Remote sensing of landslides: An analysis of the potential contribution to geo-spatial systems for hazard assessment in mountainous environments Graciela Metternicht a, * , Lorenz Hurni b , Radu Gogu b a Department of Spatial Sciences, Curtin University of Technology, GPO Box U 1987, Perth WA 6854, Australia b Institute for Cartography, Swiss Federal Institute of Technology ETH, Ho ¨nggerberg, CH 8093 Zurich, Switzerland Received 11 February 2005; received in revised form 2 August 2005; accepted 6 August 2005 Abstract Natural hazards like landslides, avalanches, floods and debris flows can result in enormous property damage and human casualties in mountainous regions. Switzerland has always been exposed to a wide variety of natural hazards mostly located in its alpine valleys. Recent natural disasters comprising avalanches, floods, debris flows and slope instabilities led to substantial loss of life and damage to property, infrastructure, cultural heritage and environment. In order to offer a solid technical infrastructure, a new concept and expert-tool based on an integrated web-based database/GIS structure is being developed under HazNETH. Given the HazNETH database design contemplates the detection and mapping of diagnostic features from remote sensors (e.g., ground, air and space borne) this paper analyses the use of remote sensing data in landslides studies during the 1980s, 1990s and 2000s, including a discussion of its potential and research challenges as result of new operational and forthcoming technologies such as the very high spatial resolution optical and infrared imagery of Ikonos, Quickbird, IRS CartoSat-1, ALOS, the satellite based interferometric SAR (InSAR and DInSAR of Radarsat, ERS, Envisat, TerraSAR-X, Cosmo/ SkyMed, ALOS), micro-satellites like the Ple `iades, DMC, RapidEye, airborne LASER altimetry or ground-based differential interferometric SAR. The use of remote sensing data, whether air-, satellite- or ground-based varies according to three main stages of a landslide related study, namely a) detection and identification; b) monitoring; c) spatial analysis and hazard prediction. Accordingly, this paper presents and discusses previous applications of remote sensing tools as related to these three main phases, proposing a conceptual framework for the contribution of remote sensing to the design of databases for natural hazards like debris flows, and identifying areas for further research. D 2005 Elsevier Inc. All rights reserved. Keywords: Remote sensing; Debris flows; Landslides; Mountainous hazards; Switzerland; Mapping; Monitoring; Spatial modelling; Hazard prediction; SAR; InSAR; DlnSAR; LiDAR 1. Introduction Natural hazards like landslides, avalanches, floods and debris flows can result in enormous property damage and human casualties in mountainous regions. A recent world disaster report (International Federation of the Red Cross and Red Crescent Societies, 2001) shows that flooding, avalanches and landslides account for 42% of the global incidence of natural disasters, with average yearly economic losses due to landslides mounting to billions of US dollars (e.g., Japan, India, Italy, USA) to millions in countries like Canada, Nepal, Sweden. Furthermore, inventories con- ducted between 1964–1999 show a steady increase in the number of landslides disasters worldwide (Kjekstad, 2002). Switzerland has always been exposed to a wide variety of natural hazards mostly located in its alpine valleys. Recent events such as those occurring in the Canton of Graubu ¨ nden in November 2002, or the Canton Valais in October 2000 comprised avalanches, floods, debris flows and slope instabilities that led to substantial loss of life and damage to property, infrastructure, cultural heritage and environment. As consequence came into consideration the need to move towards ‘‘an integrated risk management and sustainable risk prevention culture’’, designing and implementing HazNETH 0034-4257/$ - see front matter D 2005 Elsevier Inc. All rights reserved. doi:10.1016/j.rse.2005.08.004 * Corresponding author. E-mail addresses: g.metternicht@curtin.edu.au (G. Metternicht), hurni@karto.baug.ethz.ch (L. Hurni), gogu@karto.bag.ethz.ch (R. Gogu). Remote Sensing of Environment 98 (2005) 284 – 303 www.elsevier.com/locate/rse