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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

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Showing 1-25 of 70 citing articles:

Monitoring water quality using proximal remote sensing technology
Xiao Sun, Yunlin Zhang, Kun� Shi, et al.
The Science of The Total Environment (2021) Vol. 803, pp. 149805-149805
Closed Access | Times Cited: 129
Developing a novel tool for assessing the groundwater incorporating water quality index and machine learning approach
Abdul Majed Sajib, Mir Talas Mahammad Diganta, Azizur Rahman, et al.
Groundwater for Sustainable Development (2023) Vol. 23, pp. 101049-101049
Open Access | Times Cited: 60
A Comprehensive Survey of Machine Learning Methodologies with Emphasis in Water Resources Management
Maria Drogkoula, Konstantinos Kokkinos, Nicholas Samaras
Applied Sciences (2023) Vol. 13, Iss. 22, pp. 12147-12147
Open Access | Times Cited: 51
UAV-Borne Hyperspectral Imaging Remote Sensing System Based on Acousto-Optic Tunable Filter for Water Quality Monitoring
Hong Liu, Tao Yu, Bingliang Hu, et al.
Remote Sensing (2021) Vol. 13, Iss. 20, pp. 4069-4069
Open Access | Times Cited: 66
Evaluation of energy extraction of PV systems affected by environmental factors under real outdoor conditions
Muhammed A. Hassan, Nadjem Bailek, Kada Bouchouicha, et al.
Theoretical and Applied Climatology (2022) Vol. 150, Iss. 1-2, pp. 715-729
Open Access | Times Cited: 60
UAV Multispectral Image-Based Urban River Water Quality Monitoring Using Stacked Ensemble Machine Learning Algorithms—A Case Study of the Zhanghe River, China
Yi Xiao, Yahui Guo, Guodong Yin, et al.
Remote Sensing (2022) Vol. 14, Iss. 14, pp. 3272-3272
Open Access | Times Cited: 51
Improved weighted ensemble learning for predicting the daily reference evapotranspiration under the semi-arid climate conditions
El-Sayed M. El-kenawy, Bilel Zerouali, Nadjem Bailek, et al.
Environmental Science and Pollution Research (2022) Vol. 29, Iss. 54, pp. 81279-81299
Closed Access | Times Cited: 45
Water Quality Chl-a Inversion Based on Spatio-Temporal Fusion and Convolutional Neural Network
Haibo Yang, Yao Du, Hongling Zhao, et al.
Remote Sensing (2022) Vol. 14, Iss. 5, pp. 1267-1267
Open Access | Times Cited: 39
UAV-borne hyperspectral estimation of nitrogen content in tobacco leaves based on ensemble learning methods
Mingzheng Zhang, Tianen Chen, Xiaohe Gu, et al.
Computers and Electronics in Agriculture (2023) Vol. 211, pp. 108008-108008
Closed Access | Times Cited: 24
Water Quality Inversion of a Typical Rural Small River in Southeastern China Based on UAV Multispectral Imagery: A Comparison of Multiple Machine Learning Algorithms
Yujie Chen, Ke Yao, Beibei Zhu, et al.
Water (2024) Vol. 16, Iss. 4, pp. 553-553
Open Access | Times Cited: 11
Retrieval of Water Quality from UAV-Borne Hyperspectral Imagery: A Comparative Study of Machine Learning Algorithms
Qikai Lu, Wei Si, Lifei Wei, et al.
Remote Sensing (2021) Vol. 13, Iss. 19, pp. 3928-3928
Open Access | Times Cited: 51
Monitoring Water Quality of the Haihe River Based on Ground-Based Hyperspectral Remote Sensing
Qi Cao, Gongliang Yu, Shengjie Sun, et al.
Water (2021) Vol. 14, Iss. 1, pp. 22-22
Open Access | Times Cited: 45
Multispectral Remote Sensing for Estimating Water Quality Parameters: A Comparative Study of Inversion Methods Using Unmanned Aerial Vehicles (UAVs)
Yong Yan, Ying Wang, Cheng Yu, et al.
Sustainability (2023) Vol. 15, Iss. 13, pp. 10298-10298
Open Access | Times Cited: 22
Monitor water quality through retrieving water quality parameters from hyperspectral images using graph convolution network with superposition of multi-point effect: A case study in Maozhou River
Yishan Zhang, Xin Kong, Licui Deng, et al.
Journal of Environmental Management (2023) Vol. 342, pp. 118283-118283
Closed Access | Times Cited: 20
Estimation of water quality variables based on machine learning model and cluster analysis-based empirical model using multi-source remote sensing data in inland reservoirs, South China
Di Tian, Xinfeng Zhao, Lei Gao, et al.
Environmental Pollution (2023) Vol. 342, pp. 123104-123104
Closed Access | Times Cited: 20
A Machine-Learning-Based Framework for Retrieving Water Quality Parameters in Urban Rivers Using UAV Hyperspectral Images
Liu Bing, Tianhong Li
Remote Sensing (2024) Vol. 16, Iss. 5, pp. 905-905
Open Access | Times Cited: 8
Satellite and Machine Learning Monitoring of Optically Inactive Water Quality Variability in a Tropical River
Ning Li, Ziyu Ning, Miao Chen, et al.
Remote Sensing (2022) Vol. 14, Iss. 21, pp. 5466-5466
Open Access | Times Cited: 24
Machine learning algorithm inversion experiment and pollution analysis of water quality parameters in urban small and medium-sized rivers based on UAV multispectral data
Yikai Hou, Anbing Zhang, Rulan Lv, et al.
Environmental Science and Pollution Research (2023) Vol. 30, Iss. 32, pp. 78913-78932
Closed Access | Times Cited: 16
Predicting dissolved oxygen level using Young's double-slit experiment optimizer-based weighting model
Ying Dong, Yuhuan Sun, Zhenkun Liu, et al.
Journal of Environmental Management (2023) Vol. 351, pp. 119807-119807
Closed Access | Times Cited: 16
Remote Sensing for Monitoring Potato Nitrogen Status
Alfadhl Yahya Alkhaled, Philip A. Townsend, Yi Wang
American Journal of Potato Research (2023) Vol. 100, Iss. 1, pp. 1-14
Closed Access | Times Cited: 15
Advancements of remote data acquisition and processing in unmanned vehicle technologies for water quality monitoring: An extensive review
Da Yun Kwon, Jungbin Kim, Seongyeol Park, et al.
Chemosphere (2023) Vol. 343, pp. 140198-140198
Closed Access | Times Cited: 15
Recent Issues and Challenges in the Study of Inland Waters
Ryszard Staniszewski, Beata Messyasz, Piotr Dąbrowski, et al.
Water (2024) Vol. 16, Iss. 9, pp. 1216-1216
Open Access | Times Cited: 5
Spatial-temporal distribution of labeled set bias remote sensing estimation: An implication for supervised machine learning in water quality monitoring
Yadong Zhou, Wen Li, Xiaoyu Cao, et al.
International Journal of Applied Earth Observation and Geoinformation (2024) Vol. 131, pp. 103959-103959
Open Access | Times Cited: 5
Machine learning models for prediction of nutrient concentrations in surface water in an agricultural watershed
Ahmed Elsayed, Sarah Rixon, Jana Levison, et al.
Journal of Environmental Management (2024) Vol. 372, pp. 123305-123305
Open Access | Times Cited: 5
Evaluation of Total Nitrogen in Water via Airborne Hyperspectral Data: Potential of Fractional Order Discretization Algorithm and Discrete Wavelet Transform Analysis
Jinhua Liu, Jianli Ding, Xiangyu Ge, et al.
Remote Sensing (2021) Vol. 13, Iss. 22, pp. 4643-4643
Open Access | Times Cited: 30
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