Skip to main content

Advertisement

Log in

Landslide Susceptibility Mapping Using Bivariate Statistical Models and GIS in Chattagram District, Bangladesh

  • Original Paper
  • Published:
Geotechnical and Geological Engineering Aims and scope Submit manuscript

Abstract

Landslide is one of the most devastating hazards in Chattagram Dsitrict and has become a recurrent phenomenon in this region. This study attempts to produce Landslide Susceptibility Map (LSM) for Chattagram District of Bangladesh by using five GIS based bivariate statistical models, namely the Frequency Ratio (FR), Shanon’s Entropy (SE), Weight of Evidence (WofE), Information Value (IV) and Certainty Factor (CF). Landslide Inventory (2001–2017) of Chittagong Hilly Areas database was used to measure the relationship between the previous landslides with the landslide conditioning factors. SRTM DEM and Landsat satellite images were collected from USGS and the geological data were collected from GSB to produce the thematic layer of conditioning factors. Sixteen landslide conditioning factors of Slope Aspect, Slope Angle, Geology, Elevation, Plan Curvature, Profile Curvature, General Curvature, Topographic Wetness Index, Stream Power Index, Sediment Transport Index, Topographic Roughness Index, Distance to Stream, Distance to Anticline, Distance to Fault, Distance to Road and NDVI were used. The Area Under Curve (AUC) was used for validation of the LSMs. The predictive rate of AUC for FR, SE, WofE, IV and CF were 76.11%, 70.11%, 78.93%, 76.57% and 80.43% respectively. CF model indicates 15.04% of areas are highly susceptible to landslide. All the models showed that the high elevated areas are more susceptible to landslide where the low-lying river basin areas have a low probability of landslide occurrence. The findings of this research will contribute to land use planning, management and hazard mitigation of the CHT region.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

Data Availability

Data presented in the article will be available on request. https://download.geofabrik.de/. http://www.gsb.gov.bd/site/view/commondoc/Geo-scientific%20Map/-?page=3&rows=20. https://earthexplorer.usgs.gov/. https://doi.org/10.3390/data5010004

Code availability

Not Applicable

References

Download references

Acknowledgement

We are grateful to Yasin Wahid Rabby for providing the landslide inventory data.

Funding

 No funding was received for conducting this research

Author information

Authors and Affiliations

Authors

Contributions

Md. Sharafat Chowdhury analysed the data and writes up the manuscript. Bibi Hafsa writes up the manuscript and proof reading.

Corresponding author

Correspondence to Md. Sharafat Chowdhury.

Ethics declarations

Conflict of Interest

All authors declare no conflicts of interest in this paper

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Chowdhury, M., Hafsa, B. Landslide Susceptibility Mapping Using Bivariate Statistical Models and GIS in Chattagram District, Bangladesh. Geotech Geol Eng 40, 3687–3710 (2022). https://doi.org/10.1007/s10706-022-02111-y

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10706-022-02111-y

Keywords

Navigation