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Cited by 85

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

Novel Approach for Ranking DEMs: Copernicus DEM Improves One Arc Second Open Global Topography

Bielski, Conrad, López-Vázquez, Carlos, Grohmann, Carlos H., Guth, Peter L., Hawker, Laurence, Gesch, Dean, Trevisani, Sebastiano, Herrera-Cruz, Virginia, Riazanoff, Serge, Corseaux, Axel, Reuter, Hannes I., Strobl, Peter·2024·IEEE Transactions on Geoscience and Remote Sensing
DOI 10.1109/tgrs.2024.3368015
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  • COPDEM is the most precise freely available global DEM.

    “Recent studies have demonstrated that COPDEM is the most precise freely available global DEM [31][32][33][34], motivating its use in this study.”

    From ANADEM: A Digital Terrain Model for South America (2024) · cites this paper as [31]

    The Results and Conclusion report that CopDEM ranked best among the six evaluated global 1-arc-second DEMs when compared with a reference digital surface model. The unqualified claim that it is the most precise freely available global DEM overstates the finding: FABDEM ranked best against a digital terrain model, and rankings depend on the reference and criteria used. (LLM, conf=0.90)

    Experimental — accuracy not yet measured

  • SRTM is outperformed by more recent DEMs.

    “despite the fact that it is outperformed by more recent DEMs [31].”

    From ANADEM: A Digital Terrain Model for South America (2024) · cites this paper as [31]

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Research works printed but not linked: 80

  1. 10.1029/2005rg000183 · DOI · Paper page
  2. 10.1029/99eo00050 · DOI
  3. Gesch, 2006, Special Issue Foreword: The shuttle radar topography mission—Data validation and applications, Photogrammetric Eng. Remote Sens., 72, 233
  4. 10.14358/pers.72.3.249 · DOI · Paper page
  5. 10.14358/pers.72.3.279 · DOI · Paper page
  6. 10.14358/pers.72.3.269 · DOI
  7. 10.1029/2005gl023957 · DOI · Paper page
  8. Abrams, 2010, The ASTER Global DEM, Photogrammetric Eng. Remote Sens., 76, 344
  9. 10.1109/igarss.2009.5417688 · DOI
  10. 10.5194/hess-15-2091-2011 · DOI
  11. 10.14358/pers.77.4.335 · DOI
  12. Wessel, 2016, TanDEM-X Ground Segment—DEM Products Specification Document
  13. 10.1016/j.isprsjprs.2017.08.008 · DOI
  14. 10.1016/j.rse.2018.04.043 · DOI
  15. Strobl, 2020, The new Copernicus digital elevation model, GSICS Quart., 14, 1
  16. 10.5194/isprsarchives-xli-b4-157-2016 · DOI · Paper page
  17. 10.5194/isprs-archives-xli-b4-125-2016 · DOI
  18. 10.1016/j.rse.2019.02.028 · DOI
  19. 10.1016/j.rse.2019.111509 · DOI
  20. 10.1016/j.rse.2020.111724 · DOI · Paper page
  21. 10.1111/tgis.12825 · DOI · Paper page
  22. 10.1016/j.rsase.2022.100795 · DOI
  23. 10.1016/j.catena.2023.107160 · DOI
  24. 10.1080/2150704x.2019.1602790 · DOI
  25. 10.1002/2017gl072874 · DOI · Paper page
  26. 10.1016/j.rse.2019.111319 · DOI · Paper page
  27. 10.3390/rs13183581 · DOI · Paper page
  28. 10.1088/1748-9326/ac4d4f · DOI · Paper page
  29. Guth, 2023, DEMIX 10k Tile Data Set (1.0), Zenodo
  30. Evans, 1980, An integrated system of terrain analysis and slope mapping, Zeitschrift für Geomorphologie, 274
  31. 10.1109/TGRS.2010.2053546 · DOI
  32. 10.3390/rs12061044 · DOI
  33. 10.1016/j.geomorph.2006.09.012 · DOI
  34. 10.1659/0276-4741(2001)021[0034:antfma]2.0.co;2 · DOI
  35. 10.1016/j.geomorph.2012.11.005 · DOI
  36. 10.1111/tgis.12852 · DOI
  37. Guth, 2009, Geomorphometry in MicroDEM, 33, 351, 10.1016/S0166-2481(08)00015-9 · DOI
  38. Guth, 2023, MICRODEM
  39. Guth, 2023, DEMIX 1, Zenodo
  40. 10.5194/esurf-4-343-2016 · DOI
  41. Press, 2007, Numerical recipes
  42. Guth, 2023, DEMIX GIS database (2.0), Zenodo
  43. 10.2307/2681737 · DOI
  44. 10.1080/02664763.2015.1043870 · DOI
  45. 10.2307/2279372 · DOI · Paper page
  46. 10.1080/10485252.2012.675436 · DOI
  47. López-Vázquez, 2021, Exact tables for the Friedman rank test: Case with ties, Chilean J. Statist., 12, 1
  48. López-Vázquez, 2020, Tables for the Friedman’s Test With Ties
  49. 10.1080/03610918.2014.931971 · DOI · Paper page
  50. 10.2307/2282330 · DOI
  51. 10.3233/978-1-61499-649-1-87 · DOI
  52. 10.1109/mcse.2007.55 · DOI · Paper page
  53. McKinney, 2011, Pandas: A foundational Python library for data analysis and statistics, Python High Perform. Sci. Comput., 14, 1
  54. 2021, Python Programming Language, Version 3.10.x
  55. Grohmann, The DEMIX Wine Contest Jupyter notebook
  56. 10.3389/feart.2021.758606 · DOI · Paper page
  57. 10.3133/ofr20141008 · DOI
  58. 10.3390/rs12213482 · DOI · Paper page
  59. 10.3389/feart.2018.00230 · DOI
  60. 10.1007/s12665-023-10882-7 · DOI
  61. 10.1111/tgis.12819 · DOI
  62. Wilson, 2000, Terrain Analysis: Principles and Applications
  63. Hengl, 2008, Geomorphometry: Concepts, Software, Applications, 33
  64. 10.1016/c2010-0-65718-x · DOI
  65. 10.1007/s12665-021-09910-1 · DOI
  66. 10.3390/rs14184436 · DOI
  67. 10.1785/0120060267 · DOI
  68. 10.1177/8755293020911137 · DOI
  69. 10.1016/j.geomorph.2018.03.002 · DOI
  70. 10.3389/feart.2021.752669 · DOI
  71. 10.3389/feart.2018.00225 · DOI
  72. 10.1016/j.rse.2017.12.026 · DOI
  73. 10.1038/s41467-019-12808-z · DOI · Paper page
  74. Guth, Subjective criterion for the DEMIX wine contest: Hillshade maps, 115
  75. 10.5194/gmd-8-1991-2015 · DOI
  76. 2024, System for Automated Geoscientific Analyses, Version 9.3.0
  77. 10.1002/hyp.9979 · DOI
  78. 10.1016/j.catena.2016.12.009 · DOI
  79. 10.1029/2002gl016643 · DOI
  80. 10.14358/pers.72.11.1235 · DOI

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Metadata

Authors
Bielski, C., López-Vázquez, C., Grohmann, C. H., Guth, P. L., Hawker, L., Gesch, D., Trevisani, S., Herrera-Cruz, V., Riazanoff, S., Corseaux, A., Reuter, H. I., & Strobl, P.
Affiliations
  • EOXPLORE, Oberhaching, Germany
  • LatinGEO Lab IGM+ORT, Universidad ORT Uruguay, Montevideo, Uruguay
  • Spatial Analysis And Modelling Lab/Institute of Energy and Environment (SPAMLab/IEE), Universidade de Sãoo Paulo, São Paulo, Brazil
  • Department of Ocean and Atmospheric Sciences, United States Naval Academy, Annapolis, MD, USA
  • School of Geographical Sciences, University of Bristol, Bristol, U.K
  • U.S. Geological Survey, Earth Resources Observation and Science Center, Sioux Falls, SD, USA
  • Department of Culture del Progetto, Iuav University of Venice, Venice, Italy
  • Airbus Defence and Space, Friedrichshafen, Germany
  • VisioTerra, Champs-sur-Marne, France
  • European Commission, Eurostat, Luxembourg
  • European Commission, Joint Research Center (JRC), Ispra, Italy
ORCID
Venue
IEEE Transactions on Geoscience and Remote Sensing
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Published
2024
Volume
62
Pages
1-22
ISSN
  • 0196-2892
  • 1558-0644
DOI
10.1109/tgrs.2024.3368015
Cited by
85
References
1
Licence
creativecommons.org/licenses/by/4.0/legalcode (vor)
Funders
  • Conselho Nacional de Desenvolvimento Científico e Tecnológico [National Council for Scientific and Technological Development (CNPq)] (311209/2021-1)
  • Fundação de Amparo à Pesquisa do Estado de São Paulo [São Paulo Research Foundation (FAPESP)] (2019/26568-0, 2023/11197-1)
  • Natural Environment Research Council (NERC) EVOFLOOD Project (NE/S015795/1)

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