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Remote Sensing Applications in Environmental Research pp 87–111Cite as

A Comparative Assessment Between the Application of Fuzzy Unordered Rules Induction Algorithm and J48 Decision Tree Models in Spatial Prediction of Shallow Landslides at Lang Son City, Vietnam

Part of the Society of Earth Scientists Series book series (SESS)

Abstract

The main objective of this study is to investigate potential application of the Fuzzy Unordered Rules Induction Algorithm (FURIA) and the Bagging (an ensemble technique) in comparison with Decision Tree model for spatial prediction of shallow landslides in the Lang Son city area (Vietnam). First, a landslide inventory map was constructed from various sources. Then, the landslide inventory was randomly partitioned into 70 % for training the models and 30 % for the model validation. Second, six landslide conditioning factors (slope, aspect, lithology, land use, soil type, and distance to faults) were prepared. Using these factors and the training dataset, landslide susceptibility indexes were calculated using the FURIA, the FURIA with Bagging, the Decision Tree, and the Decision Tree with Bagging. Finally, prediction performances of these susceptibility maps were carried out using the Receiver Operating Characteristic (ROC) technique. The results show that area under the ROC curve (AUC) using training dataset has the largest for the Decision Tree with Bagging (0.925) and the FURIA with Bagging (0.913), followed by the Decision Tree (0.908) and the FURIA (0.878). The prediction capability of these models was estimated using the validation dataset. The highest prediction was achieved using the FURIA with Bagging (AUC = 0.802), followed by the Decision Tree (AUC = 0.783), the Decision Tree with Bagging (AUC = 0.777), and the FURIA (AUC = 0.773). We conclude that the FURIA with Bagging is the best model in this study.

Keywords

  • GIS
  • Landslide susceptibility
  • Remote sensing
  • FURIA
  • Decision tree

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Acknowledgement

This research was supported by the Geomatics Section, Department of Mathematical Sciences and Technology, Norwegian University of Life Sciences, Norway.

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Authors and Affiliations

  1. Department of Mathematical Sciences and Technology, Norwegian University of Life Sciences, P.O. Box 5003IMT, N-1432, Aas, Norway

    Dieu Tien Bui & Inge Revhaug

  2. Faculty of Surveying and Mapping, Hanoi University of Mining and Geology, Dong Ngac, Tu Liem, Hanoi, Vietnam

    Dieu Tien Bui

  3. Faculty of Information Technology, Hanoi University of Mining and Geology, Dong Ngac, Tu Liem, Hanoi, Vietnam

    Chuyen Trung Tran

  4. Faculty of Engineering, Department of Civil Engineering, University Putra Malaysia, 43400, Serdang, Selangor Darul Ehsan, Malaysia

    Biswajeet Pradhan

Authors
  1. Dieu Tien Bui
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  2. Biswajeet Pradhan
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  3. Inge Revhaug
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  4. Chuyen Trung Tran
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Correspondence to Dieu Tien Bui .

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Editors and Affiliations

  1. Hydrological Sciences, ESSIC/NASA GSFC, Greenbelt, Maryland, USA

    Prashant K. Srivastava

  2. School of Environmental Sciences, Jawaharlal Nehru University, New Delhi, India

    Saumitra Mukherjee

  3. Civil Engineering, Indian Institute of Technology (IIT), New Delhi, India

    Manika Gupta

  4. Atmospheric Sciences, CIRA/NOAA, College Park, Maryland, USA

    Tanvir Islam

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Tien Bui, D., Pradhan, B., Revhaug, I., Trung Tran, C. (2014). A Comparative Assessment Between the Application of Fuzzy Unordered Rules Induction Algorithm and J48 Decision Tree Models in Spatial Prediction of Shallow Landslides at Lang Son City, Vietnam. In: Srivastava, P., Mukherjee, S., Gupta, M., Islam, T. (eds) Remote Sensing Applications in Environmental Research. Society of Earth Scientists Series. Springer, Cham. https://doi.org/10.1007/978-3-319-05906-8_6

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