The model was designed for tree-crops semantic-segmentation and created using the AI4Copernicus service: “Deep network for pixel-level classification of S2 patches" read more of A model for tree-crops prediction in Sentinel-2 imagery

This service is focused on Long Short-Term Memory Neural Networks for classification and prediction of NDVI values on Sentinel-2 image time series. This service provides trainable models for the crop type mapping task and the prediction, and a pre-trained... read more of AI4Copernicus - Long Short-Term Memory Neural Network for Sentinel-2

The sercvice is focused on the production of monthly composites for agronomical time series of Sentinel-2 images. One of the challenges of crop type mapping at large scale is the definition of a regular temporal sampling grid to perform analysis in a stan... read more of AI4Copernicus - Harmonization of pre-processed Time Series of Sentinel-2 data

THRUST-4RESST is a multifunctional forest condition assessment tool that is based on AI-aided analytics of time-resolved satellite data read more of THRUST-4RESST

AI-RON MAN Wildfire Hazard Risk Assessment scheduled pipeline to continuously update Thermal Anomalies predictions read more of AI-RON MAN Wildfire Hazard Risk Assessment - Pipeline

AI-RON MAN Wildfire Hazard Risk Assessment web application read more of AI-RON MAN Wildfire Hazard Risk Assessment - Webapp

Backend service of AI-RON MAN Wildfire Hazard Risk Assessment platform read more of AI-RON MAN Wildfire Hazard Risk Assessment - Backend service

Frontend of EO4NOWCAST Near Real-Time Soil Moisture Assessment and Pluvial Flood Nowcasting services read more of EO4NOWCAST Near Real-Time Soil Moisture Assessment and Pluvial Flood Nowcasting - Frontend service

Backend of EO4NOWCAST Near Real-Time Soil Moisture Assessment and Pluvial Flood Nowcasting services read more of EO4NOWCAST Near Real-Time Soil Moisture Assessment and Pluvial Flood Nowcasting - Backend service

- Generation of current Soil Moisture (SM) local maps based on the use of a ML model that processes ground-based precipitation measurements and Normalized Difference Moisture Index (NDMI) processed from the last available Copernicus S2 satellite tile. - ... read more of EO4NOWCAST Near Real-Time Soil Moisture Assessment and Pluvial Flood Nowcasting - Pipeline

This asset contains the notebook of the AI model developed in the EO4NOWCAST project, which allows to estimate a current Soil Moisture Map starting from two inputs: - The most recent NDMI map available from Copernicus - The cumulative rainfall map read more of Notebook of AI model to update Soil Moisture Map from Copernicus [EO4NOWCAST]

This AI model developed in the EO4NOWCAST project allows to estimate a current Soil Moisture Map starting from two inputs: - The most recent NDMI map available from Copernicus - The cumulative rainfall map read more of Pre-trained AI model to update NDMI Map from Copernicus [EO4NOWCAST]