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.

La Pegna, V., Del Frate, F., De Santis, D., Cappelli, D., Frezza, M., Dragone, R., et al. (2024). The Econet Project: use of AI for surface water monitoring with satellite and ground sensor data. In IGARSS 2024: 2024 IEEE International Geoscience and Remote Sensing Symposium: proceedings (pp.978-981). New York : IEEE [10.1109/igarss53475.2024.10640422].

The Econet Project: use of AI for surface water monitoring with satellite and ground sensor data

La Pegna, Valeria;Del Frate, Fabio;De Santis, Davide;Cappelli, Dario;Frezza, Martina;Licciardi, Giorgio;
2024-01-01

Abstract

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.
2024 IEEE International Geoscience and Remote Sensing Symposium (IGARSS 2024)
Athens, Greece
2024
IEEE, Geoscience and Remote Sensing Society (GRSS)
Rilevanza internazionale
2024
Settore IINF-02/A - Campi elettromagnetici
English
Artificial Intelligence
Bio/chemosensoristic devices
Hyperspectral remote sensing
Water quality
Intervento a convegno
La Pegna, V., Del Frate, F., De Santis, D., Cappelli, D., Frezza, M., Dragone, R., et al. (2024). The Econet Project: use of AI for surface water monitoring with satellite and ground sensor data. In IGARSS 2024: 2024 IEEE International Geoscience and Remote Sensing Symposium: proceedings (pp.978-981). New York : IEEE [10.1109/igarss53475.2024.10640422].
La Pegna, V; Del Frate, F; De Santis, D; Cappelli, D; Frezza, M; Dragone, R; Grasso, G; Zane, D; Brunetti, B; Foglia, S; Licciardi, G; Sacco, P; Tapet...espandi
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2108/394783
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