Authors
Affiliations
1 Hanoi University of Natural Resources and Environment; bththam@hunre.edu.vn; tththu@hunre.edu.vn
2 Vietnam Institute of Surveying and Mapping; hoaivo1976@gmai.com
*Corresponding author: bththam@hunre.edu.vn; Tel.: +84–97678581
Abstracts
This study proposes a method for normalizing the elevation of the global digital elevation model (GDEM) ALOS World 3D - 30 m (AW3D30) to Vietnam's national height system, based on national GNSS/levelling data from Ninh Bình province and surrounding areas. The correction process consists of three main steps: (1) Collecting GNSS/levelling data, global DEM data, and EGM96 geoid model data to ensure accuracy and consistency; (2) Determining correction parameters to transform AW3D30 global elevations to local heights, including analyzing differences between global and local geoid models and assessing tidal influences; (3) Verifying, correcting, and evaluating the accuracy of AW3D30 after correction to align with the national height system. Experimental results show that after correction, the root mean square error of the AW3D30 model in the national vertical datum is ±1.613 m, while the maximum deviation between AW3D30 elevations and GNSS/levelling heights is reduced from 9.014 m to 5.238 m. Approximately 91.7% of GNSS/levelling points have deviations within the acceptable range, demonstrating that the correction method significantly enhances the accuracy and applicability of AW3D30 in the national vertical datum. This method not only facilitates the normalization of AW3D30 in the study area but can also be applied to other regions in Vietnam, as well as to other GDEMs. The research findings contribute to improving the accuracy of topographic data, supporting spatial planning, resource management, disaster forecasting, and related applications.
Keywords
Cite this paper
Tham, B.T.H.; Thu, T.T.H.; Hoai, D.T. Standardization of the elevation in the AW3D30 global digital elevation model to the Vietnamese national vertical datum: An experiment in Ninh Binh province and surrounding areas. J. Hydro-Meteorol. 2025, 23, 22-35.
References
1. Điểm neoYang, L.; Meng, X.; Zhang, X. SRTM DEM and its application advances. Int. J. Remote Sens. 2011, 32, 3875–3896.
2. Hirt, C.; Marti, U.; Bürki, B.; Featherstone, W.E. Assessment of EGM2008 in Europe using accurate astrogeodetic vertical deflections and omission error estimates from SRTM/DTM2006.0 residual terrain model data. J. Geophys. Res. 2010, 115, B10404.
3. Józsa, E.; Fábián, S.A.; Kovács, M. An evaluation of EU–DEM in comparison with ASTER GDEM, SRTM and contour-based DEMs over the Eastern Mecsek Mountains. Hung. Geogr. Bull. 2014, 63, 401–423.
4. Akbari, A.; Abu, S.A.; Othman, F. Integration of SRTM and TRMM date into the GIS–based hydrological model for the purpose of flood modelling. Hydrol. Earth Syst. Sci. Discuss. 2012, 9, 4747–4775.
5. Domeneghetti, A. On the use of SRTM and altimetry data for flood modeling in data–sparse regions. Water Resour. Res. 2016, 52, 2901–2918.
6. Hancock, G.R.; Martinez, C.; Evans, K.G.; Moliere, D.R. A comparison of SRTM and high–resolution digital elevation models and their use in catchment geomorphology and hydrology: Australian examples. Earth Surf. Processes Landforms 2006, 31, 1394–1412.
7. Taramelli, A.; Melelli, L. Map of deep seated gravitational slope deformations susceptibility in central Italy derived from SRTM DEM and spectral mixing analysis of the Landsat ETM + data. Int. J. Remote Sens. 2009, 30, 357–387.
8. Triarahmadhana, B.; Heliani, L.S. An evaluation of the use of SRTM data to the accuracy of local geoid determination: A case study of Yogyakarta Region, Indonesia. Proceeding of the 12th Biennial Conference of Pan Ocean Remote Sensing Conference (PORSEC 2014). 2014.
9. Blitzkow, D.; de Matos, A.C.; Cintra, J.P. Digital terrain model evaluation and computation of the terrain correction and indirect effect in South America. Asociación Argentina de Geofísicos y Geodestas 2009, 34, 59–74.
10. Monteiro, E.S.; Fonte, C.C.; de Lima, J.L. Improving the positional accuracy of drainage networks extracted from global digital elevation models using OpenStreetMap data. J. Hydrol. Hydromech. 2018, 66, 285–294.
11. Ibrahim, M.; Al-Mashaqbah, A.; Koch, B.; Datta, P. An evaluation of available digital elevation models (DEMs) for geomorphological feature analysis. Environ. Earth Sci. 2020, 79, 336.
12. Oliveira, P.T.S.; Rodrigues, D.B.B.; Sobrinho, T.A.; Panachuki, E.; Wendland, E. Use of SRTM data to calculate the (R)USLE topographic factor. Acta Scientiarum Technol. 2013, 35, 507–513.
13. Xu, K.; Fang, J.; Fang, Y.; Sun, Q.; Wu, C.; Liu, M. The importance of digital elevation model selection in flood simulation and a proposed method to reduce DEM errors: a case study in Shanghai. Int. J. Disaster Risk Sci. 2021, 12, 890–902.
14. Khattab, M.I.; Abotalib, A.Z.; Othman, A.; Selim, M.K. Evaluation of multiple digital elevation models for hypsometric analysis in the watersheds affected by the opening of the Red Sea the Egyptian. J. Remote Sens. Space Sci. 2023, 26, 1020–1035.
15. Okolie, C.J.; Mills, J.P.; Adeleke, A.K.; Smit, J.L.; Peppa, M.V.; Altunel, A.O.; Arungwa, I.D. Assessment of the global Copernicus, NASADEM, ASTER and AW3D digital elevation models in Central and Southern Africa. Geo-Spatial Inf. Sci. 2024, 27, 1362–1390.
16. Uuemaa, E.; Ahi, S.; Montibeller, B.; Muru, M.; Kmoch, A. Vertical accuracy of freely available global digital elevation models (ASTER, AW3D30, MERIT, TanDEM–X, SRTM, and NASADEM). Remote Sens. 2020, 12, 3482.
17. Rodriguez, E.; Morris, C.S.; Belz, J.E.; Chapin, E.C.; Martin, J.M.; Daffer, W.; et al. An assessment of the SRTM topographic products, Technical Report JPL D–31639. Pasadena, California: Jet Propulsion Laboratory. 2005.
18. Bettiol, G.M.; Ferreira, M.E.; Motta, L.P.; Cremon, É.H.; Sano, E.E. Conformity of the NASADEM_HGT and ALOS AW3D30 dem with the altitude from the brazilian geodetic reference stations: A case study from Brazilian Cerrado. Sensors 2021, 21, 2935.
19. Chen, X.; Zhang, Q.; Cheng, C.; Zhou, X.; Yu, X. Accuracy assessment of SRTM DEM, ASTER GDEM, AW3D30 DSM, and TanDEM–X 90 m DEM based on runway elevation data. Proceeding of the 2022 2nd International Conference on Big Data, Artificial Intelligence and Risk Management (ICBAR). IEEE. 2022.
20. Bayburt, S.; Kurtak, A.; Büyüksalih, G.; Jacobsen, K. Geometric accuracy analysis of WorldDEM in relation to AW3D30, SRTM and ASTER GDEM2. The International Archives of the Photogrammetry. Remote Sens. Spatial Inf. Sci. 2017, 42, 211–217.
21. Apeh, O.; Uzodinma, V.; Ebinne, E.; Moka, E.; Onah, E. Accuracy assessment of ALOS W3d30, ASTER GDEM and SRTM30 DEM: A case study of Nigeria, West Africa. J. Geogr. Inf. Syst. 2019, 11, 111.
22. Güvenç, M. Comparative evaluation of verticalaccuracy of ground control pointsfrom ASTER–DEM SRTM–DEM with respectto ALOS–DEM. Hasan Kalyoncu Üniversitesi. 2020.
23. del Rosario, G.M.M.; Viveen, W.; Vidal-Villalobos, R.A.; Villegas-Lanza, J.C. A performance comparison of SRTM v. 3.0, AW3D30, ASTER GDEM3, Copernicus and TanDEM–X for tectonogeomorphic analysis in the south American Andes. Catena 2023, 228, 107160.
24. Hnila, P.; Elicker, J. Quality assessment of digital elevation models in a Treeless high–mountainous landscape: A case study from Mount Aragats, Armenia. Magazen 2021, 2, 71–102.
25. Zhao, S.; Cheng, W.; Zhou, C.; Chen, X.; Zhang, S.; Zhou, Z.; et al. Accuracy assessment of the ASTER GDEM and SRTM3 DEM: an example in the Loess Plateau and North China Plain of China. Int. J. Remote Sens. 2011, 32, 8081–8093.
26. Yao, J.; Chao-lu, Y.; Ping, F. Evaluation of the accuracy of SRTM3 and ASTER GDEM in the Tibetan Plateau Mountain Ranges. E3S Web Conf. 2020, 206, 01027.
27. Mukherjee, S.; Joshi, P.K.; Mukherjee, S.; Ghosh, A.; Garg, R.D.; Mukhopadhyay, A. Evaluation of vertical accuracy of open source Digital Elevation Model (DEM). Int. J. Appl. Earth Obs. Geoinf. 2013, 21, 205–217.
28. Tachikawa, T.; Kaku, M.; Iwasaki, A.; Gesch, D.B.; Oimoen, M.J.; Zhang, Z.; et al. ASTER global digital elevation model version 2–summary of validation results. NASA. 2011.
29. Hirt, C.; Filmer, M.S.; Featherstone, W.E. Comparison and validation of the recent freely available ASTER–GDEM ver1, SRTM ver4.1 and GEODATA DEM–9s Ver3 digital elevation models over Australia. Aust. J. Earth Sci. 2010, 57, 337–347.
30. Farr, T.G.; Rosen, P.A.; Caro, E.; Crippen, R.; Duren, R.; Hensley, S.; et al. The shuttle radar topography mission. Rev. Geophys. 2007, 45, RG2004.
31. Tham, B.T.H.; Thanh, T.P. Correction of global elevation data SRTM to the national elevation system in the territory of Vietnam. Aust. J. Earth Sci. 2025, 1–10.
32. Smith, B.; Sandwell, D. Accuracy and resolution of shuttle radar topography mission data. Geophys. Res. Lett. 2003, 30(9), 1467.
33. Rodriguez, E.; Morris, C.S.; Belz, J.E. A global assessment of the SRTM performance. Photogramm. Eng. Remote Sens. 2006, 72, 249–260.
34. Gesch, D.; Oimoen, M.; Greenlee, S.; Nelson, C.; Steuck, M.; Tyler, D. The national elevation dataset. Photogramm. Eng. Remote Sens. 2002, 68, 5–32.
35. Höhle, J.; Höhle, M. Accuracy assessment of digital elevation models by means of robust statistical methods. ISPRS J. Photogramm. Remote Sens. 2009, 64, 398–406.
36. Arun, P.V. A comparative analysis of different DEM interpolation methods. Egypt. J. Remote Sens. Space. Sci. 2013, 16, 133–139.
37. Liu, X. Accuracy assessment of LiDAR elevation data using survey marks. Surv. Rev. 2011, 43, 80–93.
38. Sithole, G.; Vosselman, G. Experimental comparison of filter algorithms for bare–Earth extraction from airborne laser scanning point clouds. ISPRS J. Photogramm. Remote Sens. 2004, 59, 85–101.
39. Zhang, K.; Whitman, D. Comparison of three algorithms for filtering airborne lidar data. Photogramm. Eng. Remote Sens. 2005, 71, 313–324.
40. Hengl, T.; Heuvelink, G.B.; Stein, A. A generic framework for spatial prediction of soil variables based on regression-kriging. Geoderma 2004, 120, 75–93.
41. Gopal, S. Artificial neural networks for spatial data analysis. NCGIA Core Curriculum in GIScience. 1998.
42. Goovaerts, P. Geostatistics for natural resources evaluation. Oxford University Press. 1997.
43. Lloyd, C.D.; Atkinson, P.M. Deriving ground surface digital elevation models from LiDAR data with geostatistics. Int. J. Geogr. Inf. Sci. 2006, 20, 535–563.
44. Webster, R.; Oliver, M.A. Geostatistics for environmental scientists. John Wiley & Sons. 2007.
45. Hengl, T.; Heuvelink, G.B.; Rossiter, D.G. About regression-kriging: From equations to case studies. Comput. Geosci. 2007, 33, 1301–1315.
46. Oliver, M.A.; Webster, R. A tutorial guide to geostatistics: Computing and modelling variograms and kriging. Catena 2014, 113, 56–69.
47. Thanh, N.T.; Bac, N.X.; Huan, H.D.; Chuong, N.T.; Hoa, N.T.Q. Accuracy assesment of shuttle radar topography mission SRTM in whole area of Vietnam. Proceedings of the Fundamental Research in "Earth and Environmental Sciences". 2019, pp. 222–225.
48. Hoa, H.M.; Thuy, D.X. Estimation of ability of using of global digital terrain model with high resolution 1" x 1" for calculation of terrain corrections in mountainous regions of Vietnam. J. Geod. Cartogr. 2017, 33, 1–10.
49. Tham, B.T.H. Assessment of the Accuracy of the global digital elevation model SRTM in Vietnam. GIS 2015 Conference. 2015, pp. 639–643.
50. Thach, L.T.; Hoan, P.X. Assessment of the global digital model based on Vietnam digital elevation model. J. Geod. Cartogr. 2021, 1–7.
51. Tadono, T.; Nagai, H.; Ishida, H.; Oda, F.; Naito, S.; Minakawa, K.; et al. Generation of the 30 M–mesh global digital surface model by ALOS PRISM. Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci. 2016, 41, 157–162.
52. Takaku, J.; Tadono, T.; Tsutsui, K.; Ichikawa, M. Validation of "AW3D" global DSM generated from Alos Prism. ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci. 2016, 3, 25–31.
53. Yamazaki, D.; Ikeshima, D.; Tawatari, R.; Yamaguchi, T.; O'Loughlin, F.; Neal, J.C.; et al. A high‐accuracy map of global terrain elevations. Geophys. Res. Lett. 2017, 44, 5844–5853.
54. Ekman, M. Impacts of geodynamic phenomena on systems for height and gravity. Bull. Géodésique 1989, 63, 281–296.
55. Ghilani, C.D.; Wolf, P.R. Adjustment computations: Spatial data analysis. John Wiley & Sons, Inc, Hoboken, New Jersey. 2006.