Quality analysis of digital terrain models by the remote sensing data: A case-study of the gully–ravine relief

A wide spectrum of the basic and applied problems solvable using spatial modeling requires a digital terrain model to embrace the entire area under examination. For instance, in hydrological modeling, the relevant terrain model is a critical factor of the quality of predictive calculations. One of the highest-usage and free-of-charge terrain models is SRTM. This article offers a comparative analysis of SRTM models of land surface with the models obtained by vectorization of topo maps with a view to modeling a gully–ravine relief. The average elevation error in the whole test region was 34 mm. In some areas, however, the elevation error made 30–65 mm, which required post-processing of the input data. The authors propose a procedure for adding the digital terrain models obtained using the remote sensing data with the cloud of ground elevations from topo maps of the areas nearby the main water courses and steep slopes. The further digital modeling is advised to carry out by statistical interpolation (kriging) in order to take into account and minimize diversity in the input data as the linear interpolation can initiate even more errors in the data.

Keywords: cartography, remote sensing, GIS, digital elevation model, SRTM, DEM, level surface, horizontal error, elevation error.
For citation:

Rybnikov P. A., Smirnov A. Yu. Quality analysis of digital terrain models by the remote sensing data: A case-study of the gully–ravine relief. MIAB. Mining Inf. Anal. Bull. 2021;(5—1):235—247. [In Russ]. DOI: 10.25018/0236_1493_2021_51_0_235.

Acknowledgements:

The article is prepared in the framework of the State Contract with the Institute of Mining, Ural Branch of the Russian Academy of Sciences, Topic No. 0328-20190005.

Issue number: 5
Year: 2021
Page number: 235-247
ISBN: 0236-1493
UDK: 528.88+551.4.03
DOI: 10.25018/0236_1493_2021_51_0_235
Article receipt date: 21.12.2020
Date of review receipt: 16.03.2021
Date of the editorial board′s decision on the article′s publishing: 10.04.2021
About authors:

Rybnikov P. A.1,2, Cand. Sci. (Geol. Mineral.), Leading Researcher at the Laboratory of Geoinformation and Digital Technologies in Subsoil Management; ribnikoff@yandex.ru
Smirnov A. Yu.1,2, Junior Researcher at the Laboratory of Geoinformation and Digital Technologies in Subsoil Management; alexsm94@gmail.com;
1 Institute of Mining, Ural Branch, Russian Academy of Sciences, Ekaterinburg, Russia;
2 Ural State Mining University, Ekaterinburg, Russia.

 

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