for construction in central urban area is the core as well as the carrier of regional economic development. Spatial distribution optimization is directly related to the regional socio-economic sustainable development and ecological protection of the environment, which is of great significance to guide and control future land use.
     Currently, city and the process of forming it are widely considered to be a complex system with characteristics of open, dynamic, self-organized and non-equilibrium. At the same time, city's development process is easily disturbed by humans so that we need to coordinate each subsystem and the contradiction between multi-target actors through planning to remedy city's defect of spontaneity, blindness, and hysteresis. Therefore, based on the perspective of city complex system, this paper does research on optimization of construction land distribution in central urban, trying to achieve balance develop between urban land use planning and city's self-organizing rules. The following conclusions have been made,
     (1) Through computer simulation, we find that when the planning coordinates with the city's self-organizing rules, economic and social benefits will both improve. Adventurous decision-making body prefers economic efficiency, while, prudent decision-making body prefers social and ecological benefits. Consequently,for adventurous decision-making body, only when planning is in consistence with city's self-organizing law will the land development better meet the planning avoiding pervasive or saltant development. For prudent decision-making body, only when the planning coordinates with city's self-organization law can improve the economic value of urban development. In addition, when the planning accords with city's self-organization law, enhancing planning enforcement does good to social and ecological benefits in city development.
     (2) Based on the suitability evaluation of the central urban, this distribution is useful to determine preponderant location for future urban development, control city's spread development along main roads, and guide city to the filling development. The mentioned method also has its weakness. It is difficult to reflect the space pattern which is caused by the dynamic impact of neighborhood and the interaction between partial rules. It is not efficient to distinguish heterogeneity in a small range leading to centralized distribution. However, the reality is that anyone has the motive to pursue economic interests in regional development. Any land which has the better location around the building city is possible to be developed so that central development is always accompanied by the distributed development. Therefore, top-down construction land distribution does not take into account city's bottom-up self-organization law, which easily leads to the deviation between distribution results and the actual city development.
     (3) Before 1996, the speed of urban development is relatively slow in Hangzhou and certain city development pattern with single subject is the main mode. The driving factor for urban development is relatively simple and roads as well as existing city are the main factors for urban expansion. Edge-growth is the main mode, which city spreads along roads and the existing built-up areas. After 1996, with the growing rate of urbanization in Hangzhou, certain city development mode with single body is gradually replaced by the accident development with multi-body which is the representative of "new city development mode". Urban development is becoming more complex and has more influencing factors so that it is urgent to consider the complexity of urban development in the land planning for central urban construction.
     (4)The method of cellular automata model has superiority in forecasting likely development areas in the suburb and preventing random land development. Compared with the method of land suitability assessment, construction land distribution is more dispersed, but accords with reality, and has guiding significance. It often connects the adjacent broken patches in suburban areas, which is helpful to raise the city's compactness. According to statistic, the number of construction land patches reduced to 998 and aggregation index increased to 92.57 in 2010. Moreover, the number of patches will decrease to 875 and aggregation index will increase to 93.80 in 2020 and it is more consistent with city actual development. By comparing with the range of urban planning, this distribution result lines up with the city planning in the control of the land use for central urban area and the goodness of fit is 82.35%. Using the theory of convex hull for center city's land layout is beneficial to control the shape of urban development as well as control the land development priority in the convex shell, which will effectively promote the city development to the compact direction.
引文
[1]Aerts J C J H, Heuvelink G B M. Using simulated annealing for resource allocation[J]. International Journal of Geographical Information Science.2002,16(6):571-587.
    [2]Alberti M. The effects of urban patterns on ecosystem function[J]. International Regional Science Review.2005,28(2):168-192.
    [3]Al-Kheder S, Wang J, Shan J. Fuzzy inference guided cellular automata urban-growth modelling using multi-temporal satellite images[J]. International Journal of Geographical Information Science.2008,22(11):1271-1293.
    [4]Allen P M. Cities and regions as evolutionary, complex systems[J]. Geographical Systems. 1997a,4(1):103-130.
    [5]Allen P M. Cities and regions as self-organizing systems:models of complexity[M]. Amsterdam:Gordon and breach science pub,1997b.
    [6]Allen P M. Self-organization in the urban system[M]. Schieve W C, Allen P M. Self-organization and dissipative structures:application in the physical and social sciences. Austin:University of Texas Press,1982,132-158.
    [7]Anselin L. Spatial econometrics[M]. Oxford:Basil Blackwell,2000.
    [8]Balling R J, Taber J T, Brown M R, et al. Multi-objective urban planning using genetic algorithm[J]. Journal of Urban Planning and Development.1999,125(2):86-99.
    [9]Barber G M. Land-use planning via interactive multi-objective programming[J]. Environment and planning A.1976(8):625-636.
    [10]Baskent E Z, Jordan G A. Forest landscape management modeling using simulated annealing[J]. Forest Ecology and Management.2002,165(1):29-45.
    [11]Batty M. Cities and complexity:understanding cities with cellular automata, agent-based model, and fractals[M]. London:The MIT Press,2005.
    [12]Batty M. New ways of looking at cities[J]. Nature.1995,377(6550):574.
    [13]Batty M, Xie Y, Sun Z. Modeling urban dynamics through GIS-based cellular automata[J]. Computers, Environment and Urban Systems.1999,23(3):205-233.
    [14]Batty M, Couclelis H, Eichen M. Urban systems as cellular automata[J]. Environment and Planning B:Planning and Design.1997,24(2):159-305.
    [15]Batty M. Urban evolution on the desktop:simulation with the use of extended cellular automata[J]. Environment and Planning A.1998,30(11):1943-1967.
    [16]Batty M, Xie Y. From cells to cities[J]. Environment and planning B:Planning and Design. 1994,21:531-548.
    [17]Batty M. Cellular automata and urban form:a primer[J]. Journal of the American Planning Association.1997,63(2):266-274.
    [18]Benenson I, Omer I, Hatna E. Entity-based modeling of urban residential dynamics:The case of Yaffo, Tel Aviv[J]. Environment and Planning B:Planning and Design.2002,29(4): 491-512.
    [19]Benenson I. Multi-agent simulations of residential dynamics in the city[J]. Computers, Environment and Urban Systems.1998,22(1):25-42.
    [20]Binder P. Evidence of Lagrangian Tails in a Lattice Gas[M]. Manneville P, Boccara N, Vichniac G Y. Cellular Automata and Modeling of Complex Physical Systems. Berlin:Springer-Verlag,1989,155-160.
    [21]Braimoh A K, Onishi T. Spatial determinants of urban land use change in Lagos, Nigeria[J]. Land Use Policy.2007,24(2):502-515.
    [22]Burn S, Guerin-Pace F, Mathian H, et al. Multi-agent systems and the dynamics of a settlement system[J]. Geographical Analysis.1996,28(2):161-178.
    [23]Camagni R, Gibelli M C, Rigamonti P. Urban mobility and urban form:The social and environmental costs of different patterns of urban expansion[J]. Ecological Economics.2002, 40(2):199-216.
    [24]Charnes A, Haynes K E, Hazleton J E, et al. a hierarchical goal programming approach to environmental land-use management[J]. Geographical Analysis.1975(7):121-130.
    [25]Cheng H Q, Masser I. Urban growth pattern modeling:a case study of Wuhan city, PR China[J]. Landscape and Urban Planning.2003,62(4):199-217.
    [26]Cheng J, Masser I. Modelling urban growth patterns:A multiscale perspective[J]. Environment and Planning A.2003,35(4):679-704.
    [27]Cheung H K, Auger J A. Linear programming and land use allocation:Suboptimal solutions and policy[J]. Socio-Economic Planning Sciences.1976,10(1):43-45.
    [28]Chuvieco E. Intergration of linear programming and GIS for land-use modeling[J]. International Journal of Geographical Information Science.1993,7(1):71-83.
    [29]Clarke K C, Gaydos L J. Loose-coupling a cellular automaton model and GIS:long-term urban growth prediction for San Francisco and Washington/Baltimore[J]. International Journal of Geographical Information Science.1998,12(7):699-714.
    [30]Clarke K C, Hoppen S, Gaydos L. A self-modifying cellular automaton model of historical urbanization in the San Francisco Bay area[J]. Environment and Planning B:Planning and Design.1997,24(2):247-261.
    [31]Collins M G, Steiner F R, Rushman M J. Land-use suitability analysis in the United States: Historical development and promising technological achievements[J]. Environmental Management.2001,28(5):611-621.
    [32]de Almeida C M, Batty M, Monteiro A M V, et al. Stochastic cellular automata modeling of urban land use dynamics:Empirical development and estimation[J]. Computers, Environment and Urban Systems.2003,27(5):481-509.
    [33]de Roo G. Environmental conflicts in compact cities:complexity, decisionmaking, and policy approaches[J]. Environment and planning B:Planning and Design.2000,27(1):151-162.
    [34]Diamond J T, Wright J R. Efficient land allocation[J]. Journal of Urban Planning and Development.1989,115(2):81-96.
    [35]Dickey J W, Sharpe R. Transportation and urban and regional development impacts[J]. High Speed Ground Transp J.1974,8(2):71-80.
    [36]Dokmeci V. Multi-objective model for regional planning of health facilities[J]. Environment and Planning A.1974,11 (5):517-525.
    [37]Eastman J R, Weigen J, Kyem P A K, et al. Raster procedures for multi-criteria/multi-objective decisions[J]. Photogrammetric Engineering & Remote Sensing. 1995,61(5):539-547.
    [38]Eiser R, Plight J. Attitudes and decisions[M]. London and Newyork:Routedge,1988.
    [39]Evans T P, Sun W J, Kelley H. Spatially explicit experiments for the exploration of land-use decision-making dynamics[J]. International Journal of Geographical Information Science. 2006,20(9):1013-1037.
    [40]Ewing R, Pendall R, Chen D. Measuring sprawl and its impact[M]. Washington:Smart Growth America,2002.
    [41]Faris J M, Beever L B, Brown M. Geography information system(GIS) and urban land-use allocation model(ULAM) techniques for existing and projected land-use data[M]. Washington:Tranportation Research Board,2000.
    [42]Feng C M, Lin J J. Using a genetic algorithm to generate alternative sketch maps for urban planning[J]. Computers, Environment and Urban Systems.1999,23(2):91-108.
    [43]Goles E. Cellular automata, dynamics and complexity[M]. Manneville P, Boccara N, Vichniac G Y. Cellular Automata and Modeling of Complex Physical Systems. Berlin:Springer-Verlag,1989,10-20.
    [44]Golledge R G, Stimsion R J. Spatial behavior:a geographic Perspective[M]. New York:The Guilford Press,1997.
    [45]Haken H. A synergetic approach to the self-organization of cities and settlements[J]. Environment and planning B.1995,22(1):35-46.
    [46]Hanink D M, Cromley R G. Land-use allocation in the absence of complete market values [J]. Journal of Regional Science.1998,38(3):465-480.
    [47]Harvey D. The urban process under capitalism[J]. International journal of urban and regional research.1978,2(1):101-131.
    [48]Heath T. Revitalizing cities-attitudes toward city-center living in the United Kingdom[J]. Journal of Planning Education and Research.2001,20(4):464-475.
    [49]Hill M. Rural settlement and the urban impact on the countryside[M]. London:Hodder & Stoughton,2003.
    [50]Holland H. Adaptation in natural and artificial systems:an introductory analysis with applications to biology, control, and artificial intelligence[M]. Cambridge Massachusetts: The MIT Press,1992a.
    [51]Holland H. Complex adaptive system[M]. Boston:Winter,1992b.
    [52]Hopkins L D. The decision to plan:planning activities as public goods[M]. Lierop W R, Nijkamp P, Alphen. Urban infrastructure, location, and housing. aan den rijn:Sijthoff and Noordhoff,1981.
    [53]Hopkins L D. The logic of making plans[M]. London:Island press,2001.
    [54]Hopkins L D. Methods for generating land suitability maps:A comparative evaluation[J]. Journal for American Institute of Planners.1977,34(1):19-29.
    [55]Huang B, Zhang L, Wu B. Spatio-temporal analysis of rural-urban land conversion[J]. International Journal Geographical Information Science.2009,23(3):379-398.
    [56]Hwang C L, Yoon K. Multiple attribute decision making methods and applications:a state of the art survey[M]. Berlin:Springer-Verlag,1981.
    [57]Itami R M. Simulating spatial dynamics:cellular automata theory[J]. Landscape and Urban Planning.1994,30(1-2):27-47.
    [58]Kahneman D, Tversky A. Prospect theory:an analysis of decision under risk[J]. Econometrica.1979,47(2):263-292.
    [59]Kim D S, Chung H W. Spatial diffusion modeling of new residential area for land-use planning of rural villages[J]. Journal of Urban Planning and Development.2005,131(3): 181-194.
    [60]Knapp G J, Hopkins L D, Donaghy K P. Do plans matter? A framwork for examining the logic and effects of land use planning[J]. Journal of planning education and research.1998, 18(1):25-34.
    [61]Knapp R. Chinese landscapes:the village as place[M]. Honolulu:University of hawaii press, 1992.
    [62]Kuznar L A, Frederick W G. Environmental constraints and sigmoid utility:implications for value, risk sensitivity, and social status[J]. Ecological Economics.2003,46(2):293-306.
    [63]Kuznar L A. Evolutionary applications of risk sensitivity models to socially stratified species-Comparison of sigmoid, concave, and linear functions[J]. Evolution and Human Behavior. 2002,23(4):265-280.
    [64]Lai S K. Exploration as planning for a unitary organiaztion[J]. Planning and Market.2002, 5(1):31-42.
    [65]Lai S K. From organized anarchy to controlled structure:effects of planning on the garbage-can decision processes[J]. Environment and planning B:Planning and Design.1998, 25(1):85-102.
    [66]Li X, Yeh A G O. Modelling sustainable urban development by the integration of constrained cellular automata and GIS[J]. International Journal of Geographical Information Science. 2000,14(2):131-152.
    [67]Li X, Yeh A G O. Neural-network-based cellular automata for simulating multiple land use changes using GIS H-1585-2011[J]. International Journal of Geographical Information Science.2002,16(4):323-343.
    [68]Li X, Yen A G O. Data mining of cellular automata's transition rules[J]. International Journal of Geographical Information Science.2004,18(8):723-744.
    [69]Ligmann-Zielinska A. The impact of risk-taking attitudes on a land use pattern:an agent-based model of residential development[J]. Journal of Land Use Science.2009,4(4): 215-232.
    [70]Ligtenberg A, Bregt A K, Van Lammeren R. Multi-actor-based land use modelling:Spatial planning using agents[J]. Landscape and Urban Planning.2001,56(1-2):21-33.
    [71]Liu X H, Andersson C. Assessing the impact of temporal dynamics on land-use change modeling[J]. Computers, Environment and Urban Systems.2004,28(1-2):107-124.
    [72]Liu X P, Li X, Liu L, et al. A bottom-up approach to discover transition rules of cellular automata using ant intelligence H-1585-2011 [J]. International Journal of Geographical Information Science.2008,22(11):1247-1269.
    [73]Makowski D, Hendrix E M T, van Ittersum M K, et al. A framework to study nearly optimal solutions of linear programming models developed for agricultural land use exploration[J]. Ecological Modelling.2000,131(1):65-77.
    [74]Manson S M. Simplifying complexity:a review of complexity theory [J]. Geoforum.2001, 32(3):405-414.
    [75]Marquez L O, Smith N C. A framework for linking urban form and air quality[J]. Environmental Modelling and Software.1999,14(6):541-548.
    [76]Martin J, Pendall R, Fulton W. Holding the line:urban containment in the United States[R]. Washington D.C:The Brookings Institution Center on Urban and Metropolitan Policy,2002.
    [77]Marull J, Pino J, Mallarach J M, et al. A Land Suitability Index for Strategic Environmental Assessment in metropolitan areas[J]. Landscape and Urban Planning.2007,81(3):200-212.
    [78]Mcharg I. L著,芮经纬译.设计结合自然[M].北京:中国建筑工业出版社,1992.
    [79]Muler D, Zeller M. Land use dynamics in the central highlands of Vietnam:a spatial model combining village survey data with satellite imagery interpretation[J]. Agricultural Economics.2002,27(3):333-354.
    [80]Openshaw S. Neural network, genetic, and fuzzy logic models of spatial interaction[J]. Environment and planning A.1998,30(10):1857-1872.
    [81]O'Sullivan D, Haklay M. Agent-based models and individualism:Is the world agent-based?[J]. Environment and Planning A.2000,32(8):1409-1425.
    [82]Otter H S, Van Der Veen A, De Vriend H J. ABLOOM:Location behaviour, spatial patterns, and agent-based modelling[J]. JASSS.2001,4(4):32.
    [83]Paez A, Suzuki J. Transportation impacts on land use change:an assessment considering neighborhood effects[J]. Journal of the Eastern Asia Society for Transportation Studies. 2001(4):47-59.
    [84]Portugali J. Self-organization cities[J]. Futures.1997,29:131-138.
    [85]Portugali J. Self-organization and the city [M]. Berlin:Springer-Verlag,2000.
    [86]Prigogine I, Stengers I. Order out of chaos:man's new dialogue with nature[M]. New York: Bantam Book, Inc.,1984.
    [87]Prigogine I, Stengers I.从混沌到有序——人与自然的新对话[M].上海:上海译文出版社,1987.
    [88]Rabbinge R, Van Latesteijn H C. Long-term options for land use in the European community[J]. Agricultural Systems.1992,40(1-3):195-210.
    [89]Ren F. A training model for GIS application in land resource allocation[J]. ISPRS Journal of Photogrammetry and Remote Sensing.1997,52(6):261-265.
    [90]Roberts B K. Landscapes of settlement[M]. London:Routledge,1996.
    [91]Roberts B K. The making of the english village[M]. London:Longman,1987.
    [92]Sante R I, Crecente M R, Miranda B D. GIS-based planning support system for rural land-use allocation[J]. Computers and Electronics in Agriculture.2008,63(2):257-273.
    [93]Sasaki Y, Box P. Agent-based verification of von Thunen's location theory[J]. JASSS.2003, 6(2):30.
    [94]Schaeffer P, Hopkins L D. Behavior of land developers:planning and the economics of information[J]. Environment and planning A.1987,19(9):1221-1232.
    [95]Semboloni S. An urban and regional model based on cellular automata[J]. Environment and Planning B:Planning and Design.1997,24:219-234.
    [96]Spradlin T. A lexicon of decision making[Z].2004. http://dssresources.com/papers/features/spradlin/spradlin03052004.html.
    [97]Tietenberg T. Environmental and natural resource economics[M]. New York:Harper Collins, 1992.
    [98]Tomlin C D, Johnston K M. An experiment in land-use allocation with a geographic information system[J]. Technical Papers, ACSM-ASPRS, St. Louis.1988(5):23-34.
    [99]Torrey.B B. We need more research on the impact of rapid urban growth[J]. Chronicle of Higher Education.1998,45(9):B6.
    [100]Ventura S J, Niemann Jr B J, Moyer D D. A multipurpose land information system for rural resource planning[J]. Journal of Soil & Water Conservation.1988,43(3):226-229.
    [101]Verburg P H, Soepboer W, Veldkamp A, et al. Modeling the spatial dynamics of regional land use:The CLUE-S model[J]. Environmental Management.2002,30(3):391-405.
    [102]Verburg P H, van Eck J R R, de Nijs T C M, et al. Determinants of landuse change patterns in the Netherlands[J]. Environment and Planning B:Planning and Design.2004,31:125-150.
    [103]Wang X, Yu S, Huang G H. Land allocation based on integrated GIS-optimization modeling at a watershed level[J]. Landscape and Urban Planning.2004,66(2):61-74.
    [104]Ward D P, Murray A T, Phinn S R. A stochastically constrained cellular model of urban growth[J]. Computers, Environment and Urban Systems.2000,24(6):539-558.
    [105]Webster C J, Wu F. Regulation, land-use mix, and urban performance. Part 1:Theory[J]. Environment and Planning A.1999a,31(8):1433-1442.
    [106]Webster C J, Wu F. Regulation, land-use mix, and urban performance. Part 2:Simulation[J]. Environment and Planning A.1999b,31(9):1529-1545.
    [107]White R, Engelen G, Uljee I. The use of constrained cellular automata for high-resolution modelling of urban land-use dynamics[J]. Environment and Planning B:Planning and Design. 1997,24(3):323-343.
    [108]White R, Engelen G. Cellular automata and fractal urban form:a cellular modelling approach to the evolution of urban land-use patterns[J]. Environment and planning A.1993a,25(8): 1175-1199.
    [109]White R, Engelen G. Cellular dynamics and GIS:modeling spatial complexity[J]. Geographical Systems.1993 b,1:237-253.
    [110]White R, Engelen G. Cellular dynamics and GIS:modeling spatial complexity[J]. Geographical Systems.1994,1:237-253.
    [111]White R, Engelen G. High-resolution integrated modelling of the spatial dynamics of urban and regional systems[J]. Computers, Environment and Urban Systems.2000,24(5):383-400.
    [112]White R, Engelen G. Cellular automata as the basis of integrated dynamic regional modeling[J]. Environment and Planning B:Planning and Design.1997,24:235-246.
    [113]Wolfram S. Cellular automata:A model of complexity[J]. Nature.1984(31):419-424.
    [114]Wolfram S. A new kind of science[M]. Champaigu:Wolfram Media,2002.
    [115]Wu F, Webster C J. Simulation of land development through the integration of cellular automata and multicriteria evaluation[J]. Environment and Planning B:Planning and Design. 1998,25(1):103-126.
    [116]Wu F, Webster C J. Simulating artificial cities in a GIS environment:Urban growth under alternative regulation regimes[J]. International Journal of Geographical Information Science. 2000,14(7):625-648.
    [117]Wu F. Simulating urban encroachment on rural land with fuzzy-logic-controlled cellular automata in a geographical information system[J]. Journal of Environment Management. 1998,53(4):293-308.
    [118]Wu F, Yeh A G O. Changing spatial distribution and determinants of land development in Chinese cities in the transition from a centrally planned economy to a socialist market economy:Acase study of Guangzhou[J]. Urban Studies.1997,34(11):1851-1879.
    [119]Wu F. Polycentric urban development and land-use change in a transitional economy:the case of Guangzhou[J]. Environment and Planning A.1998,30(6):1077-1100.
    [120]Xia L. Measurement of rapid agricultural land loss in the Pearl River Delta with the integration of remote sensing and GIS[J]. Environment and Planning B:Planning and Design. 1998,25(3):447-461.
    [121]Xu C, Liu M, Zhang C, et al. The spatiotemporal dynamics of rapid urban growth in the Nanjing metropolitan region of China[J]. Landscape Ecology.2007,22(6):925-937.
    [122]Yeh A, Shi X. Applying case-based reasoning to urban planning:a new planning-support system tool A-4754-2010[J]. Environment and planning B:Planning and Design.1999, 26(1):101-115.
    [123]Yeh A G O, Li X. A constrained CA model for the simulation and planning of sustainable urban forms by using GIS[J]. Environment and Planning B:Planning and Design.2001, 28(5):733-753.
    [124]Yeh A G O, Wu F. The new land development process and urban development in Chinese cities[J]. International Journal of Urban and Regional Research.1996,20(2):330-353.
    [125]Yeh A G O, Li X. Sustainable land development model for rapid growth areas using GIS[J]. International Journal of Geographical Information Science.1998,12(2):169-189.
    [126]Yue W Z, Liu Y, Fan P L. Polycentric urban development:the case of Hangzhou[J]. Environment and planning A.2010,42(3):563-577.
    [127]Zhang T. Community features and urban sprawl:The case of the Chicagometropolitan region[J]. Land Use Policy.2001,18(3):221-232.
    [128]蔡仕谦,王剑波.用地评价与城市发展方向选择[J].惠州学院学报(自然科学版).2004,24(3):53-59.
    [129]蔡玉梅,董柞继,邓红蒂,等.FAO土地利用规划研究进展评述[J].地理科学进展.2005,24(1):70-78.
    [130]曹庆安,舒晓波,王雯,等.新一轮土地利用总体规划中基本农田布局调整案例分析——以江西省浮梁县为例[J].广东土地科学.2009,8(6):10-14.
    [131]曹凯滨.城市用地模拟和可持续发展研究[J].测绘通报.2011,(2):80-82.
    [132]陈本清,徐涵秋.城市扩展及其驱动力遥感分析——以厦门市为例[J].经济地理.2005,25(1):79-83.
    [133]陈江龙,曲福田,王启仿.经济发达地区土地利用结构变化预测——以江苏省江阴市为例[J].长江流域资源与环境.2003,12(4):317-321.
    [134]陈述彭.城市化与城市地理系统[M].北京:科学出版社,1999.
    [135]陈彦光,刘继生.城市土地利用结构和形态的定量描述:从信息熵到分数维[J].地理研究.2001,20(2):146-152.
    [136]陈彦光.中国城市发展的自组织特征与判据——为什么说所有城市都是自组织的?[J].城市规划.2006,30(8):24-30.
    [137]陈彦光.自组织与自组织城市[J].城市规划.2003,27(10):17-22.
    [138]陈燕飞.城市用地适宜性的组合分析[J].城市发展研究.2008(s1):266-269.
    [139]陈燕飞,杜鹏飞,郑筱津,等.基于GIS的南宁市建设用地生态适宜性评价[J].清华大学学报(自然科学版).2006,46(6):801-804.
    [140]陈燕莉.基于生态优先的潍坊市域空间发展战略研究[D]中国农业大学硕士学位论文, 2008.
    [141]陈宗兴,陈晓键.乡村聚落地理研究的国外动态与国内趋势[J].世界地理研究.1994(1):72-79.
    [142]程锋,石英,朱德举.耕地入选基本农田决策模型研究[Jr].地理与地理信息科学.2003,19(3):50-53.
    [143]程建权,兰运超.基于GIS的城镇发展布局优化方法研究[J].武汉城市建设学院学报.1999,16(1):17-22.
    [144]仇保兴.紧凑度和多样性——我国城市可持续发展的核心理念[J].城市规划.2006,30(11):18-24.
    [145]戴汝为.数字城市——一类开放的复杂巨系统[J].中国工程科学.2005,7(8):18-21.
    [146]丁成日.城市“摊大饼”式空间扩张的经济学动力机制[J].城市规划.2005,29(4):56-60。
    [147]丁成日.城市空间规划——理论、方法和实践[M].北京:高等教育出版社,2007.
    [148]董春,罗玉波,刘纪平,等.基于Poisson对数线性模型的居民点与地理因子的相关性研究[J].中国人口资源与环境.2005,15(4):79-84.
    [149]董品杰,赖红松.基于多目标遗传算法的土地利用空间结构优化配置[J].地理与地理信息科学.2003,19(6):52-55.
    [150]段进.城市空间发展论[M].南京:江苏科学技术出版社,2006.
    [151]方晓丽.杭州市建设用地适宜性评价研究[D].中国地质大学硕士学位论文,2008.
    [152]冯健.转型期中国城市内部空间重构[M].北京:科学出版社,2006.
    [153]冯科.城市用地蔓延的定量表达、机理分析及其调控策略研究——以杭州市为例[D].浙江大学博士学位论文,2010.
    [154]冯永玖,童小华,刘妙龙.城市形态演化的粒子群智能随机元胞模型与应用——以上海市嘉定区为例[J].2010,1(1):17-25.
    [155]冯永玖,刘妙龙,韩震.集成遥感和GIS的元胞自动机城市生长模拟——以上海市嘉定区为例[J].长江流域资源与环境.2011,20(1):9-13.
    [156]傅泽强,蔡运龙,杨友孝,等.中国粮食安全与耕地资源变化的相关分析[J].自然资源学报.2001,16(4):313-319.
    [157]高峰.城市演化与居民分布的复杂问题研究[D].吉林大学博士学位论文,2006.
    [158]耿毓修,黄均德.城市规划行政与法制[M].上海:上海科学技术文献出版社,2002.
    [159]耿志阔,张俊梅,许嗥,等.基于农用地分等定级的耕地入选基本农田定量方法研究——以河北省卢龙县为例[J].安徽农业科学.2007,35(3):844-845.
    [160]龚健,刘耀林.基于SD-MOP整合模型的土地利用总体规划研究[J].武汉大学学报(信息科学版).2005,30(4):322-325.
    [161]管驰明,崔功豪.公共交通导向的中国大都市空间结构模式探析[J].城市规划.2003,27(10):39-43.
    [162]郭鹏,薛惠锋,赵宁,等.基于复杂适应系统理论与CA模型的城市增长仿真[J].地理与地理信息科学.2004,20(6):69-72.
    [163]哈肯.协同学引论[M].北京:原子能出版社,1984.
    [164]韩笋生,秦波.借鉴紧凑城市理念,实现我国城市的可持续发展[J].国外城市规划.2004,19(6):23-27.
    [165]何春阳,史培军,陈晋,等.基于系统动力学模型和元胞自动机模型的土地利用情景模型研究[J].中国科学D辑.2005,35(05):464-473.
    [166]何春阳,史培军,陈晋,等.北京地区城市化过程与机制研究[J].地理学报.2002,57(3):363-371.
    [167]何春阳,陈晋,史培军,等.基于CA的城市空间动态模型研究[J].地球科学进展.2002,17(2):188-195。
    [168]何春阳,陈晋,史培军,等.大都市区城市扩展模型—以北京城市扩展模拟为例[J].地理学报.2003,58(2):294-304.
    [169]何春阳,史培军,陈晋,等.北京地区土地利用/覆盖变化研究[J].地理研究.2001,20(6):679-687.
    [170]何流,崔功豪.南京城市空间扩展的特征与机制[J].城市规划汇刊.2000(6):56-60.
    [171]黄杏元,倪绍祥,徐寿成,等.地理信息系统支持区域土地利用决策的研究[J].地理学报.1993,48(2):114-1、21.
    [172]姜广辉,张凤荣,秦静,等.北京山区农村居民点分布变化及其与环境的关系[J].农业工程学报.2006,22(11):85-92.
    [173]姜友华,王新生.遗传算法用于产生可供选择的城市规划方案[J].武汉大学学报(工学版).2002,35(3):63-66.
    [174]蒋芳,刘盛和,袁弘.北京城市蔓延的测度与分析[J].地理学报.2007,62(6):649-658.
    [175]金其铭,董昕,张小林.乡村地理学[-M].南京:江苏教育出版社,1990.
    [176]拉兹洛E.进化:广义综合理论[M].北京:社会科学文献出版社,1988.
    [177]赖世刚,韩昊英.复杂:城市规划的新观点[M].北京:中国建筑工业出版社,2009.
    [178]赖世刚,曾喜鹏.规划的逻辑——以萨维吉效用理论为基础的解释[J].规划学报.1995(22):85-97.
    [179]黎夏,叶嘉安.约束性单元自动演化CA模型及可持续城市发展形态的模拟[J].地理学报.1999,54(4):289-298.
    [180]黎夏,叶嘉安,刘小平.地理模拟系统在城市规划中的应用[J].城市规划.2006,30(6):69-74.
    [181]黎夏,叶嘉安.基于遥感和GIS的辅助规划模型——以珠江三角洲可持续土地开发为例[J].遥感学报.1999,3(3):215-219.
    [182]黎夏,刘小平.基于案例推理的元胞自动机及大区域城市演变模拟[J].地理学报.2007, 62(10):1097-1109.
    [183]李赓,吴次芳,曹顺爱.划定基本农田指标体系的研究[J].农机化研究.2006(8):46-48.
    [184]李君,李小建.国内外农村居民点区位研究评述[J].人文地理.2008,23(4):23-27.
    [185]李秀彬.全球环境变化研究的核心领域——土地利用/土地覆被变化的国际研究动向[J].地理学报.1996,51(6):553-558.
    [186]李轶平,鲍文东,吴泉源.采用综合评价系数法实现基本农田的空间定位[J].农机化研究.2008(3):20-23.
    [187]李猷,王仰麟,彭建,等.基于景观生态的城市土地开发适宜性评价—以丹东市为例[J].生态学报.2010,30(8):2141-2150.
    [188]梁艳平,刘兴权,刘越,等.基于GIS的城市总体规划用地适宜性评价探讨[J].地质与勘探.2001,37(3):64-67.
    [189]刘贵利,顾京涛.土地适宜性评价引导的城市发展方向选择——以汕头市为例[J].城市发展研究.2008(s1):290-296.
    [190]刘纪远,刘明亮,庄大方,等.中国近期土地利用变化的空间格局分析[J].中国科学D辑.2002,32(12):1031-1040.
    [191]刘纪远,王新生,庄大方,等.凸壳原理用于城市用地空间扩展类型识别[J].地理学报.2003,58(6):885-892.
    [192]刘纪远,战金艳,邓祥征.经济改革背景下中国城市用地扩展的时空格局及其驱动因素分析[J].人类环境杂志.2005,35(6):444-449.
    [193]刘丽荣,袁泽,张磊.基于密度分区的城市经济发展空间布局研究—以桂林漓东新城为例[J].青岛科技大学学报(社会科学版).2008,24(1):15-20.
    [194]刘荣霞,薛安,韩鹏,等.土地利用结构优化方法述评[J].北京大学学报(自然科学版).2005,41(4):655-662.
    [195]刘盛和.城市土地利用扩展的空间模式与动力机制[J].地理科学进展.2002,21(1):43-50.
    [196]刘盛和,吴传钧.基于GIS的北京城市土地利用扩展模式[J].地理学报.2000,55(4):407-416.
    [197]刘仙桃.农村居民点空间布局优化与集约用地模式研究[D].中国地质大学硕士学位论文,2009.
    [198]刘小平,黎夏,艾彬,等.基于多智能体的土地利用模拟与规划模型[J].地理学报.2006,61(10):1101-1112.
    [1.99]刘小平,黎夏.从高维特征空间中获取元胞自动机的非线性转换规则[J].地理学报.2006,61(6):663-672.
    [200]刘小平,黎夏.Fisher判别及自动获取元胞自动机的转换规则[J].测绘学报.2007,36(1):112-118.
    [201]刘彦随.区域土地利用优化配置口[M].北京:学苑出版社,1999.
    [202]刘艳芳,李兴林,龚红波.基于遗传算法的土地利用结构优化研究[J].武汉大学学报(信息科学版).2005,30(4):288-292.
    [203]刘英.基于GIS的农村居民点用地时空特征及其优化布局研究——以湖南临澧县为例[J].国土与自然资源研究.2008(4):35-36.
    [204]刘勇.城市增长与景观变化的多尺度研究[[)].浙江大学博士学位论文,2008.
    [205]罗鼎,月卿,邵晓梅,等。土地利用空间优化配置研究进展与展望[J].地理科学进展.2009,28(5):791-797.
    [206]罗平,杜清运,何素芳.人口密度模型与CA集成的城市化时空模拟实验[J].测绘科学.2003,28(4):18-21.
    [207]罗平.地理特征元胞自动机及城市土地利用演化研究[[)].武汉大学硕士学位论文,2004.
    [208]罗平,姜仁荣,李红旮,等.基于空间Logistic和Markov模型集成的区域土地利用演化方法研究[J].中国土地科学.2010,24(1):31-36.
    [209]马强,徐循初.“精明增长”策略与我国的城市空间扩展[J].城市规划汇刊.2004(3):16-22.
    [210]马荣华,陈雯,陈小卉,等.常熟市城镇用地扩展分析[J].地理学报.2004,59(3):418-426.
    [211]马素伟.城市自组织进程中的政府作用研究[D].重庆大学硕士学位论文,2010.
    [212]马天峰.城市规划中的土地适用性分析研究[J].规划师.2008,24(6):71-74.
    [213]南晓娜.GIS支持下的山地城市建设用地适宜性评价研究[D].西北大学硕士学位论文,2009.
    [214]倪绍祥,刘彦随.区域土地资源优化配置及其可持续利用[J].农村生态环境.1999,15(2):8-12.
    [215]聂婷,肖荣波,王国恩,等.基于Logistic回归的CA模型改进方法——以广州市为例[J].地理研究2010,29(10):1909-1919.
    [216]钮心毅,宋小冬.基于土地开发政策的城市用地适宜性评价[J].城市规划学刊.2007(2):57-61.
    [217]普里高津,斯唐热.确定性的终结——时间、混沌与新自然法则[M].上海:上海科技教育出版社,1998.
    [218]沈清基.新城市主义的生态思想及其分析[J].城市规划.2001,25(11):33-38.
    [219]石英,朱德举,程锋,等.属性层次模型在乡级基本农田保护区布局优化中的应用[J].农业工程学报.2006,22(3):27-31.
    [220]宋均梅,陈利根.农村居民点用地整理与土地集约利用——江苏省农村居民点整理现状及思考[J].农村经济.2006(3):26-29.
    [221]宋如华,齐实,孙保平,等.区域土地资源的适宜性评价和空间布局[J].土壤侵蚀与水土保持学报.1997,3(3):23-30.
    [222]宋嗣迪,陈燕红.基于神经网络的土地利用规划方案优化新方法研究[J].广西农业大学学报.1997,16(4):316-321.
    [223]孙华生,黄敬峰,金艳,等.基于GIS技术的县域居民点空间分布特征分析及其优化布局[J].浙江大学学报(农业与生命科学版).2007,33(3):348-354.
    [224]孙玉.层次分析法与城镇用地布局评价研究[J].山东建筑工程学院学报.1996,11(1):77-82.
    [225]谈明洪,李秀彬,吕昌河.20世纪90年代中国大中城市建设用地扩张及其对耕地的占用[J].中国科学D辑.2004,34(12):1157-1165.
    [226]谈明洪,李秀彬,吕昌河.我国城市用地扩张的驱动力分析[J].经济地理.2003,23(5):635-639.
    [227]唐燕.村庄布点规划中的文化反思-以嘉兴凤桥镇村庄布点规划为例[J].规划师.2006,22(4):49-52.
    [228]王成新,姚士谋,陈彩虹.中国农村聚落空心化问题实证研究[J].地理科学.2005,25(3):257-262.
    [229]王繁,周斌,徐建明.海涂土地资源适宜性空间分析与优化开发模式研究[J].农业工程学报.2008,24(1):119-123.
    [230]王海鹰,张新长,康停军.基于GIS的城市建设用地适宜性评价理论与应用[J].地理与地理信息科学.2009,25(1):14-17.
    [231]王汉花,刘艳芳.基于生态位与约束CA的土地资源优化配置模型研究——以武汉市黄陂区为例[J].中国人口资源与环境.2008,18(2):97-102.
    [232]王恒山,徐福缘,凌佩雯,等.村庄布局决策支持系统研究[J].系统工程学报.2000,15(1):92-98.
    [233]王丽萍,周寅康,薛俊菲.江苏省城市用地扩张及驱动机制研究[J].中国土地科学.2005,19(6):26-29.
    [234]王琳,朱天明,杨桂山,等.基于GIS空间分析的县域建设功能空间分区研究——以江苏省昆山市为例[J].长江流域资源与环境.2010,19(7):725-731.
    [235]王婷,周国华,杨延.衡阳南岳区农村居民点用地合理布局分析[J].地理科学进展.2008,27(6):25-31.
    [236]王新生,姜友华.模拟退火算法用于产生城市土地空间布局方案[J].地理研究.2004,23(6):727-735.
    [237]邬建国.景观生态学——格局、过程、尺度与等级[M].北京:高等教育出版社,2007.
    [238]吴次芳,王建弟,许红卫,等.城市土地资源分类评价及其与土地优化配置的关系[J].自然资源学报.1995,10(2):158-164.
    [239]吴宏安,蒋建军,周杰,等.西安城市扩张及其驱动力分析[J].地理学报.2005,60(1):143-150.
    [240]吴克宁,史原轲,冯新伟,等.基于农用地分等的城区扩展用地空间布局优化研究[J].中国土地科学.2007,21(6):17-22.
    [241]席一凡,杨茂盛,尚耀华.遗传算法在城市土地功能配置规划中的应用[J].西北建筑工程学院学报:自然科学版.2001,18(4):190-194.
    [242]肖文韬,宋小敏.论空心村成因及对策[J].农业经济.1999(9):16-17.
    [243]谢花林,刘黎明,李波,等.土地利用变化的多尺度空间自相关分析—以内蒙古翁牛特旗为例[J].地理学报.2006,61(4):389-400.
    [244]刑世和.土地资源与利用[M].厦门:厦门大学出版社,2000.
    [245]徐涵秋.利用改进的归一化差异水体指数(MNDWI)提取水体信息的研究[J].遥感学报.2005,9(5):589-595.
    [246]许彦曦,陈凤,濮励杰.城市空间扩展与城市土地利用扩展的研究进展[J].经济地理.2007,27(2):296-301.
    [247]薛领,杨开忠.复杂性科学理论与区域空间演化模拟研究[J].地理研究.2002,21(1):79-88.
    [248]严金明.土地利用结构的系统分析与优化设计—以南京市为例[J].南京农业大学学报.1996,19(2):88-95.
    [249]杨青生,黎夏.基于动态约束的元胞自动机与复杂城市系统的模拟[J].地理与地理信息科学.2006(5):10-15.
    [250]杨青生,黎夏.多智能体与元胞自动机结合及城市用地扩张模拟[J].地理科学.2007,27(4):542-548.
    [251]杨青生,黎夏.基于遗传算法自动获取CA模型的参数—以东莞市城市发展模拟为例[J].地理研究.2007,26(2):229-237.
    [252]杨荣南,张雪莲.城市空间扩展的动力机制与模式研究[J].地域研究与开发.1997,16(2):1-4.
    [253]杨树佳,郑新奇,王爱萍,等.耕地保护与基本农田布局方法研究——以济南市为例[J].水土保持研究.2007,14(2):4-7.
    [254]杨小雄,梁燕燕,黄小兰,等.区域土地利用规划布局研究进展[J].中国农业资源与区划.2009,30(6):1-6.
    [255]杨小雄,刘耀林,王晓红,等.基于约束条件的元胞自动机土地利用规划布局模型[J].武汉大学学报(信息科学版).2007,32(12):1164-1167.
    [256]姚士谋,朱振国,陈爽,等.香港城市空间扩展的新模式[J].现代城市研究.2002,17(2):61-64.
    [257]姚士谋,陈爽.长江三角洲地区城市空间演化趋势[J].地理学报.1998,53(s12):1-10.
    [258]叶斌,程茂吉,张嫒明.城市总体规划城市建设用地适宜性评定探讨[J].城市规划.2011,35(4):41-48.
    [259]叶嘉安,黎夏.珠江三角洲经济发展、城市扩张与农田流失研究——以东莞市为例[J].经济地理.1999,19(1):68-73.
    [260]叶艳妹,吴次芳.我国农村居民点用地整理的潜力、运作模式与政策选择[J].农业经济问题.1998(10):54-57.
    [261]伊丽莎白伯顿,凯蒂威廉姆斯,迈克詹克斯.紧缩城市——一种可持续发展的城市形态[M].北京:中国建筑工业出版社,2004.
    [262]尹长林,张鸿辉,朱建军,等.城市规划CA模型在城市空间形态演化中的应用研究[J].测绘科学.2008,33(3):133-137.
    [263]於家.基于人工智能的土地利用适宜性评价模型研究与实现[D].华东师范大学博士学位论文,2010.
    [264]俞孔坚,李迪华,刘海龙,等.基于生态基础设施的城市空间发展格局——“反规划”之台州案例[J].城市规划.2005,29(9):76-80.
    [265]张鸿辉,曾永年,金晓斌,等.多智能体城市土地扩张模型及其应用[J].地理学报.2008,63(8):869-881.
    [266]张鸿辉.多智能体城市规划空间决策模型及其应用研究[D].中南大学博士学位论文,2011.
    [267]张秋花.基于CAS理论的人工地价系统建模与仿真[D].西北工业大学硕士学位论文,2007.
    [268]张军,倪绍祥,于文静,等.三江并流区居民点空间分布规律[J].山地学报.2003,21(1):121-125.
    [269]张显峰.基于CA的城市扩展动态模拟与预测[J].中国科学院研究生院学报.2000(1):70-79.
    [270]张心怡,刘敏,孟飞.基于RS和GIS的上海城建用地扩展研究[J].长江流域资源与环境.2006,15(1):29-33.
    [271]张岩,陈云浩,李京.人口条件约束下的城市元胞自动机模型研究[J].中国图象图形学报.2007,12(8):1483-1488.
    [272]张勇强.城市空间发展自组织与城市规划[M].南京:东南大学出版社,2006.
    [273]张勇强.城市空间发展自组织研究——深圳为例[D].东南大学博士学位论文,2003.
    [274]张忠国,赵建军.青岛市城市功能布局的现状特征与发展构想[J].哈尔滨工业大学学报.2003,35(11):1332-1334.
    [275]赵庚星,王人潮,尚建业.黄河三角洲垦利县土地利用的系统动力学仿真模拟研究[J].浙江农业大学学报.1998,24(2):141-147.
    [276]赵雷,华楠.城市空间发展方向选择的层次分析方法[J].山东建筑工程学院学报.1996,11(3):38-42.
    [277]赵涛,郑新奇,邓祥征.城市土地利用优化配置分析应用——以济南市为例[J].地球信息科学.2004,6(2):53-57.
    [278]赵小敏,王人潮,吴次芳.土地利用规划的系统动力学仿真:以杭州城市土地利用总体规划为例[J].浙江农业大学学报.1996,22(2):143-148.
    [279]赵英时.遥感应用分析原理与方法[M].北京:科学出版社,2003.
    [280]赵晶.上海城市土地利用与景观格局的空间演变研究[D].华东师范大学博士学位论文,2004.
    [281]郑时龄.理性地规划和建设理想城市[J].城市规划汇刊.2004(1):1-5.
    [282]郑新奇.城市土地优化配置与集约利用评价[M].北京:科学出版社,2004.
    [283]郑新奇,杨树佳,象伟宁,等.基于农用地分等的基本农田保护空间规划方法研究[J].农业工程学报.2007,23(1):66-71.
    [284]郑新奇,阎弘文,徐宗波.基于GIS的无棣县耕地优化配置[J].国土资源遥感.2001(2):53-56.
    [285]周成虎,孙战利,谢一春.地理元胞自动机研究[M].北京:科学出版社,1999.
    [286]周干峙.城市及其区域—一个典型的开放的复杂巨系统[J].城市规划.2002,26(2):7-8.
    [287]朱光良,刘南.浙江省海宁市TM图像土地利用自动分类精度评价方法的试验研究[J].遥感学报1999,3(2):144-150.
    [288]朱喜刚.城市空间集中与分散论[M].北京:中国建筑工业出版社,2002.
    [289]宗跃光,陈红春,张振世,等.北京城郊化空间特征与发展对策[J].地理学报.2002,57(2):135-142.
    [290]宗跃光,王蓉,汪成刚,等.城市建设用地生态适宜性评价的潜力—限制性分析——以大连城市化区为例[J].地理研究.2007,26(6):1117-1126.