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Water Quality Monitoring by Remote Sensing and AI
Retrieval of Water Quality Parameters in Lake Ontario Based on Hyperspectral Remote Sensing Data and Intelligent Algorithms
EGU2020-1869 https://doi.org/10.5194/egusphere-egu2020-1869 EGU General Assembly 2020
© Author(s) 2020. This work is distributed under the Creative Commons Attribution 4.0 License.
Yu Li1,2, Youyue Sun1, Jinhui Jeanne Huang1, and Edward McBean2
1 Nankai University, Sino-Canada Joint R&D Centre for Water and Environmental Safety, College of Environmental Science and Engineering, Tianjin, China (email@example.com) 2 School of Engineering, University of Guelph, N1G 2W1, Canada
A machine learning-based strategy for estimating non-optically active water quality parameters using Sentinel-2 imagery
International Journal of Remote Sensing
ISSN: (Print) (Online) Journal homepage: https://www.tandfonline.com/loi/tres20
Hongwei Guo , Jinhui Jeanne Huang , Bowen Chen , Xiaolong Guo & Vijay P. Singh (2021) A machine learning-based strategy for estimating non-optically active water quality parameters using Sentinel-2 imagery, International Journal of Remote Sensing, 42:5, 1841-1866, DOI: 10.1080/01431161.2020.1846222
Performance of deep learning in mapping water quality of Lake Simcoe with long-term Landsat archive
Publishing by ISPRS Journal of Photogrammetry and Remote Sensing.
HongweiGuo, Shang Tian, Jinhui Jeanne Huang, Xiaotong Zhu, Bo Wang, Zijie Zhang
College of Environmental Science and Engineering/Sino-Canada Joint R&D Centre for Water and Environmental Safety, Nankai University, Tianjin 300457, China
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