Gis in studying slope failure in Penang: challenges and potential

• Main Authors: Abd Majid, Nuriah, Wan Ibrahim, Wan Mohd Muhiyuddin
• Format: Conference or Workshop Item
• Language: English
• Published: 2015
• Subjects: H Social Sciences (General)
• Online Access: http://eprints.usm.my/35097/1/PPIK19.pdf; http://eprints.usm.my/35097/

Geographic Information System (GIS) is an information system that is used to store, display, analyse and manipulate spatial data. Geographic information system (GIS) can help users to visualise, question, analyse, and interpret data to understand patterns, trends, and relationships. GISbased maps and visualizations have greatly assisted understanding of situations. In recent years, slope failure hazard assessment has played an important role in developing land utilisation planning aimed at minimizing the loss of lives and damages to property. There are various GIS-based slope failure studies that involve many approaches. These approaches can be classified into qualitative factor overlay, geotechnical process models, and statistical models. At present, not many studies have satisfactorily studied the integration of these models with GIS to map slope failure. This paper deals with several aspects of landslide by presenting a focused review of GIS-based slope failure hazard zone. The paper starts with a framework for GIS-based study of slope failure, followed by a critical review of the state-of-the-art applications of GIS and digital elevation models (DEM) for mapping and modelling landslide hazards. The paper ends with a description of an integrated system for effective landslide hazard zonation. The adoption of a GIS-based framework for knowledge discovery allows designers to identify the suitability of development within certain areas. The usage of GIS can be beneficial in various fields, including the issue of slope failure. Moreover, GIS is also beneficial to organisations of all sizes and in virtually every industry. GIS is important in understanding what is happening and forecasting future trend in a geographic space.