The DOI matches its Crossref record.
Geomorphological and historical data in assessing landslide hazard
Abstract
Traditionally, earth scientists assess landslide occurrence on the basis of geomorphological investigations carried out through aerial photograph interpretation and fieldwork. Conversely, local administrators primarily evaluate the impact of natural catastrophes, such as landsliding, on the basis of historical records and data. Owing to the substantial difference in the structure and spatial density of these two types of information, it is difficult to compare them directly and few investigators have attempted this. We compared landslide information derived from geomorphological mapping and historical data in a pilot area (the Staffora river basin, northern Italy). To do this we generated two multivariate statistical models where the dependent variable was either the mapped landslide deposits (geomorphological model), or the historical sites affected by landslide‐induced damage (historical model). By quantitatively comparing these two model maps, we demonstrate that the geomorphological model performs better in terms of percentage of terrain units correctly predicted as stable or unstable. The historical model underestimates landslide hazard mainly where human structures are lacking. However, it highlights slopes where landslide movements take place with a high frequency at the temporal scale of human life. Hence, the joint use of these two models may facilitate the knowledge of the overall instability conditions of a given region and the identification of the landslides that are most frequently reactivated. Copyright © 2003 John Wiley & Sons, Ltd.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cited by
Global fatal landslide occurrence from 2004 to 2016
Froude, M. J., & Petley, D. N. (2018) · Natural Hazards and Earth System Sciences · doi:10.5194/nhess-18-2161-2018 · Cited by 2,339
Ayalew, L., & Yamagishi, H. (2005) · Geomorphology · doi:10.1016/j.geomorph.2004.06.010 · Cited by 1,913
Estimating the quality of landslide susceptibility models
Guzzetti, F., Reichenbach, P., Ardizzone, F., Cardinali, M., & Galli, M. (2006) · Geomorphology · doi:10.1016/j.geomorph.2006.04.007 · Cited by 935
Yilmaz, I. (2010) · Environmental Earth Sciences · doi:10.1007/s12665-009-0394-9 · Cited by 537
Mapping landslide susceptibility using data-driven methods
Zêzere, J. L., Pereira, S., Melo, R., Oliveira, S. C., & Garcia, R. A. C. (2017) · Science of The Total Environment · doi:10.1016/j.scitotenv.2017.02.188 · Cited by 344
Metadata
- Authors
- Carrara, A., Crosta, G., & Frattini, P.
- Venue
- Earth Surface Processes and Landforms
- Publisher
- Wiley
- Published
- 2003-09-03
- Volume
- 28
- Issue
- 10
- Pages
- 1125-1142
- ISSN
- 0197-9337 (ISSN-L)
- 1096-9837
- OpenAlex
- W1996385777
- Cited by
- 194
- References
- 0
- FWCI
- 19.61
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.