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Abstract. The growing concern for loss of services once provided by natural ecosystems is getting increasing attention. However, the accelerating rate of natural resources destruction calls for rapid and global action. With often very limited budgets, environmental agencies and NGOs need cost-efficient ways to quickly convince decision-makers that sound management of natural resources can help to protect human lives and their welfare. The methodology described in this paper, is based on geospatial and statistical analysis, involving simple Geographical Information System (GIS) and remote sensing algorithms. It is based on free or very low-cost data. It aims to scientifically assess the potential role of vegetation in mitigating landslides triggered by earthquakes by normalising for other factors such as slopes and distance from active fault. The methodology was applied to the 2005 North Pakistan/India earthquake which generated a large number of victims and hundreds of landslides. The study shows that if slopes and proximity from active fault are the main susceptibility factors for post landslides triggered by earthquakes in this area, the results clearly revealed that areas covered by denser vegetation suffered less and smaller landslides than areas with thinner (or devoid of) vegetation cover. Short distance from roads/trails and rivers also proved to be pertinent factors in increasing landslides susceptibility. This project is a component of a wider initiative involving the Global Resource Information Database Europe from the United Nations Environment Programme, the International Union for Conservation of Nature, the Institute of Geomatics and Risk Analysis from the University of Lausanne and the "institut universitaire d'études du développement" from the University of Geneva.

With growing world population and concentration in urban and coastal areas, the exposure to natural hazards is increasing and results in higher risk of human and economic losses. Improving the identification of areas, population and assets potentially exposed to natural hazards is essential to reduce the consequences of such events. Disaster risk is a function of hazard, exposure and vulnerability. Modelling risk at the global level requires accessing and processing a large number of data, from numerous collaborating centres. These data need to be easily updated, and there is a need for centralizing access to this information as well as simplifying its use for non GIS specialists. The Hyogo Framework for Action provides the mandate for data sharing, so that governments and international development agencies can take appropriate decision for disaster risk reduction. Timely access and easy integration of geospatial data are essential to support efforts in Disaster Risk Reduction. However various issues in data availability, accessibility and integration limit the use of such data. In consequence, a framework that facilitate sharing and exchange of geospatial data on natural hazards should improve decision-making process. The PREVIEW Global Risk Data Platform is a highly interactive web-based GIS portal supported by a Spatial Data Infrastructure that offers free and interoperable access to more than 60 global data sets on nine types of natural hazards (tropical cyclones and related storm surges, drought, earthquakes, biomass fires, floods, landslides, tsunamis and volcanic eruptions) and related exposure and risk. This application portrays an easy-to-use online interactive mapping interface so that users can easily work with it and seamlessly integrate data in their own data flow using fully compliant OGC Web Services (OWS).

Abstract. With growing world population and concentration in urban and coastal areas, the exposure to natural hazards is increasing and results in higher risk of human and economic losses. Improving the identification of areas, population and assets potentially exposed to natural hazards is essential to reduce the consequences of such events. Disaster risk is a function of hazard, exposure and vulnerability. Modelling risk at the global level requires accessing and processing a large number of data, from numerous collaborating centres. These data need to be easily updated, and there is a need for centralizing access to this information as well as simplifying its use for non GIS specialists. The Hyogo Framework for Action provides the mandate for data sharing, so that governments and international development agencies can take appropriate decision for disaster risk reduction. Timely access and easy integration of geospatial data are essential to support efforts in Disaster Risk Reduction. However various issues in data availability, accessibility and integration limit the use of such data. In consequence, a framework that facilitate sharing and exchange of geospatial data on natural hazards should improve decision-making process. The PREVIEW Global Risk Data Platform is a highly interactive web-based GIS portal supported by a Spatial Data Infrastructure that offers free and interoperable access to more than 60 global data sets on nine types of natural hazards (tropical cyclones and related storm surges, drought, earthquakes, biomass fires, floods, landslides, tsunamis and volcanic eruptions) and related exposure and risk. This application portrays an easy-to-use online interactive mapping interface so that users can easily work with it and seamlessly integrate data in their own data flow using fully compliant OGC Web Services (OWS).

With growing world population and concentration in urban and coastal areas, the exposure to natural hazards is increasing and results in higher risk of human and economic losses. Improving the identification of areas, population and assets potentially exposed to natural hazards is essential to reduce the consequences of such events. Disaster risk is a function of hazard, exposure and vulnerability. Modelling risk at the global level requires accessing and processing a large number of data, from numerous collaborating centres. These data need to be easily updated, and there is a need for centralizing access to this information as well as simplifying its use for non GIS specialists. The Hyogo Framework for Action provides the mandate for data sharing, so that governments and international development agencies can take appropriate decision for disaster risk reduction. Timely access and easy integration of geospatial data are essential to support efforts in Disaster Risk Reduction. However various issues in data availability, accessibility and integration limit the use of such data. In consequence, a framework that facilitate sharing and exchange of geospatial data on natural hazards should improve decision-making process. The PREVIEW Global Risk Data Platform is a highly interactive web-based GIS portal supported by a Spatial Data Infrastructure that offers free and interoperable access to more than 60 global data sets on nine types of natural hazards (tropical cyclones and related storm surges, drought, earthquakes, biomass fires, floods, landslides, tsunamis and volcanic eruptions) and related exposure and risk. This application portrays an easy-to-use online interactive mapping interface so that users can easily work with it and seamlessly integrate data in their own data flow using fully compliant OGC Web Services (OWS).

Higher temperatures and changes in precipitation patterns have induced an acute decrease in Andean glaciers, thus leading to additional stress on water supply. To adapt to climate changes, local governments need information on the rate of glacier area and volume losses and on current ice thickness. Remote sensing analyses of Coropuna glacier (Peru) delineate an acute glaciated area decline between 1955 and 2008. We tested how volume changes can be estimated with remote sensing and GIS techniques using digital elevation models derived from both topographic maps and satellite images. Ice thickness was measured in 2004 using a Ground Penetrating Radar coupled with a Ground Positioning System during a field expedition. It provided profiles of ice thickness on different slopes, orientations and altitudes. These were used to model the current glacier volume using Geographical Information System and statistical multiple regression techniques. The results revealed a significant glacier volume loss; however the uncertainty is higher than the measured volume loss. We also provided an estimate of the remaining volume. The field study provided the scientific evidence needed by COPASA, a local Peruvian NGO, and GTZ, the German international cooperation agency, in order to alert local governments and communities and guide them in adopting new climate change adaptation policies.

Higher temperatures and changes in precipitation patterns have induced an acute decrease in Andean glaciers, thus leading to additional stress on water supply. To adapt to climate changes, local governments need information on the rate of glacier area and volume losses and on current ice thickness. Remote sensing analyses of Coropuna glacier (Peru) delineate an acute glaciated area decline between 1955 and 2008. We tested how volume changes can be estimated with remote sensing and GIS techniques using digital elevation models derived from both topographic maps and satellite images. Ice thickness was measured in 2004 using a Ground Penetrating Radar coupled with a Ground Positioning System during a field expedition. It provided profiles of ice thickness on different slopes, orientations and altitudes. These were used to model the current glacier volume using Geographical Information System and statistical multiple regression techniques. The results revealed a significant glacier volume loss; however the uncertainty is higher than the measured volume loss. We also provided an estimate of the remaining volume. The field study provided the scientific evidence needed by COPASA, a local Peruvian NGO, and GTZ, the German international cooperation agency, in order to alert local governments and communities and guide them in adopting new climate change adaptation policies.

Abstract. This paper presents a model of factors influencing levels of human losses from natural hazards at the global scale, for the period 1980–2000. This model was designed for the United Nations Development Programme as a building stone of the Disaster Risk Index (DRI), which aims at monitoring the evolution of risk. Assessing what countries are most at risk requires considering various types of hazards, such as droughts, floods, cyclones and earthquakes. Before assessing risk, these four hazards were modelled using GIS and overlaid with a model of population distribution in order to extract human exposure. Human vulnerability was measured by crossing exposure with selected socio-economic parameters. The model evaluates to what extent observed past losses are related to population exposure and vulnerability. Results reveal that human vulnerability is mostly linked with country development level and environmental quality. A classification of countries is provided, as well as recommendations on data improvement for future use of the model.