Natural risk management
Drought early warning and monitoring are crucial components of preparedness and mitigation plans. Similarly, satellite-based early warning systems and the development of risk management plans can improve disaster preparedness, the reduction of disaster impact and better response to emergency situations.
Flood vulnerability assessments also benefit from information about flood exposed land cover/land use areas as well as critical infrastructure within key areas of interest. New financial products in the field of disaster risk finance and insurance can be designed and implemented, using long and consistent time-series to detect location-specific trends and anomalies.
This service provides historical to near real-time information on crop production and infrastructure risks including drought and floods. Not only diagnosis of frequency of occurrence, but also vulnerability assessments can be provided. With hydrological discharge models floods can also be forecasted operationally. These services can be provided using TRMM or CHIRPS (precipitation), MODIS/Proba-V/SPOT VGT 250m-1km (Vegetation) and METOP-ASCAT 12.5 km (soil moisture), with emphasis on radar imagery such as Sentinel-1 20m data for flood mapping and monitoring. Another part of the service provides information on risks resulting from degradation of vegetation and excessive rainfall, including the location and extent of landslides. This type of information can be provided using Sentinel-2, Landsat at 10-30m and MODIS-type sensors at 250m.
Known Limitations
The spatial resolution of drought monitoring information is typically coarse and applicable at the regional level, within-field information is not available. Historical and in some areas current satellite imagery for flood monitoring is fragmented in time and space, and may suffer from persistent cloud cover. This hampers consistent time-series generation. The mapping and monitoring of flash floods is very challenging due to cloud cover and the revisit times of current sensors, which will most often be too long to capture short-duration floods. For landslide mapping, medium resolution (250m) data will not be sufficient and high resolution data 10-30m or better is preferred.
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