Using vertices of a triangular irregular network to calculate slope and aspect

被引:24
作者
Hu, Guanghui [1 ,2 ,3 ]
Wang, Chun [4 ]
Li, Sijin [1 ,2 ,3 ]
Dai, Wen [1 ,2 ,3 ]
Xiong, Liyang [1 ,2 ,3 ]
Tang, Guoan [1 ,2 ,3 ]
Strobl, Josef [1 ,5 ]
机构
[1] Nanjing Normal Univ, Sch Geog, Nanjing, Peoples R China
[2] Nanjing Normal Univ, Minist Educ, Key Lab Virtual Geog Environm, Nanjing, Peoples R China
[3] Jiangsu Ctr Collaborat Innovat Geog Informat Reso, Nanjing, Peoples R China
[4] Nanjing Univ Informat Sci & Technol, Sch Remote Sensing & Geomat Engn, Nanjing, Peoples R China
[5] Univ Salzburg, Dept Geoinformat Z GIS, Salzburg, Austria
基金
美国国家科学基金会;
关键词
Triangulated irregular network; terrain derivatives; digital elevation model; point clouds; TERRAIN ANALYSIS; SURFACE; RESOLUTION; MODELS; ACCURACY; PROGRESS; MATLAB; ERROR;
D O I
10.1080/13658816.2021.1933493
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Terrain derivative calculations from triangulated irregular network (TIN)-based digital elevation models (DEMs) have been extensively explored in geomorphometry. However, most calculation methods focus on the triangulation facets of TIN-based DEMs and ignore the vertices. In fact, these vertices are the original sampling points from the terrain surface and serve as the basis for triangulation. In this study, we argue that terrain derivative calculations using TIN-based DEMs should focus on the vertices. Employing examples with slope and aspect, we applied the TIN vertex-based method to a mathematical surface and a real topography using TIN-based DEMs with a range of sampling point densities. We performed a comparative analysis of the TIN vertex-based, TIN facet-based, and grid-based methods. Assessments on the mathematical surface showed that the TIN vertex-based method achieved the highest accuracy among the three methods. Error analysis for the real landform case indicated that the TIN vertex-based method performed slightly better than the grid-based method for slope calculation and slightly worse than the grid-based method for aspect calculation. Among the three methods, the TIN facet-based method was most sensitive to error. The TIN vertex-based method can provide a reference for the slope and aspect calculation based on point clouds.
引用
收藏
页码:383 / 405
页数:23
相关论文
共 52 条
[1]   A novel computational paradigm for creating a Triangular Irregular Network (TIN) from LiDAR data [J].
Ali, Tarig ;
Mehrabian, Ali .
NONLINEAR ANALYSIS-THEORY METHODS & APPLICATIONS, 2009, 71 (12) :E624-E629
[2]  
Alvioli M., 2020, GEOMORPHOMETRY 2020, DOI [10.30437/GEOMORPHOMETRY2020_12, DOI 10.30437/GEOMORPHOMETRY2020_12]
[3]   Terrainbento 1.0: a Python']Python package for multi-model analysis in long-term drainage basin evolution [J].
Barnhart, Katherine R. ;
Glade, Rachel C. ;
Shobe, Charles M. ;
Tucker, Gregory E. .
GEOSCIENTIFIC MODEL DEVELOPMENT, 2019, 12 (04) :1267-1297
[4]   CircStat: A MATLAB Toolbox for Circular Statistics [J].
Berens, Philipp .
JOURNAL OF STATISTICAL SOFTWARE, 2009, 31 (10) :1-21
[5]  
Chang K.-T., 2019, INTRO GEOGRAPHIC INF, P279
[6]   The simulation of surface flow dynamics using a flow-path network model [J].
Chen, Yumin ;
Zhou, Qiming ;
Li, Sheng ;
Meng, Fanrui ;
Bi, Xiaomei ;
Wilson, John P. ;
Xing, Zisheng ;
Qi, Junyu ;
Li, Qiang ;
Zhang, Chengfu .
INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE, 2014, 28 (11) :2242-2260
[7]   An Algorithm to Extract More Accurate Slopes From DEMs [J].
Chen, Zhende ;
Chen, Yonggang ;
Chen, Xiaoyin ;
Ma, Tianwu .
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, 2016, 13 (07) :939-942
[8]   Effects of DEM resolution on the accuracy of gully maps in loess hilly areas [J].
Dai, Wen ;
Yang, Xin ;
Na, Jiaming ;
Li, Jingwei ;
Brus, Dick ;
Xiong, Liyang ;
Tang, Guoan ;
Huang, Xiaoli .
CATENA, 2019, 177 :114-125
[9]   REVIEW OF GIS APPLICATIONS IN HYDROLOGIC MODELING [J].
DEVANTIER, BA ;
FELDMAN, AD .
JOURNAL OF WATER RESOURCES PLANNING AND MANAGEMENT-ASCE, 1993, 119 (02) :246-261
[10]   Geomorphometry and landform mapping: What is a landform? [J].
Evans, Ian S. .
GEOMORPHOLOGY, 2012, 137 (01) :94-106