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In order to assess and quantify earthquake risk over large spatial extents on a global or regional scale spatial data localizing human assets is on strong demand. However, due to the large-scale extent of human activities on our planet, the scientific community has been lacking tools and methodologies to capture the entity of elements at risk, especially with enhanced thematic and geometric detail on global scale. First generation of global land cover datasets and maps of urban extent produced since the millenium relied on coarse resolution satellite sensors such as MODIS or DMSP-OLS. Despite the availability of finer scale imagery no other product of global coverage has been made available until today. However, global human exposure mapping from remote sensing is now entering a new era and new products currently in the making such as the Global Urban Footprint and the Global Human Settlement Layer will deliver spatial information on human settlements at unprecedented spatial resolutions. Once available on a global scale, these layers will improve significantly the knowledge base for the localization of human assets with regard to georisks. This work reviews past mapping products of coarse geometric resolution and further presents first validation efforts of the two new layers based on standard accuracy measures with regard to a geometrically and thematically highly resolved building reference. This first assessment reveals that the high resolution settlement layers produce comparable outputs that are capable of mapping even smaller settlements in low-density rural areas although significant over-classification due to the specific characteristics of each classifier is obvious. To gain a deeper understanding of these layers further validations efforts using pattern-based regression analysis and measures of inter-map agreement are currently underway.

Data collected from satellite and airborne sensors have been widely used in post-earthquake damage assessment for over a decade. These data have provided crucial information to decision makers tasked with providing immediate humanitarian and financial assistance to affected populations. Furthermore, decision makers in disaster management are now increasingly using geospatial data derived from imagery to plan for and track recovery efforts. This paper describes the use of remote sensing and in-situ observations beyond the initial response and relief phases that follow damaging earthquakes. Data and information needs in earthquake recovery planning have been assessed in a series of unique user needs assessment exercises with emergency managers in Kyrgyzstan, Tajikistan and Turkey. Realistic earthquake scenarios were played-out during one-day exercises allowing key disaster managers to simulate the post-earthquake decision making process. A number of time periods were condensed into one-hour segments simulating one day, one week, one month, one year and beyond one year after the earthquake. Decision makers responded to realistic events simulating cascading hazards, physical and socio-economic effects of the disaster and the subsequent decisions taken. A suite of innovative methodologies and software tools for dynamic, multi-resolution monitoring of recovery were provided to assess if, when and how remote sensing-based tools can be integrated into existing decision workflows. These user-needs scenarios and the suite of remote sensing-based tools and methodologies are presented as part of the European Commission FP7 project SENSUM: framework to integrate space-based and in-situ sensing for dynamic vulnerability and recovery monitoring. Data derived from multi-resolution imagery are demonstrated to be effective in planning and assessing recovery to transportation networks, transitional shelters and the built environment, whilst providing proxy information for socio-economic indicators.

Central Asia belongs to the regions of the world most exposed to high levels of seismic hazard. After the collapse of Soviet Union, the seismic monitoring in this area decreased significantly in quality and quantity since the maintenance of previous analog networks dealt with serious economic difficulties. Moreover, the installation of modern digital network was limited to few cases (e.g. stations in Kazakhstan or the KNET deployed in Kyrgyzstan). In the last decade the situation improved but still the new networks are concentrated in a few regions and devoted mainly to weak-motion seismology. In this article, we describe the installation of a small strong-motion network in the Kyrgyz capital Bishkek, intended for earthquake early warning and rapid response purposes. Low cost strong-motion stations developed at GFZ have been installed in seven buildings spread over the town, each one monitored by several sensing units to accomplish also the task of structural health monitoring. The stations communicate via wireless link and the streams collected by one specific station are communicated to the data management center via internet. Each unit has computational power, allowing for decentralized operations related to on-site early warning. An extension of this network to a regional early warning network for real time risk assessment is expected in the near future., System Erde; 3

The threat to human society arising from earthquakes should never be underestimated, especially in those regions of the world more exposed to this natural hazard. The complex geodynamics of Central Asia make it a natural research laboratory for the geoscience community, but also present a source of serious concern for local populations and their administrations who have already dealt with the devastating consequence of earthquakes in the past. Evaluating expected seismic risk for the exposed communities is a great challenge that calls for a strong, unified effort by researchers and decision makers. The nature of this challenge requires holistic, multidisciplinary approaches and the development of innovative solutions and methodologies, especially in countries where few resources are available for disaster prevention and mitigation. Within several projects the GFZ Centre for Early Warning currently focuses on different components of risk in Central Asia. This article, therefore, provides a brief overview of these research activities, along with a description of an application in the framework of Early Warning and Rapid Response., System Erde; 3

This short report describes the first attempt at obtaining a preliminary cross-border risk model for Central Asia starting from datasets that were already available at the beginning of the EMCA Project.

Forecasting and early warning systems are important investments to protect lives, properties, and livelihood. While early warning systems are frequently used to predict the magnitude, location, and timing of potentially damaging events, these systems rarely provide impact estimates, such as the expected amount and distribution of physical damage, human consequences, disruption of services, or financial loss. Complementing early warning systems with impact forecasts has a twofold advantage: It would provide decision makers with richer information to take informed decisions about emergency measures and focus the attention of different disciplines on a common target. This would allow capitalizing on synergies between different disciplines and boosting the development of multihazard early warning systems. This review discusses the state of the art in impact forecasting for a wide range of natural hazards. We outline the added value of impact‐based warnings compared to hazard forecasting for the emergency phase, indicate challenges and pitfalls, and synthesize the review results across hazard types most relevant for Europe.

Forecasting and early warning systems are important investments to protect lives, properties, and livelihood. While early warning systems are frequently used to predict the magnitude, location, and timing of potentially damaging events, these systems rarely provide impact estimates, such as the expected amount and distribution of physical damage, human consequences, disruption of services, or financial loss. Complementing early warning systems with impact forecasts has a twofold advantage: It would provide decision makers with richer information to take informed decisions about emergency measures and focus the attention of different disciplines on a common target. This would allow capitalizing on synergies between different disciplines and boosting the development of multihazard early warning systems. This review discusses the state of the art in impact forecasting for a wide range of natural hazards. We outline the added value of impact-based warnings compared to hazard forecasting for the emergency phase, indicate challenges and pitfalls, and synthesize the review results across hazard types most relevant for Europe.

Forecasting and early warning systems are important investments to protect lives, properties, and livelihood. While early warning systems are frequently used to predict the magnitude, location, and timing of potentially damaging events, these systems rarely provide impact estimates, such as the expected amount and distribution of physical damage, human consequences, disruption of services, or financial loss. Complementing early warning systems with impact forecasts has a twofold advantage: It would provide decision makers with richer information to take informed decisions about emergency measures and focus the attention of different disciplines on a common target. This would allow capitalizing on synergies between different disciplines and boosting the development of multihazard early warning systems. This review discusses the state of the art in impact forecasting for a wide range of natural hazards. We outline the added value of impact‐based warnings compared to hazard forecasting for the emergency phase, indicate challenges and pitfalls, and synthesize the review results across hazard types most relevant for Europe., Reviews of Geophysics, 58 (4), ISSN:8755-1209, ISSN:0096-1043, ISSN:1944-9208

Forecasting and early warning systems are important investments to protect lives, properties and livelihood. While early warning systems are frequently used to predict the magnitude, location and timing of potentially damaging events, these systems rarely provide impact estimates, such as the expected amount and distribution of physical damage, human consequences, disruption of services or financial loss. Complementing early warning systems with impact forecasts has a two‐fold advantage: it would provide decision makers with richer information to take informed decisions about emergency measures, and focus the attention of different disciplines on a common target. This would allow capitalizing on synergies between different disciplines and boosting the development of multi‐hazard early warning systems. This review discusses the state‐of‐the‐art in impact forecasting for a wide range of natural hazards. We outline the added value of impact‐based warnings compared to hazard forecasting for the emergency phase, indicate challenges and pitfalls, and synthesize the review results across hazard types most relevant for Europe. Plain language summary Forecasting and early warning systems are important investments to protect lives, properties and livelihood. While such systems are frequently used to predict the magnitude, location and timing of potentially damaging events, they rarely provide impact estimates, such as the expected physical damage, human consequences, disruption of services or financial loss. Extending hazard forecast systems to include impact estimates promises many benefits for the emergency phase, for instance, for organising evacuations. We review and compare the state‐of‐the‐art of impact forcasting across a wide range of natural hazards, and outline opportunities and key challenges for research and development of impact forecasting.