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Global drought monitoring at high resolution

The European Drought Observatory (EDO) and the Global Drought Observatory (GDO) uses mainly modeled data for monitoring drought at the European and Global scale. The OEMC project will build 1km drought maps on a seasonal scale based on soil moisture, vegetation, and precipitation data obtained from the integration of satellite, modeled, and ground-based observations. Integrated satellite data will allow us to include the human component in drought assessment with improved reliability in areas impacted by human activity (ie extensively irrigated areas).

What is the challenge?

On the one hand, there is an increasing number of sources of elevation / altitude data while, on the other hand, users typically require only a single functional elevation service, preferably one that most accurately depicts hydrological relationships in a landscape.

Land relief parameterization follows the higher resolution DTM product. Higher resolution data product leads to higher and more intense computation.

 

Our solution

Machine learning can be used to remove canopy and buildings, although some post-processing is still needed to create hydrologically correct DTMs. We will next build such a system for the whole world (compare with FABDEM) and then also derive some key terrain variables that can be used for various projects.

Integration of WhiteBoxTool developed by a member in ISG, Prof. John Lindsay. Powered by the programme, the efficiency of connecting hydrological and parallelization improves dramatically.

Monthly soil moisture index in Europe for 2017

Who will benefit?

Civil protection agencies, agricultural and environmental agencies, researchers, municipalities, insurance companies, water resource management organizations, as well as the International Society for Geomorphometry will all benefit from this use case.