Data in Brief (Aug 2023)

A 5 m dataset of digital terrain model derivatives across mainland France

  • Léa Panhelleux,
  • Sébastien Rapinel,
  • Blandine Lemercier,
  • Guillaume Gayet,
  • Laurence Hubert-Moy

Journal volume & issue
Vol. 49
p. 109369

Abstract

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A dataset of three digital terrain model (DTM) derivatives was produced at 5 m spatial resolution across mainland France. This dataset includes (i) a topographic wetness index (TWI) that characterizes potential soil wetness as a function of the contributing area and local slope, (ii) a multi-scale topographic position color composite (MTPCC) that describes the position of a pixel relative to its neighborhood at three spatial scales, and (iii) a vertical distance to channel network index (VDCNI) that expresses the vertical height between the elevation of a pixel and the nearest channel. These three raster layers were derived from the French national airborne DTM at 5 m spatial resolution and the vector layer of the channel network of the national hydrological database. This unprecedented fine-scale dataset opens new insights for geomorphological analysis. It can be used for several purposes, such as environmental modeling, risk assessment, or water-resource management.

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