Please choose appropriate filter values to avoid request timed out.
The query result is limited to 1000 geofeatures.
Fill the temporal, semantic filters.
Fill the spatial filter. Draw the area of study by clicking on the Draw
Click on the map to add the points that make up your polygon. Double-click to
Click on Go to launch the search.
Zoom the map and choose your desired geofeatures to show corresponding
CANDELA aims at building a platform who delivers building blocks and services which enable users to
quickly use, manipulate, explore and process Copernicus data. The main objective of CANDELA is to
bridge the gap between big data technology and the Earth Observation data user community.
Semantic search tool
By semantic search we mean services to retrieve images through a semantic description of their
content (i.e. places, type of vegetation, ndvi), their location and date, or any semantic feature
coming from open data and linked to the image context (weather parameters, names of locations,
territorial units etc.). A semantic query specifies constraints on the data and their values.
Results will be not only links towards images but also some data related to their content (i.e. type
of vegetation, cities and their population, weather measures. This version of the tools is limited
to generalization restriction and available datasets.
Two use cases were firstly demonstrated.
Severe weather conditions cause huge damage in vineyards resulting in a significant loss in wine
production. The developed analytic tools in the CANDELA project will allow actors in the field of
wine production to assess the damage in their parcels.
The developed tools in the project and the access to the large amount of Copernicus data
will help building a complete damage profile for vineyard parcels belonging to farmers.
This file will be ready to be transmitted to insurance companies in case of natural hazards.
Additionally, the insurance companies will be able to rapidly get information on parcels damage.
Moreover, the large coverage of Copernicus data will save a huge budget the insurance companies
dedicate for field visits to estimate the damage levels.
forest health indicators
The objective of this use case is to detect Forest areas of reduced health. Such areas would be
later monitor and investigated by potential users. Additional resources can be allocated to such
to prevent potential damage. Detection should be carried out based on forest health indicators that
will measure in effective, repetitive and comparative way the condition of forest to provide