Crisis information is needed at different stages before and after a disaster event and with differing time relevance. A disaster event is followed by the Emergency Relief phase. To be able to minimize loss and damage data has to be as recent as possible.

“Rapid mapping” based on hyperspectral data, requires a high level of readily implemented and computationally efficient algorithms and procedures. Especially due to the large number of bands and rich information content an operational use in disaster cases has to be tested and described accurately.

Oil spills, water and land pollution with certain materials, volcanic eruptions and landslides were scenarios where hyperspectral data is a useful and powerful means to localize or identify certain (hazardous) materials.

The following major scientific and application tasks have been identified in crisis information:

• detection of water or land pollution (e.g. oil spill monitoring, determination of pollutant type, debris analysis)
• risk assessment (e.g. prediction of oil spill spread direction and rate characteristics, assessment of contaminated areas)
• determination of lava flows in case of volcanic eruption
• assessment of vulnerability (e.g. analysis of roofing types in cyclone prone areas)

They require the following goals for scientific tasks

• development of new algorithms for disaster mapping with emphasis of water and land pollution
• development of readily implemented and efficient techniques and procedures that save time during image processing
• monitoring critical infrastructure by acquiring imagery regularly
• monitoring natural phenomena, e.g. volcanoes, regularly