FIG Peer Review Journal


Mapping of Elements at Risk for Landslides in the Tropics Using Airborne Laser Scanning (4874)

Khamarrul Azahari Razak, Cees Van Westen, Menno Straatsma and Steven De Jong (Netherlands)
Mr. Khamarrul Azahari Razak
PhD scholar
Faculty of Geo-Information Science and
Earth Observation
University of Twente
Hengelosestraat 99
7511 AE Enschede
7511 AE
Corresponding author Mr. Khamarrul Azahari Razak (email: razak[at], tel.: + 31 534874416)

[ abstract ] [ paper ] [ handouts ]

Published on the web 2011-03-16
Received 2010-11-22 / Accepted 2011-02-10
This paper is one of selection of papers published for the FIG Working Week 2011 in Marrakech, Morocco and has undergone the FIG Peer Review Process.

FIG Working Week 2011
ISBN 978-87-90907-92-1 ISSN 2307-4086


Mapping elements at risk for landslides in the tropics pose as a challenging task. Aerial-photograph, satellite imagery, and synthetic aperture radar images are less effective to accurately provide physical presence of objects in a relatively short time. In this paper, we utilized an airborne laser scanning (ALS) for extracting elements at risk for landslides, which we emphasized on the buildings and roads extraction in a populated tropical region (Cameron Highlands, Malaysia). We presented the building filter derived from the hierarchical robust interpolation method for building extraction. Meanwhile, the road extraction was performed based on the ALS-derived topographic openness, analyzed in a stereoscopic model. Building and road attributes in relation to landslides were subsequently generated such as perimeter and area of building footprint; number and height of the buildings; road location; length; road gradient, and road-cuts. We quantitatively evaluated the building detection method and measured the vertical accuracy of ALS-derived road. The evaluation showed the building detection rate of 88.6%, the correctness of 90% and the overall quality of 80.7%. The vertical accuracy of the ALS-derived road was about 0.68 m and spatially improved compared to the existing road map. This study illustrates the effectiveness of ALS data for mapping elements at risks in the tropics, which are essential for landslide vulnerability and risk assessment.
Keywords: Laser scanning; Risk management; disaster management; tropical rainforest