Geographical Information Systems (GIS) and Remote Sensing (RS) Analysis for Landslides Susceptibility Mapping

Abstract

This paper presents the results of an integration of Geographical Information Systems (GIS) and Remote Sensing (RS) techniques to delineate landslide susceptible areas in Lushoto district, Tanzania. To achieve this, the study has examined the distribution of landslide events and identified susceptible areas in the district. The study collected data through a handheld Global Positioning System (GPS), open-source databases and on-screen digitization. Analytical Hierarchy Process (AHP) technique was used to evaluate factors influencing landslides and Quantum GIS software was used to analyse landslides data through multi criteria technique to generate landslide susceptible areas. The study reveals that past landslides are more concentrated in the southern habitable areas of Lushoto district in which mudflow and rock falls are more dominant. The findings further expose that rainfall (29.97%) and slopes (21.72%), are the factors that have a higher influence on the occurrence of landslides while proximity to rivers (2.48%) and NDVI (1.69%) have very low influences. Further, the findings reveal that about 45% of the total area falls under moderate to very high landslides susceptible areas. This study concludes that a large area of Lushoto district’s southern part is at risk of being battered by landslides resulting from the influence of rainfall and slopes. As such the study recommends that governmental and non-governmental organizations should intervene through the formulation of policies against human activities that induce landslides in susceptible areas and to use these geospatial results to officially demarcate these areas to minimize fatalities and other economic and environmental impacts.