在科学研究上,主要从事
GIS空间分析,基于
DEM数字地形分析的理论与方法研究,主持国家重点科学研究项目10项。研究了DEM不确定性的形成条件、空间分布及
数学模拟方法,提出并实现了特征嵌入式数字高程模型F-DEM,形成了数字地形算法并行化基础理论与系列化算法。他提出了基于DEM的地面坡谱、地形纹理、地形特征点簇等地形信息图谱理论与方法,研究了黄土高原地貌发育阶段的继承性与空间分异特征,在DDE框架下的全球高分辨率地貌制图取得了重要进展。出版研究专著及教材16部,发表研究论文200余篇,
专利12项,研究成果获国家科技进步二等奖、教育部自然科学二等奖等省部级科研奖励七项。获中国地理学会“第三届全国优秀地理科技工作者”,
国务院政府特殊津贴专家,中国地理信息产业杰出人才等荣誉称号。
教育背景
工作经历
主要社会兼职
出版图书
研究方向
主要从事地理信息系统、GIS空间分析、地学信息图谱、数字地面模型、数字地形分析、数字地貌等方面的科学研究工作,
获奖记录
个人荣誉
科研获奖
教学获奖
主要贡献
主持的主要科研项目
先后主持了4项国家863重点项目、8项
国家自然科学基金项目(含一项重点项目),及多项重要的科学研究项目
教学项目与成果
出版研究专著及教材
1. 汤国安 杨昕 张海平《ArcGIS地理信息系统空间分析实验教程(第三版)》,科学出版社,2021;
2. 钟耳顺 宋关福 汤国安《大数据地理信息系统:原理、技术与应用》,清华大学出版社,2020;
3. 闾国年 汤国安 赵军等《地理信息科学导论》,科学出版社,2019年;
4. Xiong Li-Yang, Tang Guo-An.《Loess Landform Inheritance: Modeling and Discovery》,Springer, 2019;
5. 汤国安《地理信息系统教程(第二版)》高等教育出版社,2019(国家十二五规划教材、iCouse教材);
6. 汤国安,钱柯健,熊礼阳《
地理信息系统基础实验操作100例》,科学出版社,2017;
7. 汤国安,李发源,杨昕,熊礼阳《黄土高原数字地形分析的探索与实践》,
科学出版社,2015;
8. TANG Guoan 《A Research on The Accuracy of Digital Elevation Models》, Science Press Beijing New York, 2000.7;
9. Qiming Zhou, Brian Lees, Guoan Tang《Advanced in Digital terrain Analysis》, Springer Press, 2008;
11. 汤国安,杨昕《
ArcGIS地理信息系统空间分析实验教程》(第二版),科学出版社,2012.4;
12. 汤国安,李发源,刘学军《
数字高程模型教程》,
科学出版社,2010.5(国家十一五、
十二五规划教材);
13. 汤国安,赵牡丹,杨昕,周毅《地理信息系统》(第二版),科学出版社,2010.7;
14. 杨昕,汤国安《ERDAS遥感数字图像处理实验教程》,科学出版社,2009;
15. 汤国安,刘学军,
闾国年,盛业华,王春,张婷《
地理信息系统教程》,
高等教育出版社,2007.4(国家十一五、
十二五规划教材);
17. 汤国安,张友顺,刘咏梅,谢元礼,杨昕,
刘爱利《遥感数字图像处理》,科学出版社,2004.4 ;
18. 汤国安,陈正江,赵牡丹,刘万青,刘咏梅《
ArcView地理信息系统空间分析方法》,科学出版社,2002.10;
19. 汤国安,赵牡丹《地理信息系统》,
科学出版社,2000.10;
20. 汤国安《计算机地学分析与制图》,
西北大学出版社,1994.9;
部分发表论文 50篇
1.汤国安. 共筹共建,共享共赢,构建高校地理信息科学专业共同体,人民日报(教育名家笔谈),2022.6.20.
2.汤国安,李吉龙,熊礼阳,那嘉明.(2021)论地理边界的科学属性与表达[J].地理学报,76(11):2841-2852.
3.张海平,汤国安*,熊礼阳,杨昕,李发源.(2022)面向地貌学本源的DEM增值理论框架与构建方法[J].地理学报,77(03):518-533.(通讯作者)
4. 汤国安, 那嘉明, 程维明.(2017)我国区域地貌数字地形分析研究进展,测绘学报,2017年 第10期 1570-1591页.
5. 黄骁力, 丁浒, 那嘉明, 汤国安*.(2017) 地貌发育演化研究的空代时理论与方法[J]. 地理学报,72(01):94-104.(通讯作者)
6. 汤国安, 那嘉明, 程维明.(2017) 我国区域地貌数字地形分析研究进展[J]. 测绘学报,46(10):1570-1591.
7. 蒋圣, 汤国安*, 刘凯. (2015)利用累加距离匹配函数的纹理规则度计算方法[J]. 计算机辅助设计与图形学学报, 27(10):1874-1880.(通讯作者)
8. 刘凯, 汤国安*, 江岭, 宋效东, 阳建逸. (2015)格网DEM侵蚀学坡长并行计算方法[J]. 武汉大学学报(信息科学版),40(02):274-279.(通讯作者)
9. 汤国安. (2014)我国数字高程模型与数字地形分析研究进展[J]. 地理学报,69(09):1305-1325.
10. 江岭, 汤国安*, 宋效东, 刘凯, 阳建逸. (2014)顾及粒度控制的格网DEM洼地和平坦区预处理并行算法[J]. 武汉大学学报(信息科学版),39(12):1457-1462.(通讯作者)
11. 汤国安. (2014) 我国数字高程模型与数字地形分析研究进展. 地理学报 Vol. 69, 9:1305-1325.
12. 熊礼阳, 汤国安*, 袁宝印, 陆中臣, 李发源, 张磊. (2014)基于DEM的黄土高原(重点流失区)地貌演化的继承性研究[J]. 中国科学:地球科学, 44(02):313-321.(通讯作者)
13. Xiong L Y, Li S J, Hu G H, et al. Past rainfall-driven erosion on the Chinese loess plateau inferred from archaeological evidence from Wucheng City, Shanxi[J]. Communications Earth & Environment, 2023, 4(1): 4.
14. Xiong L, Li S, Tang G, et al. Geomorphometry and terrain analysis: data, methods, platforms and applications[J]. Earth-Science Reviews, 2022: 104191.
15. Wei H, Xiong L, Zhao F, et al. Large-scale spatial variability in loess landforms and their evolution, Luohe River Basin, Chinese Loess Plateau[J]. Geomorphology, 2022, 415: 108407.
16. Li S, Li K, Xiong L, et al. Generating Terrain Data for Geomorphological Analysis by Integrating Topographical Features and Conditional Generative Adversarial Networks[J]. Remote Sensing, 2022, 14(5): 1166.
17. Tang G, Li J, Xiong L, et al. Scientific attributes and expression methods of geographical boundary[J]. Journal of Geographical Sciences, 2022, 32(6): 1119-1135.
18.Wu S, Tang G, Chen B. Envelope-Based Variable-Gain Control Strategy for Vibration Suppression of Solar Array Using Reaction Wheel Actuator[J]. International Journal of Aerospace Engineering, 2022, 2022.
19. Li J, Na J, Yang X, et al. Application of the Hilbert–Huang transform for recognition of active gully erosion sites in the Loess Plateau of China[J]. Transactions in GIS, 2019, 23(1): 137-157.
20. Liu K, Ding H, Tang G, et al. Large-scale mapping of gully-affected areas: An approach integrating Google Earth images and terrain skeleton information[J]. Geomorphology, 2018, 314: 13-26.
21. Ding H, Na J, Huang X, et al. Stability analysis unit and spatial distribution pattern of the terrain texture in the northern Shaanxi Loess Plateau[J]. Journal of Mountain Science, 2018, 15(3): 577-589.
22. Xiong L Y, Tang G A, Zhu A X, et al. Paleotopographic controls on modern gully evolution in the loess landforms of China[J]. Science China Earth Sciences, 2017, 60: 438-451.
23. Liu K, Ding H, Tang G, et al. An object-based approach for two-level gully feature mapping using high-resolution DEM and imagery: A case study on hilly loess plateau region, China[J]. Chinese Geographical Science, 2017, 27: 415-430.
24. Zhao H, Fang X, Ding H, et al. Extraction of terraces on the Loess Plateau from high-resolution DEMs and imagery utilizing object-based image analysis[J]. ISPRS International Journal of Geo-Information, 2017, 6(6): 157.
25. Xiong L Y, Tang G A, Zhu A X, et al. Paleotopographic controls on modern gully evolution in the loess landforms of China[J]. Science China Earth Sciences, 2017, 60: 438-451.
26. Liu K, Ding H, Tang G, et al. Detection of catchment-scale gully-affected areas using unmanned aerial vehicle (UAV) on the Chinese Loess Plateau[J]. ISPRS International Journal of Geo-Information, 2016, 5(12): 238.
27. Song X D, Tang G A, Liu X J, et al. Parallel viewshed analysis on a PC cluster system using triple-based irregular partition scheme[J]. Earth Science Informatics, 2016, 9: 511-523.
28. Yu T X, Xiong L Y, Cao M, et al. A new algorithm based on Region Partitioning for Filtering candidate viewpoints of a multiple viewshed[J]. International Journal of Geographical Information Science, 2016, 30(11): 2171-2187.
29. Xiong L Y, Tang G A, Strobl J, et al. Paleotopographic controls on loess deposition in the Loess Plateau of China[J]. Earth Surface Processes and Landforms, 2016, 41(9): 1155-1168.
30. Cao M, Tang G, Zhang F, et al. A cellular automata model for simulating the evolution of positive–negative terrains in a small loess watershed[J]. International Journal of Geographical Information Science, 2013, 27(7): 1349-1363.
31. Yang J, Ding R, Zhang Y, et al. An improved ant colony optimization (I-ACO) method for the quasi travelling salesman problem (Quasi-TSP)[J]. International Journal of Geographical Information Science, 2015, 29(9): 1534-1551.
32.Liu X, Tang G, Yang J, et al. Simulating evolution of a loess gully head with cellular automata[J]. Chinese Geographical Science, 2015, 25: 765-774.
33. Liu K, Tang G, Jiang L, et al. Regional-scale calculation of the LS factor using parallel processing[J]. Computers & Geosciences, 2015, 78: 110-122.
34. Cao M, Tang G, Shen Q, et al. A new discovery of transition rules for cellular automata by using cuckoo search algorithm[J]. International Journal of Geographical Information Science, 2015, 29(5): 806-824.
35. Tang G, Song X, Li F, et al. Slope spectrum critical area and its spatial variation in the Loess Plateau of China[J]. Journal of Geographical Sciences, 2015, 25: 1452-1466.
36. Zhu S, Tang G, Xiong L, et al. Uncertainty of slope length derived from digital elevation models of the Loess Plateau, China[J]. Journal of Mountain Science, 2014, 11: 1169-1181.
37. Xiong L Y, Tang G A, Li F Y, et al. Modeling the evolution of loess-covered landforms in the Loess Plateau of China using a DEM of underground bedrock surface[J]. Geomorphology, 2014, 209: 18-26.
38. Xiong L, Tang G, Yan S, et al. Landform‐oriented flow‐routing algorithm for the dual‐structure loess terrain based on digital elevation models[J]. Hydrological Processes, 2014, 28(4): 1756-1766.
39. Xiong L Y, Tang G A, Yuan B Y, et al. Geomorphological inheritance for loess landform evolution in a severe soil erosion region of Loess Plateau of China based on digital elevation models[J]. Science China Earth Sciences, 2014, 57: 1944-1952.
40. Yan S, Tang G, Li F, et al. Snake model for the extraction of loess shoulder-line from DEMs[J]. Journal of Mountain Science, 2014, 11: 1552-1559.
41. Song X, Tang G, Li F, et al. Extraction of loess shoulder-line based on the parallel GVF snake model in the loess hilly area of China[J]. Computers & Geosciences, 2013, 52: 11-20.
42. Yang J, Tang G, Cao M, et al. An intelligent method to discover transition rules for cellular automata using bee colony optimisation[J]. International Journal of Geographical Information Science, 2013, 27(10): 1849-1864.
43. Jiang L, Tang G, Liu X, et al. Parallel contributing area calculation with granularity control on massive grid terrain datasets[J]. Computers & Geosciences, 2013, 60: 70-80.
44. Xie Y, Tang G, Yan S, et al. Crater detection using the morphological characteristics of Chang'E-1 digital elevation models[J]. IEEE Geoscience and Remote Sensing Letters, 2013, 10(4): 885-889.
45.Xiong L Y, Tang G A, Li F Y, et al. Modeling the evolution of loess-covered landforms in the Loess Plateau of China using a DEM of underground bedrock surface[J]. Geomorphology, 2014, 209: 18-26.
46. Tao Y, Tang G, Strobl J. Spatial structure characteristics detecting of landform based on improved 3D Lacunarity model[J]. Chinese Geographical Science, 2012, 22: 88-96.
47.Yang X, Tang G, Xiao C, et al. The scaling method of specific catchment area from DEMs[J]. Journal of Geographical Sciences, 2011, 21: 689-704.
48. Zhou Y, Tang G, Yang X, et al. Positive and negative terrains on northern Shaanxi Loess Plateau[J]. Journal of Geographical Sciences, 2010, 20: 64-76.
49. Tang G A, Li F Y, Liu X J, et al. Research on the slope spectrum of the Loess Plateau[J]. Science in China Series E: Technological Sciences, 2008, 51(Suppl 1): 175-185.
50. Yang X, Tang G, Xiao C, et al. Terrain revised model for air temperature in mountainous area based on DEMs: A case study in Yaoxian county[J]. Journal of Geographical Sciences, 2007, 17: 399-408.
获批专利