GeoHazard Challenges

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The field of GeoHazards is related to the analysis of global scale long time series EO based information of volcanic activity, earthquakes; Landslides and land subsidence are key in improving forecast and early warning systems for these natural disasters and highly demanding in terms of EO data volume, due to its spatiotemporal scale and the resolution of the required imagery.

In these data challenges we are looking forward to derive information of volcanic activity, earthquakes, landslides and land subsidence to forecast and early warning of these natural disasters. Their research can be integrated in the scope of the Copernicus Emergency Management, mainly in the Risk and Recovery Mapping component.


The main topics in this challenge will be related to:

  • Forecasting the impact of earthquakes,
  • Rapid generation of landslide inventories,
  • Forecasting surface deformation.

 

Currently the Swiss Federal Institute of Technology Zurich (ETHZ) is doing research in this filed, their work has been already been integrated in the GeoHazards TEP and its scope fits perfectly into the needs of the Copernicus Emergency Management, mainly in the Risk and Recovery Mapping component. Their work can also influence other related areas from civil protection to the insurance sector. During the project this connections will be further analysed to connect to additional promoters coming from these sectors and develop higher-level products that can bring additional value to the project.

GeoHazards Data Challenges
Identified Challenge Short Description Result
GH1: Global catalogue of co-seismic deformation (2002-2010)

ENVISAT satellite acquired SAR imagery during the period 2002-2010. Many earthquakes occurred during this observation time and the analyses performed have consolidated the DInSAR as an extremely important technique to map and characterize co-seismic deformation. However, the DInSAR analyses were performed relying on different software and parameters, thus results are heterogeneous. In this challenge produce a homogeneous catalog of co-seismic deformation associated with earthquakes with Magnitude >5 by relying on the Envisat ASAR dataset.

Availability expected mid-2019.
GH2: Exploitation of co-seismic DInSAR interferograms

Systematic processing of SAR data is a major trend due to the increased data availability and spatial/temporal coverage (e.g. DLR systematic processing of Sentinel 1). Accordingly, interferograms already generated and stored could be selected (filtered) starting from an input list (catalogue) defining date and time as well as coordinates of an earthquake event. After identification of the relevant interferograms, basic tools to measure results characteristics are necessary, i.e. extension of the deforming area, identification of linear features, etc. This information can later be useful for visual data mining as well as to obtain training datasets for machine learning algorithms used for automatic identification of specific features on SAR interferograms associated to earthquake events.

Availability expected mid-2019.
GH3: Automated/systematic detection of changes due to earthquakes

Earthquakes cause changes/damages that can be mapped tacking advantage of different EO data, as for example SAR data. In this challenge we aim at automatically mapping co-seismic deformation and interferometric coherence changes due to earthquakes with M>5.

Availability expected mid-2019.

 

Challenges Overview
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