The showcase exemplifies how IQmulus could respond to the requirements and expectations of expert users (typically hydrologists or geologists) supporting decision makers in civil protection in events related to flooding. The goal is to demonstrate the usefulness of IQmulus to compute rapidly, even roughly, parameters needed to run flooding simulation or landslide models.
Organizations involved: CNR-IMATI (Italy), Regione Liguria (Italy)
The workflow addresses extraction of drainage basins from terrain model built from large data set acquired by Lidar, and efficient indexing and partitioning of such data sets for distributed processing of workflow in the cloud. The resulting models targets hydrographic and cartographic professionals.
Organizations involved: CNR-IMATI (Italy), Regione Liguria (Italy)
The workflow address approximation of precipitation fields from rain data sensors. From the data measured, accumulated values of rain in standard time intervals are computed (typically, 30min, 1h, 2h, 3h, 6h, 12h, 24h). Based on these accumulated values, the precipitation field is computed over the whole area of interest and the precipitation maxima are analysed, together with their temporal evolution.
Organizations involved: FÖMI (Hungary)
The workflow provides a highly automated pre-processing and classification of satellite images for detection of flooded and waterlogged areas. This complex workflow contains multiple algorithms. Compared to the current („as-is“) solution implemented using commercial software components at FÖMI, it provides a higher level of automation via smarter algorithms; it improves overall processing time and implies a better use of human resources.
Organizations involved: UBO (France)
The workflows targets to detect slow-moving landslides from a time-series of Very High Resolution satellite images. Slow-moving landslides are widespread in many landscapes with significant impacts on the topographic relief, sediment transfer and human settlements, whereas their area-wide mapping and monitoring in mountainous terrain is still challenging. The growing archives of optical remote sensing images offer a great potential for the operational detection and monitoring of surface motion in such areas. This workflow provides tools for measuring piece‐wise locally the shift among two or more co-registered datasets provided in GeoTIFF format.