The optimal method for water quality parameters retrieval of urban river based on machine learning algorithms using remote sensing images
Author:
Affiliation:
1. School of Earth Science and Resources, Chang’an University, Xi’an, China
2. School of Geological Engineering and Geomatics, Chang’an University, Xi’an, China
Funder
the Department of Science and Technology of the Shaanxi Province’s key research and development projects
Publisher
Informa UK Limited
Subject
General Earth and Planetary Sciences
Link
https://www.tandfonline.com/doi/pdf/10.1080/01431161.2023.2209918
Reference48 articles.
1. Monitoring Water Quality of Valle de Bravo Reservoir, Mexico, Using Entire Lifespan of MERIS Data and Machine Learning Approaches
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3. Improved red-edge chlorophyll-a detection for Sentinel 2
4. A machine learning approach to estimate chlorophyll-a from Landsat-8 measurements in inland lakes
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