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Discussion papers | Copyright
https://doi.org/10.5194/nhess-2018-88
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 09 Apr 2018

Research article | 09 Apr 2018

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

Effective surveyed area and its role in statistical landslide susceptibility assessments

Txomin Bornaetxea1, Mauro Rossi2, Ivan Marchesini2, and Massimiliano Alvioli2 Txomin Bornaetxea et al.
  • 1Department of Geography, Prehistory and Archaeology, Faculty of Arts of the University of the Basque Country UPV/EHU. c/ Tomás y Valiente, s/n, 01006, Vitoria-Gasteiz
  • 2Consiglio Nazionale delle Ricerche, Istituto di Ricerca per la Protezione Idrogeologica, via Madonna Alta 126, 06128 Perugia, Italy

Abstract. Geomorphological field mapping is a conventional method to prepare landslide inventories. The approach is typically hampered by the accessibility and visibility, during field campaigns for landslide mapping, of the different portions of the study area. Statistical significance of landlside susceptibility maps can be significantly reduced if the classification algorithm is trained in unsurveyed regions of the study area, for which landslide absence is tipically assumed, while ingnorance about landslide presence should actually be aknowledged. We compare different landslide susceptibility zonations obtained by training the classification model either in the entire study area or in the only portion of the area that was actually surveyed, which we name effective surveyed area. The latter was delineated by an automatic procedure specifically devised for the purpose, which uses information gathered during surveys, along with landslide locations. The method was tested in Gipuzkoa Province (Basque Country), North of the Iberian Peninsula, where digital thematic maps were available and a landslide survey was performed. We prepared the landslide susceptibility maps and the associated uncertainty within a logistic regression model, using both slope units and regular grid cells as reference mapping unit. Results indicate that the use of effective surveyed area for landslide susceptibility zonation is a valid approach to minimize the limitations stemming from unsurveyed regions at landslide mapping time. Use of slope units as mapping units, instead of grid cells, mitigates the uncertainties introduced by training the automatic classifier within the entire study area. Our method pertains to data preparation and, as such, the relevance of our conclusions is not limited to the logistic regression but are valid for virtually all the existing multivariate landslide susceptibility models.

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Txomin Bornaetxea et al.
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Short summary
Trying to perform a landslide susceptibility map using a field-work-based landslide inventory and a Logistic Regression model, two crucial questions came to our minds: (i) Shall we consider unsurveyed regions of the study area, for which landslide absence is typically assumed? and (ii) Which reference mapping unit should be used in our model? So, we compared four maps and found that rejecting unsurveyed regions together with slope units as reference mapping unit should be the best option.
Trying to perform a landslide susceptibility map using a field-work-based landslide inventory...
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