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INTERPRETING RESULTS OF A GIS-BASED LANDSLIDE SUSCEPTIBILITY ASSESSMENT USING GEOTECHNICAL INVESTIGATIONS FOR A ROAD SECTOR IN NORTH-WESTERN ROMANIA

Ioan-Aurel Irimus

First published: 2014-06-20https://doi.org/10.5593/sgem2014/b23/s11.088View metrics

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Title
INTERPRETING RESULTS OF A GIS-BASED LANDSLIDE SUSCEPTIBILITY ASSESSMENT USING GEOTECHNICAL INVESTIGATIONS FOR A ROAD SECTOR IN NORTH-WESTERN ROMANIA
Authors
Ioan-Aurel Irimus
Proceedings
14th International Multidisciplinary Scientific GeoConference SGEM 2014, Geoinformatics, Remote Sensing, and Artificial Intelligence, Vol. 14, Book 2, Volume 3
Publisher
Stef92 Technology
Year
2014
Pages
Not available yet
ISSN
1314-2704
ISBN
Not available yet
Language
en
Publication type
Conference Paper
Proceedings volume
14th International Multidisciplinary Scientific GeoConference SGEM 2014, Geoinformatics, Remote Sensing, and Artificial Intelligence, Vol. 14, Book 2, Volume 3 · Issue Book 2, Volume 3
References15
  1. Ayalew L. & Yamagishi H. The application of GIS-based logistic regression for landslide susceptibility mapping in the Kakuda-Yahiko Mountains, Central Japan, Geomorphology, vol. 65, pp 15 –31, 2005.

  2. Bishop A.W. The use of the slip circle in the stability analysis of slope, Geotechnique, UK , vol.5/1, pp 7-17, 1955.

  3. Brenning A. Spatial prediction models for landslide hazards: review, comparison and evaluation, Nat. Hazards Earth Syst. Sci., vol.5/6, pp 853-862, 2005.

  4. Carrara A. & Cardinali M. & Guzzetti F. & Reichenbach P. GIS technology in mapping landslide hazard, Geographical Information Systems in Assessing Natural Hazards, Edited by A. Carrara & F. Guzzetti, Holland, pp 135–175, 1995.

  5. Chung C.-J.F. & Fabbri A.G. Probalistic prediction models for landslide hazard mapping, Photogrammetric Engineering and Remote Sensing, vol. 65/12, pp 1389-1399, 1999.

  6. Chung C.-J.F. & Fabbri A.G. Predicting landslides for risk analysis – Spatial models tested by a cross-validation technique, Geomorphology, vol. 94, pp 438-452, 2008.

  7. Crozier M.J. & Glade T. Landslide Hazard and Risk: Issues, Concepts and Approach, Landslide Hazard and Risk, Edited by Th. Glade & M. Anderson & M J. Crozier, John Wiley & Sons, pp 1-38, 2005.

  8. Gelman A. & Hill J. Data analysis using regression and multilevel/hierarchical models, Cambridge University Press, New York, 2007.

  9. Guzzetti F. & Reichenbach P. & Ardizzone F. & Cardinali M. & Galli M. Estimating the quality of landslide susceptibility models, Geomorphology, vol. 81, pp 166–184, 2007 .

  10. Hilbe J. Logistic regression models, CRC Press INC, 2009.

  11. Lee S. Application of likelihood ratio and logistic regression models to landslide susceptibility mapping using GIS, Environmental management, vol.34/2, pp 223-232, 2004.

  12. Mărgărint M.C. & Grozavu A. & Patriche C.V. Assessing the spatial variability of weights of landslide causal factors in different regions from Romania using logistic regression, Nat. Hazards Earth Syst. Sci. Discussions, vol. 1, pp 1749-1774, 2013.

  13. Van Den Eeckhaut M. & Vanwalleghem T. & Poesen J. & Govers G. & Verstraeten G. & Vandekerckhove L. Prediction of landslide susceptibility using rare events logistic regression: A case-study in the Flemish Ardennes (Belgium), Geomorphology, vol. 76, pp 392-410, 2006.

  14. Van Westen C.J. & Rengers N. & Soeters R. Use of geomorphological information in indirect landslide susceptibility assessment, Natural Hazards, Holland, vol. 30, pp 399-419, 2003.

  15. GEOPROIECT Baia Mare & PROIECT BIHOR Studiul geotehnic necesar proiectului nr. 2800-2013 “Reabilitare traseu de drum judeţean Baia Sprie (DN18) – Cavnic (DJ 184) - Ocna Șugatag (DJ 109F) - Călineşti (DJ185) – Bârsana (DJ185)” , Romania, 2013.

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