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GIS-based analysis of landslides susceptibility mapping: a case study of Lushoto district, north-eastern Tanzania

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Abstract

Landslides are becoming increasingly widespread, claiming tens of thousands of fatalities, hundreds of thousands of injuries, and billions of dollars in economic losses each year. Thus, studies for geographically locating landslides, vulnerable areas have been increasingly relevant in recent decades. This research is aimed at integrating Geographical Information Systems (GIS) and Remote Sensing (RS) techniques to delineate landslides susceptibility areas of Lushoto district, Tanzania. RS assisted in providing remote datasets including; Digital Elevation Models (DEMs), Landsat 8 OLI imageries, and past spatially distributed landslides coordinate with the use of a handheld Global Position System (GPS) receiver, while various GIS analysis techniques were used in the preparation and analysis of landslides influencing factors hence, generating landslides susceptibility areas index values. However, rainfall, slope angle, elevation, soil type, lithology, proximity to roads, rivers, faults, and Normalized Difference Vegetation Index (NDVI) factors were found to have a direct influence on the occurrence of landslides in the study area. These factors were evaluated, weighted, and ranked using Analytical Hierarchy Process (AHP) technique in which a 0.086 (8.6%) Consistency Ratio (CR) was attained (highly accepted). Findings reveal that rainfall (29.97%), slopes’ angle (21.72%), elevation (15.68%), and soil types (11.77%) were found to have high influence on the occurrence of landslides, while proximity to faults (8.35%), lithology (4.94%), proximity to roads (3.41%), rivers (2.48%), and NDVI (1.69%) had very low influences, respectively. The overall results, obtained through Weighted Linear Combination (WLC) analysis techniques indicate that about 97669.65 Hectares (ha) of land are under very low levels of landslides susceptibility, which accounts for 24.03% of the total study area. Low susceptibility levels had 123105.84 ha (30.28%), moderate landslides susceptibility areas were found to have 140264.79 ha (34.50%), while high and very high susceptibility areas were found to cover about 45423.43 ha (11.17%) and 57.78 ha (0.01%), respectively. Furthermore, 81% overall model accuracy was obtained as computed from the Area Under the Curve (AUC) using Receiver Operating Characteristic (ROC) curve.

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Acknowledgements

We thank the University of Dodoma (UDOM) for providing financial support in facilitating this project.

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Authors and Affiliations

  1. Department of Geology, College of Earth Sciences and Engineering, The University of Dodoma, Dodoma, Tanzania

    Michael Makonyo

  2. Department of Geography, University of Dar es Salaam, Dar es Salaam, Tanzania

    Zahor Zahor

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  1. Michael Makonyo
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MM performed funding acquisition, collected and analysed data, as well as drafted this manuscript. ZZ guided the research procedures, reviewed, and edited the manuscript. Both authors read and approved the final manuscript

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Correspondence to Michael Makonyo.

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Makonyo, M., Zahor, Z. GIS-based analysis of landslides susceptibility mapping: a case study of Lushoto district, north-eastern Tanzania. Nat Hazards 118, 1085–1115 (2023). https://doi.org/10.1007/s11069-023-06038-2

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