The Econet Project: Use of AI for Surface Water Monitoring with Satellite and Ground Sensor Data

The activities undertaken within the EcoNet project aim at the design and development of an integrated system for the monitoring of changes in surface waters natural status based on different sensoristic techniques. The proposed integration approach combines ground measurements and hyperspectral sat...

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Bibliographic Details
Main Authors: La Pegna, Valeria, Del Frate, Fabio, De Santis, Davide, Cappelli, Dario, Frezza, Martina, Dragone, Roberto, Grasso, Gerardo, Zane, Daniela, Brunetti, Bruno, Foglia, Sabrina, Licciardi, Giorgio, Sacco, Patrizia, Tapete, Deodato
Format: Conference Proceeding
Language:English
Subjects:
Artificial intelligence
bio/chemosensoristic devices
Environmental monitoring
Hyperspectral remote sensing
Satellite images
Satellites
Training
Water monitoring
Water quality
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Summary:The activities undertaken within the EcoNet project aim at the design and development of an integrated system for the monitoring of changes in surface waters natural status based on different sensoristic techniques. The proposed integration approach combines ground measurements and hyperspectral satellite images. The promising dialogue that occurs between these two multi-sensoristic technologies requires the implementation of appropriate tools for data handling and analysis which in this work are represented by Artificial Intelligence (AI), particularly suitable to retrieve very subtle relationships among the data. This integration can open enormous potential for overcoming the limits of traditional environmental monitoring and diagnostic techniques.
ISSN:2153-7003
DOI:10.1109/IGARSS53475.2024.10640422