1B V Mathew, Professor, HoD, Department of Civil Engineering, APJ Abdul Kalam Technological University/Ahalia School of Engineering and Technology, Palakkad, Kerala, India
2Jayakrishnan R, Assistant Professor, Department of Civil Engineering, APJ Abdul Kalam Technological University/Ahalia School of Engineering and Technology, Palakkad, Kerala, India
3Anagha Chandran, B.Tech Final Year Student, Department of Civil Engineering, APJ Abdul Kalam Technological University/Ahalia School of Engineering and Technology, Palakkad, Kerala, India
4Pranav A, B.Tech Final Year Student, Department of Civil Engineering, APJ Abdul Kalam Technological University/Ahalia School of Engineering and Technology, Palakkad, Kerala, India
5V S Rishikesh, B.Tech Final Year Student, Department of Civil Engineering, APJ Abdul Kalam Technological University/Ahalia School of Engineering and Technology, Palakkad, Kerala, India
*Corresponding Author: Jayakrishnan R, Assistant Professor, Department of Civil Engineering, APJ Abdul Kalam Technological University/Ahalia School of Engineering and Technology, Palakkad, Kerala, India, Email: jayan1615@gmail.com
Online Published on 25 June, 2025.
Landslides are a major natural hazard in hilly regions, posturing critical dangers to life, infrastructure, and the environment. This study centers on landslide vulnerability mapping in Veezhumala, Palakkad, utilizing QGIS as the essential apparatus for geospatial investigation. Different conditioning components such as slope, elevation, aspect, soil type, land use, and rainfall patterns have been considered to evaluate landslide-prone regions.
Information collection included getting Digital Elevation Models (DEMs), meteorological rainfall data, and chronicled landslide events. Thematic maps for each calculate were generated in QGIS to establish their spatial dispersion and impact on landslide vulnerability. The another stage of the ponder will include applying the Evidence-Based Frequency (EBF) Method, which can assign probability weights to each calculate based on its relationship with past landslides. This will empower the creation of a landslide vulnerability index, categorizing the think about region into distinctive chance zones.
The discoveries of this study will contribute to disaster readiness, urban planning, and natural administration by recognizing high-risk zones and suggesting moderation measures. The ultimate vulnerability outline will serve as a important instrument for policymakers, engineers, and nearby specialists in landslide risk evaluation and administration methodologies.
GIS, QGIS, Landslide, Mapping
