Науковий вісник НГУ

Assessment of digital elevation models accuracy for local geoid modeling

• 
• 

User Rating:  / 0

PoorBest 

Details

Category: Content №5 2024

Last Updated on 29 October 2024

Published on 30 November -0001

Hits: 697

Authors:

A.S.Urazaliyev, orcid.org/0000-0001-7444-2897, Institute of Ionosphere, Almaty, the Republic of Kazakhstan; Satbayev University, Almaty, the Republic of Kazakhstan

D.A.Shoganbekova*, orcid.org/0000-0002-6825-4774, Institute of Ionosphere, Almaty, the Republic of Kazakhstan; International Education Corporation, Almaty, the Republic of Kazakhstan, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

Sh.Kydyrkozhakyzy, orcid.org/0009-0000-0608-8902, Institute of Ionosphere, Almaty, the Republic of Kazakhstan; International Education Corporation, Almaty, the Republic of Kazakhstan

M.S.Kozhakhmetov, orcid.org/0009-0004-9433-8674, Institute of Ionosphere, Almaty, the Republic of Kazakhstan; Satbayev University, Almaty, the Republic of Kazakhstan

Sh.K.Aitkazinova, orcid.org/0000-0002-0964-3008, Satbayev University, Almaty, the Republic of Kazakhstan

* Corresponding author e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

повний текст / full article

Naukovyi Visnyk Natsionalnoho Hirnychoho Universytetu. 2024, (5): 151 - 156

https://doi.org/10.33271/nvngu/2024-5/151

Abstract:

One of the critical factors influencing the accuracy of a local geoid model is the quality of the digital elevation model (DEM). A properly selected high-resolution DEM can significantly mitigate errors in geoid modeling, gravity anomaly processing, and topography and downward continuation correction.

Purpose. Evaluating the accuracy of five global DEMs obtained from open sources to identify the most suitable model for creating a local geoid.

Methodology. The vertical accuracy of the DEMs was assessed by comparing the heights between the DEM and control points across different types of terrain. The reference values are based on 344 ground benchmarks, where GNSS observations were performed with subsequent adjustment of coordinates and heights. The accuracy analysis involved calculating statistical indicators of the height differences between the GNSS data and the DEM data.

Findings. The standard deviation assessment showed favorable values for the COPERNICUS and ALOS DEMs, followed by SRTM, ASTER, and ETOPO. In the mean absolute error calculations for mountainous areas, the ALOS model performed best, followed by COPERNICUS, SRTM, ASTER, and ETOPO. For other types of terrain, COPERNICUS demonstrated the best results in mean absolute error.

Originality. This study distinguishes itself through the incorporation of advanced high-resolution DEMs, such as GLO30, providing a modern and thorough evaluation of DEM accuracy specifically for Kazakhstan. What is new is a detailed analysis of the impact of terrain features (plain, hilly, mountainous) on modeling accuracy. This approach advances beyond previous assessments, delivering new and significant insights into the performance of contemporary DEMs.

Practice value. The practical value of the results obtained consists in issuing recommendations regarding the possibility of using the studied DEM for the regions of Kazakhstan which differ among themselves in terms of landscape characteristics. The findings indicate that COPERNICUS and ALOS DEMs are highly suitable for precise geoid modeling in southern Kazakhstan. These models can significantly improve the accuracy of local geoid models, benefiting applications in geospatial science and engineering.

Keywords: digital terrain model, geoid, accuracy assessment, ASTER, ALOS, ETOPO, SRTM, COPERNICUS

References.

1. Jalal, S. J., Musa, T. A., Din, A. H. M., Aris, W. A. W., Shen, W., & Pa’suya, M. F. (2019). Influencing factors on the accuracy of local geoid model. Geodesy and geodynamics, 10(6), 439-445. https://doi.org/10.1016/j.geog.2019.07.003.

2. Farahani, H. H., Klees, R., & Slobbe, C. (2017). Data requirements for a 5-mm quasi-geoid in the Netherlands. Studia Geophysica et Geodaetica: a journal of geophysics, geodesy, meteorology and climatology, 61(4), 675-702. https://doi.org/10.1007/s11200-016-0171-7.

3. Uuemaa, E., Ahi, S., Montibeller, B., Muru, M., & Kmoch, A. (2020). Vertical accuracy of freely available global digital elevation models (ASTER, AW3D30, MERIT, TanDEM-X, SRTM, and NASADEM). Remote Sensing, 12(21), 3482. https://doi.org/10.3390/rs12213482.

4. Polidori, L., & El Hage, M. (2020). Digital elevation model quality assessment methods: A critical review. Remote sensing, 12(21), 3522. https://doi.org/10.3390/rs12213522.

5. Chymyrov, A. (2021). Comparison of different DEMs for hydrological studies in the mountainous areas. The Egyptian Journal of Remote Sensing and Space Science, 24(3), 587-594. https://doi.org/10.1016/j.ejrs.2021.08.001.

6. López-Vázquez, C., & Ariza-López, F. J. (2023). Global Digital Elevation Model Comparison Criteria: An Evident Need to Consider Their Application. ISPRS International Journal of Geo-Information, 12(8), 337. https://doi.org/10.3390/ijgi12080337.

7. Bielski, C., López-Vázquez, C., Grohmann, C. H., Guth, P. L., Hawker, L., Gesch, D., ..., & Strobl, P. (2024). Novel approach for ranking DEMs: Copernicus DEM improves one arc second open global topography. IEEE Transactions on Geoscience and Remote Sensing, 62, 1-22. https://doi.org/10.1109/TGRS.2024.3368015.

8. Shoganbekova, D., Fan, H., & Pentayev, T. (2015). Gravimetric geoid model over Kazakhstan. In 15 ^th International Multidisciplinary Scientific Geoconference SGEM 2015, (pp. 283-290). https://doi.org/10.5593/sgem2015/b22/s9.035.

9. Geoportal of Turkestan region (n.d.). Retrieved from https://map.iturkistan.kz/.

10. Elkhrachy, I. (2017). Feature extraction of laser scan data based on geometric properties. Journal of the Indian Society of Remote Sensing, 45, 1-10. https://doi.org/10.1007/s12524-016-0569-2.

11. Mukherjee, S., Mukhopadhyay, A., Bhardwaj, A., Mondal, A., Kundu, S., & Hazra, S. (2012). Digital elevation model generation and retrieval of terrain attributes using CARTOSAT-1 stereo data. International Journal of Science and Technology, 2(5), 265-271. ISSN 2224-3577.

12. Tadono, T., Ishida, H., Oda, F., Naito, S., Minakawa, K., & Iwamoto, H. (2014). Precise global DEM generation by ALOS PRISM. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2, 71-76. https://doi.org/10.5194/isprsannals-II-4-71-2014.

13. Tadono, T., Nagai, H., Ishida, H., Oda, F., Naito, S., Minakawa, K., & Iwamoto, H. (2016). Generation of the 30 m-mesh global digital surface model by ALOS PRISM. The international archives of the photogrammetry, remote sensing and spatial information sciences, 41, 157-162. https://doi.org/10.5194/isprs-archives-XLI-B4-157-2016.

14. Takaku, J., & Tadono, T. (2017, July). Quality updates of ‘AW3D’global DSM generated from ALOS PRISM. In 2017 IEEE international geoscience and remote sensing symposium (IGARSS),  (pp. 5666-5669). IEEE. https://doi.org/10.1109/IGARSS.2017.8128293.

15. Tachikawa, T., Hato, M., Kaku, M., & Iwasaki, A. (2011, July). Characteristics of ASTER GDEM version 2. In 2011 IEEE international geoscience and remote sensing symposium, (pp. 3657-3660). IEEE. https://doi.org/10.1109/IGARSS.2011.6050017.

16. Mukul, M., Srivastava, V., & Mukul, M. (2015). Analysis of the accuracy of shuttle radar topography mission (SRTM) height models using international global navigation satellite system service (IGS) network. Journal of Earth System Science, 124, 1343-1357. https://doi.org/10.1007/s12040-015-0597-2.

17. Yap, L., Kandé, L. H., Nouayou, R., Kamguia, J., Ngouh, N. A., & Makuate, M. B. (2019). Vertical accuracy evaluation of freely available latest high-resolution (30 m) global digital elevation models over Cameroon (Central Africa) with GPS/leveling ground control points. International Journal of Digital Earth, 12(5), 500-524. https://doi.org/10.1080/17538947.2018.1458163.

18. Mukherjee, S., Joshi, P. K., Mukherjee, S., Ghosh, A., Garg, R. D., & Mukhopadhyay, A. (2013). Evaluation of vertical accuracy of open source Digital Elevation Model (DEM). International Journal of Applied Earth Observation and Geoinformation, 21, 205-217. https://doi.org/10.1016/j.jag.2012.09.004.

19. Ghani, M. F. A., Hussin, H., Fauzi, A., & Jaya, A. (2022, June). An approach to find the potential landslide source based on intersection of lineament using SRTM DEM. In AIP Conference Proceedings, (Vol. 2454, No. 1). AIP Publishing. https://doi.org/10.1063/5.0078941.

20. Du, X., Guo, H., Fan, X., Zhu, J., Yan, Z., & Zhan, Q. (2016). Vertical accuracy assessment of freely available digital elevation models over low-lying coastal plains. International Journal of Digital Earth, 9(3), 252-271. https://doi.org/10.1080/17538947.2015.1026853.

21. Zhao, S., Cheng, W., Zhou, C., Chen, X., Zhang, S., Zhou, Z., ..., & Chai, H. (2011). Accuracy assessment of the ASTER GDEM and SRTM3 DEM: an example in the Loess Plateau and North China Plain of China. International Journal of Remote Sensing, 32(23), 8081-8093. https://doi.org/10.1080/01431161.2010.532176.

22. Hu, Z., Peng, J., Hou, Y., & Shan, J. (2017). Evaluation of recently released open global digital elevation models of Hubei, China. Remote Sensing, 9(3), 262. https://doi.org/10.3390/rs9030262.

23. Rexer, M., & Hirt, C. (2014). Comparison of free high resolution digital elevation data sets (ASTER GDEM2, SRTM v2. 1/v4. 1) and validation against accurate heights from the Australian National Gravity Database. Australian Journal of Earth Sciences, 61(2), 213-226. https://doi.org/10.1080/08120099.2014.884983.

24. Hladik, C., & Alber, M. (2012). Accuracy assessment and correction of a LIDAR-derived salt marsh digital elevation model. Remote Sensing of Environment, 121, 224-235. https://doi.org/10.1016/j.rse.2012.01.018.

25. Mispan, M. R., Rasid, M. Z. A., Rahman, N. F. A., Khalid, K., Haron, S. H., & Ahmad, N. (2015). Assessment of ASTER and SRTM derived digital elevation model for highland areas of Peninsular Malaysia region. International Research Journal of Innovations in Engineering and Technology, 2, 316-320.

26. Szabó, G., Singh, S. K., & Szabó, S. (2015). Slope angle and aspect as influencing factors on the accuracy of the SRTM and the ASTER GDEM databases. Physics and Chemistry of the Earth, Parts A/B/C, 83, 137-145. https://doi.org/10.1016/j.pce.2015.06.003.

27. Jain, A. O., Thaker, T., Chaurasia, A., Patel, P., & Singh, A. K. (2018). Vertical accuracy evaluation of SRTM-GL1, GDEM-V2, AW3D30 and CartoDEM-V3. 1 of 30-m resolution with dual frequency GNSS for lower Tapi Basin India. Geocarto International, 33(11), 1237-1256. https://doi.org/10.1080/10106049.2017.1343392.

28. Kozub, Y. I. (2018). The Digital Elevation Model Improving for the Landscape Mapping of the Republic of Dagestan. Dagestan State Pedagogical University. Journal. Natural and Exact Sciences, 12(3), 96-102.

29. Corti, G., Cioni, R., Franceschini, Z., Sani, F., Scaillet, S., Molin, P., ..., & Glerum, A. (2019). Aborted propagation of the Ethiopian rift caused by linkage with the Kenyan rift. Nature Communications, 10(1), 1309. https://doi.org/10.1038/s41467-019-09335-2.

30. Eakins, B. W., & Sharman, G. F. (2010). Volumes of the World’s Oceans from ETOPO1. NOAA National Geophysical Data Center, Boulder, CO, 7(1).

31. Ruijie, H., Xiaoyun, W., Xiaohong, S., Yongjun, J., & Xing, W. (2022). Research status and analysis of seafloor topography survey and model development. Reviews of Geophysics and Planetary Physics, 53(2), 172-186. https://doi.org/10.19975/j.dqyxx.2021-061.

32. National Centers for Environmental Information (2020). ETOPO1. https://doi.org/10.7289/V5C8276M.

33. Leister-Taylor, V., Jacob, P., Schrader, H., & Kahabka, H. (2020). Copernicus digital elevation model product handbook. Tech. Rep. GEO. 2018-1988-2. https://doi.org/10.3389/feart.2021.758606.

34. Purinton, B., & Bookhagen, B. (2021). Beyond vertical point accuracy: Assessing inter-pixel consistency in 30 m global DEMs for the arid Central Andes. Frontiers in Earth Science, 9, 758606. https://doi.org/10.3389/feart.2021.758606.

35. Huang, J., Yang, Y., Yu, Y., & Zhang, Y. (2024). Vertical accuracy of open-source remote sensing data (AW3D30, TanDEM-X, ATLAS) for understory terrain estimation. Geocarto International, 39(1), 2356855. https://doi.org/10.1080/10106049.2024.2356855.

36. Kaplan, E. D., & Hegarty, C. (Eds.) (2017). Understanding GPS/GNSS: principles and applications. Artech house. ISBN-13: 978-1-63081-058-0.

37. Baltiyeva, A., Shamganova, L., & Chernov, A. (2017). Analysis of mathematical models for solving problems of high-accuracy satellite geodesy. International Multidisciplinary Scientific GeoConference: SGEM, 17, 91-98. https://doi.org/10.5593/sgem2017/22.

38. Trevisani, S., Skrypitsyna, T. N., & Florinsky, I. V. (2023). Global digital elevation models for terrain morphology analysis in mountain environments: insights on Copernicus GLO-30 and ALOS AW3D30 for a large Alpine area. Environmental Earth Sciences, 82(9), 198. https://doi.org/10.1007/s12665-023-10882-7.

• < Prev
• Next >