| Issue |
MATEC Web Conf.
Volume 149, 2018
2nd International Congress on Materials & Structural Stability (CMSS-2017)
|
|
|---|---|---|
| Article Number | 02082 | |
| Number of page(s) | 7 | |
| Section | Session 2 : Structures & Stability | |
| DOI | https://doi.org/10.1051/matecconf/201814902082 | |
| Published online | 14 February 2018 | |
Application Of Logistic Regression Method To Produce Landslide Susceptibility Map: A Case Study Of Tetouan Mazari, Morocco
University Mohamed V, Faculty of Science, Research Unit GeoRisk: Geological Risks, Remote Sensing and sustainable development, LGRN Ibn Battouta Avenue. Zip code 1014, Rabat – Agdal, Morocco.
The main purpose of this study is to use logistic regression (RL) model to map landslide susceptibility in and around the area of Tetouan Mazari in the Northern Morocco. Parameters, such as lithology, slope gradient, slope aspect, faults, drainage lines, and hillshade, were considered. Landslide susceptibility map was produced using RL method and then compared and validated. Before the modeling and validation, the observed landslides were separated into two groups. The first group was for training, and the other group was for validation steps. The accuracy of the model was measured by fitting them to a validation set of observed landslides. For validation process, the half landslides remaining was used. The final map was classified into five classes: Very High (32%), High (40%), Medium (7%), Low (7%) and Nil (15%). According to these values logistic regression was determined to be one of the most accurate method to generate landslide susceptibility map. Last but not least, logistic regression model can be used to manage and mitigate hazards related to landslides and to aid in land-use planning for the city of Tetouan‥
© The Authors, published by EDP Sciences, 2018
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (http://creativecommons.org/licenses/by/4.0/).
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.