Selection of optimal pixel resolution for landslide susceptibility analysis within the Bukit Antarabangsa, Kuala Lumpur, by using image processing and multivariate statistical tools

Abstract

Landslides are considered as one of the natural hazards responsible for casualties, damage of assets, and infrastructures. In many situations, collection of field data from remote places is difficult due to inaccessibility of landslide area. This paper examines landslide susceptibility in the Bukit Antarabangsa, Kuala Lumpur, to ease geographical studies, using image processing and multivariate statistical tools by reviewing the digital images using remote-sensing technique without any physical survey. We considered different pixel resolutions and report the effectiveness of using factor analysis, principal component analysis, linear discriminant analysis, and their hybridization. Eight types of databases for heavy, medium, and no landslide were created. The modeling works were carried out at 2 × 2, 4 × 4, 8 × 8, 16 × 16, 32 × 32, 64 × 64, 128 × 128, and 256 × 256 pixel resolutions. Results indicate 2 × 2 was optimal in both heavy and medium while 8 × 8 found to be ideal for no landslide region. Performance at different pixel resolutions was compared using receiver operating characteristic (ROC) curves, and average success of 87.36% was found. This simple yet robust system holds great potential for saving lives.