Journal cover Journal topic
Earth Surface Dynamics An interactive open-access journal of the European Geosciences Union
Journal topic

Journal metrics

Journal metrics

  • IF value: 3.928 IF 3.928
  • IF 5-year value: 3.864 IF 5-year
    3.864
  • CiteScore value: 6.2 CiteScore
    6.2
  • SNIP value: 1.469 SNIP 1.469
  • IPP value: 4.21 IPP 4.21
  • SJR value: 1.666 SJR 1.666
  • Scimago H <br class='hide-on-tablet hide-on-mobile'>index value: 21 Scimago H
    index 21
  • h5-index value: 23 h5-index 23
Volume 3, issue 4
Earth Surf. Dynam., 3, 587–598, 2015
https://doi.org/10.5194/esurf-3-587-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.

Special issue: Frontiers in geomorphometry

Earth Surf. Dynam., 3, 587–598, 2015
https://doi.org/10.5194/esurf-3-587-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.

Review article 16 Dec 2015

Review article | 16 Dec 2015

Perspective – synthetic DEMs: A vital underpinning for the quantitative future of landform analysis?

J. K. Hillier1, G. Sofia2, and S. J. Conway3,a J. K. Hillier et al.
  • 1Dept. Geography, Loughborough University, Loughborough, LE11 3TU, UK
  • 2Dept. Land, Environment, Agriculture and Forestry, University of Padova, Agripolis, viale dell'Università 16, 35020 Legnaro (PD), Italy
  • 3Dept. Physical Sciences, The Open University, Milton Keynes, MK7 6AA, UK
  • anow at: Laboratoire de Planétologie et Géodynamique de Nantes, Université de Nantes, 2 rue de la Houssinière, Nantes, 44300 CEDEX 3, France

Abstract. Physical processes, including anthropogenic feedbacks, sculpt planetary surfaces (e.g. Earth's). A fundamental tenet of geomorphology is that the shapes created, when combined with other measurements, can be used to understand those processes. Artificial or synthetic digital elevation models (DEMs) might be vital in progressing further with this endeavour in two ways. First, synthetic DEMs can be built (e.g. by directly using governing equations) to encapsulate the processes, making predictions from theory. A second, arguably underutilised, role is to perform checks on accuracy and robustness that we dub "synthetic tests". Specifically, synthetic DEMs can contain a priori known, idealised morphologies that numerical landscape evolution models, DEM-analysis algorithms, and even manual mapping can be assessed against. Some such tests, for instance examining inaccuracies caused by noise, are moderately commonly employed, whilst others are much less so. Derived morphological properties, including metrics and mapping (manual and automated), are required to establish whether or not conceptual models represent reality well, but at present their quality is typically weakly constrained (e.g. by mapper inter-comparison). Relatively rare examples illustrate how synthetic tests can make strong "absolute" statements about landform detection and quantification; for example, 84 % of valley heads in the real landscape are identified correctly. From our perspective, it is vital to verify such statistics quantifying the properties of landscapes as ultimately this is the link between physics-driven models of processes and morphological observations that allows quantitative hypotheses to be tested. As such the additional rigour possible with this second usage of synthetic DEMs feeds directly into a problem central to the validity of much of geomorphology. Thus, this note introduces synthetic tests and DEMs and then outlines a typology of synthetic DEMs along with their benefits, challenges, and future potential to provide constraints and insights. The aim is to discuss how we best proceed with uncertainty-aware landscape analysis to examine physical processes.

Publications Copernicus
Download
Short summary
How good are measurements of shapes in the landscape? This is not well constrained. We suggest that "synthetic tests" using constructed digital landscapes called synthetic DEMs are a powerful and necessary tool to establish the reliability of these data (e.g. mapped sizes). Thus, the tests have a key, complementary role in determining if conceptual and physics-driven models of processes can be reconciled with morphological observations of reality. A typology of synthetic DEMs is proposed.
How good are measurements of shapes in the landscape? This is not well constrained. We suggest...
Citation