Remote sensing and Earth Observation (EO) data are used increasingly in the different phases of risk management, due to the challenges posed by contemporary issues such as climate change, and increasingly complex social interactions. The advent of new, more powerful sensors and more finely tuned detection algorithms provides the opportunity to assess and quantify natural hazards, their consequences, and identify vulnerable regions, more comprehensively than ever before.
EO data have proven to be crucial for hazard, vulnerability, and risk mapping from small to large regions around the globe, during the occurrence of disasters and the pre/post hazard phases. In this framework, the Committee on Earth Observation Satellites (CEOS) has been working for several years on disaster management related to natural hazards (e.g., volcanic, seismic, landslides and floods), including pilots, demonstrators, recovery observatory concepts, Geohazard Supersites, and Natural Laboratory (GSNL) initiatives and multi-hazard management projects. Moreover, European Ground Motion Service (EGMS) has significantly improved the ability to monitor and analyse geohazards using Interferometric Synthetic Apeture Radar data. Data are available since mid-2022 from the Copernicus Land Monitoring Service (CLMS) under the responsibility of the European Environment Agency (EEA).
The session is dedicated to multidisciplinary contributions focused on the demonstration of the benefit of the use of EO for assessment of natural hazards and risk management.
The contributions may include:
- Innovative applications of EO data for rapid hazard/risk assessment
- Development of tools for assessment and validation of hazard/risk models
- Use of EGMS data/products to monitor and investigate different kinds of geohazards and their impact on both environment and infrastructure
The use of different types of remote sensing data (e.g. thermal, visual, radar, laser, and/or the fusion of these) or platforms (e.g. space-borne, airborne, UAS, drone, etc.) is highly recommended, with an evaluation of their respective pros and cons focusing also on future opportunities (e.g. new sensors or algorithms).
Early-stage researchers are strongly encouraged to present their research. Contributions demonstrating innovative, cross-disciplinary approaches and case studies with practical implications are particularly welcome. In addition, we invite contributions from international collaborations, such as CEOS, GSNL and GEO.