The performance of the maximum entropy algorithm and geographic information system in shallow landslide susceptibility assessment

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RAJABZADEH FAEZEH; Ghiasi Seid Saeed; RAHMATI OMID

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Journal: JOURNAL OF WATER AND SOIL RESOURCES CONSERVATION Year:2019 | Volume:8 | Issue:2 Page(s): 57-73

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Title

The performance of the maximum entropy algorithm and geographic information system in shallow landslide susceptibility assessment

Author(s)

RAJABZADEH FAEZEH | Ghiasi Seid Saeed | RAHMATI OMID | Issue Writer Certificate

Keywords

PredictionQ1

Response CurveQ1

ROC CurveQ1

Shallow landslideQ1

SusceptibilityQ1

Abstract

Shallow landslide is one of the natural hazards that damage life and property of people in mountainous watershed. Due to the fact that a lot of landslides events have been occurred in this watershed, assessment the risk of Shallow landslides by using appropriate methods and determine of effective factors in reduce the hazards is so effective. The potential of using maximum entropy modeling for landslide Susceptibility mapping is investigated. In the case study west of Ardabil province, 74 landslide occurrences were identified, 52 landslides (70%) used for training and the 22 landslides (30%) applied for validation purpose. environmental factors including continuous (altitude, slope, aspect, plan curvature, drainage density, and rainfall) and categorical (lithology and landuse) data were used as inputs for modeling. From the optimal setting test based on crossvalidation, a continuous data and its combination with categorical data showed the best predictive performance. The results of validation showed that the ROC and AUC for success and Prediction rate of model was 96. 1 and 97. 6%, respectively. Factor contribution analysis indicated that altitude and rainfall layers were the most influential factors. From interpretations on a Response Curve, steeply sloping areas that consisted of excessively covered with old alluvial terrace soils were very susceptible to landslides. Predictive performance of maximum entropy modeling was slightly better than that other models like of a logistic regression which has been used widely to assess landslide Susceptibility. ROC for this model is 0. 961 and for logistic regression AUC is 0. 572 in different investigation at this region. Therefore, Maximum entropy modeling is shown to be an effective Prediction model for landslide Susceptibility mapping.

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APA: Copy

RAJABZADEH, FAEZEH, Ghiasi, Seid Saeed, & RAHMATI, OMID. (2019). The performance of the maximum entropy algorithm and geographic information system in shallow landslide susceptibility assessment. JOURNAL OF WATER AND SOIL RESOURCES CONSERVATION, 8(2 ), 57-73. SID. https://sid.ir/paper/232164/en

Vancouver: Copy

RAJABZADEH FAEZEH, Ghiasi Seid Saeed, RAHMATI OMID. The performance of the maximum entropy algorithm and geographic information system in shallow landslide susceptibility assessment. JOURNAL OF WATER AND SOIL RESOURCES CONSERVATION[Internet]. 2019;8(2 ):57-73. Available from: https://sid.ir/paper/232164/en

IEEE: Copy

FAEZEH RAJABZADEH, Seid Saeed Ghiasi, and OMID RAHMATI, “The performance of the maximum entropy algorithm and geographic information system in shallow landslide susceptibility assessment,” JOURNAL OF WATER AND SOIL RESOURCES CONSERVATION, vol. 8, no. 2 , pp. 57–73, 2019, [Online]. Available: https://sid.ir/paper/232164/en

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