Global Landform classification

Global Landform classification
Resource Type: 
Datasets
Soil Projects Data
Registration is requested: 
Yes
Publisher: 
European Commission - DG JRC
Year: 
2026
Projects: 
Completed Projects
Completed Projects›Landform Classification

Data

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  • The landform classification following Meybeck et al. (2001) presents relief classes, which are calculated based on the relief roughness. Roughness and elevation are classified based on a DEM according to static thresholds, with a given window size ( e.g. 20 in the dataset shown). This is an example of a static (in terms of thresholds) landform classification method.
  • The landform classification following Iwahashi and Pike (2007) present relief classes which are classified using an unsupervised nested-means algorithms and a three part geometric signature. Slope gradient, surface texture and local convexity are calculated based on the SRTM30 DEM, within a given window size (e.g. 10 in the dataset shown) and classified according to the inherent data set properties. This is an example for a dynamic (in terms of thresholds) landform classification method.

Information about the data in the section: Landform classification

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Notification:

  1. The data have been prepared for use by the EU Soil Observatory in the Joint Research Centre (JRC) of the European Commission.
  2. The data were developed for research purposes of the JRC (European Commission). The JRC does not accept any liability whatsoever for any error, missing data or omission in the data, or for any loss or damage arising from its use. The JRC agrees to provide the data free of charge but is not bound to justify the content and values contained in the databases.
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Reference of source (Citations) :

  1. Meybeck, M., P. Green and C. J. Vorosmarty (2001), A New Typology for Mountains and Other Relief Classes: An Application to Global Continental Water Resources and Population Distribution, Mount. Res. Dev., 21, 34 - 45.
  2. Iwahashi, J. and R. J. Pike (2007). "Automated classifications of topography from DEMs by an unsupervised nested-means algorithm and a three-part geometric signature." Geomorphology 86(3-4): 409-440.

 

When making reference to the ESDAC

  • Panagos, P., Van Liedekerke, M., Borrelli, P., Köninger, J., Ballabio, C., Orgiazzi, A., Lugato, E., Liakos, L., Hervas, J., Jones, A.  Montanarella, L. 2022. European Soil Data Centre 2.0: Soil data and knowledge in support of the EU policies. European Journal of Soil Science, 73(6), e13315. DOI: 10.1111/ejss.13315
  • Panagos P., Van Liedekerke M., Jones A., Montanarella L., “European Soil Data Centre: Response to European policy support and public data requirements”; (2012) Land Use Policy, 29 (2), pp. 329-338. doi:10.1016/j.landusepol.2011.07.003
  • European Soil Data Centre (ESDAC), esdac.jrc.ec.europa.eu, European Commission, Joint Research Centre