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OpenAlex Citation Counts

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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.

Requested Article:

Machine learning-based inversion of water quality parameters in typical reach of the urban river by UAV multispectral data
Botao Chen, Xidong Mu, Peng Chen, et al.
Ecological Indicators (2021) Vol. 133, pp. 108434-108434
Open Access | Times Cited: 87

Showing 1-25 of 87 citing articles:

Machine learning and remote sensing integration for leveraging urban sustainability: A review and framework
Fei Li, Tan Yiğitcanlar, Madhav Prasad Nepal, et al.
Sustainable Cities and Society (2023) Vol. 96, pp. 104653-104653
Open Access | Times Cited: 101
Applications of XGBoost in water resources engineering: A systematic literature review (Dec 2018–May 2023)
Majid Niazkar, Andrea Menapace, Bruno Brentan, et al.
Environmental Modelling & Software (2024) Vol. 174, pp. 105971-105971
Closed Access | Times Cited: 84
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
Urban river water quality monitoring based on self-optimizing machine learning method using multi-source remote sensing data
Peng Chen, Biao Wang, Yanlan Wu, et al.
Ecological Indicators (2022) Vol. 146, pp. 109750-109750
Open Access | Times Cited: 48
Retrieving SPAD Values of Summer Maize Using UAV Hyperspectral Data Based on Multiple Machine Learning Algorithm
Bilige Sudu, Guangzhi Rong, Suri Guga, et al.
Remote Sensing (2022) Vol. 14, Iss. 21, pp. 5407-5407
Open Access | Times Cited: 47
Multi-sensor and multi-platform retrieval of water chlorophyll a concentration in karst wetlands using transfer learning frameworks with ASD, UAV, and Planet CubeSate reflectance data
Bolin Fu, Sunzhe Li, Zhinan Lao, et al.
The Science of The Total Environment (2023) Vol. 901, pp. 165963-165963
Closed Access | Times Cited: 33
Impact of land use on water quality in buffer zones at different scales in the Poyang Lake, middle reaches of the Yangtze River basin
Wenyu Wang, Peng Yang, Junshi Xia, et al.
The Science of The Total Environment (2023) Vol. 896, pp. 165161-165161
Closed Access | Times Cited: 32
Application of Remote Sensing Technology in Water Quality Monitoring: From Traditional Approaches to Artificial Intelligence
Yuan Sun, Denghui Wang, P. R. Li, et al.
Water Research (2024) Vol. 267, pp. 122546-122546
Closed Access | Times Cited: 14
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
A novel hierarchical approach to insight to spectral characteristics in surface water of karst wetlands and estimate its non-optically active parameters using field hyperspectral data
Bolin Fu, Sunzhe Li, Zhinan Lao, et al.
Water Research (2024) Vol. 257, pp. 121673-121673
Closed Access | Times Cited: 10
Research progress of inland river water quality monitoring technology based on unmanned aerial vehicle hyperspectral imaging technology
Xueqin Bai, Jiajia Wang, Ruya Chen, et al.
Environmental Research (2024) Vol. 257, pp. 119254-119254
Closed Access | Times Cited: 10
Estimation algorithm for chlorophyll-a concentrations in water from hyperspectral images based on feature derivation and ensemble learning
Jiawei Zhang, Pingjie Fu, Fei Meng, et al.
Ecological Informatics (2022) Vol. 71, pp. 101783-101783
Closed Access | Times Cited: 31
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
Water Quality Prediction of Small-Micro Water Body Based on the Intelligent-Algorithm-Optimized Support Vector Machine Regression Method and Unmanned Aerial Vehicles Multispectral Data
Ke Yao, Yujie Chen, Yucheng Li, et al.
Sustainability (2024) Vol. 16, Iss. 2, pp. 559-559
Open Access | Times Cited: 8
Estimation of the Biogeochemical and Physical Properties of Lakes Based on Remote Sensing and Artificial Intelligence Applications
Kaire Toming, Hui Liu, Tuuli Soomets, et al.
Remote Sensing (2024) Vol. 16, Iss. 3, pp. 464-464
Open Access | Times Cited: 8
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
The global progress on the non-point source pollution research from 2012 to 2021: a bibliometric analysis
Zijian Xie, Chun Ye, Chunhua Li, et al.
Environmental Sciences Europe (2022) Vol. 34, Iss. 1
Open Access | Times Cited: 25
Evaluating optically and non-optically active water quality and its response relationship to hydro-meteorology using multi-source data in Poyang Lake, China
Bolin Fu, Zhinan Lao, Yiyin Liang, et al.
Ecological Indicators (2022) Vol. 145, pp. 109675-109675
Open Access | Times Cited: 24
Medium-Sized Lake Water Quality Parameters Retrieval Using Multispectral UAV Image and Machine Learning Algorithms: A Case Study of the Yuandang Lake, China
Ying Lo, Lang Fu, Tiancheng Lu, et al.
Drones (2023) Vol. 7, Iss. 4, pp. 244-244
Open Access | Times Cited: 16
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
A Survey on UAV Applications in Smart City Management: Challenges, Advances, and Opportunities
Haoran Xu, Lizhe Wang, Wei Han, et al.
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (2023) Vol. 16, pp. 8982-9010
Open Access | Times Cited: 15
A novel framework to predict chlorophyll-a concentrations in water bodies through multi-source big data and machine learning algorithms
Hamed Karimian, Jinhuang Huang, Youliang Chen, et al.
Environmental Science and Pollution Research (2023) Vol. 30, Iss. 32, pp. 79402-79422
Closed Access | Times Cited: 14
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
Synergistic Use of Earth Observation Driven Techniques to Support the Implementation of Water Framework Directive in Europe: A Review
Nikiforos Samarinas, Marios Spiliotopoulos, Nikolaos Tziolas, et al.
Remote Sensing (2023) Vol. 15, Iss. 8, pp. 1983-1983
Open Access | Times Cited: 12
Quantitative Retrieval of Chlorophyll-a Concentrations in the Bohai–Yellow Sea Using GOCI Surface Reflectance Products
Jiru Wang, Jiakui Tang, Wuhua Wang, et al.
Remote Sensing (2023) Vol. 15, Iss. 22, pp. 5285-5285
Open Access | Times Cited: 12
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