Hazards and Risks

Image: Etna, Sicily (Italy), DESIS / ISS RGB (639 nm, 550 nm, 470 nm)
Source: DLR/Teledyne Brown

With growing population and infrastructure the world’s exposure to natural hazards is increasing. In particular, coastal areas record the strongest increase in population growth concurrently with an increasing exposure to floods, cyclones and tidal waves. Natural hazards encompass a wide range of phenomena from geologic and climatic hazards to fires and diseases. Many naturally occurring phenomena grow into natural hazards once we are faced with their extremes. Thus, several topics related to hazards and risks are closely linked to other applications and research topics (e.g. algal blooms, soil contamination, oil spills, land degradation, marine litter, industrial waste, etc.) and can also be synergistically adjusted to meet the needs of hazard and risk management.

During previous disaster events airborne imaging spectroscopy data were employed to localize and identify materials related to environmental pollution and hazards. However, airborne imaging systems are of limited use to cover events of large geographic extent on an operational level. With EnMAP, an operational sensor system is provided that records an area of suitable geographic extent. The main challenge in using EnMAP data to monitor natural hazards and remediate risk is to optimize and adapt existing algorithms to be operational during the pressing early disaster stages. In most previous disaster events imaging spectroscopy data were used during the later reconstruction and risk analysis phase (monitoring oil spills, identifying and measuring damage, assessing situations, scientific applications), rather than during the urgent emergency relief phase.

Therefore, such disaster applications require the following main scientific tasks:

  • Development of new algorithms for disaster mapping using the hyperspectral band information
  • Development of time-efficient image processing techniques
  • Monitoring areas affected by natural hazards for long-term studies and to derive early warning indicators.
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