大庆市中心城区土地利用演化时空模拟研究
摘要
大庆市中心城区的土地利用是一个自然、社会、经济相互作用的复合和开放的复杂巨系统,具有离散性、非平衡性、多尺度性、层次性、不确定性和交互性等复杂性的特征。本研究以大庆市中心城区为研究对象,从系统内部微观层次出发,以一种进化的角度来理解大庆市中心城区土地利用复杂系统的演化过程。主要依据《大庆市土地利用总体规划(2006-2020)》,结合CA、MAS和GIS二次开发技术,根据系统动力学原理、资源经济极限理论、可持续发展理论、大庆市城市发展战略等理论,构建大庆市中心城区土地利用演化时空模拟模型。
将模型分为环境要素层、MAS决策层和CA模拟层三个层次。其中环境要素层是由交通要素、经济趋势要素、产能用地要素等组成,是决策单元或评价单元所处的环境。MAS要素层包括政府Agent、、石油Agent和居民Agent三个多智能体用来相互协商和决策。政府Agent表现出规划行为。石油Agent表现出协商行为。居民Agent表现出选择行为。各Agent根据自身的依据对CA模拟层计算出的概率进行判断并与其他Agent协商决策被选地块t+1时刻的土地利用形式。CA模拟层包括元胞状态、元胞邻域及元胞转换规则,用来进行候选地块的评价和地类转换。三个层相互作用,相互协商共同理解所处环境。利用ArcGIS二次开发技术,设计和构建时空演变模拟平台,然后根据大庆市中心城区土地利用现状,反向模拟2000年大庆市土地利用情况。通过对比模拟成果与2000年中心城区土地利用数据的分析,检验模型准确性。
利用时空演化模拟平台,依托交通衰减系数等20种可控参数,设计无干预、产能用地、城市转型战略和可持续发展理论四种情境,以2005为基期,设置近期(5年,即至2010年)、中期(15年,即至2020年)、远期(45年,即至2050年)三个时间维度。在时间和空间上模拟大庆市中心城区土地利用演化进行模拟。通过对不同情境下、不同时间维度上的模拟实验结果进行对比分析,得出大庆市中心城区土地利用的突出特点。主要特点包括:耕地减少是必然趋势,但应控其减少速度,同时产能用地占用耕地数量极少,城市建设才是耕地减少的根本原因;园地比重少,但对大庆市中心城区可持续发展有重要作用;重视林地建设,但宜林地有限。同时,当地林地发展到一定规模,可改善周围环境,使周围土地经济价值增加;自然条件下草地退化迅速,但大庆市政府部门具备治理盐碱化草地的能力,同时油区土地的复垦利用、城市绿化可增加草地,对草地进行补充;湿地近期减少迅速,却具有规模极限;建设用地呈现出近期可控性,远期不可遇见性;产能用地规模可以进行控制,但用于产能建设以后难以转变其他用途;大庆市中心城区未利用地不适合城市建设。
再根据其特点,以时间和空间上合理利用土地资源为目标,针对性的提出土地利用建议,以避免大庆市中心城区土地资源的浪费。主要建议包括:控制耕地规模减少速度,防止耕地撂荒、沙化等情况发生;加大林地建设和园地、草地、湿地保护,林地可起到防风固沙的作用的同时美化城市景观。园地、草地、湿地对生态环境起着重要的作用,可根据2050年的演化极限值选择适合的区域设置园地集中区、草地核心区和湿地保护区并进行分区管制;积极开展油区土地集约、节约和复合利用。其中,油区复合利用的土地可选用生物能源植物绿化油区的同时生产可再生能源;加强土地利用总体规划的宏观调控作用。并将规划前置于用地行为执行,指导土地科学利用实现土地的集约、节约利用;加强土地的开发复垦整理。由于大庆市独特的地质构造和景观格局导致土地开发复垦整理成本过高,但大庆市应依托自身经济实力对具有区位优势的地块进行开发复垦整理。用于城市建设,缓解新增建设用地不足的矛盾。
最后根据建议,设计模型参数,模拟出不同时间纬度上理想情境下的土地利用情况,直观展现科学合理的大庆市中心城区土地利用发展情况。
根据实验结果,可以看出大庆市中心城区土地利用呈现出耕地必然减少、宜林地有限、自然条件下草地退化迅速、湿地具有规模极限、建设用地呈现出近期可控性和远期不可遇见性、产能用地规模可控制但建设后难以转变其他用途、未利用地不适合城市建设等特点。并提出控制耕地减少速度;设置林、园、草、湿等土地资源保护核心区,严格控制产能用地和建设用地发展等建议。根据以上特点和建议,可以为大庆市中心城区土地利用工作提供有意义的依据。
The land use of Daqing city center is a natural, social, and economic interaction between the compound and the open complex giant system with discrete, non-equilibrium, multi-scale nature, hierarchy, such as uncertainty and complexity of interaction feature. In this study, the research object of Daqing city center, Starting from the micro-level within the system, An evolutionary perspective to understand the complex systems of land-use evolution of Daqing city center. Mainly based on《land use in Master Plan (2006-2020)》, combined with CA, MAS and secondary development of GIS technology, according to the system dynamics, the limit theory of economic resources, sustainable development theory, strategy for city development theory , construct land use evolution simulation model of Daqing city center.
The model contain environmental factors layer, MAS decision-making layer and the CA simulation layer. Environmental factor layers are composed by transport element, economic trends element and energy-land elements, which is decision-making unit or the environment of evaluation units. MAS element layer including the government agent, oil agent, and residents agent, the three agents mutual consultation and decision-making. The government Agent show planning act. Oil Agent show negotiation behavior. Residents Agent show choice behavior. The Agent according to oneself on the basis of CA simulation calculate the probability of layer and negotiate with other Agent decision-making chosen plot t + 1 time of land utilization form.CA emulation layer including cellular state,CA neighborhood and cellular transformation rules, which used for the evaluation of the candidate block and land type conversion. Three layer interaction , mutual consultation and common understand their environment. Using ArcGIS secondary development, design and build space-time evolution simulation platform, and then under the current land use in Daqing city center, reverse simulate land use situations in 2000. By comparing the simulation results of the 2000 downtown land-use data analysis to test model accuracy.
Use of space-time evolution simulation platform, Relying on the traffic attenuation coefficient of controllable parameter, 20 etc,designed four situation of non-intervention, energy-land, urban transformation strategies and the theory of sustainable development , 2005 as the base, set the near term (5 years, until 2010), medium (15 years, until 2020), long-term(45 years, until 2050) the three time dimensions. Simulation in time and space evolution of land use in Daqing city center. Through a variety of contexts, compared and analyzed the simulation results in different time scales obtain salient features of land use in Daqing city center. Main features include: the decrease is an inevitable trend, but should control the speed and capacity, reduce the quantity of cultivated land occupied land, urban construction is the root cause of the cultivated land change, Garden in daqing, but the proportion of urban sustainable development center has an important role, Attention, but the leading construction land. Meanwhile, the local land development to a certain scale, improve environment, economic value added to the land around, Under the conditions of natural grassland degradation of daqing rapidly, but the government departments have governance capability, and insert the land reclamation and utilization, and urban greening can increase of grass, grass complement, Wetland has recently reduced size limit, rapid, Presents recent construction land shall meet, long-term, Production scale can be controlled, but for the construction of a productivity to change other purposes; after Daqing city center unused land is not suitable for urban construction.
Then according to their characteristics, reasonable use land resources as the goal in time and space, proposed land use recommendations, to avoid the waste of land resources in Daqing City center. Mainly include: reduce speed control land scale, prevent farmland abandoned, desertification, etc, Increasing woodland and grassland construction and gardens, wetland protection forest can have the effect of sand-fixation and beautify urban landscape. Garden, grassland, wetland ecological environment plays an important role, but according to the evolution of 2050 to choose suitable locale related field, grassland area and high wetland nature reserve and zoning regulation, Actively exploited, saving and composite intensive land utilization. Among them, the land use oil compound bio-energy can choose oil production plant virescence and renewable energy, To strengthen the general land use planning of macro-control role. And the land will be placed before planning, execution behavior of land utilization of land scientific realization by intensive, saving, To strengthen the development of land reclamation. Due to the unique daqing geological structure and landscape pattern of land reclamation arrangement to develop high cost, but the daqing should rely on its economic strength of locational advantage of plot development reclamation. For urban construction, alleviate the shortage of newly-increased construction land.
Finally, according to recommendations design model parameters to simulate the ideal situation in different time scales under the land use, intuitive display a scientific and rational land use development in Daqing city center. According to the experimental results, we can see that farmland will be reduced, forest land be limited , grassland rapidly degradation under natural conditions, the size of wetlands have limition, construction land shows control in the recent and non-met in long-term, energy-land can be controlled but is difficult to change to other uses after construction, unused land is not suitable for urban construction, etc. And proposed that control the reduce speed of arable land; Setting the core protection of land resources in forest, garden, grass, wet areas, strictly control the energy-land and construction land development. According to the above characteristics and recommendations to provide a meaningful basis for land use in Daqing city center.
将模型分为环境要素层、MAS决策层和CA模拟层三个层次。其中环境要素层是由交通要素、经济趋势要素、产能用地要素等组成,是决策单元或评价单元所处的环境。MAS要素层包括政府Agent、、石油Agent和居民Agent三个多智能体用来相互协商和决策。政府Agent表现出规划行为。石油Agent表现出协商行为。居民Agent表现出选择行为。各Agent根据自身的依据对CA模拟层计算出的概率进行判断并与其他Agent协商决策被选地块t+1时刻的土地利用形式。CA模拟层包括元胞状态、元胞邻域及元胞转换规则,用来进行候选地块的评价和地类转换。三个层相互作用,相互协商共同理解所处环境。利用ArcGIS二次开发技术,设计和构建时空演变模拟平台,然后根据大庆市中心城区土地利用现状,反向模拟2000年大庆市土地利用情况。通过对比模拟成果与2000年中心城区土地利用数据的分析,检验模型准确性。
利用时空演化模拟平台,依托交通衰减系数等20种可控参数,设计无干预、产能用地、城市转型战略和可持续发展理论四种情境,以2005为基期,设置近期(5年,即至2010年)、中期(15年,即至2020年)、远期(45年,即至2050年)三个时间维度。在时间和空间上模拟大庆市中心城区土地利用演化进行模拟。通过对不同情境下、不同时间维度上的模拟实验结果进行对比分析,得出大庆市中心城区土地利用的突出特点。主要特点包括:耕地减少是必然趋势,但应控其减少速度,同时产能用地占用耕地数量极少,城市建设才是耕地减少的根本原因;园地比重少,但对大庆市中心城区可持续发展有重要作用;重视林地建设,但宜林地有限。同时,当地林地发展到一定规模,可改善周围环境,使周围土地经济价值增加;自然条件下草地退化迅速,但大庆市政府部门具备治理盐碱化草地的能力,同时油区土地的复垦利用、城市绿化可增加草地,对草地进行补充;湿地近期减少迅速,却具有规模极限;建设用地呈现出近期可控性,远期不可遇见性;产能用地规模可以进行控制,但用于产能建设以后难以转变其他用途;大庆市中心城区未利用地不适合城市建设。
再根据其特点,以时间和空间上合理利用土地资源为目标,针对性的提出土地利用建议,以避免大庆市中心城区土地资源的浪费。主要建议包括:控制耕地规模减少速度,防止耕地撂荒、沙化等情况发生;加大林地建设和园地、草地、湿地保护,林地可起到防风固沙的作用的同时美化城市景观。园地、草地、湿地对生态环境起着重要的作用,可根据2050年的演化极限值选择适合的区域设置园地集中区、草地核心区和湿地保护区并进行分区管制;积极开展油区土地集约、节约和复合利用。其中,油区复合利用的土地可选用生物能源植物绿化油区的同时生产可再生能源;加强土地利用总体规划的宏观调控作用。并将规划前置于用地行为执行,指导土地科学利用实现土地的集约、节约利用;加强土地的开发复垦整理。由于大庆市独特的地质构造和景观格局导致土地开发复垦整理成本过高,但大庆市应依托自身经济实力对具有区位优势的地块进行开发复垦整理。用于城市建设,缓解新增建设用地不足的矛盾。
最后根据建议,设计模型参数,模拟出不同时间纬度上理想情境下的土地利用情况,直观展现科学合理的大庆市中心城区土地利用发展情况。
根据实验结果,可以看出大庆市中心城区土地利用呈现出耕地必然减少、宜林地有限、自然条件下草地退化迅速、湿地具有规模极限、建设用地呈现出近期可控性和远期不可遇见性、产能用地规模可控制但建设后难以转变其他用途、未利用地不适合城市建设等特点。并提出控制耕地减少速度;设置林、园、草、湿等土地资源保护核心区,严格控制产能用地和建设用地发展等建议。根据以上特点和建议,可以为大庆市中心城区土地利用工作提供有意义的依据。
The land use of Daqing city center is a natural, social, and economic interaction between the compound and the open complex giant system with discrete, non-equilibrium, multi-scale nature, hierarchy, such as uncertainty and complexity of interaction feature. In this study, the research object of Daqing city center, Starting from the micro-level within the system, An evolutionary perspective to understand the complex systems of land-use evolution of Daqing city center. Mainly based on《land use in Master Plan (2006-2020)》, combined with CA, MAS and secondary development of GIS technology, according to the system dynamics, the limit theory of economic resources, sustainable development theory, strategy for city development theory , construct land use evolution simulation model of Daqing city center.
The model contain environmental factors layer, MAS decision-making layer and the CA simulation layer. Environmental factor layers are composed by transport element, economic trends element and energy-land elements, which is decision-making unit or the environment of evaluation units. MAS element layer including the government agent, oil agent, and residents agent, the three agents mutual consultation and decision-making. The government Agent show planning act. Oil Agent show negotiation behavior. Residents Agent show choice behavior. The Agent according to oneself on the basis of CA simulation calculate the probability of layer and negotiate with other Agent decision-making chosen plot t + 1 time of land utilization form.CA emulation layer including cellular state,CA neighborhood and cellular transformation rules, which used for the evaluation of the candidate block and land type conversion. Three layer interaction , mutual consultation and common understand their environment. Using ArcGIS secondary development, design and build space-time evolution simulation platform, and then under the current land use in Daqing city center, reverse simulate land use situations in 2000. By comparing the simulation results of the 2000 downtown land-use data analysis to test model accuracy.
Use of space-time evolution simulation platform, Relying on the traffic attenuation coefficient of controllable parameter, 20 etc,designed four situation of non-intervention, energy-land, urban transformation strategies and the theory of sustainable development , 2005 as the base, set the near term (5 years, until 2010), medium (15 years, until 2020), long-term(45 years, until 2050) the three time dimensions. Simulation in time and space evolution of land use in Daqing city center. Through a variety of contexts, compared and analyzed the simulation results in different time scales obtain salient features of land use in Daqing city center. Main features include: the decrease is an inevitable trend, but should control the speed and capacity, reduce the quantity of cultivated land occupied land, urban construction is the root cause of the cultivated land change, Garden in daqing, but the proportion of urban sustainable development center has an important role, Attention, but the leading construction land. Meanwhile, the local land development to a certain scale, improve environment, economic value added to the land around, Under the conditions of natural grassland degradation of daqing rapidly, but the government departments have governance capability, and insert the land reclamation and utilization, and urban greening can increase of grass, grass complement, Wetland has recently reduced size limit, rapid, Presents recent construction land shall meet, long-term, Production scale can be controlled, but for the construction of a productivity to change other purposes; after Daqing city center unused land is not suitable for urban construction.
Then according to their characteristics, reasonable use land resources as the goal in time and space, proposed land use recommendations, to avoid the waste of land resources in Daqing City center. Mainly include: reduce speed control land scale, prevent farmland abandoned, desertification, etc, Increasing woodland and grassland construction and gardens, wetland protection forest can have the effect of sand-fixation and beautify urban landscape. Garden, grassland, wetland ecological environment plays an important role, but according to the evolution of 2050 to choose suitable locale related field, grassland area and high wetland nature reserve and zoning regulation, Actively exploited, saving and composite intensive land utilization. Among them, the land use oil compound bio-energy can choose oil production plant virescence and renewable energy, To strengthen the general land use planning of macro-control role. And the land will be placed before planning, execution behavior of land utilization of land scientific realization by intensive, saving, To strengthen the development of land reclamation. Due to the unique daqing geological structure and landscape pattern of land reclamation arrangement to develop high cost, but the daqing should rely on its economic strength of locational advantage of plot development reclamation. For urban construction, alleviate the shortage of newly-increased construction land.
Finally, according to recommendations design model parameters to simulate the ideal situation in different time scales under the land use, intuitive display a scientific and rational land use development in Daqing city center. According to the experimental results, we can see that farmland will be reduced, forest land be limited , grassland rapidly degradation under natural conditions, the size of wetlands have limition, construction land shows control in the recent and non-met in long-term, energy-land can be controlled but is difficult to change to other uses after construction, unused land is not suitable for urban construction, etc. And proposed that control the reduce speed of arable land; Setting the core protection of land resources in forest, garden, grass, wet areas, strictly control the energy-land and construction land development. According to the above characteristics and recommendations to provide a meaningful basis for land use in Daqing city center.
引文
摆万奇,赵土洞.1997.土地利用和土地覆盖变化研究模型综述.自然资源学报12(2) 169~174
陈小祥.2007.基于贝叶斯概率城市土地利用动态变化模拟研究[D].中南大学
陈常松.2003.地理信息共享的理论与政策研究.中国科学出版社.37~38
陈述彭.1999.城市化与城市地理信息系统.北京:科学出版社.194~195
陈佑启,PETER H Verburg,徐彬.2000.中国土地利用变化及其影响的空间建模分析.地理科学进展.19(2) 116~127
陈佑启,PETER H Verburg.2000.中国土地利用/覆被的多尺度空间分布特征分析.地理科学.20(3) 197~202
董玉祥,李森,董光荣.1999.雅鲁藏布江流域土地沙漠化现状与成因初步研究.地理科学.19(1)35~41
龚子同,张甘霖,赵文君.2003海南岛土壤中铝钙的地球化学特征及其对生态环境的影响.地理科学.23(2) 200~207
郭鹏,薛惠锋,赵宁.2004.基于复杂适应系统理论与CA模型的城市增长仿真.地理与地理信息科学. 20(6) 69~72
郭仁忠.2001.空间分析.武汉:武汉大学出版社.193~211
郭荣朝.2004.生态城市空间结构优化组合模式及应用—以襄樊市为例.地理研究.3
韩玲玲,何政伟.2003.GeoCA-Urban模型在城市增长与土地增值研究中的应用.国土资源科技管理.2 48~51
何素芳,罗平,黄耀丽.2002.CA模型的缺陷及拓展研究.佛山科技学院学报. 20(2) 52~56
金晓斌,周寅康.2005.快速城市化背景下的城市土地储备策略研究—以深圳市龙岗区为例.自然资源学报.20(4) 522~529
雷国平.2001.黑龙江区域土地利用变化机制与对策研究[D].华中农业大学
黎夏,叶嘉安.1999.约束性自动演化CA模型及可持续城市发展形态的模拟.地理学报.54(4) 289~298
黎夏,叶嘉安.2006.基于元胞自动机的城市发展密度模拟.地理科学. 26(2)165~172
黎夏,叶嘉安.2000.单元自动演化模型自动生成农田保护区的研究.中国环境科学.20(4) 318~322
黎夏,叶嘉安.2001.主成分分析与CA在空间决策与城市模拟中的应用.中国科学.31(8) 683~690
黎夏,叶嘉安.2002.基于神经网络的单元自动机CA及真实和优化的城市模拟.地理学报.57(2) 159~166
李才伟.1997.元胞自动机及复杂系统的时空演化模拟.武汉:华中理工大学
李才伟.1997.自组织现象的元胞自动机模拟与图示.计算机辅助设计与图形学学报.9(6) 532~537
李辉霞,李森.2006.基于NDWI的沙漠化信息自动提取——以海南岛西部为例.中国沙漠.2215~219
李森,孙武,李凡.2005.海南岛西部热带沙漠化土地特征与成因.地理学报.61(3) 433~442
林培松,李森.2005.近20年来海南岛西部土地沙漠化与气候变化关联度研究.中国沙漠.1 27~32
刘继生,陈彦光.2002.基于GIS的细胞自动机模型与人地关系的复杂性探讨.地理研究.21(2) 155~162
刘妙龙,黄蓓佩.2004.上海大都市交通网络分形的时空特征演变研究.地理科学.24(2) 144~149
陆立军,朱海就.2004.长三角“四个中心”和上海大都市圈建设研究.经济地理.6
罗平,杜清运,雷元新.2004.城市土地利用CA模型的扩展研究.地理与地理信息科学. 20(4) 48~51
罗平,杜清运.2002.基于关系数据库的CA扩展和时空模拟研究.地理学与国土研究.3
罗平,杜清运.2003.人口密度模型与CA集成的城市化时空模拟实验.测绘科学.4
罗平,杜清运.2004.地理特征元胞自动机及城市土地利用演化研究.武汉大学学报(信息科学版).29(6) 504~507
罗平,杜清运.2004.基于经典地理过程分析概念的CA模型扩展研究.武汉大学学报(工学版). 4
罗平,杜清运.2004.基于生命机制概念的城市土地利用演化CA模型研究.地理与地理信息科学.4
罗平,杜清运.2004.基于特征的CA概念模型及城市土地利用演化研究.武汉大学学报(信息科学版). 6
罗平,耿继进,李森.2005.元胞自动机地理过程模拟机制及扩展.地理科学.25(6) 504~507
罗平,何素芳,杜清运.2002.基于GIS-SD模型的兰州市住宅价格时空模拟研究.兰州大学学报(自然科学版).38(4)
罗平.2001.基于GIS和多媒体集成的旅游信息系统开发实验研究.测绘通报.12
罗平.2002.基于RS和GIS的云东海土地覆盖变化研究.佛山科技学院学报.1
骆剑承,周成虎,杨艳.2001.遥感地学智能图解模型支持下的土地覆盖/土地利用分类.自然资源学报.16(2) 179~183
马义德,齐春亮,杜鸿飞.2006.一种基于分类的改进BP神经网络图像压缩方法同.兰州大学学报(自然科学版).42(2) 68~71
牛文元.1992.理论地理学.北京:商务印书馆出版.104~106
牛文元.2004.组团式城市群是获取“发展红利”的最有效途径.领导决策信息.16
彭建,蔡运龙,P. H. Verburg.2007.喀斯特山区土地利用/土地覆被变化情景模拟[J].农业工程学报,23(7):64-70
盛晟.2008.CLUE-S模型在南京市土地利用变化研究中的应用[J].生态学杂志,27(2):235-239
史忠植.1998.高级人工智能.北京:中国科学出版社.10~58
唐菊兴,李少达,王乾.2001.城市区位模式与城市地价研究.成都理工大学学报.28(4) 429~435
王富海.2003.深圳城市空间演进研究.北京:北京大学博士学位论文.
王磊.2000.城市产业结构调整与城市空间结构演化一一以武汉市为例.城市规划汇刊.1(3)
王良健,包浩生,彭补拙.2000.基于遥感与GIS的区域土地利用变化的动态监测与预测研究.经济地理.20(2) 47~51
王微波.2004.城市战略规划研究.地域研究与开发.4
王兮之,郑影华,李森.2006.海南岛西部土地利用变化及其景观格局动态分析.中国沙漠.3 409~414
吴桂平.2008.在CLUE-S模型的改进与区域土地利用变化模拟研究[D].中南大学
吴正,黄山,胡守真.1995.华南海岸风沙地貌研究.北京:科学出版社.38~39
武晓波,赵健等.2002.细胞自动机模型用于城市发展模拟的方法初探一以海口市为例.城市规划.26(8) 69~73
谢峰.2007.基于CLUE-S模型的吐鲁番市土地利用动态变化模拟研究[D].新疆大学
姚士谋,陈爽.1998.长江三角洲区域城市空间演化趋势.地理学报.53
姚士谋.2006.中国城市快速发展及其土地政策问题的思考.深圳.第二届中国城市发展与土地政策国际研讨会论文集. 170~177
张永民,周成虎,郑纯辉等. 2006.沽源县土地利用格局的多尺度模拟与分析[J].资源科学,28(2):88-96
张显峰,崔伟宏.2001.集成GIS和元胞自动机模型进行地理时空过程模拟与预测的新方法.测绘学报.30(2) 148~155
张显峰.2000.基于CA的城市扩展动态模拟与预测.中国科学院研究生院学报.17(1) 70~79
郑丽英,刘丽艳,王海涌.2006.基于Kohonen网络一粗集一模糊神经网络获取模糊规则的集成方法.兰州大学学报(自然科学版).42(2) 68~71
周成虎,孙战利,谢一春.1999.地理元胞自动机研究.北京:科学出版社. 1~163
朱震达,刘恕,邸醒民.1989.中国的沙漠化及其治理.北京:科学出版社.234~248
Amorosos,Patty.1972.Decision Procedures for Surjectivity and Injectivity of Parallel Maps for Tessellation Structures. Computer System Sci.6 448~464
Attym, XIE Y, SUN Z.1999. Modeling Urban Dynamics through GIS-Based Cellular Automata. Computer. Environmental and Urban System.23 1~29
Banister D,Watson S, Wood C.1997. Sustainable Cities: Transport Energy and Urban Form. Environment and Planning B.24 125~143
Batty M,Xie Y.1994. From cells to cities. Environment and planning B.21 531~548
Batty M. 1997. Urban systems as cellular automata. Environment and Planning B. 24 159~164
Battym, Couclelish, Eichenm.1997.Urban System as a Cellular Automata. Environment and Planning B.24 159~164
Burks A W.1970. Eassys on Cellualr automata. University of Illinois Press UrbanaⅡCastella J.C.,Kam S.P.,Quang D.D.,et al.2007.Combining top-down and bottom-up modellingapproaches of Land Use/Cover Change to support public policies:Application to sustainable management of natural resources in northern Vietnam[J].Land Use Policy,24(3):531-545.
Castella J. C.,P.H.Verburg.2007.Combination of process-oriented and pattern-oriented models of land-use change in a mountain area of Vietnam[J].Ecological modeling,202: 410-420.
Clarke K C,Gaydos L J.1998.Loose-coupling a Cellular Automaton Model and GIS: Long-term Urban Growth Prediction for San Francisco and Washington/Baltimore . Geographical Information Science.12(7) 699~714
Couclelis H.1997.From cellular automata to urban models: New principles for model development and implementation. Environment and Planning B.24 165~174
Couelelis H.1985.Cellularworlds:A framework for modeling miero-maero dynamics. Environment and Planning A.17 585~596
Couelelis H.1989. Maerostrueture and mierobehaviour in ametropolitan area. Environment and Planning B. 16 151~154
CUPR (Center for Urban Policy Research).1992. Impact Assessment of the New Jersey Interim State Development Plan . Trenton, N J: New Jersey Office of State Planning
Ewing R.1997. Is Los Angeles-style spraw l desirable? . Journal of the American Planning Association.63(1) 107~126
Larke K C,Gaydos L J.1988. Loose-Couping a Cellular Automaton Model and GIS: Long-Term Urban Growth Prediction for San Francisco and Washington/Baltimore. Int J Geographic Science. 2(7) 699~714
Li X,Yeh A G O.2002. Neural-network-based cellular automata for simulating multiple land use changes using GIS. International Journal of Geographical Information Science. 16(4) 323~343
Luo Ping,Du Qingyun.2002. A Study on Cellular Automata Based on Relational Databases and Overmars K. P.,De Groot W. T.,Huigen M. G. A. 2007.Comparing inductive and deductive modelling of land use decisions:Principles,a model and an illustration from the Philippines[J].Human Ecology,35:439-452
Overmars,K. P.,P.H.Verburg,Veldkamp A. 2007. Comparison of a deductive and an inductive approachto specify land suitability in a spatially explicit land use model. Land Use Policy.24(3):584-599
O Sullivan D,Haklay M.2000. Agent-based models and individualism: is the world agent-based. Environment and Planning A.32(8) 1409~1425
O Sullivan D,P M Torrens.2000. Cellular models of urban systems. In Theoretical and Practical Issues on Cellular Automata. London:Springer-Verlag
P.H.Verburg, Overmars K. P.2007.Dynamic simulation of land-use change trajectories with the CLUE-s model[M].Netherlands:Springer Netherlands: 321-337
Spatio-temporal Simulations of Culture Diffusion. Chinese Geography science.4
Tobler W R.1970.A computer movie simulating urban growth in the Detroit region.EeonomicGeography.46 234~240
U lam S.1976. Adventures of a Mathematician . New York:Charles scribner’s sons Ward D P,Murray A T,Phinn S R.2000.A stochastically constrained cellular model of urban growth. Computers Environment and Urban Systems. 24 539~558
White R,Engelen G. 1993.Cellular automata and fractal urban form: a cellular modelling approach to the evolution of urban land-use patterns. Environment and Planning A.25 1175~1199
White R,G Engelen, I U ljee.1997. The use of constrained cellular automata for high-resolution modelling of urban land use dynamics. Environment and Planning B.24 323~343
Wu F,C JWebster.1998. Simulation of land development through the integration of cellular automata and multicriteria evaluation. Environment and Planning B.25 103~126
Wu F,David Martin.2002. Urban expansion simulation of Southeast England using population surface modelling and cellular automata. Environment and Planning A.34 1855~1876
Wu F.1998. SimLand: a prototype to simulate land conversion through the integrated GIS and CA with AHP-derived transition rules. Geographical Information Science. 12(1) 63~82
陈小祥.2007.基于贝叶斯概率城市土地利用动态变化模拟研究[D].中南大学
陈常松.2003.地理信息共享的理论与政策研究.中国科学出版社.37~38
陈述彭.1999.城市化与城市地理信息系统.北京:科学出版社.194~195
陈佑启,PETER H Verburg,徐彬.2000.中国土地利用变化及其影响的空间建模分析.地理科学进展.19(2) 116~127
陈佑启,PETER H Verburg.2000.中国土地利用/覆被的多尺度空间分布特征分析.地理科学.20(3) 197~202
董玉祥,李森,董光荣.1999.雅鲁藏布江流域土地沙漠化现状与成因初步研究.地理科学.19(1)35~41
龚子同,张甘霖,赵文君.2003海南岛土壤中铝钙的地球化学特征及其对生态环境的影响.地理科学.23(2) 200~207
郭鹏,薛惠锋,赵宁.2004.基于复杂适应系统理论与CA模型的城市增长仿真.地理与地理信息科学. 20(6) 69~72
郭仁忠.2001.空间分析.武汉:武汉大学出版社.193~211
郭荣朝.2004.生态城市空间结构优化组合模式及应用—以襄樊市为例.地理研究.3
韩玲玲,何政伟.2003.GeoCA-Urban模型在城市增长与土地增值研究中的应用.国土资源科技管理.2 48~51
何素芳,罗平,黄耀丽.2002.CA模型的缺陷及拓展研究.佛山科技学院学报. 20(2) 52~56
金晓斌,周寅康.2005.快速城市化背景下的城市土地储备策略研究—以深圳市龙岗区为例.自然资源学报.20(4) 522~529
雷国平.2001.黑龙江区域土地利用变化机制与对策研究[D].华中农业大学
黎夏,叶嘉安.1999.约束性自动演化CA模型及可持续城市发展形态的模拟.地理学报.54(4) 289~298
黎夏,叶嘉安.2006.基于元胞自动机的城市发展密度模拟.地理科学. 26(2)165~172
黎夏,叶嘉安.2000.单元自动演化模型自动生成农田保护区的研究.中国环境科学.20(4) 318~322
黎夏,叶嘉安.2001.主成分分析与CA在空间决策与城市模拟中的应用.中国科学.31(8) 683~690
黎夏,叶嘉安.2002.基于神经网络的单元自动机CA及真实和优化的城市模拟.地理学报.57(2) 159~166
李才伟.1997.元胞自动机及复杂系统的时空演化模拟.武汉:华中理工大学
李才伟.1997.自组织现象的元胞自动机模拟与图示.计算机辅助设计与图形学学报.9(6) 532~537
李辉霞,李森.2006.基于NDWI的沙漠化信息自动提取——以海南岛西部为例.中国沙漠.2215~219
李森,孙武,李凡.2005.海南岛西部热带沙漠化土地特征与成因.地理学报.61(3) 433~442
林培松,李森.2005.近20年来海南岛西部土地沙漠化与气候变化关联度研究.中国沙漠.1 27~32
刘继生,陈彦光.2002.基于GIS的细胞自动机模型与人地关系的复杂性探讨.地理研究.21(2) 155~162
刘妙龙,黄蓓佩.2004.上海大都市交通网络分形的时空特征演变研究.地理科学.24(2) 144~149
陆立军,朱海就.2004.长三角“四个中心”和上海大都市圈建设研究.经济地理.6
罗平,杜清运,雷元新.2004.城市土地利用CA模型的扩展研究.地理与地理信息科学. 20(4) 48~51
罗平,杜清运.2002.基于关系数据库的CA扩展和时空模拟研究.地理学与国土研究.3
罗平,杜清运.2003.人口密度模型与CA集成的城市化时空模拟实验.测绘科学.4
罗平,杜清运.2004.地理特征元胞自动机及城市土地利用演化研究.武汉大学学报(信息科学版).29(6) 504~507
罗平,杜清运.2004.基于经典地理过程分析概念的CA模型扩展研究.武汉大学学报(工学版). 4
罗平,杜清运.2004.基于生命机制概念的城市土地利用演化CA模型研究.地理与地理信息科学.4
罗平,杜清运.2004.基于特征的CA概念模型及城市土地利用演化研究.武汉大学学报(信息科学版). 6
罗平,耿继进,李森.2005.元胞自动机地理过程模拟机制及扩展.地理科学.25(6) 504~507
罗平,何素芳,杜清运.2002.基于GIS-SD模型的兰州市住宅价格时空模拟研究.兰州大学学报(自然科学版).38(4)
罗平.2001.基于GIS和多媒体集成的旅游信息系统开发实验研究.测绘通报.12
罗平.2002.基于RS和GIS的云东海土地覆盖变化研究.佛山科技学院学报.1
骆剑承,周成虎,杨艳.2001.遥感地学智能图解模型支持下的土地覆盖/土地利用分类.自然资源学报.16(2) 179~183
马义德,齐春亮,杜鸿飞.2006.一种基于分类的改进BP神经网络图像压缩方法同.兰州大学学报(自然科学版).42(2) 68~71
牛文元.1992.理论地理学.北京:商务印书馆出版.104~106
牛文元.2004.组团式城市群是获取“发展红利”的最有效途径.领导决策信息.16
彭建,蔡运龙,P. H. Verburg.2007.喀斯特山区土地利用/土地覆被变化情景模拟[J].农业工程学报,23(7):64-70
盛晟.2008.CLUE-S模型在南京市土地利用变化研究中的应用[J].生态学杂志,27(2):235-239
史忠植.1998.高级人工智能.北京:中国科学出版社.10~58
唐菊兴,李少达,王乾.2001.城市区位模式与城市地价研究.成都理工大学学报.28(4) 429~435
王富海.2003.深圳城市空间演进研究.北京:北京大学博士学位论文.
王磊.2000.城市产业结构调整与城市空间结构演化一一以武汉市为例.城市规划汇刊.1(3)
王良健,包浩生,彭补拙.2000.基于遥感与GIS的区域土地利用变化的动态监测与预测研究.经济地理.20(2) 47~51
王微波.2004.城市战略规划研究.地域研究与开发.4
王兮之,郑影华,李森.2006.海南岛西部土地利用变化及其景观格局动态分析.中国沙漠.3 409~414
吴桂平.2008.在CLUE-S模型的改进与区域土地利用变化模拟研究[D].中南大学
吴正,黄山,胡守真.1995.华南海岸风沙地貌研究.北京:科学出版社.38~39
武晓波,赵健等.2002.细胞自动机模型用于城市发展模拟的方法初探一以海口市为例.城市规划.26(8) 69~73
谢峰.2007.基于CLUE-S模型的吐鲁番市土地利用动态变化模拟研究[D].新疆大学
姚士谋,陈爽.1998.长江三角洲区域城市空间演化趋势.地理学报.53
姚士谋.2006.中国城市快速发展及其土地政策问题的思考.深圳.第二届中国城市发展与土地政策国际研讨会论文集. 170~177
张永民,周成虎,郑纯辉等. 2006.沽源县土地利用格局的多尺度模拟与分析[J].资源科学,28(2):88-96
张显峰,崔伟宏.2001.集成GIS和元胞自动机模型进行地理时空过程模拟与预测的新方法.测绘学报.30(2) 148~155
张显峰.2000.基于CA的城市扩展动态模拟与预测.中国科学院研究生院学报.17(1) 70~79
郑丽英,刘丽艳,王海涌.2006.基于Kohonen网络一粗集一模糊神经网络获取模糊规则的集成方法.兰州大学学报(自然科学版).42(2) 68~71
周成虎,孙战利,谢一春.1999.地理元胞自动机研究.北京:科学出版社. 1~163
朱震达,刘恕,邸醒民.1989.中国的沙漠化及其治理.北京:科学出版社.234~248
Amorosos,Patty.1972.Decision Procedures for Surjectivity and Injectivity of Parallel Maps for Tessellation Structures. Computer System Sci.6 448~464
Attym, XIE Y, SUN Z.1999. Modeling Urban Dynamics through GIS-Based Cellular Automata. Computer. Environmental and Urban System.23 1~29
Banister D,Watson S, Wood C.1997. Sustainable Cities: Transport Energy and Urban Form. Environment and Planning B.24 125~143
Batty M,Xie Y.1994. From cells to cities. Environment and planning B.21 531~548
Batty M. 1997. Urban systems as cellular automata. Environment and Planning B. 24 159~164
Battym, Couclelish, Eichenm.1997.Urban System as a Cellular Automata. Environment and Planning B.24 159~164
Burks A W.1970. Eassys on Cellualr automata. University of Illinois Press UrbanaⅡCastella J.C.,Kam S.P.,Quang D.D.,et al.2007.Combining top-down and bottom-up modellingapproaches of Land Use/Cover Change to support public policies:Application to sustainable management of natural resources in northern Vietnam[J].Land Use Policy,24(3):531-545.
Castella J. C.,P.H.Verburg.2007.Combination of process-oriented and pattern-oriented models of land-use change in a mountain area of Vietnam[J].Ecological modeling,202: 410-420.
Clarke K C,Gaydos L J.1998.Loose-coupling a Cellular Automaton Model and GIS: Long-term Urban Growth Prediction for San Francisco and Washington/Baltimore . Geographical Information Science.12(7) 699~714
Couclelis H.1997.From cellular automata to urban models: New principles for model development and implementation. Environment and Planning B.24 165~174
Couelelis H.1985.Cellularworlds:A framework for modeling miero-maero dynamics. Environment and Planning A.17 585~596
Couelelis H.1989. Maerostrueture and mierobehaviour in ametropolitan area. Environment and Planning B. 16 151~154
CUPR (Center for Urban Policy Research).1992. Impact Assessment of the New Jersey Interim State Development Plan . Trenton, N J: New Jersey Office of State Planning
Ewing R.1997. Is Los Angeles-style spraw l desirable? . Journal of the American Planning Association.63(1) 107~126
Larke K C,Gaydos L J.1988. Loose-Couping a Cellular Automaton Model and GIS: Long-Term Urban Growth Prediction for San Francisco and Washington/Baltimore. Int J Geographic Science. 2(7) 699~714
Li X,Yeh A G O.2002. Neural-network-based cellular automata for simulating multiple land use changes using GIS. International Journal of Geographical Information Science. 16(4) 323~343
Luo Ping,Du Qingyun.2002. A Study on Cellular Automata Based on Relational Databases and Overmars K. P.,De Groot W. T.,Huigen M. G. A. 2007.Comparing inductive and deductive modelling of land use decisions:Principles,a model and an illustration from the Philippines[J].Human Ecology,35:439-452
Overmars,K. P.,P.H.Verburg,Veldkamp A. 2007. Comparison of a deductive and an inductive approachto specify land suitability in a spatially explicit land use model. Land Use Policy.24(3):584-599
O Sullivan D,Haklay M.2000. Agent-based models and individualism: is the world agent-based. Environment and Planning A.32(8) 1409~1425
O Sullivan D,P M Torrens.2000. Cellular models of urban systems. In Theoretical and Practical Issues on Cellular Automata. London:Springer-Verlag
P.H.Verburg, Overmars K. P.2007.Dynamic simulation of land-use change trajectories with the CLUE-s model[M].Netherlands:Springer Netherlands: 321-337
Spatio-temporal Simulations of Culture Diffusion. Chinese Geography science.4
Tobler W R.1970.A computer movie simulating urban growth in the Detroit region.EeonomicGeography.46 234~240
U lam S.1976. Adventures of a Mathematician . New York:Charles scribner’s sons Ward D P,Murray A T,Phinn S R.2000.A stochastically constrained cellular model of urban growth. Computers Environment and Urban Systems. 24 539~558
White R,Engelen G. 1993.Cellular automata and fractal urban form: a cellular modelling approach to the evolution of urban land-use patterns. Environment and Planning A.25 1175~1199
White R,G Engelen, I U ljee.1997. The use of constrained cellular automata for high-resolution modelling of urban land use dynamics. Environment and Planning B.24 323~343
Wu F,C JWebster.1998. Simulation of land development through the integration of cellular automata and multicriteria evaluation. Environment and Planning B.25 103~126
Wu F,David Martin.2002. Urban expansion simulation of Southeast England using population surface modelling and cellular automata. Environment and Planning A.34 1855~1876
Wu F.1998. SimLand: a prototype to simulate land conversion through the integrated GIS and CA with AHP-derived transition rules. Geographical Information Science. 12(1) 63~82