Deep-Learning-Based Retrieval of an Orange Band Sensitive to Cyanobacteria for Landsat-8/9 and Sentinel-2
Author:
Affiliation:
1. Digital Society Center, Fondazione Bruno Kessler, Trento, Italy
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Atmospheric Science,Computers in Earth Sciences
Link
http://xplorestaging.ieee.org/ielx7/4609443/9973430/10101812.pdf?arnumber=10101812
Reference44 articles.
1. Bathymetry retrieval from CubeSat image sequences with short time lags;niroumand-jadidi;Int J Appl Earth Observ Geoinf,2022
2. Passive optical remote sensing of cyanobacteria and other intense phytoplankton blooms in coastal and inland waters
3. Acolite/data/RSR at main acolite/acolite Github;vanhellemont,2022
4. Water Quality Retrieval from PRISMA Hyperspectral Images: First Experience in a Turbid Lake and Comparison with Sentinel-2
5. River Bathymetry Retrieval From Landsat-9 Images Based on Neural Networks and Comparison to SuperDove and Sentinel-2
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1. Monitoring Water Diversity and Water Quality with Remote Sensing and Traits;Remote Sensing;2024-07-01
2. Harmful Cyanobacterial Blooms: Going beyond the “Green” to Monitor and Predict HCBs;Hydrobiology;2024-01-02
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