1.Zhang, C., T. Zhao, and W. Li. 2010. Automatic search of geospatial features for disaster and emergency 管理学 International Journal of Applied 地球 Observation and Geoinformation, doi:10.1016/j.jag.2010.05.004.
2., W., C. Zhang, Dplus KIA Dey, and S. Wang. 2010. Estimating threshold-exceeding probability maps of continuous environmental variables with Markov chain random fields. Stochastic Environmental Research and Risk Assessment, doi:10.1007/略-9.
3.Zhang, C., T. Zhao, W. Li, and J. Osleeb. 2010. Towards logic-based geospatial feature discovery and integration using web feature service and geospatial semantic web. International Journal of Geographical Information Science, 24(6): 903-923.
4., W. and C. Zhang. 2010. Linear interpolation and joint model fitting of experimental transiograms for Markov chain simulation of categorical spatial variables. International Journal of Geographical Information Science, 24(6): 821-839.
5.Zhang, C., T. Zhao, and W. Li. 2010. The framework for a geospatial semantic web based spatial decision support system for digital 地球 International Journal of Digital Earth, 3(2): 111-134.
6., W. and C. Zhang. 2010. Simulating spatial distribution of clay layer occurrence depth in alluvial soils with a Markov chain geostatistical approach. Environmetrics, 21(1): 21?32.
7.Zhang, C. W. Li, and D. Travis. 2009. Geostatistical restoration of clouded pixels in multispectral remotely sensed imagery. International Journal of Remote Sensing, 30(9): 2173-2195.
8.Zhang, C., Z-R. peng, T. Zhao and W. Li. 2008. Transformation of transportation data models from unified modeling language to web 本体论 language. Journal of the Transportation Research Board: Transportation Research Record, 2064: 81-89.
9.Zhang, C, and W. Li. 2008. Regional-scale modeling of the spatial distribution of surface and subsurface textural types in alluvial soils using Markov chain geostatistics. Soil Use and 管理学, 24(3): 263-272.
10., W., and C. Zhang. 2008. A single-chain-based multidimensional Markov chain model for subsurface characterization. Environmental and Ecological Statistics, 15(2): 157-174.
11.Zhang, C., and W. Li. 2008. A comparative study of nonlinear Markov chain models in conditional simulation of categorical variables from regular samples. Stochastic Environmental Research and Risk Assessment, 22(2): 217-230.
12., W. 2007. Markov chain random fields for estimation of categorical variables. Mathematically Geology, 39(3): 321-335.
13., W. 2007. A fixed-path Markov chain algorithm for conditional simulation of discrete spatial variables. Mathematical Geology, 39(2): 159-176.
14., W. 2007. Transiograms for characterizing spatial variability of soil classes. Soil Science Society of American Journal, 71(3): 881-893.
15., W., and C. Zhang, 2007. A random-path Markov chain algorithm for simulating categorical soil variables from random point samples. Soil Science Society of American Journal, 71(3): 656-668.
16.Zhang, C., W. Li, and T. Zhao. 2007. Geospatial data sharing based on geospatial semantic web technologies. Journal of Spatial Science, 52(2): 11-25.
17.Zhang, C., and W. Li. 2007. Comparing a fixed-path Markov chain geostatistical algorithm with sequential indicator simulation in categorical variable simulation from regular samples. GIScience \u0026 Remote Sensing, 44(3): 251-266.
18.Zhang, C., W. Li, and D. Travis. 2007. Gaps-fill of SLC-off Landsat ETM+ satellite image using a geostatistical approach. International Journal of Remote Sensing, 28(22): 5103-5122.
19. W. 2006. Transiogram: A spatial relationship measure for categorical data. International Journal of Geographical Information Science, 20(6): 693-699.
20., W., and C. Zhang. 2006. A generalized Markov chain approach for conditional simulation of categorical variables from grid samples. Transactions in GIS, 10(4): 651-669.
21.Zhang, C., W. Li and M. Day. 2006. Effective protected-area boundary designation in China using a web-based spatial decision support system. Journal of Spatial Science, 51(2): 33-46.
22., W., and C. Zhang. 2005. Application of transiograms to Markov chain modeling and spatial uncertainty assessment of land cover classes. GIScience \u0026 Remote Sensing, 42(4): 297-319.
23., W., C. Zhang, J.E. Burt, and A. Zhu. 2005. A Markov chain-based probability vector approach for modeling spatial uncertainties of soil classes. Soil Science Society of American Journal, 69(6): 1931-1942.
24.Zhang, C., and W. Li. 2005. The roles of Web Feature and Web Map Services in real-时间 geospatial data sharing for time-critical applications. Cartography and Geographical Information Science, 32(4): 269-283.
25.Zhang, C., W. Li and M. Day. 2005. Towards establishing effective protective boundaries for the Lunan Stone Forest using an online spatial decision support system. Acta Cars.
随机推荐
李卫东，男，博士，教授，华中农业大学资源与环境学院博士生导师
基本情况
教育背景
1988获华中农业大学土壤农化系土壤与植物营养专业学士。
1991获华中农业大学土壤学专业土壤地理学方向硕士。
1995获中国农业大学土壤学专业土壤物理学方向博士。
2003获美国马克特大学数学和计算机科学系数学计算职业硕士。
工作经历
1991任河南省科学院地理研究所研究实习员。
1995任中国科学院地理研究所博士后。
1997任中国科学院地理研究所副研究员。
1998年底出国，先后任天主教鲁汶大学土地研究所青年研究员（博士后）、以色列理工学院水文水资源系博士后、威斯康星学院大学、肯特州立大学和康涅提格大学研究员和客座教授。
2008年冬任华中农业大学教授。
主要科研方向与项目
科研方向
研究方向主要为中低产田改良、土壤和水资源管理、土壤土地景观时空变异模拟、地统计学和地理信息科学及其在资源环境模拟评估上的应用、地统计学和地球时空分析的理论、方法和技术
科研项目
自1991年以来，李卫东博士先后主持和参与了一批国家、地方和国外的科学研究项目，包括国家自然科学基金面上和重大项目、中科院和河南省黄淮海平原农业开发重大项目、中外合作项目和国外的科学基金项目。主要致力于空间统计和信息科学理论方法及其在资源、环境和生态评估上的应用研究。在地统计学、地理信息科学、土壤学和自然地理学研究上取得了一系列突出进展
1、空间统计学：提出了马链随机域理论及转移概率函数（Transiogram）理论，并以此为基础构建了马链地统计学的理论框架。提出了马链地统计学的随机路径算法和两个固定路径算法。提出了联合模拟试验转移概率函数图的线性插值法和数学模型模拟法。又提出了模拟环境变量阈值超越概率的马链方法。马链地统计学是在极其艰难的环境下提出的，也是十几年潜心探索研究的结果。它不仅解决了地球数学上半个世纪以来在把马链由一维扩展到多维的长期努力中遇到的一系列难题，更为马链成为一个新的地球统计学方法奠定了理论和方法学基础。另外，还提出了用经典地统计学方法填充遥感图像丢失信息的方法。针对可观察范畴变量，提出可采用线状调查。进一步的研究在考虑时空联合、非稳态、辅助数据和软件开发等。
2、地理信息科学：参与探讨了网络GIS的一些问题诸如数据兼容和共享，并参与提出了一些算法。探索了面积级图的空间不确定性并提出了表达范畴场不确定性的概率图法。提出了模拟范畴地理变量的马链地统计学。采用地球统计学进行卫星遥感图像信息缺失处理。
3、土壤学：从区域尺度上定量冲积土壤质地层次的空间变异，采用一维马链理论建立了冲积土壤质地剖面的随机模拟模型，并与农田水平衡模型相结合。1999年利用‘厄耳费机’提出的耦合二维马链模型模拟了土壤类型和质地剖面，发现其因模型假设和算法不适当而不能产生合理结果，近年提出的马链地统计学最终解决了有关问题。利用马链地统计学模拟了土壤质地剖面、土壤类型分布、土壤层次厚度和出现深度等。对我国暖温带的黑粘土（沙姜黑土）的发生学特性进行了系统的分析，阐释了形成过程以及黑色和僵瘦成因，并提出了分类和治理建议。
4、自然地理学：利用空间统计学进行土地覆被类型的空间分布模拟。多次参与黄淮海平原农业综合治理与开发研究，探讨了黄淮海平原农业持续发展的有关策略。较早地认识到了开展陆地生态系统水、氮和碳循环研究的迫切性并综述了国外研究进展。
5、农田水文学：采用综合方法模拟区域尺度农田土壤的空间变异性，与农田水分和溶质运移的点模型相结合，从区域尺度上定量有关转换量。2000年采用随机方法和美国地质调查局的Sutra水文地质模型联动验证了‘因德尔曼’提出的土壤溶质平均剖面分析解，发现其因假设问题而不切合实际。
主要科研成果与论著
科研成果
如硕士论文（1991年）系统研究了中国暖温带变性土（黑粘土类）的形成和分类。博士论文（1995年）研究了华北平原冲积土壤的质地层次空间分异特征及对农田水平衡的影响。1998年主持国家自然科学基金面上项目“冲积土壤质地层次空间变化的模拟研究”。自1999年以来在开展离散空间变量的多维马尔可夫链模拟研究中，通过长期不懈的努力，在艰难处境中与张传荣教授合作逐步提出了多维马尔可夫链模拟的一系列理论、方法和技术，构建了“马尔可夫链地统计学”，成为地统计学和地球空间分析上的一个独立的理论方法体系。另外在网络GIS、遥感图像处理、土壤空间变异描述模拟和区域环境模拟等方面也取得了重要进展。
马尔可夫链地统计学(Markov chain geostatistics)的主要论文于2007年发表于数学地质（数学 Geol.）和美国土壤学会会刊(Soil Sci. Soc. Am. J.)等国际刊物上，主要内容包括“马链随机域”(Markov chain random field)理论及有关模拟算法和“转移概率函数”(Transiogram)理论及有关联合拟合方法。有关理论分别从数学推导和实例验证上得到了证明。该研究被认为是“对地统计学和地球空间分析的重大贡献”，提出了新的概念、理论和方法，开辟了空间统计学研究上的一个新领域。在国际数学地质、地理学、土壤学和水文学等学界引起很大关注。在地理信息、土壤、数学地质、环境统计和遥感等领域国际刊物上发表了一系列重要学术论文。该研究到目前为止已发表有关国际刊物论文17篇，建立起了一个理论方法体系框架，未来的扩展和应用仍将是一个长期的工作。
自1992年以来，李卫东博士共发表学术论文近70篇，其中第一作者论文40余篇，英文论文40余篇，国际刊物论文30余篇。他于2007年春应邀编写国际人文地理百科全书马尔可夫链分析一文，在2008年和2009年多次被提名到美洲名人录。
主要论文
1.Zhang, C., T. Zhao, and W. Li. 2010. Automatic search of geospatial features for disaster and emergency 管理学 International Journal of Applied 地球 Observation and Geoinformation, doi:10.1016/j.jag.2010.05.004.
2., W., C. Zhang, Dplus KIA Dey, and S. Wang. 2010. Estimating threshold-exceeding probability maps of continuous environmental variables with Markov chain random fields. Stochastic Environmental Research and Risk Assessment, doi:10.1007/略-9.
3.Zhang, C., T. Zhao, W. Li, and J. Osleeb. 2010. Towards logic-based geospatial feature discovery and integration using web feature service and geospatial semantic web. International Journal of Geographical Information Science, 24(6): 903-923.
4., W. and C. Zhang. 2010. Linear interpolation and joint model fitting of experimental transiograms for Markov chain simulation of categorical spatial variables. International Journal of Geographical Information Science, 24(6): 821-839.
5.Zhang, C., T. Zhao, and W. Li. 2010. The framework for a geospatial semantic web based spatial decision support system for digital 地球 International Journal of Digital Earth, 3(2): 111-134.
6., W. and C. Zhang. 2010. Simulating spatial distribution of clay layer occurrence depth in alluvial soils with a Markov chain geostatistical approach. Environmetrics, 21(1): 21?32.
7.Zhang, C. W. Li, and D. Travis. 2009. Geostatistical restoration of clouded pixels in multispectral remotely sensed imagery. International Journal of Remote Sensing, 30(9): 2173-2195.
8.Zhang, C., Z-R. peng, T. Zhao and W. Li. 2008. Transformation of transportation data models from unified modeling language to web 本体论 language. Journal of the Transportation Research Board: Transportation Research Record, 2064: 81-89.
9.Zhang, C, and W. Li. 2008. Regional-scale modeling of the spatial distribution of surface and subsurface textural types in alluvial soils using Markov chain geostatistics. Soil Use and 管理学, 24(3): 263-272.
10., W., and C. Zhang. 2008. A single-chain-based multidimensional Markov chain model for subsurface characterization. Environmental and Ecological Statistics, 15(2): 157-174.
11.Zhang, C., and W. Li. 2008. A comparative study of nonlinear Markov chain models in conditional simulation of categorical variables from regular samples. Stochastic Environmental Research and Risk Assessment, 22(2): 217-230.
12., W. 2007. Markov chain random fields for estimation of categorical variables. Mathematically Geology, 39(3): 321-335.
13., W. 2007. A fixed-path Markov chain algorithm for conditional simulation of discrete spatial variables. Mathematical Geology, 39(2): 159-176.
14., W. 2007. Transiograms for characterizing spatial variability of soil classes. Soil Science Society of American Journal, 71(3): 881-893.
15., W., and C. Zhang, 2007. A random-path Markov chain algorithm for simulating categorical soil variables from random point samples. Soil Science Society of American Journal, 71(3): 656-668.
16.Zhang, C., W. Li, and T. Zhao. 2007. Geospatial data sharing based on geospatial semantic web technologies. Journal of Spatial Science, 52(2): 11-25.
17.Zhang, C., and W. Li. 2007. Comparing a fixed-path Markov chain geostatistical algorithm with sequential indicator simulation in categorical variable simulation from regular samples. GIScience \u0026 Remote Sensing, 44(3): 251-266.
18.Zhang, C., W. Li, and D. Travis. 2007. Gaps-fill of SLC-off Landsat ETM+ satellite image using a geostatistical approach. International Journal of Remote Sensing, 28(22): 5103-5122.
19. W. 2006. Transiogram: A spatial relationship measure for categorical data. International Journal of Geographical Information Science, 20(6): 693-699.
20., W., and C. Zhang. 2006. A generalized Markov chain approach for conditional simulation of categorical variables from grid samples. Transactions in GIS, 10(4): 651-669.
21.Zhang, C., W. Li and M. Day. 2006. Effective protected-area boundary designation in China using a web-based spatial decision support system. Journal of Spatial Science, 51(2): 33-46.
22., W., and C. Zhang. 2005. Application of transiograms to Markov chain modeling and spatial uncertainty assessment of land cover classes. GIScience \u0026 Remote Sensing, 42(4): 297-319.
23., W., C. Zhang, J.E. Burt, and A. Zhu. 2005. A Markov chain-based probability vector approach for modeling spatial uncertainties of soil classes. Soil Science Society of American Journal, 69(6): 1931-1942.
24.Zhang, C., and W. Li. 2005. The roles of Web Feature and Web Map Services in real-时间 geospatial data sharing for time-critical applications. Cartography and Geographical Information Science, 32(4): 269-283.
25.Zhang, C., W. Li and M. Day. 2005. Towards establishing effective protective boundaries for the Lunan Stone Forest using an online spatial decision support system. Acta Cars.
参考资料