Earth observation plays a crucial role in supporting policy-making processes and developing some economic areas. A vast amount of earth observation data is collected that can feed AI models and methods and thus help to acquire new knowledge and develop innovative products. This section gives references on on-going projects and presents results in the area of AI in earth observation.
Through the integration of the Earth Observation data in the usage of AI based applications we could give an insight into what is happening with the environment in fragile and hard to reach areas. The areas of interest here are Ukraine and Mali.
Agriculture productivity maps based on satellite images and machine learning algorithms have become powerful tools for understanding and optimizing agricultural practices. By combining the capabilities of satellite imagery and machine learning algorithms,...
A pipeline generation to get and process images from Sentinel-2 for a specific ROI (Region of interest) to display and rescale NVDI values.
5 year dataset with information on when phenological states have been reached in 11 different plots in La Rioja - Spain.