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<p><strong>Abstract.</strong> One of the most critical steps towards landslide risk analysis is the determination of element at risk. Element at risk describes any object that could potentially fail or exposed to hazards during disaster. Without quantification of element at risk information, it is difficult to estimate risk. This paper aims at developing a methodology to extract and quantity element at risk from airborne Light Detection and Ranging (LiDAR) data. The element at risk map produced was then used to construct exposure map which describes the amount of hazard for each element at risk involved. This study presented two study sites at Kundasang and Kota Kinabalu in Sabah with both areas have experienced major earthquake in June 2015. The results show that not all the features can be automatically extracted from the LiDAR data. For example, automatic extraction process could be done for building footprint and building heights, but for others such as roads and vegetation areas, a manual digitization is still needed because of the difficulties to differentiate between these features. In addition to this, there were also difficulties in identifying attribute for each feature, for example to separate between federal roads with state and unpaved roads. Therefore, for large area hazard and risk mapping, the authors suggested that an automatic process should be investigated in the future to reduce time and cost to extract important features from LiDAR data.</p>

Abstract. Land use development in the mountainous environment must be risk-informed especially in the area highly vulnerable to disaster and extreme climate. Kundasang, Sabah, Malaysia is one of the tourist-demanding areas characterized by mountainous landscape and agriculture activity. The increasing number of tourists and agriculture activity affects the land use exploration. This area is vulnerable to geohazards such as earthquakes and landslides due to its location under seismically active region and complex geological environment. In this study, geospatial technique was used to assess the land use activity in Kundasang, Sabah pertaining to geological risk in this area. The assessment started with the identification of geohazard activities and its associated tectonic features using field investigation and mapping for coherent visualization. Subsequently, multiple high-resolution satellite imageries were used to detect land use changes before and after the disaster. In order to detect the land use change, object-based change detection was applied based on segmentation and object-based classification compared to the classical pixel-based method. The output of this study shows a number of field evidences associated with geohazard features that affecting the land use activities especially build-up area and agriculture land. In conclusion, the combined results provide an important benefit for better understanding the interaction between geohazard activity and landscape patterns in order to support the planning and decision making through spatial analysis and appropriate object-based processing method.