Volume 43 Issue 5
May  2018
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CHEN Chuanfa, YAN Changqing, LIU Fengying, ZHAO Na, LIU Guolin. A Total Error-Based Interpolation Method for DEM Generation[J]. Geomatics and Information Science of Wuhan University, 2018, 43(5): 739-744. DOI: 10.13203/j.whugis20150695
Citation: CHEN Chuanfa, YAN Changqing, LIU Fengying, ZHAO Na, LIU Guolin. A Total Error-Based Interpolation Method for DEM Generation[J]. Geomatics and Information Science of Wuhan University, 2018, 43(5): 739-744. DOI: 10.13203/j.whugis20150695
shu

A Total Error-Based Interpolation Method for DEM Generation

  • 1.

    State Key Laboratory of Mining Disaster Prevention and Control Co-founded by Shandong Province and the Ministry of Science and Technology, Shandong University of Science and Technology, Qingdao 266590, China

  • 2.

    Key Laboratory of Geomatics and Digital Technology of Shandong Province, Shandong University of Science and Technology, Qingdao 266590, China

  • 3.

    Department of Information Engineering, Shandong University of Science and Technology, Tai'an 271019, China

  • 4.

    State Key Laboratory of Resources and Environment Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China

Funds: 

The National Natural Science Foundation of China 41371367

The National Natural Science Foundation of China 41101433

SDUST Research Fund 

Joint Innovative Center for Safe and Effective Mining Technology and Equipment of Coal Resources of Shandong Province 

Special Project Fund of Taishan Scholars of Shandong Province 

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  • Author Bio:

    CHEN Chuanfa, PhD, professor. E-mail: chencf@lreis.ac.cn

  • Received Date: May 09, 2016
  • Published Date: May 04, 2018
    Graphical Abstract
    • Abstract
  • Motivated by the idea of total least squared method, a total error-based multiquadric method (MQ-T) has been developed to decrease the effect of both horizontal and vertical errors inherent in sample points on surface modeling. Two examples including a numerical test and a real-world example were, respectively, employed to test the robustness of MQ-T to sample errors. The numerical test indicates that when sample points are only subject to vertical errors, MQ-T has a similar performance to MQ. When sample points are subject to horizontal errors, MQ-T is more accurate than MQ. In the real-world example, MQ-T was used to construct DEMs with sample points collected by a total station instrument, and its accuracy was compared with those of classical interpolation methods including inverse distance weighting, ordinary Kriging (Kriging) and ANUDEM. Results indicate that with the decrease of sample density, the interpolation accuracies of all methods become lower. Regardless of sample density, MQ-T is always more accurate than the other methods. Yet, compared with Kriging, MQ-T has a peak-cutting problem.
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    • References (23)
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