土地利用变化的时空可视化分析方法研究
|
摘要
土地利用变化已成为全球变化研究的热点之一。现有的土地利用变化分析模型都有各自的适用范围和适合解决的问题。时空可视化是土地利用变化分析的重要方法,能够使人们深入和全面地了解土地时空变化所反映的规律。为了加强土地利用变化科学的研究,本文从人工智能角度探讨土地利用空间数据库的更新方法,建立具有空间效应的模型来分析土地利用变化和其影响因素变化的过程,提出土地利用变化的时空可视化方法。
数据是研究的基础,现势性是衡量土地数据使用价值的重要标志。为了使土地数据库具有高度的现势性,通过对现有空间数据库更新模式的研究,利用维基思想协同工作的特点,引入人工智能领域的多代理技术,提出了一个全方位和智能化的增量式空间数据库更新机制。该机制能够激发数据使用者的互动性,缩短数据更新周期,提高数据的使用价值。
在土地利用变化过程中,耕地由于关系到区域食物安全与生态安全而备受关注。本研究综合考虑局部与整体的关系,采用年作为时间尺度,成都平原和成都平原各区县作为空间尺度,从耕地数量变化和空间变化的角度,系统地分析1998-2007年成都平原耕地数量的时空变化。同时,根据成都平原耕地数量呈现空间自相关的特征,建立空间回归模型,分析不同时期影响成都平原耕地数量变化的内在因素和外在因素。结果显示成都平原耕地数量下降趋势变得缓慢,耕地变化的空间结构趋于稳定,每年耕地变化影响因子和其影响程度均不同。据此,可以通过加强产业结构调整、土地整理与复垦来增加耕地数量,实现成都平原人地和谐发展。
针对面要素边界的复杂性,提出了求解任意形状多边形最大内接圆圆心位置和半径的等值二分法。它采用缓冲区边界生成算法中的凸角圆弧法生成等距多边形,利用二分法的原理,确定面要素最大内接圆的圆心和半径。通过与现有方法比较,利用等值二分法求解多边形最大内接圆的半径最大,适用于制图中任何形状的多边形。
可视化范围的确定是地图设计的一个重要环节,它的好坏直接影响地图的美观程度和信息的表达效果。为了解决可视化范围的占位问题,将点要素的几何中心和面要素最大内接圆的圆心作为其可视化范围的视觉中心,利用断裂点理论,从有无视图约束和可视化范围大小是否与要素特征值相关四个方面,给出了不压盖情况下点要素和面要素圆形和水平方向正方形可视化结果范围最大的计算方法。通过实例分析验证了方法的有效性。
现有的土地利用变化时空可视化方法缺乏可比性,难以满足用户的需求。考虑到用户分析和理解土地利用变化的具体要求,从显示方式的改进、降维和图形组合方式入手,引入尺寸和色彩等视觉变量,提出了一种土地利用变化的静态时空可视化方法。这种方法能够保证在较少数据量的情况下,用户能直观、形象地了解土地数量随时间变化的趋势,比较不同时间点的土地利用变化。利用现有可视化评价方法,选择可比性、易读性、是否压盖和数据表达的明确性作为可视化结果的评价因子,显示了这种可视化方法操作简单,数据直观性强,具有较强的可比性。
Land use change has become a hot topic in global change research. The existing land-use change analysis model has its own scope of application and suitable to solve problems. Spatio-temporal visualization is the important method of land use change analysis. It enables people to in-depth and comprehensive understand the spatio-temporal changes of land. In order to strengthen scientific research in land use change, the thesis built the spatial effect model to analysis the process of land use change and its influence factors, proposed in spatio-temporal visualization method of land use change, and discussed the new update method of spatial database from the perspective of artificial intelligence.
Land database must appropriately be organized and constantly be updated to make better use. This thesis outlines the current spatial database update modes and discusses some related practical issues. In order to shorten land database update periods and improve the intelligence level of system, an omnidirectional and incremental spatial database update mechanism was proposed by using the cooperative work characteristic of Wiki idea and the multi-agent technology in artificial intelligence research fields. Special resolve method, mechanism elements and data update processes are presented in detail. This multi-agent spatial database update mechanism based Wiki idea can arouse the interaction of users, shorten the period of spatial data update, improve the use value of land data and make the spatial database update more convenient and flexible.
In the process of land use change, cultivated land is more concerned for food safety and ecological security. Because of the limitations of obtainable data, by looking year as time scale, Chengdu plain and its county as spatial scale, as viewed from the amount and spatial change of arable land, this research analyzed spatio-temporal change of cultivated land in Chengdu plain from 1998 to 2007. Based on the spatial autocorrelation of cultivated land in Chengdu plain, its intrinsic factors and outer factors are systemically analyzed by setting up spatial regression models. The result indicates that the downtrend of cultivated land in Chengdu plain become slow, spatial structure change go stable, influence factors and their influence degrees is different every year. Accordingly, several suggestions are proposed in the study to realizing the harmonious development of people and cultivated land by adjusting industry structure and land consolidation and reclamation.
To fit the higher complexity of area boundary in map, we derive the equal-distance dichotomy method that determines the centre and radius of maximum inscribed circle. It creates equal-distance polygon based on the method of circular arc for convex vertex. Then, the maximum inscribed circle's centre and radius is computed by using dichotomy. Comparison with existing methods, the equal-distance dichotomy method can obtain the best results and be applied to any shape of polygons in cartography.
Determining visualization scope is an important part of map design. And it has a direct impact on the beauty of map and expression of information. To solve problem of overlap with other visualization results or other graphical features, looking upon geometric center of point or maximum inscribed circle's centre of area as vision center of its visualization, in the four ways that view constraints, no view constraints, and whether and the characteristic values associated with the size of visualization results, the maximum circular and square sizes of points or areas are obtained by using breaking point theory. Experimental results show that this method is simple and effective.
The existing space-time visualization methods of land use change are difficult to meet users' requirements by lack of comparability. Considering the users' specific requirements in analyzing and understanding land use change, the static space-time visualization method for land use change is proposed by improving display mode, reducing dimension and compounding graphs. In our method, colors are used to distinguish land type and size is used to represent land amount. Users may intuitively know the trend of land use change with time and compare the land use change of regions in different time. Selecting comparability, readability, whether overlap, and data clarity as evaluation factors by analyzing existing visual evaluation methods, the experiment result shows that this method is simple and has more comparability.
数据是研究的基础,现势性是衡量土地数据使用价值的重要标志。为了使土地数据库具有高度的现势性,通过对现有空间数据库更新模式的研究,利用维基思想协同工作的特点,引入人工智能领域的多代理技术,提出了一个全方位和智能化的增量式空间数据库更新机制。该机制能够激发数据使用者的互动性,缩短数据更新周期,提高数据的使用价值。
在土地利用变化过程中,耕地由于关系到区域食物安全与生态安全而备受关注。本研究综合考虑局部与整体的关系,采用年作为时间尺度,成都平原和成都平原各区县作为空间尺度,从耕地数量变化和空间变化的角度,系统地分析1998-2007年成都平原耕地数量的时空变化。同时,根据成都平原耕地数量呈现空间自相关的特征,建立空间回归模型,分析不同时期影响成都平原耕地数量变化的内在因素和外在因素。结果显示成都平原耕地数量下降趋势变得缓慢,耕地变化的空间结构趋于稳定,每年耕地变化影响因子和其影响程度均不同。据此,可以通过加强产业结构调整、土地整理与复垦来增加耕地数量,实现成都平原人地和谐发展。
针对面要素边界的复杂性,提出了求解任意形状多边形最大内接圆圆心位置和半径的等值二分法。它采用缓冲区边界生成算法中的凸角圆弧法生成等距多边形,利用二分法的原理,确定面要素最大内接圆的圆心和半径。通过与现有方法比较,利用等值二分法求解多边形最大内接圆的半径最大,适用于制图中任何形状的多边形。
可视化范围的确定是地图设计的一个重要环节,它的好坏直接影响地图的美观程度和信息的表达效果。为了解决可视化范围的占位问题,将点要素的几何中心和面要素最大内接圆的圆心作为其可视化范围的视觉中心,利用断裂点理论,从有无视图约束和可视化范围大小是否与要素特征值相关四个方面,给出了不压盖情况下点要素和面要素圆形和水平方向正方形可视化结果范围最大的计算方法。通过实例分析验证了方法的有效性。
现有的土地利用变化时空可视化方法缺乏可比性,难以满足用户的需求。考虑到用户分析和理解土地利用变化的具体要求,从显示方式的改进、降维和图形组合方式入手,引入尺寸和色彩等视觉变量,提出了一种土地利用变化的静态时空可视化方法。这种方法能够保证在较少数据量的情况下,用户能直观、形象地了解土地数量随时间变化的趋势,比较不同时间点的土地利用变化。利用现有可视化评价方法,选择可比性、易读性、是否压盖和数据表达的明确性作为可视化结果的评价因子,显示了这种可视化方法操作简单,数据直观性强,具有较强的可比性。
Land use change has become a hot topic in global change research. The existing land-use change analysis model has its own scope of application and suitable to solve problems. Spatio-temporal visualization is the important method of land use change analysis. It enables people to in-depth and comprehensive understand the spatio-temporal changes of land. In order to strengthen scientific research in land use change, the thesis built the spatial effect model to analysis the process of land use change and its influence factors, proposed in spatio-temporal visualization method of land use change, and discussed the new update method of spatial database from the perspective of artificial intelligence.
Land database must appropriately be organized and constantly be updated to make better use. This thesis outlines the current spatial database update modes and discusses some related practical issues. In order to shorten land database update periods and improve the intelligence level of system, an omnidirectional and incremental spatial database update mechanism was proposed by using the cooperative work characteristic of Wiki idea and the multi-agent technology in artificial intelligence research fields. Special resolve method, mechanism elements and data update processes are presented in detail. This multi-agent spatial database update mechanism based Wiki idea can arouse the interaction of users, shorten the period of spatial data update, improve the use value of land data and make the spatial database update more convenient and flexible.
In the process of land use change, cultivated land is more concerned for food safety and ecological security. Because of the limitations of obtainable data, by looking year as time scale, Chengdu plain and its county as spatial scale, as viewed from the amount and spatial change of arable land, this research analyzed spatio-temporal change of cultivated land in Chengdu plain from 1998 to 2007. Based on the spatial autocorrelation of cultivated land in Chengdu plain, its intrinsic factors and outer factors are systemically analyzed by setting up spatial regression models. The result indicates that the downtrend of cultivated land in Chengdu plain become slow, spatial structure change go stable, influence factors and their influence degrees is different every year. Accordingly, several suggestions are proposed in the study to realizing the harmonious development of people and cultivated land by adjusting industry structure and land consolidation and reclamation.
To fit the higher complexity of area boundary in map, we derive the equal-distance dichotomy method that determines the centre and radius of maximum inscribed circle. It creates equal-distance polygon based on the method of circular arc for convex vertex. Then, the maximum inscribed circle's centre and radius is computed by using dichotomy. Comparison with existing methods, the equal-distance dichotomy method can obtain the best results and be applied to any shape of polygons in cartography.
Determining visualization scope is an important part of map design. And it has a direct impact on the beauty of map and expression of information. To solve problem of overlap with other visualization results or other graphical features, looking upon geometric center of point or maximum inscribed circle's centre of area as vision center of its visualization, in the four ways that view constraints, no view constraints, and whether and the characteristic values associated with the size of visualization results, the maximum circular and square sizes of points or areas are obtained by using breaking point theory. Experimental results show that this method is simple and effective.
The existing space-time visualization methods of land use change are difficult to meet users' requirements by lack of comparability. Considering the users' specific requirements in analyzing and understanding land use change, the static space-time visualization method for land use change is proposed by improving display mode, reducing dimension and compounding graphs. In our method, colors are used to distinguish land type and size is used to represent land amount. Users may intuitively know the trend of land use change with time and compare the land use change of regions in different time. Selecting comparability, readability, whether overlap, and data clarity as evaluation factors by analyzing existing visual evaluation methods, the experiment result shows that this method is simple and has more comparability.
引文
[1]陈曦.中国干旱区土地利用与土地覆被变化[M].北京：科学出版社,2006.
[2]梁学庆,杨凤海,刘卫东.土地资源学[M].北京：科学出版社,2006.
[3]刘耀林,何建华.土地信息学[M].北京：科学出版社,2007.
[4]刘纪远,张增祥,庄大方等.20世纪90年代中国土地利用变化的遥感时空信息研究[M].北京：科学出版社,2006.
[5]Andrienko G, Andrienko N. Visual Exploration of the Spatial Distribution of Temporal Behaviors [A]. In:Proceedings of the Ninth International Conference on Information Visualisation[C]. Washington:IEEE Computer Society,2005:799-806.
[6]陈华斌,李伯楠,廖克等.多维动态地图中时态信息可视化[J].地理学报,2001,56：4348.
[7]杨国清,吴志峰,祝国瑞.广州地区土地利用景观格局变化研究[J].农业工程学报,22(5)：218-221.
[8]殷少美,周寅康,濮励杰等.马尔科夫链在预测土地利用结构中的应用[J].经济地理,2006,26(S1)：120-123.
[9]杨爽,冯晓明,陈利顶.土地利用变化的时空分异特征及驱动机制[J].生态学报,2009,29(8)：4501-4511.
[10]杨武,王玉树.偏最小二乘回归分析在土地利用变化研究中的应用[J].南京农业大学学报,2005,28(1)：115-120.
[11]Rutherford GN, Guisan A, Zimmermann NE. Evaluating sampling strategies and logistic regression methods for modeling complex land cover changes [J]. Ecology, 2007,44:414-424
[12]Irwin EG, Geoghegan J. Theory, data, methods:developing spatially explicit economic models of land use change [J]. Agriculture, Ecosystems and Environment,2001,85(1)：7-23.
[13]摆万奇.深圳市土地利用动态趋势分析[J].自然资源学报,2000,25(2)：112-116.
[14]汤发树,陈曦,罗格平.新疆三工河绿洲土地利用变化系统动力学仿真[J].中国沙漠,2007,27(4)：593-599.
[15]Shen Q, Chen Q, Tang B, et al. A system dynamics model for the sustainable land use planning and development [J]. Habitat International,2009,33(1):15-25.
[16]Saysel AK, Barlas Y, Yenigun O. Long term sustainability in an agricultural development project:A System Dynamics Approach [J]. Journal of Environmental Management,2002,64:247-260.
[17]杨青生.地理元胞自动机及空间动态转换规则的获取[J].中山大学学报(自然科学版),2008,47(4)：122-127.
[18]Moreno N, Wang F, Marceau DJ. Implementation of a dynamic neighborhood in a land-use vector-based cellular automata model [J]. Computers, Environment and Urban Systems,2009,33(1):44-54.
[19]罗平,杜清运,雷元新.地理特征元胞自动机及城市土地利用演化研究[J].武汉大学学报(信息科学版),2004,29(6)：504-507.
[20]王劲峰.空间分析[M].北京：科学出版社,2006.
[21]朱利凯,蒙吉军.国际LUCC模型研究进展及趋势[J].地理科学进展,2009,28(5)：782-790.
[22]彭翀,杜宁睿,刘云.大城市居住用地扩展的多主体模型研究[J].武汉大学学报(信息科学版),2007,32(6)：548-551.
[23]李新延,李德仁.应用多主体系统预测和分析城市用地变化[J].武汉大学学报(工学版),2005,38(5)：111-115.
[24]Le QB, Park SJ, Vlek PLG, et al. Land-Use Dynamic Simulator (LUDAS):A multi-agent system model for simulating spatio-temporal dynamics of coupled human-landscape system. Ⅰ. Structure and theoretical specification [J]. Ecological Informatics,2008,3(2):135-153.
[25]Ligtenberg A, Bregt AK, Van Lammeren R. Multi-actor-based land use modelling: spatial planning using agents [J].Landscape and Urban Planning,2001,56:21-33.
[26]段学军,秦贤宏,陈江龙.基于生态-经济导向的泰州市建设用地优化配置[J].自然资源学报,2009,24(7)：1181-1191.
[27]姜文亮.基于GIS和空间Logistic模型的城市扩展预测[J].经济地理,2007,(5)：800-804.
[28]何春阳,史培军,陈晋.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(5)：464-473.
[29]黎夏,叶嘉安.基于神经网络的单元自动机CA及真实和优化的城市模拟[J].地理学报,2002,57(2)：159-166.
[30]Verburg PH, Soepboer W, Veldkamp A,et al. Modeling the spatial dynamics of regional land use:The CLUE-S model [J]. Environmental Management,2002,30:391-405.
[31]段增强,Verburg PH,张凤荣等.土地利用动态模拟模型的构建及其应用[J].地理学报,2004,59(6)：1037-1047.
[32]蔡玉梅,刘彦随,宇振荣,等.土地利用变化空间模拟的进展——CLUE-S模型及其应用[J].地理科学进展,2004,8(4)：63-71.
[33]Verburg PH, Schot PP, Dijst MJ,et al. Land use change modelling:current practice and research priorities [J]. GeoJournal,2004,61:309-324.
[34]Andrienko N, Andrienko G., Gatalsky P. Exploratory Spatio-Temporal Visualization:an Analytical Review [J]. Journal of Visual Languages and Computing,2003, 14(6):503-541.
[35]Hewagamage KP, Hirakawa M, Ichikawa T. Interactive Visualization of Spatiotemporal Patterns Using Spirals on a Geographical Map [A]. In:Proceedings IEEE Symposium on Visual Languages[C]. Washington:IEEE Computer Society Press,1999:296-303.
[36]Chen J, Guo D, MacEachren AM. Space-Time-Attribute Analysis and Visualization of U.S. Company Data [A]. IEEE Symposium on Information Visualization [C]. Minneapolis,2005:55-56.
[37]Inselberg A, Dimsdale B. Parallel coordinates:A tool for visualizing multi-dimensional geometry [J]. Proc visualization,1990:361-370.
[38]王英杰,袁堪省,余卓渊.多维动态地学信息可视化[M].北京：科学出版社,2003.
[39]Shanbhag P, Rheingans P, desJardins M. Temporal visualization of planning polygons for efficient partitioning of geo-spatial data [A]. IEEE Symposium on Information Visualization [C].Washington:IEEE Computer Society,2005:211-218.
[40]Kraak M,周小红,王吉军.时空体在地理可视化环境中的应用[J].测绘文摘,2004,(1)：8-9.
[41]Kraak MJ. The space-time cube revisited from a geovisualization perspective [A]. In: Proceedings of the 21st international cartographic conference [C]. Durban:International Cartographic Association,2003:1988-1996.
[42]焦健,曾琪明.地图学[M].北京：北京大学出版社,2005.
[43]李霖,苗蕾.时间动态地图模型[J].武汉大学学报(信息科学版),2004,29(6)：484-487.
[44]Andrienko N, Andrienko G., Gatalsky P. Impact of Data and Task Characteristics on Design of Spatio-Temporal Data Visualization Tools[A]. In:Dykes J, MacEachren AM, Kraak MJ (Eds). Exploring Geovisualization [C]. Amsterdam:Elsevier,2005:201-222.
[45]Andrienko N, Andrienko G, Gatalsky P. Tools for visual comparison of spatial development scenarios [A].In Proceedings of the Seventh International Conference on Information Visualization [C]. Washington:IEEE Computer Society,2003:237-244.
[46]Rensink RA, O'Regan JK, Clark J. To See or Not to See:The Need for Attention to Perceive Changes in Scenes [J]. Psychological Science,1997,8:368-373.
[47]Openshaw S. Two exploratory space-time-attribute pattern analysers relevant to GIS[A]. In:Fotheringham, AS, Rogerson, PA (Eds). Spatial analysis and GIS [C]. London: Taylor and Francis Ltd,1994:83-103.
[48]Koua EL, MacEachren AM, Kraak MJ. Evaluating the usability of visualization methods in an exploratory geovisualization environment [J]. International Journal of Geographic Information Science,2006,20(4):425-448.
[49]四川省统计局,国家统计局,四川调查总队.四川省统计年鉴[M].北京：中国统计出版社,1999-2008.
[50]周晓光.基于拓扑关系的地籍数据库增量更新方法研究[J].测绘学报,2005,34(4)：372.
[51]Fritsch D. GIS Data Revision visions and Reality[R]. Keynote Speech in Joint ISPRS Commission Workshop on Dynamic and Multi-dimensional GIS Beijing:NGCC,1999.
[52]Patynen V. Digital Orthophotos and Map Revision in National Land Survey of Finland[J].International Archives of Photogrammetry and Remote Sensing on GIS between Visions and Application,1998,32(4):463-466.
[53]王少华,边馥苓.GIS数据库自动更新机制研究[J].武汉大学学报(信息科学版),2004,29(12)：1059-1062.
[54]范玉顺,曹军威.多代理系统理论、方法与应用[M].北京：清华大学出版社,2002.
[55]裘伟廷.维客在网络教育中的应用[J].计算机系统应用,2006,(2)：2-5.
[56]宋其友,杨喜敏,李泰轩.土地信息学[M].北京：科学出版社,2000.
[57]Tor Bernhardsen地理信息系统导论[M].北京：机械工业出版社,2005.
[58]Pedersen B, Kearns F, Kelly M. Methods for facilitating web-based participatory research informatics [J]. Ecological Informatics,2007,2(1):33-42.
[59]倪凯,祝晓东.多智能体在WebGIS中的应用研究[J].计算机工程,2007,33(3)：183185.
[60]Gao G, Wang S. A multi--Agent system architecture for geographic information gathering [J]. Journal of Zhejiang University Science,2004,5(1 J):1367-1373.
[61]Hanzl M. Information technology as a tool for public participation in urban planning:a review of experiments and potentials [J].Design Studies,2007,28(3):289-307.
[62]Ma R, Wan B, Hu Q, et al. A Multi-Agent System Using in Spatial Information Sharing on Web-Based GIS [A].In:Proceedings of IEEE NLP-KE'05:Natural Language Processing and Knowledge Engineering [C]. Piscataway:IEEE Press Center,2005, 466-471.
[63]朱会义,李秀彬.关于区域土地利用变化指数模型方法的讨论[J].地理学报,2003,58(5)：643-650.
[64]何国松,祝国瑞.基于时空分析的贫困丘陵山区耕地变化机理研究[J].武汉大学学 报(信息科学版),2004,29(6)：508-512.
[65]Goodchild MF. Keynote address:geography and statisticians [A].In:Proceedings, Symposium'91:Spatial Issues in Statistics[C]. Ottawa:Statistics Canada 1992:7-14.
[66]Overmars KP, De Koning GHJ, Veldkamp A. Spatial autocorrelation in multi-scale land use models [J].Ecological Modelling,2003,164:257-270.
[67]Nicolas D, Mark R, Patrick B. Spatial analysis and modelling of land use distributions in Belgium [J]. Computers, Environment and Urban Systems,2007,31(2):188-205.
[68]Goodchild MF. Geography and statisticians [J]. The Operational Geographer,1992, 10(2):3-11.
[69]刘旭华,王劲峰,刘纪远,等.国家尺度耕地变化驱动力的定量分析方法[J].农业工程学报,2005,21(4)：56-60.
[70]Anselin L. Spatial econometrics:Methods and Models [M]. Dordrecht:Kluwer Academic Publishers,1988.
[71]Nascimento HAD, Eades P. User Hints for map labeling [J]. Journal of Visual Languages and Computing,2008,19 (1):39-74.
[72]江南,夏丽华,薛本新.GIS中空间信息多种地图显示模式的研究[J].测绘科学技术学报,2006,23(3)：157-160.
[73]Morgan MJ. The visual computation of 2-D area by human observers [J]. Vision Research,2005,45:2564-2570.
[74]祝国瑞.地图学[M].武汉：武汉大学出版社,2004.
[75]王家耀,孙群,王光霞等.地图学原理与方法[M].北京：科学出版社,2006.
[76]基茨JS.地图设计与生产[M].北京：测绘出版社,1983.
[77]陈毓芬,江南.地图设计原理[M].北京：解放军出版社,2001.
[78]Longley PA, Goodchild MF, Maguire DJ, et al. Geographical Information Systems and Science [M]. England:John Wiley & Sons Ltd,2005.
[79]Haeeie L, Revell P. Automation of Vegetation Symbol Placement on Ordnance Survey 1:50000 Scale Maps [J]. Cartographic Journal,2007,44 (3):258-267.
[80]Guo D. Visual analytics of spatial interaction patterns for pandemic decision support [J]. International Journal of Geographical Information Science,2007,21(8):859-877.
[81]程红霞,李永树,林粤江.一种新的邻近点间相互作用大小的可视化方法[J].地理与地理信息科学,2009,25(1)：68-70.
[82]刘平.用计算机求最小外接圆和最大内切圆的快速、精确方法[J].宇航计测技术,1990(2)：20-25.
[83]孙玉琴,车仁生.求解最大内切圆的一种新方法[J].光学精密工程,2003,11(2)：181 185.
[84]郑梅生,陈宁,宋超.计算任意多边形最大内圆的一种算法[J].机械设计与制造,2003,(5)：84-85.
[85]刘书桂,杨芳,邹志华等.计算几何在测试计量技术中的应用—求解最大内接圆[J].仪器仪表学报,1998,19(6)：576-519.
[86]王结臣,芮一康,李永全.一种基于矢量边界追踪的缓冲区生成方法[J].计算机工程与应用,2007,43(33)：66-68.
[87]毋河海.关于GIS缓冲区的建立问题[J].武汉测绘科技大学学报,1997,22(4)：358366.
[88]吴立新,史文中.地理信息系统原理与算法[M].北京：科学出版社,2003.
[89]栾晓岩,孙群,耿忠.时态信息可视化模型研究及实现[J].测绘科学技术学报,2008,25(6)：451-454.
[90]黄培之,Poh-Chin Lai时间序列空间数据可视化中有关问题的研究[J].武汉大学学报(信息科学版),2004,29(7)：584-587.
[91]陈宏敏,战守义,高宇,等.航天测控中时空数据的可视化技术研究[J].系统仿真学报,2009,21(8)：5775-5778.
[92]DiBiase D.Visualization in the earth sciences [J].Mineral Sciences,1990,59 (2):13-18.
[93]Taylor DRF. Cartography for Knowledge, Action and Development:Retrospective and Prospective [J]. The Cartography Journal,1994,31:52-55.
[94]Kraak MJ. Cartography and the Use of Animation [A]. In:Cartwright W, Peterson M P, Gartner G, eds. Multimedia Cartography[C]. New York:Springer,2007:317-325.
[95]夏慧琼,李德仁,邵振峰,等.一种时空数据静态可视化表达方法[J].测绘科学,2008,33(6)：116-118.
[96]付永恒.2维地图符号与3维可视化的关系[J].测绘科学技术学报,2007,24(S0)：7375.
[97]Fischer MM. Spatial analysis and geocomputation [M]. Berlin:Springer,2006.
[98]黎夏,刘凯.GIS与空间分析原理与方法[M].北京：科学出版社,2006：149.
[99]Keim D, Andrienko G, Fekete JD, et al. Visual Analytics Definition, Process, and Challenges [A]. In:Information visualization [C]. Berlin:Springer,2008,4950: 154-175.
[100]MacEachren AM. Map Complexity:Comparison and Measurement [J].The American Cartographer,1982,9(1):31-46.
[101]Andrienko N. Testing the Usability of Interactive Maps in CommonGIS [J]. Cartography and Geographic Information Science,2002,29(4):325-342.
[102]Slocum TA, Blok C, Jiang B, et al.Cognitive and usability issues in geovisualization [J]. International Journal of Geographical Information Science,2001,28(1):61-75.
[103]Tobon C. Evaluating Geographic Visualization Tools and Methods:An Approach and Experiment Based upon User Tasks [A]. In:Dykes J, MacEachren AM, Kraak MJ (Eds). Exploring Geovisualization [C]. Amsterdam:Elsevier,2005:645-666.
[104]Sven Fuhrmann. Making Useful and Useable Geovisualization:Design and Evaluation Issues [A]. In:Dykes J, MacEachren AM, Kraak MJ (Eds). Exploring Geovisualization [C]. Amsterdam:Elsevier,2005:553-566.
[105]Fuhrmann S, Pike W. User-centered Design of Collaborative Geovisualization Tools[A]. In:Dykes J, MacEachren AM, Kraak MJ (Eds). Exploring Geovisualization [C]. Amsterdam:Elsevier,2005:591-609.
[106]MacEachren AM. Accuracy of thematic maps Implications of choropleth symbolization [J].Cartographica,1985,22(I):38-58.
[107]MacEachren AM. The role of complexity and symbolization method in thematic map effectiveness [J]. Annals of the Association of American Geographers,1982,72(4): 495-513.
[2]梁学庆,杨凤海,刘卫东.土地资源学[M].北京：科学出版社,2006.
[3]刘耀林,何建华.土地信息学[M].北京：科学出版社,2007.
[4]刘纪远,张增祥,庄大方等.20世纪90年代中国土地利用变化的遥感时空信息研究[M].北京：科学出版社,2006.
[5]Andrienko G, Andrienko N. Visual Exploration of the Spatial Distribution of Temporal Behaviors [A]. In:Proceedings of the Ninth International Conference on Information Visualisation[C]. Washington:IEEE Computer Society,2005:799-806.
[6]陈华斌,李伯楠,廖克等.多维动态地图中时态信息可视化[J].地理学报,2001,56：4348.
[7]杨国清,吴志峰,祝国瑞.广州地区土地利用景观格局变化研究[J].农业工程学报,22(5)：218-221.
[8]殷少美,周寅康,濮励杰等.马尔科夫链在预测土地利用结构中的应用[J].经济地理,2006,26(S1)：120-123.
[9]杨爽,冯晓明,陈利顶.土地利用变化的时空分异特征及驱动机制[J].生态学报,2009,29(8)：4501-4511.
[10]杨武,王玉树.偏最小二乘回归分析在土地利用变化研究中的应用[J].南京农业大学学报,2005,28(1)：115-120.
[11]Rutherford GN, Guisan A, Zimmermann NE. Evaluating sampling strategies and logistic regression methods for modeling complex land cover changes [J]. Ecology, 2007,44:414-424
[12]Irwin EG, Geoghegan J. Theory, data, methods:developing spatially explicit economic models of land use change [J]. Agriculture, Ecosystems and Environment,2001,85(1)：7-23.
[13]摆万奇.深圳市土地利用动态趋势分析[J].自然资源学报,2000,25(2)：112-116.
[14]汤发树,陈曦,罗格平.新疆三工河绿洲土地利用变化系统动力学仿真[J].中国沙漠,2007,27(4)：593-599.
[15]Shen Q, Chen Q, Tang B, et al. A system dynamics model for the sustainable land use planning and development [J]. Habitat International,2009,33(1):15-25.
[16]Saysel AK, Barlas Y, Yenigun O. Long term sustainability in an agricultural development project:A System Dynamics Approach [J]. Journal of Environmental Management,2002,64:247-260.
[17]杨青生.地理元胞自动机及空间动态转换规则的获取[J].中山大学学报(自然科学版),2008,47(4)：122-127.
[18]Moreno N, Wang F, Marceau DJ. Implementation of a dynamic neighborhood in a land-use vector-based cellular automata model [J]. Computers, Environment and Urban Systems,2009,33(1):44-54.
[19]罗平,杜清运,雷元新.地理特征元胞自动机及城市土地利用演化研究[J].武汉大学学报(信息科学版),2004,29(6)：504-507.
[20]王劲峰.空间分析[M].北京：科学出版社,2006.
[21]朱利凯,蒙吉军.国际LUCC模型研究进展及趋势[J].地理科学进展,2009,28(5)：782-790.
[22]彭翀,杜宁睿,刘云.大城市居住用地扩展的多主体模型研究[J].武汉大学学报(信息科学版),2007,32(6)：548-551.
[23]李新延,李德仁.应用多主体系统预测和分析城市用地变化[J].武汉大学学报(工学版),2005,38(5)：111-115.
[24]Le QB, Park SJ, Vlek PLG, et al. Land-Use Dynamic Simulator (LUDAS):A multi-agent system model for simulating spatio-temporal dynamics of coupled human-landscape system. Ⅰ. Structure and theoretical specification [J]. Ecological Informatics,2008,3(2):135-153.
[25]Ligtenberg A, Bregt AK, Van Lammeren R. Multi-actor-based land use modelling: spatial planning using agents [J].Landscape and Urban Planning,2001,56:21-33.
[26]段学军,秦贤宏,陈江龙.基于生态-经济导向的泰州市建设用地优化配置[J].自然资源学报,2009,24(7)：1181-1191.
[27]姜文亮.基于GIS和空间Logistic模型的城市扩展预测[J].经济地理,2007,(5)：800-804.
[28]何春阳,史培军,陈晋.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(5)：464-473.
[29]黎夏,叶嘉安.基于神经网络的单元自动机CA及真实和优化的城市模拟[J].地理学报,2002,57(2)：159-166.
[30]Verburg PH, Soepboer W, Veldkamp A,et al. Modeling the spatial dynamics of regional land use:The CLUE-S model [J]. Environmental Management,2002,30:391-405.
[31]段增强,Verburg PH,张凤荣等.土地利用动态模拟模型的构建及其应用[J].地理学报,2004,59(6)：1037-1047.
[32]蔡玉梅,刘彦随,宇振荣,等.土地利用变化空间模拟的进展——CLUE-S模型及其应用[J].地理科学进展,2004,8(4)：63-71.
[33]Verburg PH, Schot PP, Dijst MJ,et al. Land use change modelling:current practice and research priorities [J]. GeoJournal,2004,61:309-324.
[34]Andrienko N, Andrienko G., Gatalsky P. Exploratory Spatio-Temporal Visualization:an Analytical Review [J]. Journal of Visual Languages and Computing,2003, 14(6):503-541.
[35]Hewagamage KP, Hirakawa M, Ichikawa T. Interactive Visualization of Spatiotemporal Patterns Using Spirals on a Geographical Map [A]. In:Proceedings IEEE Symposium on Visual Languages[C]. Washington:IEEE Computer Society Press,1999:296-303.
[36]Chen J, Guo D, MacEachren AM. Space-Time-Attribute Analysis and Visualization of U.S. Company Data [A]. IEEE Symposium on Information Visualization [C]. Minneapolis,2005:55-56.
[37]Inselberg A, Dimsdale B. Parallel coordinates:A tool for visualizing multi-dimensional geometry [J]. Proc visualization,1990:361-370.
[38]王英杰,袁堪省,余卓渊.多维动态地学信息可视化[M].北京：科学出版社,2003.
[39]Shanbhag P, Rheingans P, desJardins M. Temporal visualization of planning polygons for efficient partitioning of geo-spatial data [A]. IEEE Symposium on Information Visualization [C].Washington:IEEE Computer Society,2005:211-218.
[40]Kraak M,周小红,王吉军.时空体在地理可视化环境中的应用[J].测绘文摘,2004,(1)：8-9.
[41]Kraak MJ. The space-time cube revisited from a geovisualization perspective [A]. In: Proceedings of the 21st international cartographic conference [C]. Durban:International Cartographic Association,2003:1988-1996.
[42]焦健,曾琪明.地图学[M].北京：北京大学出版社,2005.
[43]李霖,苗蕾.时间动态地图模型[J].武汉大学学报(信息科学版),2004,29(6)：484-487.
[44]Andrienko N, Andrienko G., Gatalsky P. Impact of Data and Task Characteristics on Design of Spatio-Temporal Data Visualization Tools[A]. In:Dykes J, MacEachren AM, Kraak MJ (Eds). Exploring Geovisualization [C]. Amsterdam:Elsevier,2005:201-222.
[45]Andrienko N, Andrienko G, Gatalsky P. Tools for visual comparison of spatial development scenarios [A].In Proceedings of the Seventh International Conference on Information Visualization [C]. Washington:IEEE Computer Society,2003:237-244.
[46]Rensink RA, O'Regan JK, Clark J. To See or Not to See:The Need for Attention to Perceive Changes in Scenes [J]. Psychological Science,1997,8:368-373.
[47]Openshaw S. Two exploratory space-time-attribute pattern analysers relevant to GIS[A]. In:Fotheringham, AS, Rogerson, PA (Eds). Spatial analysis and GIS [C]. London: Taylor and Francis Ltd,1994:83-103.
[48]Koua EL, MacEachren AM, Kraak MJ. Evaluating the usability of visualization methods in an exploratory geovisualization environment [J]. International Journal of Geographic Information Science,2006,20(4):425-448.
[49]四川省统计局,国家统计局,四川调查总队.四川省统计年鉴[M].北京：中国统计出版社,1999-2008.
[50]周晓光.基于拓扑关系的地籍数据库增量更新方法研究[J].测绘学报,2005,34(4)：372.
[51]Fritsch D. GIS Data Revision visions and Reality[R]. Keynote Speech in Joint ISPRS Commission Workshop on Dynamic and Multi-dimensional GIS Beijing:NGCC,1999.
[52]Patynen V. Digital Orthophotos and Map Revision in National Land Survey of Finland[J].International Archives of Photogrammetry and Remote Sensing on GIS between Visions and Application,1998,32(4):463-466.
[53]王少华,边馥苓.GIS数据库自动更新机制研究[J].武汉大学学报(信息科学版),2004,29(12)：1059-1062.
[54]范玉顺,曹军威.多代理系统理论、方法与应用[M].北京：清华大学出版社,2002.
[55]裘伟廷.维客在网络教育中的应用[J].计算机系统应用,2006,(2)：2-5.
[56]宋其友,杨喜敏,李泰轩.土地信息学[M].北京：科学出版社,2000.
[57]Tor Bernhardsen地理信息系统导论[M].北京：机械工业出版社,2005.
[58]Pedersen B, Kearns F, Kelly M. Methods for facilitating web-based participatory research informatics [J]. Ecological Informatics,2007,2(1):33-42.
[59]倪凯,祝晓东.多智能体在WebGIS中的应用研究[J].计算机工程,2007,33(3)：183185.
[60]Gao G, Wang S. A multi--Agent system architecture for geographic information gathering [J]. Journal of Zhejiang University Science,2004,5(1 J):1367-1373.
[61]Hanzl M. Information technology as a tool for public participation in urban planning:a review of experiments and potentials [J].Design Studies,2007,28(3):289-307.
[62]Ma R, Wan B, Hu Q, et al. A Multi-Agent System Using in Spatial Information Sharing on Web-Based GIS [A].In:Proceedings of IEEE NLP-KE'05:Natural Language Processing and Knowledge Engineering [C]. Piscataway:IEEE Press Center,2005, 466-471.
[63]朱会义,李秀彬.关于区域土地利用变化指数模型方法的讨论[J].地理学报,2003,58(5)：643-650.
[64]何国松,祝国瑞.基于时空分析的贫困丘陵山区耕地变化机理研究[J].武汉大学学 报(信息科学版),2004,29(6)：508-512.
[65]Goodchild MF. Keynote address:geography and statisticians [A].In:Proceedings, Symposium'91:Spatial Issues in Statistics[C]. Ottawa:Statistics Canada 1992:7-14.
[66]Overmars KP, De Koning GHJ, Veldkamp A. Spatial autocorrelation in multi-scale land use models [J].Ecological Modelling,2003,164:257-270.
[67]Nicolas D, Mark R, Patrick B. Spatial analysis and modelling of land use distributions in Belgium [J]. Computers, Environment and Urban Systems,2007,31(2):188-205.
[68]Goodchild MF. Geography and statisticians [J]. The Operational Geographer,1992, 10(2):3-11.
[69]刘旭华,王劲峰,刘纪远,等.国家尺度耕地变化驱动力的定量分析方法[J].农业工程学报,2005,21(4)：56-60.
[70]Anselin L. Spatial econometrics:Methods and Models [M]. Dordrecht:Kluwer Academic Publishers,1988.
[71]Nascimento HAD, Eades P. User Hints for map labeling [J]. Journal of Visual Languages and Computing,2008,19 (1):39-74.
[72]江南,夏丽华,薛本新.GIS中空间信息多种地图显示模式的研究[J].测绘科学技术学报,2006,23(3)：157-160.
[73]Morgan MJ. The visual computation of 2-D area by human observers [J]. Vision Research,2005,45:2564-2570.
[74]祝国瑞.地图学[M].武汉：武汉大学出版社,2004.
[75]王家耀,孙群,王光霞等.地图学原理与方法[M].北京：科学出版社,2006.
[76]基茨JS.地图设计与生产[M].北京：测绘出版社,1983.
[77]陈毓芬,江南.地图设计原理[M].北京：解放军出版社,2001.
[78]Longley PA, Goodchild MF, Maguire DJ, et al. Geographical Information Systems and Science [M]. England:John Wiley & Sons Ltd,2005.
[79]Haeeie L, Revell P. Automation of Vegetation Symbol Placement on Ordnance Survey 1:50000 Scale Maps [J]. Cartographic Journal,2007,44 (3):258-267.
[80]Guo D. Visual analytics of spatial interaction patterns for pandemic decision support [J]. International Journal of Geographical Information Science,2007,21(8):859-877.
[81]程红霞,李永树,林粤江.一种新的邻近点间相互作用大小的可视化方法[J].地理与地理信息科学,2009,25(1)：68-70.
[82]刘平.用计算机求最小外接圆和最大内切圆的快速、精确方法[J].宇航计测技术,1990(2)：20-25.
[83]孙玉琴,车仁生.求解最大内切圆的一种新方法[J].光学精密工程,2003,11(2)：181 185.
[84]郑梅生,陈宁,宋超.计算任意多边形最大内圆的一种算法[J].机械设计与制造,2003,(5)：84-85.
[85]刘书桂,杨芳,邹志华等.计算几何在测试计量技术中的应用—求解最大内接圆[J].仪器仪表学报,1998,19(6)：576-519.
[86]王结臣,芮一康,李永全.一种基于矢量边界追踪的缓冲区生成方法[J].计算机工程与应用,2007,43(33)：66-68.
[87]毋河海.关于GIS缓冲区的建立问题[J].武汉测绘科技大学学报,1997,22(4)：358366.
[88]吴立新,史文中.地理信息系统原理与算法[M].北京：科学出版社,2003.
[89]栾晓岩,孙群,耿忠.时态信息可视化模型研究及实现[J].测绘科学技术学报,2008,25(6)：451-454.
[90]黄培之,Poh-Chin Lai时间序列空间数据可视化中有关问题的研究[J].武汉大学学报(信息科学版),2004,29(7)：584-587.
[91]陈宏敏,战守义,高宇,等.航天测控中时空数据的可视化技术研究[J].系统仿真学报,2009,21(8)：5775-5778.
[92]DiBiase D.Visualization in the earth sciences [J].Mineral Sciences,1990,59 (2):13-18.
[93]Taylor DRF. Cartography for Knowledge, Action and Development:Retrospective and Prospective [J]. The Cartography Journal,1994,31:52-55.
[94]Kraak MJ. Cartography and the Use of Animation [A]. In:Cartwright W, Peterson M P, Gartner G, eds. Multimedia Cartography[C]. New York:Springer,2007:317-325.
[95]夏慧琼,李德仁,邵振峰,等.一种时空数据静态可视化表达方法[J].测绘科学,2008,33(6)：116-118.
[96]付永恒.2维地图符号与3维可视化的关系[J].测绘科学技术学报,2007,24(S0)：7375.
[97]Fischer MM. Spatial analysis and geocomputation [M]. Berlin:Springer,2006.
[98]黎夏,刘凯.GIS与空间分析原理与方法[M].北京：科学出版社,2006：149.
[99]Keim D, Andrienko G, Fekete JD, et al. Visual Analytics Definition, Process, and Challenges [A]. In:Information visualization [C]. Berlin:Springer,2008,4950: 154-175.
[100]MacEachren AM. Map Complexity:Comparison and Measurement [J].The American Cartographer,1982,9(1):31-46.
[101]Andrienko N. Testing the Usability of Interactive Maps in CommonGIS [J]. Cartography and Geographic Information Science,2002,29(4):325-342.
[102]Slocum TA, Blok C, Jiang B, et al.Cognitive and usability issues in geovisualization [J]. International Journal of Geographical Information Science,2001,28(1):61-75.
[103]Tobon C. Evaluating Geographic Visualization Tools and Methods:An Approach and Experiment Based upon User Tasks [A]. In:Dykes J, MacEachren AM, Kraak MJ (Eds). Exploring Geovisualization [C]. Amsterdam:Elsevier,2005:645-666.
[104]Sven Fuhrmann. Making Useful and Useable Geovisualization:Design and Evaluation Issues [A]. In:Dykes J, MacEachren AM, Kraak MJ (Eds). Exploring Geovisualization [C]. Amsterdam:Elsevier,2005:553-566.
[105]Fuhrmann S, Pike W. User-centered Design of Collaborative Geovisualization Tools[A]. In:Dykes J, MacEachren AM, Kraak MJ (Eds). Exploring Geovisualization [C]. Amsterdam:Elsevier,2005:591-609.
[106]MacEachren AM. Accuracy of thematic maps Implications of choropleth symbolization [J].Cartographica,1985,22(I):38-58.
[107]MacEachren AM. The role of complexity and symbolization method in thematic map effectiveness [J]. Annals of the Association of American Geographers,1982,72(4): 495-513.