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| Titel |
Assessing the spatial variability of coefficients of landslide predictors in different regions of Romania using logistic regression |
| VerfasserIn |
M. C. Margarint, A. Grozavu, C. V. Patriche |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1561-8633
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| Digitales Dokument |
URL |
| Erschienen |
In: Natural Hazards and Earth System Science ; 13, no. 12 ; Nr. 13, no. 12 (2013-12-19), S.3339-3355 |
| Datensatznummer |
250085589
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| Publikation (Nr.) |
 copernicus.org/nhess-13-3339-2013.pdf |
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| Zusammenfassung |
| In landslide susceptibility assessment, an important issue is the correct
identification of significant contributing factors, which leads to the
improvement of predictions regarding this type of geomorphologic processes.
In the scientific literature, different weightings are assigned to these
factors, but contain large variations. This study aims to identify the
spatial variability and range of variation for the coefficients of landslide
predictors in different geographical conditions. Four sectors of
15 km × 15 km (225 km2) were selected for analysis from
representative regions in Romania in terms of spatial extent of landslides,
situated both on the hilly areas (the Transylvanian Plateau and Moldavian
Plateau) and lower mountain region (Subcarpathians). The following factors
were taken into consideration: elevation, slope angle, slope height, terrain
curvature (mean, plan and profile), distance from drainage network, slope
aspect, land use, and lithology. For each sector, landslide inventory,
digital elevation model and thematic layers of the mentioned predictors were
achieved and integrated in a georeferenced environment. The logistic
regression was applied separately for the four study sectors as the statistical
method for assessing terrain landsliding susceptibility. Maps of landslide
susceptibility were produced, the values of which were classified by using
the natural breaks method (Jenks). The accuracy of the logistic regression
outcomes was evaluated using the ROC (receiver operating characteristic) curve and AUC (area under the curve) parameter, which show
values between 0.852 and 0.922 for training samples, and between 0.851 and
0.940 for validation samples. The values of coefficients are generally
confined within the limits specified by the scientific literature. In each
sector, landslide susceptibility is essentially related to some specific
predictors, such as the slope angle, land use, slope height, and lithology.
The study points out that the coefficients assigned to the landslide
predictors through logistic regression are capable to reveal some important
characteristics in landslide manifestation. The study also shows that the
logistic regression could be an alternative method to the current Romanian
methodology for landslide susceptibility and hazard mapping. |
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