Journal metrics

Journal metrics

  • IF value: 2.281 IF 2.281
  • IF 5-year value: 2.693 IF 5-year 2.693
  • CiteScore value: 2.43 CiteScore 2.43
  • SNIP value: 1.193 SNIP 1.193
  • SJR value: 0.965 SJR 0.965
  • IPP value: 2.31 IPP 2.31
  • h5-index value: 40 h5-index 40
  • Scimago H index value: 73 Scimago H index 73
Discussion papers | Copyright
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 18 Dec 2017

Research article | 18 Dec 2017

Review status
This discussion paper is a preprint. It is a manuscript under review for the journal Natural Hazards and Earth System Sciences (NHESS).

Land use and land cover geoinformation properties and its influence on the landslide susceptibility zonation of road network

Bruno M. Meneses, Susana Pereira, and Eusébio Reis Bruno M. Meneses et al.
  • Centre for Geographical Studies, Institute of Geography and Spatial Planning, Universidade de Lisboa, Edif. IGOT, Rua Branca Edmée Marques, Lisboa, 1600-276, Portugal

Abstract. This paper evaluates the influence of land use and land cover (LUC) geoinformation with different properties on landslide susceptibility zonation of the road network in Zêzere watershed (Portugal). The Information Value method was used to assess landslide susceptibility using two models: one including detailed LUC geoinformation (Portuguese Land Cover Map – COS) and other including more generalized LUC geoinformation (Corine Land Cover – CLC). A set of six fixed independent layers were considered as landslide predisposing factors (slope angle, slope aspect, slope curvature, slope over area ratio, soil, and lithology), while COS and CLC were used to find the differences in the landslide susceptibility zonation. A landslide inventory was used as dependent layer, including 259 shallow landslides obtained from photo-interpretation of orthophotos of 2005 and further validated in three sample areas (128 landslides). The landslide susceptibility maps were merged into road network geoinformation, and resulted in two landslide susceptibility road network maps. Models performance was evaluated with success rate curves and area under the curve. Landslide susceptibility results obtained in the two models are very good, but in comparison the model obtained with more detailed LUC geoinformation (COS) produces better results in the landslide susceptibility zonation and on the road network detection with the highest landslide susceptibility. This last map also provides more detailed information about the locals where the next landslides will probably occur with possible road network disturbances.

Bruno M. Meneses et al.
Interactive discussion
Status: final response (author comments only)
Status: final response (author comments only)
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
[Login for Authors/Editors] [Subscribe to comment alert] Printer-friendly Version - Printer-friendly version Supplement - Supplement
Bruno M. Meneses et al.
Bruno M. Meneses et al.
Total article views: 484 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
358 98 28 484 3 14
  • HTML: 358
  • PDF: 98
  • XML: 28
  • Total: 484
  • BibTeX: 3
  • EndNote: 14
Views and downloads (calculated since 18 Dec 2017)
Cumulative views and downloads (calculated since 18 Dec 2017)
Viewed (geographical distribution)
Total article views: 480 (including HTML, PDF, and XML) Thereof 477 with geography defined and 3 with unknown origin.
Country # Views %
  • 1
No saved metrics found.
No discussed metrics found.
Latest update: 18 Oct 2018
Publications Copernicus
Special issue