Environment & Ecosystem Science (EES) 4(1) (2020) 23-27 Environment & Ecosystem Science (EES) DOI: http://doi.org/10.26480/ees.01.2020.23.27 ISSN: 2521-0882 (Print) ISSN: 2521-0483 (Online) CODEN: EESND2 RESEARCH ARTICLE LANDSLIDE SUSCEPTIBILITY MODELLING IN SELECTED STATES ACROSS SE. NIGERIA R. O. E. Ulakpaa*, V.U.D. Okwua, K. E. Chukwua, M. O. Eyankwareb a Department of Geography and Meteorology, Faculty of Environmental Science, Enugu State University of Science and Technology, Enugu State, Nigeria. b Department of Geology, Faculty of Science Ebonyi State University, Abakaliki. Nigeria. *Corresponding author:
[email protected] This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. ARTICLE DETAILS ABSTRACT Article History: Identification and mapping of landslide is essential for landslide risk and hazard assessment. This paper gives information on the uses of landsat imagery for mapping landslide areas ranging in size from safe area to highly Received 12 January 2020 prone areas. Landslide mitigation largely depends on the understanding of the nature of the factors namely: Accepted 15 February 2020 slope, soil type, lineament, lineament density, elevation, rainfall and vegetation. These factors have direct Available online March 2020 bearing on the occurrence of landslide. Identification of these factors is of paramount importance in setting 30 out appropriate and strategic landslides control measures. Images for this study was downloaded by using remote sensing with landsat 8 ETM and aerial photos using ArcGIS 10.7 and Surfer 8 software, while Digital Elevation Model (DEM) and Google EarthPro TM were used to produce slope, drainage, lineament and elevation.