新数字高程模型下的数字综合研究及关键生产技术
|
摘要
数字高程模型(Digital Elevation Model, DEM)是国家级地球信息基础产品之一,横跨水利、测绘、国防建设和所有涉及地球三维信息的部门,作为地球空间数据框架(DGDF)的主要内容之一,在半个多世纪的发展中,已有了相当大规模的生产实践,在许多应用领域里发挥着巨大作用。
国家测绘部门经过多年的共同努力,已完成全国1：1万、1：5万、1：25万DEM的初始建库工作。关于如何持续与及时的精化现有全国1：5万、1：1万、1：25万DEM成果,保证高程数据的准确性、可靠性,已经成为基础测绘工作者和广大用户共同关切的热点问题。
数字高程模型作为地形表面的一种数字表达,具有传统地形图无法比拟的优点,同时在长期实践中也显露出的一些“由来已久”的问题,尤其是质量问题,让人们不得不去反思由于理论基础的薄弱带来的技术基础的不足。DEM从定义到生成,从实际地形到质量评价,都是一环扣一环紧密进行的。针对当前DEM质量评价没有统一规范来检测,以及应用中普遍存在的问题,新数字高程模型的理论方法应用的提出,为如何生成高质量(高保真)DEM打开了思路。
随着数据获取源多元化和应用需求多样化,在数据组织多尺度与高程采样性的双重制约下,本文在地面三大本质特性的基础上,对递归数字综合技术方法实现进行了研究,并对DEM大规模数据试生产也做相关了探讨。具体研究工作如下：
第一,对传统DEM在地图/地貌综合,地形地貌特征保持,DEM质量标准,DEM精度评价方法,多尺度可视化以及DEM工程生产等方面国内外研究现状进行总结分析,针对热门疑难问题,提出了解决问题的理想途径——新数字高程模型。强调两个基本论点①致密的高保真DEM是DEM综合的基础和根本保证；②生成指定分辨率下高质量DEM必须通过DEM数字综合。尤其是在“特征保持”问题上,与传统自顶向下不同,提出了特征建模下的数字综合——采用地图代数的栅格方法由底向上途径,采用邻域点高程特征比较有效实现相对特征点的保留,为疑难问题的解决带来了新思路。
第二,实际和新的研究表明地面三大本质特性：①高程准确性、②高程序列正确性、③高程的极值特征和结构特性,是DEM必须具备的。结合实际需求以及当前DEM发展情况,分析了三大特性相互独立而又相互支撑的关系,明确了“数字综合”的基本原理与前提环境基础,为技术实现做了理论准备。
第三,结合当前研究动态,在特征建模下以“地形地貌特征保持”为出发点,考虑到特征的层次系统关系,顾及各层次(间)的局部与全局的关系,交互中尽量避免阈值的设置,使得算法实现容易,应用简单方便。不同地形地貌的数据实验的等高线回放图表明,该算法可行,且一定程度上结果较优。
第四,在DEM数字递归综合及可视化的基础上,对于传统的等高线综合这个百年难题,理论上只有通过三维形体的结构综合,才能以令人信服的可靠性实现解算,而DEM数字综合恰恰正是三维形体的结构综合,综合后的DEM将是该分辨率上科学的高程模型。并且,这样的DEM即和其间距相应0.1毫米的比例尺地图相当。不同区域的实验结果表明,在DEM数字综合的同时实际上相应完成了该地区等高线的综合,不同综合程度的等高线是DEM数字综合得到产品中的一种伴生品。参考地图综合,主要针对DEM数字综合与等高线综合的联系和区别做了相关探讨,最终从等高线多尺度的可视化角度,对相关结果进行比较分析,说明综合的意义。
第五,在实验室前期丰富成果的基础上,结合数字综合技术的实现,将高质量DEM生产软件进行集成。探讨了DEM生产的技术流程,技术指标以及关键技术实现。同时开展了大规模数据实验。实验结果表明新数字高程模型的生产技术软件的成熟性,以及工程化的实用性。
第六,通过对大规模的数据试生产实验的数据结果做详细的质量评价分析,验证了新数字高程模型的优越性以及其带来的现实意义。质量评价分析,主要是针对新提出的质量标准,对局部特征,以及从全局的角度上,理论结合实际,进行DEM质量检查：方面,等高线多尺度可视化,实现视觉效果对比；一方面,结合检验算法,开发检验工具,对这些质量指标实现DEM质量量化统计分析。最终用统计结果说明了新数字高程模型这套理论到技术的可行性和优越性。
Digital Elevation Model (DEM) is one kind of the national products of geography information, which has been widely applied in many departments about the earth's three-dimensional information such as water resources, mapping, national defense and others, and is the most important part of DGDF. In half of a century's development, it already has a very large-scale production in practice and has played a significant role in many applications.
For many-years'efforts, the National Survey and Mapping Department has build the DEM databases in scale of 1:10000,1:50000,1:25000. The follow work is how to keep the quality and update the databases in time, which is the focus for many users and the mapping workers.
DEM, as a digital representation of terrain surface, has many advantages that the traditional topographic map can not compare with. But it also has much problem in practice, especially in quality assessment. So we should take the theory basis and the technical basis to think through their shortages. As we know, from the definition to the production, from the real terrain to the quality assessment, every process is closely related. So in this situation, the new DEM theory and technology in application have given us a new way to solve all these problems.
At present there are many kinds of data sources and application requirements, then there presents many discussions about data organization in multi-scale and sampling of elevation. So in this paper, we do some researches about the processive digital generalization and its technology based on three characteristics of terrain, at the same time, we also do some data experiments on large-scale DEM production generation. The material works as followed:
Chapter One: We have analyzed researches at home and aborad about the traditional map generalization/DEM generalization, how to reserve terrain features, DEM quality standards, DEM quality assessment, the visualization in multi-scale, the production process and so on. For there are so much problem, we find the new DEM is another effective way for DEM generation. There are two basic principles:(1) the high fidelity DEM is the base and the guarantee for the DEM generalization; (2) To generate the high quality DEM in appointed resolution, it should be through DEM digital generalization. Especially in the feature-reservation problem, we take the grid method based on map algebra through the bottom to the top, which is different from the traditional----digital generalization in feature modeling. We compare with the adjacent elevation to judge which is feature point or in the feature tree. We find it is a effective new way.
Chapter Two:There are three characteristics of terrain:(1) the accuracy of elevation; (2) the right order of elevation; (3) the feature structure of elevation. In the practice and DEM development, three characteristics are independent and interrelated, we should understand the relationships among them. They are the base and the prerequisite for the digital generalization.
Chapter Three: In feature modeling, we find the "feature reservation" is the key to the problem, so based on this point, we take the levels and system structures of features to consideration, then find the relationship of terrain features, and reserve these important features in different levels. And finally we can do the DEM generation through digital generalization easily. Some data experiment results show that for different types of terrain, this algorithm is nice and practical.
Chapter Four: As we know, the problem of contour lines generalization is a century challenge. If we want to solve this problem, we should consider the structure in three dimension. Since the "digital generalization" is based on the three dimension model. Such DEM is equivalent to the topographic map in resolution at 0.1mm. So we can take two results from one "digital generalization" theory: one is DEM generalization, the other is contour lines generalization. At the same time, we do some data experiments, and we also find the results are very ideal.
Chapter Five:Based on the previous results and the technology of "digital generalization", we can integrate those softwares to form a new process for high-quality DEM generation. In this paper, we have discussed about the technical processes, specifications and the two core technologies. And we have done large-scale data experiments, the results show us the new process is feasible and mature in application.
Chapter Six:Through the large-scale data experiments results, we have done much anaysis on the quality assessment under the new quality standards. On one hand, we do the compare in multi-scale visualization; on another hand, we make some tools to do quantitative statistics to show the new quality standards through figure. The final statistic results tell us the new theory and technology of DEM is feasible and superior.
国家测绘部门经过多年的共同努力,已完成全国1：1万、1：5万、1：25万DEM的初始建库工作。关于如何持续与及时的精化现有全国1：5万、1：1万、1：25万DEM成果,保证高程数据的准确性、可靠性,已经成为基础测绘工作者和广大用户共同关切的热点问题。
数字高程模型作为地形表面的一种数字表达,具有传统地形图无法比拟的优点,同时在长期实践中也显露出的一些“由来已久”的问题,尤其是质量问题,让人们不得不去反思由于理论基础的薄弱带来的技术基础的不足。DEM从定义到生成,从实际地形到质量评价,都是一环扣一环紧密进行的。针对当前DEM质量评价没有统一规范来检测,以及应用中普遍存在的问题,新数字高程模型的理论方法应用的提出,为如何生成高质量(高保真)DEM打开了思路。
随着数据获取源多元化和应用需求多样化,在数据组织多尺度与高程采样性的双重制约下,本文在地面三大本质特性的基础上,对递归数字综合技术方法实现进行了研究,并对DEM大规模数据试生产也做相关了探讨。具体研究工作如下：
第一,对传统DEM在地图/地貌综合,地形地貌特征保持,DEM质量标准,DEM精度评价方法,多尺度可视化以及DEM工程生产等方面国内外研究现状进行总结分析,针对热门疑难问题,提出了解决问题的理想途径——新数字高程模型。强调两个基本论点①致密的高保真DEM是DEM综合的基础和根本保证；②生成指定分辨率下高质量DEM必须通过DEM数字综合。尤其是在“特征保持”问题上,与传统自顶向下不同,提出了特征建模下的数字综合——采用地图代数的栅格方法由底向上途径,采用邻域点高程特征比较有效实现相对特征点的保留,为疑难问题的解决带来了新思路。
第二,实际和新的研究表明地面三大本质特性：①高程准确性、②高程序列正确性、③高程的极值特征和结构特性,是DEM必须具备的。结合实际需求以及当前DEM发展情况,分析了三大特性相互独立而又相互支撑的关系,明确了“数字综合”的基本原理与前提环境基础,为技术实现做了理论准备。
第三,结合当前研究动态,在特征建模下以“地形地貌特征保持”为出发点,考虑到特征的层次系统关系,顾及各层次(间)的局部与全局的关系,交互中尽量避免阈值的设置,使得算法实现容易,应用简单方便。不同地形地貌的数据实验的等高线回放图表明,该算法可行,且一定程度上结果较优。
第四,在DEM数字递归综合及可视化的基础上,对于传统的等高线综合这个百年难题,理论上只有通过三维形体的结构综合,才能以令人信服的可靠性实现解算,而DEM数字综合恰恰正是三维形体的结构综合,综合后的DEM将是该分辨率上科学的高程模型。并且,这样的DEM即和其间距相应0.1毫米的比例尺地图相当。不同区域的实验结果表明,在DEM数字综合的同时实际上相应完成了该地区等高线的综合,不同综合程度的等高线是DEM数字综合得到产品中的一种伴生品。参考地图综合,主要针对DEM数字综合与等高线综合的联系和区别做了相关探讨,最终从等高线多尺度的可视化角度,对相关结果进行比较分析,说明综合的意义。
第五,在实验室前期丰富成果的基础上,结合数字综合技术的实现,将高质量DEM生产软件进行集成。探讨了DEM生产的技术流程,技术指标以及关键技术实现。同时开展了大规模数据实验。实验结果表明新数字高程模型的生产技术软件的成熟性,以及工程化的实用性。
第六,通过对大规模的数据试生产实验的数据结果做详细的质量评价分析,验证了新数字高程模型的优越性以及其带来的现实意义。质量评价分析,主要是针对新提出的质量标准,对局部特征,以及从全局的角度上,理论结合实际,进行DEM质量检查：方面,等高线多尺度可视化,实现视觉效果对比；一方面,结合检验算法,开发检验工具,对这些质量指标实现DEM质量量化统计分析。最终用统计结果说明了新数字高程模型这套理论到技术的可行性和优越性。
Digital Elevation Model (DEM) is one kind of the national products of geography information, which has been widely applied in many departments about the earth's three-dimensional information such as water resources, mapping, national defense and others, and is the most important part of DGDF. In half of a century's development, it already has a very large-scale production in practice and has played a significant role in many applications.
For many-years'efforts, the National Survey and Mapping Department has build the DEM databases in scale of 1:10000,1:50000,1:25000. The follow work is how to keep the quality and update the databases in time, which is the focus for many users and the mapping workers.
DEM, as a digital representation of terrain surface, has many advantages that the traditional topographic map can not compare with. But it also has much problem in practice, especially in quality assessment. So we should take the theory basis and the technical basis to think through their shortages. As we know, from the definition to the production, from the real terrain to the quality assessment, every process is closely related. So in this situation, the new DEM theory and technology in application have given us a new way to solve all these problems.
At present there are many kinds of data sources and application requirements, then there presents many discussions about data organization in multi-scale and sampling of elevation. So in this paper, we do some researches about the processive digital generalization and its technology based on three characteristics of terrain, at the same time, we also do some data experiments on large-scale DEM production generation. The material works as followed:
Chapter One: We have analyzed researches at home and aborad about the traditional map generalization/DEM generalization, how to reserve terrain features, DEM quality standards, DEM quality assessment, the visualization in multi-scale, the production process and so on. For there are so much problem, we find the new DEM is another effective way for DEM generation. There are two basic principles:(1) the high fidelity DEM is the base and the guarantee for the DEM generalization; (2) To generate the high quality DEM in appointed resolution, it should be through DEM digital generalization. Especially in the feature-reservation problem, we take the grid method based on map algebra through the bottom to the top, which is different from the traditional----digital generalization in feature modeling. We compare with the adjacent elevation to judge which is feature point or in the feature tree. We find it is a effective new way.
Chapter Two:There are three characteristics of terrain:(1) the accuracy of elevation; (2) the right order of elevation; (3) the feature structure of elevation. In the practice and DEM development, three characteristics are independent and interrelated, we should understand the relationships among them. They are the base and the prerequisite for the digital generalization.
Chapter Three: In feature modeling, we find the "feature reservation" is the key to the problem, so based on this point, we take the levels and system structures of features to consideration, then find the relationship of terrain features, and reserve these important features in different levels. And finally we can do the DEM generation through digital generalization easily. Some data experiment results show that for different types of terrain, this algorithm is nice and practical.
Chapter Four: As we know, the problem of contour lines generalization is a century challenge. If we want to solve this problem, we should consider the structure in three dimension. Since the "digital generalization" is based on the three dimension model. Such DEM is equivalent to the topographic map in resolution at 0.1mm. So we can take two results from one "digital generalization" theory: one is DEM generalization, the other is contour lines generalization. At the same time, we do some data experiments, and we also find the results are very ideal.
Chapter Five:Based on the previous results and the technology of "digital generalization", we can integrate those softwares to form a new process for high-quality DEM generation. In this paper, we have discussed about the technical processes, specifications and the two core technologies. And we have done large-scale data experiments, the results show us the new process is feasible and mature in application.
Chapter Six:Through the large-scale data experiments results, we have done much anaysis on the quality assessment under the new quality standards. On one hand, we do the compare in multi-scale visualization; on another hand, we make some tools to do quantitative statistics to show the new quality standards through figure. The final statistic results tell us the new theory and technology of DEM is feasible and superior.
引文
[1]Ackermann, F. Techniques and strategies for DEM generation[J].Digital Photogrammetry-Addendum of the Manual of Photogrammetry,1996,108-144.
[2]Aguilar, et al. Modelling vertical error in LiDAR-derived digital elevation models[J], ISPRS Journal of Photogrammetry and Remote Sensing,2010,65(1):103-110.
[3]A.Kobler, N.Pfeifer, P.Ogrinc, L.Todorovski, K.Ostir, S.Dzeroski. Repetitive interpolation: A robust algorithm for DTM generation from Aerial Laser Scanner Data in forested terrain[J], Remote Sensing of Environment,2007,108:9-23.
[4]Alberto C., Gabriele B., Roberto C.. Comparison of techniques for generating digital terrain models from contour lines[J], International Journal of Geographical Information Science,1997, 15(5):451-473.
[5]Andrew, K.Skidmore. Terrain position as mapped from a gridded digital elevation model[J], IJGIS,1990,4(1):33-49.
[6]Bjorke J. T. Framework for entroy_based map evaluation [J]. Cartography and Geographic Information Systems,1996,24(2):78-95.
[7]Bolstad, P.V., T. Stowe. An evaluation of DEM accuracy: Elevation slope and aspect[J], Photogrammetric Engineering Re-mote Sensing,1994,60(11):1327-1332.
[8]Bonin O, Rousseaux F. Digital Terrain Model Computation from Contour Lines:How to Derive Quality Information from Artifact Analysis[J], Geo Informatica,2005,9:253-268.
[9]Burrough P. A. Principles of Geographical Information Systems for Land Resources Assessment. University Press, Oxford,1986, p.193.
[10]Chang Y C, Song G S,Hsu S K. Automatic extraction of ridge and valley axes using the profile recognition and polygonbrealcing algorithm.computers and geosciences,1998,24(1):83-93.
[11]Chou J. Voronoi Diagrams for Planar Shapes [J], IEEE Computer Graphs and Applications, 1995,15(2):52-59.
[12]C. Liu, J.L. Wang and D.J. Liu. Generalization of DEM Grid Data Based on Multi-band Wavelet Analysis[J], Journal of Image and Graphics,2004.3,9(3):340-344.
[13]Cohen J., Varshney A., Manocha D. Turk G, Weber H. Agarwal P., Brooks F., Wright W. Simplification evelopes[C], Proceedings of SIGGRAPH'1996,119-128.
[14]Cronin T. Automated Reasoning with Contour Maps[J], Computers & Geosciences,1995,21 (5):609-618.
[15]D.J. Pennock and A. Veldkamp. Advances in landscape-scale soil research[J], Geoderma, 2006,133:1-5.
[16]D.J. Pennocka and M.D.Corre. Development and application of landform segmentation procedures[J], Soil & Tillage Research,2001,58:151-162.
[17]D.J. Pennock. Terrain attributes, landform segmentation, and soil redistribution[J], Soil & Tillage Research,2003,69:15-26.
[18]ESRI. ArcInfo User's Guide[M]. Environmental Systems Research Institute, Redlands, California, 2005.
[19]Fei Lifan, He Jin, Ma Chenyan, Yan Huiwu. Three Dimensional Douglas-Peucker Algorithm and the Study of Its Application to Automated Generalization of DEM[J], Acta Geodaetica Et Cartographic Sinica,2006.8,35(8).
[20]Fern A, Musavi MT, Miranda J. Automatic extraction of drainage networks from digital terrain elevation data:A local network approach[C],1997 IEEE International Conference on Neural Networks (ICNN 97),1997,1-4:1512-1517.
[21]Florinsky, I.V. Accuracy of local topographic variables derived from digital elevation models [J], International Journal of Geographical Information Science,1998,12(1):47-62.
[22]Florinsky, I.V., Kuryakova, GA.. Determination of grid size for digital terrain modeling in landscape investigations--exemplified by soil moisture distribution at a mircoscale[J], International Journal of Geographical Information Science,2000,14(8):815-832.
[23]Frederic Baudemont, Jean-Francois ParrotStructural. Analysis of DEM's by Intersection of Surface Normals in a Three-Dimensional Accumulator Space[J], IEEE Transactions On Geoscience And Remote Sensing,2000.5,38(3):1191-1198.
[24]Galanda M., Weibel R. An agent_based framework for polygonal subdivision generalization. In Proceedings of Spatial Data Handling,2002 [C/CD], Ottawa Canada,2002.
[25]Gao J.. Impact of sampling intervals on the reliability of topographic variables mapped from grid DEMs at a mircoscale [J], International Journal of Geographical Information Science,1998, 12(8),875-890.
[26]Gieng T S., Hamann B., Joy K L. et al. Smooth hierarchical surface triangulations [C]. In: Proceedings of Visualization'97, USA:Phoenix,1997.
[27]G. J. Robinson. The Accuracy of digital elevation models derived from digitized contour data[J], The Photogrammetric Record,1994,14(83):805-814.
[28]G. Jordan. Morphometric analysis and tectonic interpretation of digital terrain data: a case study[J], Earth Surface Processes and Landforms,2003,28:807-822.
[29]G Jordan. Adaptive smoothing of valleys in DEMs using TIN interpolation from ridgeline elevations:An application to morphotectonic aspect analysis[J], Computers & Geosciences,2007, 33:573-585.
[30]Gruber and Haefner, U. Gruber and H. Haefner. Avalanche hazard mapping with satellite data and a digital elevation model[J]. Applied Geography,1995,15(2):99-113.
[31]Hamann B. Curvature approximation for 3D manifolds in 4D space, Computer Aided Geometric Design [J],1994a,11(6):621-632.
[32]Hamann B. A data reduction scheme for triangulated Computer Aided Geometric Design [J], 1994b,11(2):179-214.
[33]H.I. Reuter, O. Wendrot and K.C. Kersebaum. Optimisation of relief classification for different levels of generalisation[J], Geomorphology,2006,77:79-89.
[34]Hoppe H. Progressive meshes[J], Computer Graphics,1996,30(1):99-108.
[35]Hu Hai, Gao Jun, Hu Peng, The Digital Generalization Principle of Digital Elevation Model[C]. International Symposium on Spatial Analysis, Spatial-Temporal Data Modeling, and Data Mining, 2009, Proc. of SPIE Vol.7492,749221.
[36]Hu Peng, Liu Xiaohang, Hu Hai. Accuracy Assessment of Digital Elevation Models based on Approximation Theory[J], Photogrammetric Engineering and Remote Sensing,2009.1,75(1): 49-56.
[37]Hu Peng, Liu Xiaohang, Hu Hai. Isomorphism in Digital Elevation Models and Its Implication to Interpolation Functions[J], Photogrammetric Engineering and Remote Sensing,2009.6, 75(6):713-721.
[38]Hu Peng, Yang Li, DEM's digital progressive Generalization and multi-scale Visualization of contour lines[C]. International Symposium on Spatial Analysis, Spatial-Temporal Data Modeling, and Data Mining,2009, Proc. of SPIE Vol.74922L.
[39]I.D. Moore, A. Lewis, J.C. Gallant. Terrain attributes:estimation methods and scale effects In: A.J. Jakeman, M.J. Beek, M.J. McAleer, (Eds.), Modelling Change in Environmental Systems[M], London:John Willey and Sons,1993.
[40]I.S. Evans. An integrated system of terrain analysis and slope mapping[J], Zeitschrift fur Geomorphologie, N.F.,1980, Supplementband 36:274-295.
[41]Isler V, LauR W H., Green Mark. Real-time multi-resolution modeling for complex virtual environments[C]. In:Proc of VRST'96. HongKong,1996,11-19.
[42]Jurgen Garbrecht, Lawrence W.Martz. The assignment of drainage direction over flat surfaces in raster digital elevation models[J], Journal of hydrology,1997,193:204-213.
[43]J. Iwahashi and R J. Pike. Automated classifications of topography from DEMs by an unsupervised nested-means algorithm and a three-part geometric signature[J],2006,32-64.
[44]J. Schmidt, I. s. Evans and J. Brinkmann. Comparison of polynomial models for land surface curvature calculation[J], Geographical Information Science,2003,17(8):797-814.
[45]J. Schmidt and A. Hewitt. Fuzzy land element classification from DTMs based on geometry and terrain position[J], Geoderma,2004,121:243-256.
[46]Kazuo O., Tadashi T., Wang P., Tommo O., Takeshi D., Ryosuke S. Automatic 3-D City Modeling Based on Fusion of Laser Scanner Data and Aerial Photo Images [J]. Journal of the Japan Society of Photogrammetry and Remote Sensing,2004,43(5):16-23.
[47]K.Jenson, J.O.Domingue. Extrating Topographic Structure from Digital Elevation Data for
Geographic Information System Analysis[J], Photogrammetry Engineering and Remote Sensing, 1988,54(11):1593-1600.
[48]K Tempfli. Spectral analysis of terrain relief for the accuracy estimation of digital terrain models[J]. ITC Journal,1980, (3):478-510.
[49]Kyoung Min Kim, Joong Jo Park, Myung Hyun Song, In Cheol Kim, Ching Y. Suen. Detection of ridges and ravines using fuzzy logic operations[J], Pattern Recognition Letters,2004,25: 743-751.
[50]L. Dragut, T. Blaschke. Automated classification of landform elements using object-based image analysis[J], Geomorphology,2006,81:330-344.
[51]Lawrence W. Martz, Jurgen Garbrecht. Short Communication automated recognition of valley lines and drainage networks from grid digital elevation models:a review and a new method-Comment[J], Journal of Hydrology,1995,167:393-396.
[52]Lee.J, Stucky.D. On applying viewshed analysis fro determining least-cost paths on digital elevation model[J], International Journal of Geographical Information Science,1998, 12(8):891-905.
[53]Lee I K, Kim M S, Elber G. Planar Curve Offset Based on Circle Approximation[J], Computer-Aided Design,1996,28(8):617-630.
[54]Martz L W, Garbrecht J. Numerical Definition of Drainage Network and Subcatchment Areas from Digital elevation Models[J].Computers & Geosciences,1992,18(6):747-767.
[55]Martz L W, Garbrecht J. An Outlet Breaching Algorithm for the Treatment of Closed Depressions in a Raster DEM[J], Computers & Geosciences,1999,25(6):835-844.
[56]Michael F. Goodchild, A general framework for error analysis in measurement-based GIS[J], Journal of Geographical Systems,2004.12,6(4):323-324.
[57]M.F. Hutchinson. A new procedure for gridding elevation and stream line data with automatic removal of spurious pits[J], Journal of Hydrology,1989,106:211-232.
[58]Muller J C, Wang Z S. Area_patch Generalisation:A Competitive Approach[J]. The Cartographic Journal,1992,29(2):137-144.
[59]O'Callaghan, Mark, J.F. O'Callaghan, D.M. Mark, The extraction of drainage networks from digital elevation data. Computer Vision[J], Graphics and Image Processing,1984,28 (3):323-344.
[60]Okabe A., Boots B, Sugihara K. N earest neighborhood operations with generalized Voronoi diagram [J], International Journal of Geographical Information Systems,1994,8(1):43-71.
[61]Ozdemir H, Bird D. Evaluation of morphometric parameters of drainage networks derived from topographic maps and DEM in point of floods[J], ENVIRONMENTAL GEOLOGY,2009.2, 56(7):1405-1415.
[62]P.A. Burrough. Principles of Geographical Information Systems for Land Resources
Assessment[M], New York:Oxford University Press,1986.
[63]Philip T. Giles, Steven E.Franklin. Comparison of Derivative Topographic Surface、 of a DEM Generated from Stereoscopic SPOT Images with Field Measurements[J], Photogrammetric Engineering & Remote Sensing,1996,62(10):1165-1171.
[64]Plazanet C, Affholder and F. Erirsch,.The Importance of Geometric Modeling Generalization. Cartography and Geographic Information Systems,1995,22(4):291-305.
[65]P.Longley, MF Goodchild, DJ Maguire, DW, Geographical information systems and science[M], wiley, british,2004.
[66]Prima Oky D. A., Ryuzo Y. DEM generation method from contour lines basedon the steepest slope segment chain and a monotone interpolation function[J], Journal of Photogrammetry and Remote Sensing,2002,57(1-2):86-101.
[67]P. Shary, L.S. Sharaya, A.V. Mitusov. Fundamental quantitative methods of land surface analysis[J], Geoderma,2002,107:1-32.
[68]P. T. Giles, S. E. Franklin. An automated approach to the classification of the slope units using digital data[J], Geomorphology,1998,21:251-264.
[69]Puecker T K, Doughlas D H. Detection of surface specific points by local parallel processing of discrete terrain elevation data[J], Computer Graphics and Image Processing,1975,375-387.
[70]Raghavan V, Masumoto S,Koike K etal. Automatic Lineament Extraction from Digital Images Using a Segment Tracing and Rotation Transformation Approach [J]. Computers &Geosciences, 1995,21(4):555-591.
[71]Rossignac J., Borrel P. Multi-resolution 3D approximation for rendering complex scenes, In: Falconine B, KuniiT. Editors, Geometric Modelingin Computer Graphics[M]. New York: Springer Verlag,1993:455-465.
[72]San B. T., Suzen M. L.. Digital elevation model (DEM) generation and accuracy assessment from ASTER stereo data[J], International Journal of Remote Sensing,2005,26(22):5013-5027.
[73]Sefercik, U. G. Comparison of DEM accuracies generated by various methods[C],2007 3rd International Conference On Recent Advances In Space Technologies,2007,379-382.
[74]Schoeder W J., Zarge J A. Lornensen WE. Decimation of triangle meshes [J], Proceedings of SIGGRAPH'92, Computer Graphics,1992,26(2):65-70.
[75]S.J. Park, K. McSweeney, B. Lowery. Identification of the spatial distribution of soils using a process-based terrain characterization[J], Geoderma,2001,103:249-272.
[76]Steven V D., Dirk T, Mark D.B. Using Genetic Algorithms for Solving Hard Problems in GIS[J], GeoInformaiica,2002,6(4):381-413.
[77]Tang Guoan, Gong Jianya,Chen Zhengjiang. A Simulation on the Accuracy of DEM Terrain Representation[J], Acta Geodaetica Et Cartographic Sinica,2001,30(4),361-365.
[78]Tedeusz Chrobak. A Numerical Method for Generalizing the Linear Elements of Large-Scale
Maps, Based on the Example of Rivers. Chartographica.2000. Vol.37, No.l:49-55.
[79]USGS 2006, web site, National Mapping Program, Standards Digital Elevation Model tandards, Part 2 Specifications, Standards for Digital Elevation Models, URL:http://rockyweb.cr.usgs.gov/nmpstds/acrodocs/dem/2DEM0198.PDF, US Department of the Interior, US Geological Survey, National Mapping Division
[80]Wang DM, Tian YA, Gao Y, Wu L. A new method of generating grid DEM from contour lines[C], IGARSS 2005:IEEE International Geoscience and Remote Sensing Symposium,2005, 657-660.
[81]Wang L, Liu H. An efficient method for identifying and filling surface depressions in digital elevation models for hydrologic analysis and modelling[J], International Journal Of Geographical Information Science,2006.2,20(2):193-213.
[82]Wanning Peng. Automated Generalization in GIS[M], ITC Publication Series,1997.
[83]Weibel.R. Models and Experiments for Adaptive Computer-Assisted Terrain Generalization[J], Cartography and Geographic Information Systems,1992,19(3):133-153.
[84]Weibel.R. Map generation in the context of digital system[J], Cartography and Geographic Information System,1995,22(4).
[85]Weibel.R., Jones, C.B. Computational Perspectives on Map Generalization [J], GeoInformatica, 1998,2(4):307-314.
[86]Werschlein T., Robert Weibel.1994. Use of Neural Networks in Line Generaliztion. http://spatialod}sse}ursus.maine.edu/gisweb/spatdb/egis/eg94009.html
[87]Wu yanlan, Oguchi Takashi, Liu yongqiong,et.al. Flow paths tracing from raster contours using distance transform[C]. International Symposium on Spatial Analysis, Spatial-Temporal Data Modeling, and Data Mining,2009, Proc. of SPIE Vol.749255.
[88]Xu JW, Zhang WC, Liu CS. A novel method for filling the depressions in massive DEM data[C], IGARSS:2007 IEEE International Geoscience And Remote Sensing Symposium,2007, 4080-4083.
[89]Xu XL, Zhuang DF. Automated extraction of drainages in China based on DEM in GIS environment[C], IGARSS 2003:IEEE International Geoscience And Remote Sensing Symposium,2003,3344-3346.
[90]Zaksek K., Podobnikar T., An effective DEM generalization with basic GIS operations [A].8th ICA WORKSHOP on Generalisation and Multiple Representation [C], A Coruna, July 7-8th, 2005.
[91]Zhou Q.M., Liu X.J..Error assessment of grid-based flow routing algorithms used in hydrological models[J], Int. J. Geographical Information Science,2002,16(8):819-842.
[92]Zhou Q.M., Liu X.J..Error Analysis on Grid Based Slope and Aspect Algorithm[J], Photogrammetric Engineering and Remote Sensing,,2004,70(8):957-962.
[93]Zhang Sheng, Zhu Cailian, Zhong Shiming. Improvement and Application of Douglas-Peucker Compresing Algorithm[J], Journal of Wuhan University of Technology(Transportation Science & Engineering),2005.10,129(5).
[94]艾廷华.城市地图数据库综合的支撑数据模型与方法的研究[D],博士学位论文,武汉,武汉测绘科技大学,2000.
[95]艾自兴、毋河海等.Delaunay三角形剖分在河流自动综合中的应用研究[C],中国地理学与GIS学术讨论会文集,中国地理学会地图学与GIS专业委员会,青岛,2002,230-238
[96]毕华兴,谭秀英,李笑吟.基于DEM的数字地形分析[J],北京林业大学学报,2005,3.
[97]曹志冬,刘学军,王叶飞,汤国安.基于DEM的地形简化方法对比分析[J],现代测绘,2005.2,28(1)：9-13.
[98]曹志冬,刘学军,王叶飞,汤国安.DEM地形简化指标的分析研究,地理与地理信息科学,2005.3,21(2)：10-15.
[99]测绘发展研究中心.数字中国地理空间基础框架建设的发展,2008.5,http://fazhan.sbsm.gov.cn/article/wxzy/200805/20080500035366.shtml.
[100]测绘发展研究中心.论发展我国地理信息产业的基础设施建设,2008.5,http://fazhan.sbsm.gov.cn/article/wxzy/200805/20080500035472.shtml.
[101]陈波,武芳,钱海忠.空间分析方法在道路网自动综合拓扑构建中的应用[J],测绘科学,2006,31(1)：101-104.
[102]陈楠,林宗坚,李成名,朱红春,徐增让,汤国安.基于信息论的不同比例尺DEM地形信息比较分析,遥感信息(理论研究),2004.3：5-9.
[103]陈军,李志林,蒋捷等.多维动态GIS空间数据模型与方法的研究[J].武汉大学学报(信息科学版),2004,29(10),858-862.
[104]陈述彭.地图学面临的挑战与机遇[J],地理学报,1994,49(1)：5-7.
[105]陈述彭,鲁学军,周成虎.地理信息系统导论[M],科学出版社,1999.
[106]陈涛,艾廷华.多边形骨架线与形心自动搜寻算法研究[J],武汉大学学报(信息科学版),2004,29(5)：443-447.
[107]陈晓勇.数学形态学理论和模型的若干扩展及在CCD扫描等高线图的DEM自动建立中的应用[D],博士学位论文,武汉测绘科技大学,1990.
[108]陈旭,朱欣焰,杜道生,张路.影像与栅格元数据本体实现及语义查询扩展应用[J],武汉大学学报·信息科学版,2009.6,34(6)：646-649.
[109]陈永良,刘大有.一种新的山脊线和山谷线自动提取方法[J],中国图象图形学报,2001.12,6A(12)：1230-1234.
[110]陈永良,刘大有,虞强源.从DEM中自动提取自然水系[J],中国图象图形学报,2002.1,7A(1)：91-96.
[111]陈永良,刘大有,虞强源.地球物理位场图象特征信息自动提取[J],中国图象图形学报,2002.1,7A(2)：132-136.
[112]杜世宏,杜道生,樊红,万幼川.基于栅格数据提取主骨架线的新算法[J],武汉测绘科技大学学报,2000.10,25(5)：432-436.
[113]费立凡.地形图等高线成组综合的试验[J],武汉测绘科技大学学报,1993,18(增刊)：6-22.
[114]弗.特普费尔(著),江安宁(译).制图综合[M],北京：测绘出版社,1982.
[115]冯桂,林宗坚,张继贤,张丽.DEM高精度内插算法及其实现[J],遥感信息-理.仑研究,2000.4：18-20.
[116]范青松.DEM综合生成技术研究[D],博士学位论文,武汉大学,2007.12.
[117]范青松,汤翠莲,胡鹏.DEM精度检查中等高线回放的量化方法[J],测绘科学,2008,33(3)：118-120.
[118]方鹏,谭仁春,李霖.小波变换在多尺度DEM模型建立中的应用[J],四川测绘,2003.3,26(1)：8-11.
[119]郭庆胜.线状要素图形综合的渐进式方法研究[J],武汉测绘科技大学学报,1998.
[120]郭仁忠.空间分析[M],北京：高等教育出版社,2001.
[121]郝红科,田江博,陈永贵.用地形图生成DEM的新方法研究[J],陕西林业科技,2005,(1)：35-37.
[122]国家测绘局.1：5万数字高程模型(DEM)生产技术规定(暂行本),1998.7.
[123]高俊.地图的空间认知和认知地图学[M],地图学年鉴,北京：中国地图出版社,1991.
[124]高俊.地理空间数据的可视化[J],测绘工程,2000.9,9(3)
[125]高安秀树.分数维[M],沈步明,常子文译,北京：地震出版社,1994.
[126]葛金辉,郭丽丽.曲面简化算法研究的发展现状[J],通化师范学院学报,2006,27(6)：18-21.
[127]何丽丽.基于不同比例尺和分辨率DEM的数字地形分析[D],硕士学位论文,西南大学,2007.5.
[128]胡海,杨传勇,胡鹏.DEM最优线性生成技术——MADEM[J],华中科技大学学报(自然科学版),2007,635(6)：118-121.
[129]胡鹏,游涟,杨传勇,吴艳兰.地图代数[M],武汉大学出版社,2002.
[130]胡鹏,吴艳兰,胡海.关于DEM精度评定的基本理论问题[J],地球信息科学,2003,5(3)： 64-70.
[131]胡鹏,吴艳兰,胡海.数字高程模型精度评定的基本理论[J],地球信息科学,2003,5(3)：64-70.
[132]胡鹏,吴艳兰,胡海.再论数字高程模型精度评定的基本理论问题[J],地球信息科学,2005,7(3)：28-33.
[133]胡鹏,王海军等.论多边形中轴问题和算法[J],武汉大学学报(信息科学版),2005,30(10)：853-857.
[134]胡鹏,黄雪莲,吴艳兰等.DEM若干理论问题思考[J],哈尔滨工业大学学报,2006,
38(12)： 2143-2147.
[135]胡鹏,杨传勇,吴艳兰等.新数字高程模型理论方法标准和应用[M],测绘出版社,2007.2.
[136]胡鹏,游涟,胡海.地图代数概论[M],测绘出版社,2008.
[137]胡鹏,白轶多,胡海.数字高程模型(DEM)生成中的序同构问题[J],武汉大学学报(信息科学版),2009.3,34(3)：352-357.
[138]胡鹏,高俊.数字高程模型的数字综合原理研究[J],武汉大学学报(信息科学版),2009.8,34(8)：940-942.
[139]黄培之.提取山脊线和山谷线的一种新方法[J],武汉大学学报(信息科学版),2001.6,26(3)：247-252.
[140]黄培之,刘泽慧.基于地形梯度方向的山脊线和山谷线的提取[J],武汉大学(信息科学版)2005,30(5)：396-399.
[141]黄雯雯.1：5万中低山地区DEM数字综合和等高线综合实验研究[D],硕士学位论文,武汉大学,2009.5.
[142]黄杏元,马劲松,唐勤.地理信息系统(修订版)[M],高等教育出版社,2001.
[143]柯正谊,何健邦等.数字地面模型[M],北京：中国科学技术出版社,1993.
[144]马小虎,潘志庚,石教英.基于三角形移去准则的多面体模型简化方法[J],计算机学报,1998,21(6)：492-498.
[145]马小虎.一种新的基于二次误差的三角形格网简化方法[J],计算机应用,2001,21(12)：22-24.
[146]刘锦中,马辉.基于等高线的DEM生成算法研究和实现[J],现代测绘,2004.6,27(3)：34-35,48.
[147]刘敏.基于三维道格拉斯改进算法的地貌自动综合研究—以在黄土高原的实验为例[D],硕士学位,论文西北大学,2007.6.
[148]刘永琼,吴艳兰,胡海等.数字高程模型精度评价及其问题探讨[J],测绘信息与工程,2009,34(5)：32-36.
[149]刘学军,龚建雅,周启鸣.DEM结构特征对坡度坡向的影响分析[J],地理与地理信息科学,2004,20(6)：1-5.
[150]刘学军,卢华兴,仁政,任志峰.论DEM地形分析中的尺度问题[J],地理研究,2007.5,26(3)：433-442.
[151]刘学军,汤国安.数字地形分析：机遇与挑战[J],地理信息世界,2009.2,1：6-7.
[152]刘泽慧,黄培之.DEM数据辅助的山脊线和山谷线提取方法的研究[J],测绘科学,2003.12,28(4)：33-36.
[153]龙毅,毋河海等.分形学：现代地图学的非线性数学分析方法[J],2003,28(2)：1-3.
[154]李炳元,潘保田,韩嘉福.中国陆地基本地貌类型及其划分指标讨论[J],第四纪研究,2008,28(4)：535-543.
[155]李成名,陈军.Voronoi图生成的栅格算法[J],武汉测绘科技大学学报,1998,23(3)：208-210.
[156]李德仁.关于空间数据不确定性的思考[J],测绘科学技术学报,2006,23(6).
[157]李德仁,郭晟,胡庆武,刘守军,魏建魁.GIS新引擎-“真图”数据解决方案[J],地理信息世界,2008.6,3：5-10.
[158]李基拓,陆国栋.基于边折叠和质点弹簧模型的网络简化优化算法[J],计算机辅助设计与图形学学报,2006,(03).
[159]李圣权,胡鹏.图形部件Voronoi图生成算法与应用研究[J],2005,31(10)：42-44.
[160]李志林,朱庆.数字高程模型(第二版)[M],武汉：武汉大学出版社,2003.
[161]陆毅,翟京生等.数字海图点群状特征的识别、量测与综合[J],武汉大学学报(信息科学版),2001,26(2)：133-139.
[162]马龙,杜道生.GIS中DEM产品精度的分析和评价[J],测绘信息与工程,2003.6,28(3)：4-6.
[163]穆宣社,游雄.支持突发事件应急反应的建筑物内部交通网络分析[J],测绘科学技术学报,2006,(06)
[164]宁津生,张祖勋,祝国瑞,张正禄,翟国君.高新技术与测绘学科发展[J],中国测绘学科发展兰皮书2003卷,测绘出版社,2003.9.
[165]倪星航.基于规则格网DEM提取地形特征线的方法研究[D],硕士学位论文,西南交通大学,2008.5.
[166]牛志宏,李太星.数字高程模型误差分析及精度评价述评[J],长江工程职业技术学院学报,2007,(03)：73-77
[167]Pinhas Yoeli.数字地形模型中的山谷线和山脊线的机助确定[J],万晓霞,朱海红译自《国际制图年鉴1984卷》,胡毓巨,郭仁忠校.
[168]潘志庚,庞明勇.几何格网简化研究与进展[J],江苏大学学报(自然科学版),2005,26(1)：67-71.
[169]邵春丽,胡鹏等.DELAUNAY三角网的算法详述及其应用发展前景[J],测绘科学,2004,12.
[170]苏时雨,李钜章.地貌制图[M],北京：测绘出版社,1999.
[171]史巍巍,裘昱,戴宗友.数字高程模型与等高线质量相关性研究[J],测绘通报,2006,2：23-26.
[172]沈晶.基于机载LiDAR数据的DEM综合生成和建筑物提取[D],博士学位论文,武汉大学,2009.12.
[173]陶旸.DEM数值精度与地形形态精度分析[A],中国地理信息系统协会第四次会员代表大会暨第十一届年会论文集[C],2007.
[174]汤国安,赵牡丹,曹菡.DEM地形描述误差空间结构分析[J],西北大学学报(自然科学版),2000,30(4)：349-352.
[175]汤国安,杨勤科,张勇,刘咏梅.刘新华.不同比例尺DEM提取地面坡度的精度研究——以在黄土丘陵沟壑区的试验为例[J],水士保持通报,2001.2,21(1)：53-56.
[176]汤国安,龚健雅,陈正江等.数字高程模型地形描述精度量化模拟研究[J],测绘学报,2001,30(4)：361-365.
[177]汤国安,杨玮莹等.对DEM地形定量因子挖掘中若干问题的讨论[J],测绘科学,2003,28(1)： 28-32.
[178]汤国安,刘学军,闾国年.数字高程模型及地学分析的原理与方法[M],北京：科学出版社,2005.
[179]汤国安,刘学军,房亮,罗明良.DEM及数字地形分析中尺度问题研究综述[J],武汉大学学报(信息科学版),2006.12,31(12)：1059-1066.
[180]万刚,朱长青.多进制小波及其在DEM数据有损压缩中的应用[J],测绘学报,1999,28(1)：35-39.
[181]唐心红,柳健,张继贤.多尺度地形结构提取方法[J],红外与激光工程,1998,27(3)：18-22.
[182]唐新明,林宗坚,吴岚.基于等高线和高程点建立DEM的精度评价方法探讨[J],遥感信息,1999,03.
[183]王春,陶肠,贾敦新,朱雪坚.规则格网DEM地形描述形态精度研究[J],地理信息世界,2008,(01).
[184]王春,刘学军,汤国安,陶玚.格网DEM地形模拟的形态保真度研究[J],武汉大学学报-信息科学版,2009.2,34(2)：146-149.
[185]王东华,刘建军,商瑶玲等.全国1：25万数字高程模型数据库的设计与建库[J],测绘通报,2001,(10)：28-31.
[186]王家耀.图论在道路网自动选取中的应用[J],解放军测绘学院学报,1985,(1)
[187]王家耀.普通地图制图综合原理[M],测绘出版社,1992.
[188]王家耀,武芳.数字地图自动制图综合原理[M],北京：解放军出版社,1998.
[189]王家耀,田震.海图水深综合的人工神经元网络方法[J],测绘学报,1999.11,28(4)：335-339.
[190]王家耀.地图制图学和地理信息工程学科发展现状[J],中国测绘学科发展兰皮书2003卷,测绘出版社,2003.9.
[191]王家耀,崔铁军,苗国强.数字高程模型及其数据结构[J],海洋测绘,2004.5,24(3)：1-4.
[192]王建,杜道生.规则格网DEM化简的一种改进方法[J],测绘信息与工程,2007.4,32(2)：34-36.
[193]王建,杜道生.栅格数据表示空间信息的不确定性初探[J],地理信息世界,2007.4,2：50-54.
[194]王建,杜道生.规则格网DEM自动综合方法的评价[J],武汉大学学报(信息科学版),
2007.12,32(12)：1111-1114.
[195]王宇宙,赵宗涛.一种多进制小波变换DEM数据简化方法[J],计算机应用,2003,23(6)：107-109.
[196]王玉海,朱长青等.基于B样条小波的等高线数据简化[J],测绘科学,2003,28(2)：23-26.
[197]王建宇,滕树钦.一种基于等高线生成DEM的方法[J],计算机应用,2002.8,22(8)：30-31,35.
[198]王光霞,朱长青,史文中,张国芹.数字高程模型地形描述精度的研究[J],测绘学报,2004.5,33(2)：168-173.
[199]王光霞,张寅宝,李江.DEM精度评估方法的研究与实践[J],测绘科学,2006,(03)
[200]王桥.分形理论在地图图形数据自动处理中的若干扩展与应用研究[D],博士学位论文,武汉测绘科技大学,1996.
[201]王桥.毋河海.地图图斑群自动综合的分形方法研究[J],武汉测绘科技大学学报,1996,21(1)：50-63.
f202] 王桥,毋河海.地图信息的分形描述与自动综合研究[M],武汉：武汉测绘科技大学出版社,1998.
[203]王新生,刘纪远等.一种新的构建Voronoi图的栅格方法[J],中国矿业大学学报,2003,32(3)：293-296.
[204]王友昆.等高线自动综合算法研究与实现[D],硕士学位论文,昆明理工大学,2008.5.
[205]武芳.协同式自动综合的研究与实践[D],博士学位论文,中国人民解放军信息工程大学,2000.
[206]武芳,王家耀.地图自动综合概念框架分析与研究[J],2002,11(2)：18-21.
[2071 吴凡,祝国瑞.基于小波分析的地貌多尺度表达与自动综合[J],武汉大学学报(信息科学版),2001,26(2)：171-177
[208]吴纪桃,王桥.小波分析在GIS线状数据图形简化中的应用研究[J],测绘学报,2000,29(1)：71-75.
[209]吴纪桃,王桥.小波理论用于地图数据处理中若干理论问题的探讨[J],测绘学报,2002,31(3)：245-248.
[210]吴纪桃,王桥.复杂地貌形态多比例尺表达的二维小波分析研究[J],遥感学报,2003,7(2)：93-97.
[211]吴立新,史文中,地理信息系统原理与算法[M],科学出版社,2003.
[212]吴艳兰,胡鹏.由栅格等高线快速建立DEM的新方法-CSE法[J],武汉大学学报信息科学版,2001,2.
[213]吴艳兰.地貌三维综合的地图代数模型和方法研究[D],博士学位论文,武汉大学,2004.4.
[214]吴艳兰,胡鹏.几何特性与流线追踪相结合的地形结构线提取法[J],武汉大学学报(信
息科学版),2005,30(10)：1115-1119.
[215]吴艳兰,胡鹏.基于地图代数的数字地表流线模型研究[J],水科学进展,2007.3,18(3)：356-361.
[216]毋河海.地貌形态自动综合问题[J],武汉测绘科技大学学报,1995a,20(增)：1-6.
[217]毋河海.河系树结构的自动建立[J],武汉测绘科技大学学报,1995b,20(增)：7-14.
[218]毋河海.地形图等高浅树的自动建立[J],武汉测绘科技大学学报,1995c,20(增)：15-19.
[219]毋河海.自动综合的结构化实现[J],武汉测绘科技大学学报,1996,21(3)：277-285.
[220]毋河海.凸壳原理在点群目标综合中的应用[J],测绘工程,1997,6(1)：1-6.
[221]毋河海.地图信息自动综合基本问题研究[J],武汉测绘科技大学学报,2000a,25(5)：377-386.
[222]毋河海.地貌形态自动综合基础理论与方法体系研究[J],第三届两岸测绘发展研讨会,“测绘与可持续发展”论文集,2000b,12：611-632.
[223]毋河海.基于扩展分形的地图信息自动综合研究[J],地理科学进展,2001,(sup)：14-28.
[224]毋河海.地图综合基础理论与技术方法研究[M],测绘出版社,2004.1.
[225]毋河海.机助制图综合原理[M],武汉大学教材,2006.
[226]颜加斌.等高线自动综合技术研究及软件开发[D],硕士学位论文,昆明理工大学,2008.6.
[227]杨晓云,唐咸远,梁鑫.基于等高线生成DEM的内插算法及其精度分析[J],测绘工程,2006.4,15(2)：37-39.
[228]杨晓云,顾利亚,岑敏仪.数字高程模型的误差处理与精度评估[J],铁道勘察,2004,05.
[229]杨晓云,梁鑫.数字高程模型(DEM)的质量控制及精度分析[J],广西工学院学报,2006,(S2).
[230]杨族桥,郭庆胜.基于提升方法的DEM多尺度表达研究[J],武汉大学学报(信息科学版),2003a,28(4)：496-498.
[231]杨族桥,熊新阶,张子宪,高汉平,郭庆胜.基于小波变换的DEM多尺度分析模型的研究[J],黄冈师范学院学报,2003.12b,23(6).
[232]余生晨,刘大有,刘洪.山脊线与山谷线的计算机自动检测[J],中国图象图形学报,1999,4(A)8：693-696.
[233]中国测绘学会.中国地图学与地理信息工程技术科学的新进展[J],中国测绘学科发展兰皮书2003卷,测绘出版社,2003.9.
[234]钟业勋,魏文展,李占元.基本地貌形态数学定义的研究[J],测绘科学,2002.9,27(3)：16-18.
[235]愰玉忠.基于DEM的数字地形分析[D],硕士学位论文,武汉理工大学,2008.
[236]查正军.基于数字高程模型(DEM)的地形特征提取,硕士学位论文,同济大学,2007.1.
[237]张必强,邢渊,阮雪榆.基于特征保持和三角形优化的格网模型简化[J],上海交通大
学学报,2004,38(8)：1373-1374.
[238]张彩霞,杨勤科,段建军.一种高质量的数字高程模型(DEM)建立方法——ANUDEM法[J],中国农业通报,2005,21(12)：411-415.
[239]张彩霞,杨勤科,段建军.高分辨率数字高程模型的构建方法[J],水利学报,2006,37(8)：1009-1015.
[240]张锦.多分辨率空间数据模型理论与实现技术研究[M],北京：测绘出版社,2004.
[241]张军.数字高程模型的建立及应用研究[D].硕士学位论文,辽宁工程技术大学,2007.3.
[242]张青年.线状要素的动态分段与制图综合[J],中山大学学报(自然科学版),2004,43(2)：104-107.
[243]张勇,汤国安,彭财.数字高程模型地形描述误差的量化模拟——以黄土丘陵沟壑区的实验为例[J],山地学报,2003.4,21(2)：252-256.
[244]张宇军.基于DEM骨架特征点线的地貌自动综合研究——以岔巴沟流域为例[D],硕士学位论文,西北大学,2008.6.
[245]张占睦.基于地形图的DEM的构建及其精度分析[D],硕士研究论文,信息工程大学,2001.
[246]张祖勋,张剑清.数字摄影测量[M],武汉大学出版社,1996.2.
[247]赵杰.数字地形模拟——地形数据获取与数字地形分析研究[D],博士学位论文,武汉：武汉大学测绘遥感信息工程国家重点实验室,2004.
[248]周昆,潘志庚,石教英.基于三角形折叠的格网简化算法[J],计算机学报,1998,21(6)：506-513.
[249]周培德,周忠平.确定任意多边形中轴的算法[J],北京理工大学学报,2000,20(6)：708-711.
[250]周启鸣,刘学军.数字地形分析[M],北京：科学出版社,2006.
[251]周廷儒,施雅风,陈述彭.中国地形区划草案[M],中国自然区划草案北京：科学出版社,1956.
[252]周兴华,姚艺强,赵吉先.DEM内插方法与精度评定[J],测绘科学,2005.10,30(5)：86-88.
[253]朱长青,王玉海等.基于小波分析的等高线数据压缩模型[J],中国图象图形学报,2004,9(7),841-845.
[254]朱庆,赵杰等.基于规则格网DEM的地形特征提取算法[J],测绘学报,2004,33(1),77-82.
[255]朱文博,毕如田,郭磐石,张锦.一种基于多分辨率模型简化算法的等高线自动综合方法研究[J],山西农业大学学报(自然科学版),2008.3,28(3)：332-337.
[256]朱文博.基于多分辨率DEM模型的等高线综合方法研究[D],硕士学位论文,太原理工大学,2005.5.
[257]祝国瑞.地图学[M],武汉：武汉大学出版社,2003.
[258]祝国瑞,郭礼珍,尹贡白,徐永利.地图设计与编绘[M],武汉大学,2001.
[259]祝国瑞,尹贡白.普通地图编制[M],测绘出版社,1983.
[2]Aguilar, et al. Modelling vertical error in LiDAR-derived digital elevation models[J], ISPRS Journal of Photogrammetry and Remote Sensing,2010,65(1):103-110.
[3]A.Kobler, N.Pfeifer, P.Ogrinc, L.Todorovski, K.Ostir, S.Dzeroski. Repetitive interpolation: A robust algorithm for DTM generation from Aerial Laser Scanner Data in forested terrain[J], Remote Sensing of Environment,2007,108:9-23.
[4]Alberto C., Gabriele B., Roberto C.. Comparison of techniques for generating digital terrain models from contour lines[J], International Journal of Geographical Information Science,1997, 15(5):451-473.
[5]Andrew, K.Skidmore. Terrain position as mapped from a gridded digital elevation model[J], IJGIS,1990,4(1):33-49.
[6]Bjorke J. T. Framework for entroy_based map evaluation [J]. Cartography and Geographic Information Systems,1996,24(2):78-95.
[7]Bolstad, P.V., T. Stowe. An evaluation of DEM accuracy: Elevation slope and aspect[J], Photogrammetric Engineering Re-mote Sensing,1994,60(11):1327-1332.
[8]Bonin O, Rousseaux F. Digital Terrain Model Computation from Contour Lines:How to Derive Quality Information from Artifact Analysis[J], Geo Informatica,2005,9:253-268.
[9]Burrough P. A. Principles of Geographical Information Systems for Land Resources Assessment. University Press, Oxford,1986, p.193.
[10]Chang Y C, Song G S,Hsu S K. Automatic extraction of ridge and valley axes using the profile recognition and polygonbrealcing algorithm.computers and geosciences,1998,24(1):83-93.
[11]Chou J. Voronoi Diagrams for Planar Shapes [J], IEEE Computer Graphs and Applications, 1995,15(2):52-59.
[12]C. Liu, J.L. Wang and D.J. Liu. Generalization of DEM Grid Data Based on Multi-band Wavelet Analysis[J], Journal of Image and Graphics,2004.3,9(3):340-344.
[13]Cohen J., Varshney A., Manocha D. Turk G, Weber H. Agarwal P., Brooks F., Wright W. Simplification evelopes[C], Proceedings of SIGGRAPH'1996,119-128.
[14]Cronin T. Automated Reasoning with Contour Maps[J], Computers & Geosciences,1995,21 (5):609-618.
[15]D.J. Pennock and A. Veldkamp. Advances in landscape-scale soil research[J], Geoderma, 2006,133:1-5.
[16]D.J. Pennocka and M.D.Corre. Development and application of landform segmentation procedures[J], Soil & Tillage Research,2001,58:151-162.
[17]D.J. Pennock. Terrain attributes, landform segmentation, and soil redistribution[J], Soil & Tillage Research,2003,69:15-26.
[18]ESRI. ArcInfo User's Guide[M]. Environmental Systems Research Institute, Redlands, California, 2005.
[19]Fei Lifan, He Jin, Ma Chenyan, Yan Huiwu. Three Dimensional Douglas-Peucker Algorithm and the Study of Its Application to Automated Generalization of DEM[J], Acta Geodaetica Et Cartographic Sinica,2006.8,35(8).
[20]Fern A, Musavi MT, Miranda J. Automatic extraction of drainage networks from digital terrain elevation data:A local network approach[C],1997 IEEE International Conference on Neural Networks (ICNN 97),1997,1-4:1512-1517.
[21]Florinsky, I.V. Accuracy of local topographic variables derived from digital elevation models [J], International Journal of Geographical Information Science,1998,12(1):47-62.
[22]Florinsky, I.V., Kuryakova, GA.. Determination of grid size for digital terrain modeling in landscape investigations--exemplified by soil moisture distribution at a mircoscale[J], International Journal of Geographical Information Science,2000,14(8):815-832.
[23]Frederic Baudemont, Jean-Francois ParrotStructural. Analysis of DEM's by Intersection of Surface Normals in a Three-Dimensional Accumulator Space[J], IEEE Transactions On Geoscience And Remote Sensing,2000.5,38(3):1191-1198.
[24]Galanda M., Weibel R. An agent_based framework for polygonal subdivision generalization. In Proceedings of Spatial Data Handling,2002 [C/CD], Ottawa Canada,2002.
[25]Gao J.. Impact of sampling intervals on the reliability of topographic variables mapped from grid DEMs at a mircoscale [J], International Journal of Geographical Information Science,1998, 12(8),875-890.
[26]Gieng T S., Hamann B., Joy K L. et al. Smooth hierarchical surface triangulations [C]. In: Proceedings of Visualization'97, USA:Phoenix,1997.
[27]G. J. Robinson. The Accuracy of digital elevation models derived from digitized contour data[J], The Photogrammetric Record,1994,14(83):805-814.
[28]G. Jordan. Morphometric analysis and tectonic interpretation of digital terrain data: a case study[J], Earth Surface Processes and Landforms,2003,28:807-822.
[29]G Jordan. Adaptive smoothing of valleys in DEMs using TIN interpolation from ridgeline elevations:An application to morphotectonic aspect analysis[J], Computers & Geosciences,2007, 33:573-585.
[30]Gruber and Haefner, U. Gruber and H. Haefner. Avalanche hazard mapping with satellite data and a digital elevation model[J]. Applied Geography,1995,15(2):99-113.
[31]Hamann B. Curvature approximation for 3D manifolds in 4D space, Computer Aided Geometric Design [J],1994a,11(6):621-632.
[32]Hamann B. A data reduction scheme for triangulated Computer Aided Geometric Design [J], 1994b,11(2):179-214.
[33]H.I. Reuter, O. Wendrot and K.C. Kersebaum. Optimisation of relief classification for different levels of generalisation[J], Geomorphology,2006,77:79-89.
[34]Hoppe H. Progressive meshes[J], Computer Graphics,1996,30(1):99-108.
[35]Hu Hai, Gao Jun, Hu Peng, The Digital Generalization Principle of Digital Elevation Model[C]. International Symposium on Spatial Analysis, Spatial-Temporal Data Modeling, and Data Mining, 2009, Proc. of SPIE Vol.7492,749221.
[36]Hu Peng, Liu Xiaohang, Hu Hai. Accuracy Assessment of Digital Elevation Models based on Approximation Theory[J], Photogrammetric Engineering and Remote Sensing,2009.1,75(1): 49-56.
[37]Hu Peng, Liu Xiaohang, Hu Hai. Isomorphism in Digital Elevation Models and Its Implication to Interpolation Functions[J], Photogrammetric Engineering and Remote Sensing,2009.6, 75(6):713-721.
[38]Hu Peng, Yang Li, DEM's digital progressive Generalization and multi-scale Visualization of contour lines[C]. International Symposium on Spatial Analysis, Spatial-Temporal Data Modeling, and Data Mining,2009, Proc. of SPIE Vol.74922L.
[39]I.D. Moore, A. Lewis, J.C. Gallant. Terrain attributes:estimation methods and scale effects In: A.J. Jakeman, M.J. Beek, M.J. McAleer, (Eds.), Modelling Change in Environmental Systems[M], London:John Willey and Sons,1993.
[40]I.S. Evans. An integrated system of terrain analysis and slope mapping[J], Zeitschrift fur Geomorphologie, N.F.,1980, Supplementband 36:274-295.
[41]Isler V, LauR W H., Green Mark. Real-time multi-resolution modeling for complex virtual environments[C]. In:Proc of VRST'96. HongKong,1996,11-19.
[42]Jurgen Garbrecht, Lawrence W.Martz. The assignment of drainage direction over flat surfaces in raster digital elevation models[J], Journal of hydrology,1997,193:204-213.
[43]J. Iwahashi and R J. Pike. Automated classifications of topography from DEMs by an unsupervised nested-means algorithm and a three-part geometric signature[J],2006,32-64.
[44]J. Schmidt, I. s. Evans and J. Brinkmann. Comparison of polynomial models for land surface curvature calculation[J], Geographical Information Science,2003,17(8):797-814.
[45]J. Schmidt and A. Hewitt. Fuzzy land element classification from DTMs based on geometry and terrain position[J], Geoderma,2004,121:243-256.
[46]Kazuo O., Tadashi T., Wang P., Tommo O., Takeshi D., Ryosuke S. Automatic 3-D City Modeling Based on Fusion of Laser Scanner Data and Aerial Photo Images [J]. Journal of the Japan Society of Photogrammetry and Remote Sensing,2004,43(5):16-23.
[47]K.Jenson, J.O.Domingue. Extrating Topographic Structure from Digital Elevation Data for
Geographic Information System Analysis[J], Photogrammetry Engineering and Remote Sensing, 1988,54(11):1593-1600.
[48]K Tempfli. Spectral analysis of terrain relief for the accuracy estimation of digital terrain models[J]. ITC Journal,1980, (3):478-510.
[49]Kyoung Min Kim, Joong Jo Park, Myung Hyun Song, In Cheol Kim, Ching Y. Suen. Detection of ridges and ravines using fuzzy logic operations[J], Pattern Recognition Letters,2004,25: 743-751.
[50]L. Dragut, T. Blaschke. Automated classification of landform elements using object-based image analysis[J], Geomorphology,2006,81:330-344.
[51]Lawrence W. Martz, Jurgen Garbrecht. Short Communication automated recognition of valley lines and drainage networks from grid digital elevation models:a review and a new method-Comment[J], Journal of Hydrology,1995,167:393-396.
[52]Lee.J, Stucky.D. On applying viewshed analysis fro determining least-cost paths on digital elevation model[J], International Journal of Geographical Information Science,1998, 12(8):891-905.
[53]Lee I K, Kim M S, Elber G. Planar Curve Offset Based on Circle Approximation[J], Computer-Aided Design,1996,28(8):617-630.
[54]Martz L W, Garbrecht J. Numerical Definition of Drainage Network and Subcatchment Areas from Digital elevation Models[J].Computers & Geosciences,1992,18(6):747-767.
[55]Martz L W, Garbrecht J. An Outlet Breaching Algorithm for the Treatment of Closed Depressions in a Raster DEM[J], Computers & Geosciences,1999,25(6):835-844.
[56]Michael F. Goodchild, A general framework for error analysis in measurement-based GIS[J], Journal of Geographical Systems,2004.12,6(4):323-324.
[57]M.F. Hutchinson. A new procedure for gridding elevation and stream line data with automatic removal of spurious pits[J], Journal of Hydrology,1989,106:211-232.
[58]Muller J C, Wang Z S. Area_patch Generalisation:A Competitive Approach[J]. The Cartographic Journal,1992,29(2):137-144.
[59]O'Callaghan, Mark, J.F. O'Callaghan, D.M. Mark, The extraction of drainage networks from digital elevation data. Computer Vision[J], Graphics and Image Processing,1984,28 (3):323-344.
[60]Okabe A., Boots B, Sugihara K. N earest neighborhood operations with generalized Voronoi diagram [J], International Journal of Geographical Information Systems,1994,8(1):43-71.
[61]Ozdemir H, Bird D. Evaluation of morphometric parameters of drainage networks derived from topographic maps and DEM in point of floods[J], ENVIRONMENTAL GEOLOGY,2009.2, 56(7):1405-1415.
[62]P.A. Burrough. Principles of Geographical Information Systems for Land Resources
Assessment[M], New York:Oxford University Press,1986.
[63]Philip T. Giles, Steven E.Franklin. Comparison of Derivative Topographic Surface、 of a DEM Generated from Stereoscopic SPOT Images with Field Measurements[J], Photogrammetric Engineering & Remote Sensing,1996,62(10):1165-1171.
[64]Plazanet C, Affholder and F. Erirsch,.The Importance of Geometric Modeling Generalization. Cartography and Geographic Information Systems,1995,22(4):291-305.
[65]P.Longley, MF Goodchild, DJ Maguire, DW, Geographical information systems and science[M], wiley, british,2004.
[66]Prima Oky D. A., Ryuzo Y. DEM generation method from contour lines basedon the steepest slope segment chain and a monotone interpolation function[J], Journal of Photogrammetry and Remote Sensing,2002,57(1-2):86-101.
[67]P. Shary, L.S. Sharaya, A.V. Mitusov. Fundamental quantitative methods of land surface analysis[J], Geoderma,2002,107:1-32.
[68]P. T. Giles, S. E. Franklin. An automated approach to the classification of the slope units using digital data[J], Geomorphology,1998,21:251-264.
[69]Puecker T K, Doughlas D H. Detection of surface specific points by local parallel processing of discrete terrain elevation data[J], Computer Graphics and Image Processing,1975,375-387.
[70]Raghavan V, Masumoto S,Koike K etal. Automatic Lineament Extraction from Digital Images Using a Segment Tracing and Rotation Transformation Approach [J]. Computers &Geosciences, 1995,21(4):555-591.
[71]Rossignac J., Borrel P. Multi-resolution 3D approximation for rendering complex scenes, In: Falconine B, KuniiT. Editors, Geometric Modelingin Computer Graphics[M]. New York: Springer Verlag,1993:455-465.
[72]San B. T., Suzen M. L.. Digital elevation model (DEM) generation and accuracy assessment from ASTER stereo data[J], International Journal of Remote Sensing,2005,26(22):5013-5027.
[73]Sefercik, U. G. Comparison of DEM accuracies generated by various methods[C],2007 3rd International Conference On Recent Advances In Space Technologies,2007,379-382.
[74]Schoeder W J., Zarge J A. Lornensen WE. Decimation of triangle meshes [J], Proceedings of SIGGRAPH'92, Computer Graphics,1992,26(2):65-70.
[75]S.J. Park, K. McSweeney, B. Lowery. Identification of the spatial distribution of soils using a process-based terrain characterization[J], Geoderma,2001,103:249-272.
[76]Steven V D., Dirk T, Mark D.B. Using Genetic Algorithms for Solving Hard Problems in GIS[J], GeoInformaiica,2002,6(4):381-413.
[77]Tang Guoan, Gong Jianya,Chen Zhengjiang. A Simulation on the Accuracy of DEM Terrain Representation[J], Acta Geodaetica Et Cartographic Sinica,2001,30(4),361-365.
[78]Tedeusz Chrobak. A Numerical Method for Generalizing the Linear Elements of Large-Scale
Maps, Based on the Example of Rivers. Chartographica.2000. Vol.37, No.l:49-55.
[79]USGS 2006, web site, National Mapping Program, Standards Digital Elevation Model tandards, Part 2 Specifications, Standards for Digital Elevation Models, URL:http://rockyweb.cr.usgs.gov/nmpstds/acrodocs/dem/2DEM0198.PDF, US Department of the Interior, US Geological Survey, National Mapping Division
[80]Wang DM, Tian YA, Gao Y, Wu L. A new method of generating grid DEM from contour lines[C], IGARSS 2005:IEEE International Geoscience and Remote Sensing Symposium,2005, 657-660.
[81]Wang L, Liu H. An efficient method for identifying and filling surface depressions in digital elevation models for hydrologic analysis and modelling[J], International Journal Of Geographical Information Science,2006.2,20(2):193-213.
[82]Wanning Peng. Automated Generalization in GIS[M], ITC Publication Series,1997.
[83]Weibel.R. Models and Experiments for Adaptive Computer-Assisted Terrain Generalization[J], Cartography and Geographic Information Systems,1992,19(3):133-153.
[84]Weibel.R. Map generation in the context of digital system[J], Cartography and Geographic Information System,1995,22(4).
[85]Weibel.R., Jones, C.B. Computational Perspectives on Map Generalization [J], GeoInformatica, 1998,2(4):307-314.
[86]Werschlein T., Robert Weibel.1994. Use of Neural Networks in Line Generaliztion. http://spatialod}sse}ursus.maine.edu/gisweb/spatdb/egis/eg94009.html
[87]Wu yanlan, Oguchi Takashi, Liu yongqiong,et.al. Flow paths tracing from raster contours using distance transform[C]. International Symposium on Spatial Analysis, Spatial-Temporal Data Modeling, and Data Mining,2009, Proc. of SPIE Vol.749255.
[88]Xu JW, Zhang WC, Liu CS. A novel method for filling the depressions in massive DEM data[C], IGARSS:2007 IEEE International Geoscience And Remote Sensing Symposium,2007, 4080-4083.
[89]Xu XL, Zhuang DF. Automated extraction of drainages in China based on DEM in GIS environment[C], IGARSS 2003:IEEE International Geoscience And Remote Sensing Symposium,2003,3344-3346.
[90]Zaksek K., Podobnikar T., An effective DEM generalization with basic GIS operations [A].8th ICA WORKSHOP on Generalisation and Multiple Representation [C], A Coruna, July 7-8th, 2005.
[91]Zhou Q.M., Liu X.J..Error assessment of grid-based flow routing algorithms used in hydrological models[J], Int. J. Geographical Information Science,2002,16(8):819-842.
[92]Zhou Q.M., Liu X.J..Error Analysis on Grid Based Slope and Aspect Algorithm[J], Photogrammetric Engineering and Remote Sensing,,2004,70(8):957-962.
[93]Zhang Sheng, Zhu Cailian, Zhong Shiming. Improvement and Application of Douglas-Peucker Compresing Algorithm[J], Journal of Wuhan University of Technology(Transportation Science & Engineering),2005.10,129(5).
[94]艾廷华.城市地图数据库综合的支撑数据模型与方法的研究[D],博士学位论文,武汉,武汉测绘科技大学,2000.
[95]艾自兴、毋河海等.Delaunay三角形剖分在河流自动综合中的应用研究[C],中国地理学与GIS学术讨论会文集,中国地理学会地图学与GIS专业委员会,青岛,2002,230-238
[96]毕华兴,谭秀英,李笑吟.基于DEM的数字地形分析[J],北京林业大学学报,2005,3.
[97]曹志冬,刘学军,王叶飞,汤国安.基于DEM的地形简化方法对比分析[J],现代测绘,2005.2,28(1)：9-13.
[98]曹志冬,刘学军,王叶飞,汤国安.DEM地形简化指标的分析研究,地理与地理信息科学,2005.3,21(2)：10-15.
[99]测绘发展研究中心.数字中国地理空间基础框架建设的发展,2008.5,http://fazhan.sbsm.gov.cn/article/wxzy/200805/20080500035366.shtml.
[100]测绘发展研究中心.论发展我国地理信息产业的基础设施建设,2008.5,http://fazhan.sbsm.gov.cn/article/wxzy/200805/20080500035472.shtml.
[101]陈波,武芳,钱海忠.空间分析方法在道路网自动综合拓扑构建中的应用[J],测绘科学,2006,31(1)：101-104.
[102]陈楠,林宗坚,李成名,朱红春,徐增让,汤国安.基于信息论的不同比例尺DEM地形信息比较分析,遥感信息(理论研究),2004.3：5-9.
[103]陈军,李志林,蒋捷等.多维动态GIS空间数据模型与方法的研究[J].武汉大学学报(信息科学版),2004,29(10),858-862.
[104]陈述彭.地图学面临的挑战与机遇[J],地理学报,1994,49(1)：5-7.
[105]陈述彭,鲁学军,周成虎.地理信息系统导论[M],科学出版社,1999.
[106]陈涛,艾廷华.多边形骨架线与形心自动搜寻算法研究[J],武汉大学学报(信息科学版),2004,29(5)：443-447.
[107]陈晓勇.数学形态学理论和模型的若干扩展及在CCD扫描等高线图的DEM自动建立中的应用[D],博士学位论文,武汉测绘科技大学,1990.
[108]陈旭,朱欣焰,杜道生,张路.影像与栅格元数据本体实现及语义查询扩展应用[J],武汉大学学报·信息科学版,2009.6,34(6)：646-649.
[109]陈永良,刘大有.一种新的山脊线和山谷线自动提取方法[J],中国图象图形学报,2001.12,6A(12)：1230-1234.
[110]陈永良,刘大有,虞强源.从DEM中自动提取自然水系[J],中国图象图形学报,2002.1,7A(1)：91-96.
[111]陈永良,刘大有,虞强源.地球物理位场图象特征信息自动提取[J],中国图象图形学报,2002.1,7A(2)：132-136.
[112]杜世宏,杜道生,樊红,万幼川.基于栅格数据提取主骨架线的新算法[J],武汉测绘科技大学学报,2000.10,25(5)：432-436.
[113]费立凡.地形图等高线成组综合的试验[J],武汉测绘科技大学学报,1993,18(增刊)：6-22.
[114]弗.特普费尔(著),江安宁(译).制图综合[M],北京：测绘出版社,1982.
[115]冯桂,林宗坚,张继贤,张丽.DEM高精度内插算法及其实现[J],遥感信息-理.仑研究,2000.4：18-20.
[116]范青松.DEM综合生成技术研究[D],博士学位论文,武汉大学,2007.12.
[117]范青松,汤翠莲,胡鹏.DEM精度检查中等高线回放的量化方法[J],测绘科学,2008,33(3)：118-120.
[118]方鹏,谭仁春,李霖.小波变换在多尺度DEM模型建立中的应用[J],四川测绘,2003.3,26(1)：8-11.
[119]郭庆胜.线状要素图形综合的渐进式方法研究[J],武汉测绘科技大学学报,1998.
[120]郭仁忠.空间分析[M],北京：高等教育出版社,2001.
[121]郝红科,田江博,陈永贵.用地形图生成DEM的新方法研究[J],陕西林业科技,2005,(1)：35-37.
[122]国家测绘局.1：5万数字高程模型(DEM)生产技术规定(暂行本),1998.7.
[123]高俊.地图的空间认知和认知地图学[M],地图学年鉴,北京：中国地图出版社,1991.
[124]高俊.地理空间数据的可视化[J],测绘工程,2000.9,9(3)
[125]高安秀树.分数维[M],沈步明,常子文译,北京：地震出版社,1994.
[126]葛金辉,郭丽丽.曲面简化算法研究的发展现状[J],通化师范学院学报,2006,27(6)：18-21.
[127]何丽丽.基于不同比例尺和分辨率DEM的数字地形分析[D],硕士学位论文,西南大学,2007.5.
[128]胡海,杨传勇,胡鹏.DEM最优线性生成技术——MADEM[J],华中科技大学学报(自然科学版),2007,635(6)：118-121.
[129]胡鹏,游涟,杨传勇,吴艳兰.地图代数[M],武汉大学出版社,2002.
[130]胡鹏,吴艳兰,胡海.关于DEM精度评定的基本理论问题[J],地球信息科学,2003,5(3)： 64-70.
[131]胡鹏,吴艳兰,胡海.数字高程模型精度评定的基本理论[J],地球信息科学,2003,5(3)：64-70.
[132]胡鹏,吴艳兰,胡海.再论数字高程模型精度评定的基本理论问题[J],地球信息科学,2005,7(3)：28-33.
[133]胡鹏,王海军等.论多边形中轴问题和算法[J],武汉大学学报(信息科学版),2005,30(10)：853-857.
[134]胡鹏,黄雪莲,吴艳兰等.DEM若干理论问题思考[J],哈尔滨工业大学学报,2006,
38(12)： 2143-2147.
[135]胡鹏,杨传勇,吴艳兰等.新数字高程模型理论方法标准和应用[M],测绘出版社,2007.2.
[136]胡鹏,游涟,胡海.地图代数概论[M],测绘出版社,2008.
[137]胡鹏,白轶多,胡海.数字高程模型(DEM)生成中的序同构问题[J],武汉大学学报(信息科学版),2009.3,34(3)：352-357.
[138]胡鹏,高俊.数字高程模型的数字综合原理研究[J],武汉大学学报(信息科学版),2009.8,34(8)：940-942.
[139]黄培之.提取山脊线和山谷线的一种新方法[J],武汉大学学报(信息科学版),2001.6,26(3)：247-252.
[140]黄培之,刘泽慧.基于地形梯度方向的山脊线和山谷线的提取[J],武汉大学(信息科学版)2005,30(5)：396-399.
[141]黄雯雯.1：5万中低山地区DEM数字综合和等高线综合实验研究[D],硕士学位论文,武汉大学,2009.5.
[142]黄杏元,马劲松,唐勤.地理信息系统(修订版)[M],高等教育出版社,2001.
[143]柯正谊,何健邦等.数字地面模型[M],北京：中国科学技术出版社,1993.
[144]马小虎,潘志庚,石教英.基于三角形移去准则的多面体模型简化方法[J],计算机学报,1998,21(6)：492-498.
[145]马小虎.一种新的基于二次误差的三角形格网简化方法[J],计算机应用,2001,21(12)：22-24.
[146]刘锦中,马辉.基于等高线的DEM生成算法研究和实现[J],现代测绘,2004.6,27(3)：34-35,48.
[147]刘敏.基于三维道格拉斯改进算法的地貌自动综合研究—以在黄土高原的实验为例[D],硕士学位,论文西北大学,2007.6.
[148]刘永琼,吴艳兰,胡海等.数字高程模型精度评价及其问题探讨[J],测绘信息与工程,2009,34(5)：32-36.
[149]刘学军,龚建雅,周启鸣.DEM结构特征对坡度坡向的影响分析[J],地理与地理信息科学,2004,20(6)：1-5.
[150]刘学军,卢华兴,仁政,任志峰.论DEM地形分析中的尺度问题[J],地理研究,2007.5,26(3)：433-442.
[151]刘学军,汤国安.数字地形分析：机遇与挑战[J],地理信息世界,2009.2,1：6-7.
[152]刘泽慧,黄培之.DEM数据辅助的山脊线和山谷线提取方法的研究[J],测绘科学,2003.12,28(4)：33-36.
[153]龙毅,毋河海等.分形学：现代地图学的非线性数学分析方法[J],2003,28(2)：1-3.
[154]李炳元,潘保田,韩嘉福.中国陆地基本地貌类型及其划分指标讨论[J],第四纪研究,2008,28(4)：535-543.
[155]李成名,陈军.Voronoi图生成的栅格算法[J],武汉测绘科技大学学报,1998,23(3)：208-210.
[156]李德仁.关于空间数据不确定性的思考[J],测绘科学技术学报,2006,23(6).
[157]李德仁,郭晟,胡庆武,刘守军,魏建魁.GIS新引擎-“真图”数据解决方案[J],地理信息世界,2008.6,3：5-10.
[158]李基拓,陆国栋.基于边折叠和质点弹簧模型的网络简化优化算法[J],计算机辅助设计与图形学学报,2006,(03).
[159]李圣权,胡鹏.图形部件Voronoi图生成算法与应用研究[J],2005,31(10)：42-44.
[160]李志林,朱庆.数字高程模型(第二版)[M],武汉：武汉大学出版社,2003.
[161]陆毅,翟京生等.数字海图点群状特征的识别、量测与综合[J],武汉大学学报(信息科学版),2001,26(2)：133-139.
[162]马龙,杜道生.GIS中DEM产品精度的分析和评价[J],测绘信息与工程,2003.6,28(3)：4-6.
[163]穆宣社,游雄.支持突发事件应急反应的建筑物内部交通网络分析[J],测绘科学技术学报,2006,(06)
[164]宁津生,张祖勋,祝国瑞,张正禄,翟国君.高新技术与测绘学科发展[J],中国测绘学科发展兰皮书2003卷,测绘出版社,2003.9.
[165]倪星航.基于规则格网DEM提取地形特征线的方法研究[D],硕士学位论文,西南交通大学,2008.5.
[166]牛志宏,李太星.数字高程模型误差分析及精度评价述评[J],长江工程职业技术学院学报,2007,(03)：73-77
[167]Pinhas Yoeli.数字地形模型中的山谷线和山脊线的机助确定[J],万晓霞,朱海红译自《国际制图年鉴1984卷》,胡毓巨,郭仁忠校.
[168]潘志庚,庞明勇.几何格网简化研究与进展[J],江苏大学学报(自然科学版),2005,26(1)：67-71.
[169]邵春丽,胡鹏等.DELAUNAY三角网的算法详述及其应用发展前景[J],测绘科学,2004,12.
[170]苏时雨,李钜章.地貌制图[M],北京：测绘出版社,1999.
[171]史巍巍,裘昱,戴宗友.数字高程模型与等高线质量相关性研究[J],测绘通报,2006,2：23-26.
[172]沈晶.基于机载LiDAR数据的DEM综合生成和建筑物提取[D],博士学位论文,武汉大学,2009.12.
[173]陶旸.DEM数值精度与地形形态精度分析[A],中国地理信息系统协会第四次会员代表大会暨第十一届年会论文集[C],2007.
[174]汤国安,赵牡丹,曹菡.DEM地形描述误差空间结构分析[J],西北大学学报(自然科学版),2000,30(4)：349-352.
[175]汤国安,杨勤科,张勇,刘咏梅.刘新华.不同比例尺DEM提取地面坡度的精度研究——以在黄土丘陵沟壑区的试验为例[J],水士保持通报,2001.2,21(1)：53-56.
[176]汤国安,龚健雅,陈正江等.数字高程模型地形描述精度量化模拟研究[J],测绘学报,2001,30(4)：361-365.
[177]汤国安,杨玮莹等.对DEM地形定量因子挖掘中若干问题的讨论[J],测绘科学,2003,28(1)： 28-32.
[178]汤国安,刘学军,闾国年.数字高程模型及地学分析的原理与方法[M],北京：科学出版社,2005.
[179]汤国安,刘学军,房亮,罗明良.DEM及数字地形分析中尺度问题研究综述[J],武汉大学学报(信息科学版),2006.12,31(12)：1059-1066.
[180]万刚,朱长青.多进制小波及其在DEM数据有损压缩中的应用[J],测绘学报,1999,28(1)：35-39.
[181]唐心红,柳健,张继贤.多尺度地形结构提取方法[J],红外与激光工程,1998,27(3)：18-22.
[182]唐新明,林宗坚,吴岚.基于等高线和高程点建立DEM的精度评价方法探讨[J],遥感信息,1999,03.
[183]王春,陶肠,贾敦新,朱雪坚.规则格网DEM地形描述形态精度研究[J],地理信息世界,2008,(01).
[184]王春,刘学军,汤国安,陶玚.格网DEM地形模拟的形态保真度研究[J],武汉大学学报-信息科学版,2009.2,34(2)：146-149.
[185]王东华,刘建军,商瑶玲等.全国1：25万数字高程模型数据库的设计与建库[J],测绘通报,2001,(10)：28-31.
[186]王家耀.图论在道路网自动选取中的应用[J],解放军测绘学院学报,1985,(1)
[187]王家耀.普通地图制图综合原理[M],测绘出版社,1992.
[188]王家耀,武芳.数字地图自动制图综合原理[M],北京：解放军出版社,1998.
[189]王家耀,田震.海图水深综合的人工神经元网络方法[J],测绘学报,1999.11,28(4)：335-339.
[190]王家耀.地图制图学和地理信息工程学科发展现状[J],中国测绘学科发展兰皮书2003卷,测绘出版社,2003.9.
[191]王家耀,崔铁军,苗国强.数字高程模型及其数据结构[J],海洋测绘,2004.5,24(3)：1-4.
[192]王建,杜道生.规则格网DEM化简的一种改进方法[J],测绘信息与工程,2007.4,32(2)：34-36.
[193]王建,杜道生.栅格数据表示空间信息的不确定性初探[J],地理信息世界,2007.4,2：50-54.
[194]王建,杜道生.规则格网DEM自动综合方法的评价[J],武汉大学学报(信息科学版),
2007.12,32(12)：1111-1114.
[195]王宇宙,赵宗涛.一种多进制小波变换DEM数据简化方法[J],计算机应用,2003,23(6)：107-109.
[196]王玉海,朱长青等.基于B样条小波的等高线数据简化[J],测绘科学,2003,28(2)：23-26.
[197]王建宇,滕树钦.一种基于等高线生成DEM的方法[J],计算机应用,2002.8,22(8)：30-31,35.
[198]王光霞,朱长青,史文中,张国芹.数字高程模型地形描述精度的研究[J],测绘学报,2004.5,33(2)：168-173.
[199]王光霞,张寅宝,李江.DEM精度评估方法的研究与实践[J],测绘科学,2006,(03)
[200]王桥.分形理论在地图图形数据自动处理中的若干扩展与应用研究[D],博士学位论文,武汉测绘科技大学,1996.
[201]王桥.毋河海.地图图斑群自动综合的分形方法研究[J],武汉测绘科技大学学报,1996,21(1)：50-63.
f202] 王桥,毋河海.地图信息的分形描述与自动综合研究[M],武汉：武汉测绘科技大学出版社,1998.
[203]王新生,刘纪远等.一种新的构建Voronoi图的栅格方法[J],中国矿业大学学报,2003,32(3)：293-296.
[204]王友昆.等高线自动综合算法研究与实现[D],硕士学位论文,昆明理工大学,2008.5.
[205]武芳.协同式自动综合的研究与实践[D],博士学位论文,中国人民解放军信息工程大学,2000.
[206]武芳,王家耀.地图自动综合概念框架分析与研究[J],2002,11(2)：18-21.
[2071 吴凡,祝国瑞.基于小波分析的地貌多尺度表达与自动综合[J],武汉大学学报(信息科学版),2001,26(2)：171-177
[208]吴纪桃,王桥.小波分析在GIS线状数据图形简化中的应用研究[J],测绘学报,2000,29(1)：71-75.
[209]吴纪桃,王桥.小波理论用于地图数据处理中若干理论问题的探讨[J],测绘学报,2002,31(3)：245-248.
[210]吴纪桃,王桥.复杂地貌形态多比例尺表达的二维小波分析研究[J],遥感学报,2003,7(2)：93-97.
[211]吴立新,史文中,地理信息系统原理与算法[M],科学出版社,2003.
[212]吴艳兰,胡鹏.由栅格等高线快速建立DEM的新方法-CSE法[J],武汉大学学报信息科学版,2001,2.
[213]吴艳兰.地貌三维综合的地图代数模型和方法研究[D],博士学位论文,武汉大学,2004.4.
[214]吴艳兰,胡鹏.几何特性与流线追踪相结合的地形结构线提取法[J],武汉大学学报(信
息科学版),2005,30(10)：1115-1119.
[215]吴艳兰,胡鹏.基于地图代数的数字地表流线模型研究[J],水科学进展,2007.3,18(3)：356-361.
[216]毋河海.地貌形态自动综合问题[J],武汉测绘科技大学学报,1995a,20(增)：1-6.
[217]毋河海.河系树结构的自动建立[J],武汉测绘科技大学学报,1995b,20(增)：7-14.
[218]毋河海.地形图等高浅树的自动建立[J],武汉测绘科技大学学报,1995c,20(增)：15-19.
[219]毋河海.自动综合的结构化实现[J],武汉测绘科技大学学报,1996,21(3)：277-285.
[220]毋河海.凸壳原理在点群目标综合中的应用[J],测绘工程,1997,6(1)：1-6.
[221]毋河海.地图信息自动综合基本问题研究[J],武汉测绘科技大学学报,2000a,25(5)：377-386.
[222]毋河海.地貌形态自动综合基础理论与方法体系研究[J],第三届两岸测绘发展研讨会,“测绘与可持续发展”论文集,2000b,12：611-632.
[223]毋河海.基于扩展分形的地图信息自动综合研究[J],地理科学进展,2001,(sup)：14-28.
[224]毋河海.地图综合基础理论与技术方法研究[M],测绘出版社,2004.1.
[225]毋河海.机助制图综合原理[M],武汉大学教材,2006.
[226]颜加斌.等高线自动综合技术研究及软件开发[D],硕士学位论文,昆明理工大学,2008.6.
[227]杨晓云,唐咸远,梁鑫.基于等高线生成DEM的内插算法及其精度分析[J],测绘工程,2006.4,15(2)：37-39.
[228]杨晓云,顾利亚,岑敏仪.数字高程模型的误差处理与精度评估[J],铁道勘察,2004,05.
[229]杨晓云,梁鑫.数字高程模型(DEM)的质量控制及精度分析[J],广西工学院学报,2006,(S2).
[230]杨族桥,郭庆胜.基于提升方法的DEM多尺度表达研究[J],武汉大学学报(信息科学版),2003a,28(4)：496-498.
[231]杨族桥,熊新阶,张子宪,高汉平,郭庆胜.基于小波变换的DEM多尺度分析模型的研究[J],黄冈师范学院学报,2003.12b,23(6).
[232]余生晨,刘大有,刘洪.山脊线与山谷线的计算机自动检测[J],中国图象图形学报,1999,4(A)8：693-696.
[233]中国测绘学会.中国地图学与地理信息工程技术科学的新进展[J],中国测绘学科发展兰皮书2003卷,测绘出版社,2003.9.
[234]钟业勋,魏文展,李占元.基本地貌形态数学定义的研究[J],测绘科学,2002.9,27(3)：16-18.
[235]愰玉忠.基于DEM的数字地形分析[D],硕士学位论文,武汉理工大学,2008.
[236]查正军.基于数字高程模型(DEM)的地形特征提取,硕士学位论文,同济大学,2007.1.
[237]张必强,邢渊,阮雪榆.基于特征保持和三角形优化的格网模型简化[J],上海交通大
学学报,2004,38(8)：1373-1374.
[238]张彩霞,杨勤科,段建军.一种高质量的数字高程模型(DEM)建立方法——ANUDEM法[J],中国农业通报,2005,21(12)：411-415.
[239]张彩霞,杨勤科,段建军.高分辨率数字高程模型的构建方法[J],水利学报,2006,37(8)：1009-1015.
[240]张锦.多分辨率空间数据模型理论与实现技术研究[M],北京：测绘出版社,2004.
[241]张军.数字高程模型的建立及应用研究[D].硕士学位论文,辽宁工程技术大学,2007.3.
[242]张青年.线状要素的动态分段与制图综合[J],中山大学学报(自然科学版),2004,43(2)：104-107.
[243]张勇,汤国安,彭财.数字高程模型地形描述误差的量化模拟——以黄土丘陵沟壑区的实验为例[J],山地学报,2003.4,21(2)：252-256.
[244]张宇军.基于DEM骨架特征点线的地貌自动综合研究——以岔巴沟流域为例[D],硕士学位论文,西北大学,2008.6.
[245]张占睦.基于地形图的DEM的构建及其精度分析[D],硕士研究论文,信息工程大学,2001.
[246]张祖勋,张剑清.数字摄影测量[M],武汉大学出版社,1996.2.
[247]赵杰.数字地形模拟——地形数据获取与数字地形分析研究[D],博士学位论文,武汉：武汉大学测绘遥感信息工程国家重点实验室,2004.
[248]周昆,潘志庚,石教英.基于三角形折叠的格网简化算法[J],计算机学报,1998,21(6)：506-513.
[249]周培德,周忠平.确定任意多边形中轴的算法[J],北京理工大学学报,2000,20(6)：708-711.
[250]周启鸣,刘学军.数字地形分析[M],北京：科学出版社,2006.
[251]周廷儒,施雅风,陈述彭.中国地形区划草案[M],中国自然区划草案北京：科学出版社,1956.
[252]周兴华,姚艺强,赵吉先.DEM内插方法与精度评定[J],测绘科学,2005.10,30(5)：86-88.
[253]朱长青,王玉海等.基于小波分析的等高线数据压缩模型[J],中国图象图形学报,2004,9(7),841-845.
[254]朱庆,赵杰等.基于规则格网DEM的地形特征提取算法[J],测绘学报,2004,33(1),77-82.
[255]朱文博,毕如田,郭磐石,张锦.一种基于多分辨率模型简化算法的等高线自动综合方法研究[J],山西农业大学学报(自然科学版),2008.3,28(3)：332-337.
[256]朱文博.基于多分辨率DEM模型的等高线综合方法研究[D],硕士学位论文,太原理工大学,2005.5.
[257]祝国瑞.地图学[M],武汉：武汉大学出版社,2003.
[258]祝国瑞,郭礼珍,尹贡白,徐永利.地图设计与编绘[M],武汉大学,2001.
[259]祝国瑞,尹贡白.普通地图编制[M],测绘出版社,1983.