The DOI matches its Crossref record; 28 of the 28 references it cites were found in a registry or an index.
Landslide hazard assessment: recent trends and techniques
Open accessAbstract
Landslide hazard assessment is an important step towards landslide hazard and risk management. There are several methods of Landslide Hazard Zonation (LHZ) viz. heuristic, semi quantitative, quantitative, probabilistic and multi-criteria decision making process. However, no one method is accepted universally for effective assessment of landslide hazards. In recent years, several attempts have been made to apply different methods of LHZ and to compare results in order to find the best suited model. This paper presents the review of researches on landslide hazard mapping published in recent years. The advanced multivariate techniques are proved to be effective in spatial prediction of landslides with high degree of accuracy. Physical process based models also perform well in LHZ mapping even in the areas with poor database. Multi-criteria decision making approach also play significant role in determining relative importance of landslide causative factors in slope instability process. Remote Sensing and Geographical Information System (GIS) are powerful tools to assess landslide hazards and are being used extensively in landslide researches since last decade. Aerial photographs and high resolution satellite data are useful in detection, mapping and monitoring landslide processes. GIS based LHZ models helps not only to map and monitor landslides but also to predict future slope failures. The advancements in Geo-spatial technologies have opened the doors for detailed and accurate assessment of landslide hazards.
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
Cites
Decision making with the analytic hierarchy process
Saaty, T. L. (2008) · International Journal of Services Sciences · doi:10.1504/ijssci.2008.017590 · Cited by 10,301
Tufford (2017) · doi:10.1007/s · Cited by 2,003
Ayalew, L., & Yamagishi, H. (2005) · Geomorphology · doi:10.1016/j.geomorph.2004.06.010 · Cited by 1,913
Landslide hazard zonation: A review of principles and practice
Varnes, D. J. (1984) · Cited by 1,368
Burton, I., Kates, R. W., & White, G. F. (1978) · Cited by 1,273
Kavzoglu, T., Sahin, E. K., & Colkesen, I. (2014) · Landslides · doi:10.1007/s10346-013-0391-7 · Cited by 711
Lee, S. (2005) · International Journal of Remote Sensing · doi:10.1080/01431160412331331012 · Cited by 698
Ohlmacher, G. C., & Davis, J. C. (2003) · Engineering Geology · doi:10.1016/s0013-7952(03)00069-3 · Cited by 664
Comparing landslide inventory maps
Galli, M., Ardizzone, F., Cardinali, M., Guzzetti, F., & Reichenbach, P. (2008) · Geomorphology · doi:10.1016/j.geomorph.2006.09.023 · Cited by 580
GENERALISED LINEAR MODELLING OF SUSCEPTIBILITY TO LANDSLIDING IN THE CENTRAL APENNINES, ITALY
Atkinson, P. M., & Massari, R. (1998) · Computers & Geosciences · doi:10.1016/s0098-3004(97)00117-9 · Cited by 548
Cited by
A review of statistically-based landslide susceptibility models
Reichenbach, P., Rossi, M., Malamud, B. D., Mihir, M., & Guzzetti, F. (2018) · Earth-Science Reviews · doi:10.1016/j.earscirev.2018.03.001 · Cited by 2,347
Alvioli, M., Marchesini, I., Reichenbach, P., Rossi, M., Ardizzone, F., Fiorucci, F., & Guzzetti, F. (2016) · Geoscientific Model Development · doi:10.5194/gmd-9-3975-2016 · Cited by 355
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
Landslide susceptibility evaluation and hazard zonation techniques – a review
Shano, L., Raghuvanshi, T. K., & Meten, M. (2020) · Geoenvironmental Disasters · doi:10.1186/s40677-020-00152-0 · Cited by 344
Metadata
- Authors
- Pardeshi, S. D., Autade, S. E., & Pardeshi, S. S.
- Venue
- SpringerPlus
- Published
- 2013-10-17
- Volume
- 2
- Issue
- 1
- Pages
- 523-523
- ISSN
- 2193-1801 (ISSN-L)
- OpenAlex
- W2116864993
- Cited by
- 301
- References
- 28
- FWCI
- 24.52
- Type
- journal article
- Language
- en
- Open access
- diamond
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
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Landslide hazard assessment: recent trends and techniques. https://app.cochat.ai/papers/10.1186/2193-1801-2-523
- The paper
- Pardeshi, S. D., Autade, S. E., & Pardeshi, S. S. (2013). Landslide hazard assessment: recent trends and techniques. SpringerPlus. https://doi.org/10.1186/2193-1801-2-523
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.