Post-disaster assessment of landslides in southern Taiwan after 2009 Typhoon Morakot using remote sensing and spatial analysis

Abstract

Abstract. On 8 August 2009, the extreme rainfall of Typhoon Morakot triggered enormous landslides in mountainous regions of southern Taiwan, causing catastrophic infrastructure and property damages and human casualties. A comprehensive evaluation of the landslides is essential for the post-disaster reconstruction and should be helpful for future hazard mitigation. This paper presents a systematic approach to utilize multi-temporal satellite images and other geo-spatial data for the post-disaster assessment of landslides on a regional scale. Rigorous orthorectification and radiometric correction procedures were applied to the satellite images. Landslides were identified with NDVI filtering, change detection analysis and interactive post-analysis editing to produce an accurate landslide map. Spatial analysis was performed to obtain statistical characteristics of the identified landslides and their relationship with topographical factors. A total of 9333 landslides (22 590 ha) was detected from change detection analysis of satellite images. Most of the detected landslides are smaller than 10 ha. Less than 5% of them are larger than 10 ha but together they constitute more than 45% of the total landslide area. Spatial analysis of the detected landslides indicates that most of them have average elevations between 500 m to 2000 m and with average slope gradients between 20 • and 40 • . In addition, a particularly devastating landslide whose debris flow destroyed a riverside village was examined in depth for detailed investigation. The volume of this slide is estimated to be more than 2.6 million m 3 with an average depth of 40 m.

Automated Spatiotemporal Landslide Mapping over Large Areas Using RapidEye Time Series Data

“…Furthermore, in most of the published studies, the methods have been applied to rather small test sites of 100 km 2 or less. In only two recent studies [28,31] have the proposed methods been developed for study areas of more than 1000 km 2 . During the last years, an increasing number of studies has proposed methods for object-oriented landslide mapping (e.g., [20,[32][33][34][35][36][37]), which is required for landslide inventories and also for the integration of additional contextual information in order to further improve the mapping reliability [33].…”

Technical Note: Use of remote sensing for landslide studies in Europe

“…The analysis of optical imagery for landslide mapping can be performed through (i) visual interpretation of single and stereoscopic images ; (ii) image classification with semi-automated pixel-based methods (Borghuis et al, 2007;Marcelino et al, 2009); (iii) image classification with semi-automated object-oriented methods (Martha et al, 2010;Lu et al, 2011;Stumpf and Kerle, 2011); (iv) change detection techniques (Nichol and Wong, 2005;Weirich and Blesius, 2007;Tsai et al, 2010); and (v) correlation of optical images (Delacourt et al, 2007;Leprince et al, 2007;Debella-Gilo and Kääb, 2011).…”

Satellite-based emergency mapping using optical imagery: experience and reflections from the 2015 Nepal earthquakes

“…Semiautomated and automated approaches to image segmentation hold potential for more time efficient landslide mapping, with considerable success reported outside immediate post-disaster contexts (e.g., Tsai et al, 2010). However, discernible spectral changes across a landscape, upon which pixel-based segmentation depends, may only occur for failures within densely vegetated areas that have the potential to revegetate over short periods.…”