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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:

Decision-Tree, Rule-Based, and Random Forest Classification of High-Resolution Multispectral Imagery for Wetland Mapping and Inventory
Tedros Berhane, Charles R. Lane, Qiusheng Wu, et al.
Remote Sensing (2018) Vol. 10, Iss. 4, pp. 580-580
Open Access | Times Cited: 214

Showing 1-25 of 214 citing articles:

Support Vector Machine Versus Random Forest for Remote Sensing Image Classification: A Meta-Analysis and Systematic Review
Mohammadreza Sheykhmousa, Masoud Mahdianpari, Hamid Ghanbari, et al.
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (2020) Vol. 13, pp. 6308-6325
Open Access | Times Cited: 739
Application of the Random Forest Classifier to Map Irrigated Areas Using Google Earth Engine
James Magidi, Luxon Nhamo, Sylvester Mpandeli, et al.
Remote Sensing (2021) Vol. 13, Iss. 5, pp. 876-876
Open Access | Times Cited: 123
A tree-based stacking ensemble technique with feature selection for network intrusion detection
Md. Mamunur Rashid, Joarder Kamruzzaman, Tasadduq Imam, et al.
Applied Intelligence (2022) Vol. 52, Iss. 9, pp. 9768-9781
Open Access | Times Cited: 108
Ensemble regression based on polynomial regression-based decision tree and its application in the in-situ data of tunnel boring machine
Maolin Shi, Weifei Hu, Muxi Li, et al.
Mechanical Systems and Signal Processing (2022) Vol. 188, pp. 110022-110022
Closed Access | Times Cited: 98
Development of a spatially complete floodplain map of the conterminous United States using random forest
Sean A. Woznicki, Jeremy Baynes, Stephanie Panlasigui, et al.
The Science of The Total Environment (2018) Vol. 647, pp. 942-953
Open Access | Times Cited: 129
Coastal Wetland Mapping Using Ensemble Learning Algorithms: A Comparative Study of Bagging, Boosting and Stacking Techniques
Li Wen, Michael G. Hughes
Remote Sensing (2020) Vol. 12, Iss. 10, pp. 1683-1683
Open Access | Times Cited: 116
Comparison between random forest and support vector machine algorithms for LULC classification
Cengiz Avci, Muhammed BUDAK, Nur Yağmur, et al.
International Journal of Engineering and Geosciences (2021) Vol. 8, Iss. 1, pp. 1-10
Open Access | Times Cited: 103
Comparison of multi-source satellite images for classifying marsh vegetation using DeepLabV3 Plus deep learning algorithm
Man Liu, Bolin Fu, Shuyu Xie, et al.
Ecological Indicators (2021) Vol. 125, pp. 107562-107562
Open Access | Times Cited: 89
Automated Mapping of Antarctic Supraglacial Lakes Using a Machine Learning Approach
Mariel Dirscherl, A.J. Dietz, Christof Kneisel, et al.
Remote Sensing (2020) Vol. 12, Iss. 7, pp. 1203-1203
Open Access | Times Cited: 79
Hyperspectral remote sensing for assessment of chlorophyll sufficiency levels in mature oil palm (Elaeis guineensis) based on frond numbers: Analysis of decision tree and random forest
Amiratul Diyana Amirruddin, Farrah Melissa Muharam, Mohd Hasmadi Ismail, et al.
Computers and Electronics in Agriculture (2020) Vol. 169, pp. 105221-105221
Open Access | Times Cited: 74
Cotton Classification Method at the County Scale Based on Multi-Features and Random Forest Feature Selection Algorithm and Classifier
Fei Hao, Zehua Fan, Chengkun Wang, et al.
Remote Sensing (2022) Vol. 14, Iss. 4, pp. 829-829
Open Access | Times Cited: 65
Evaluating capabilities of machine learning algorithms for aquatic vegetation classification in temperate wetlands using multi-temporal Sentinel-2 data
Erika Piaser, Paolo Villa
International Journal of Applied Earth Observation and Geoinformation (2023) Vol. 117, pp. 103202-103202
Open Access | Times Cited: 28
Comparison of high-resolution NAIP and unmanned aerial vehicle (UAV) imagery for natural vegetation communities classification using machine learning approaches
Parth Bhatt, Ann L. Maclean
GIScience & Remote Sensing (2023) Vol. 60, Iss. 1
Open Access | Times Cited: 25
U-Net Convolutional Networks for Mining Land Cover Classification Based on High-Resolution UAV Imagery
Tuan Linh Giang, Kinh Bac Dang, Quang Toan Le, et al.
IEEE Access (2020) Vol. 8, pp. 186257-186273
Open Access | Times Cited: 69
Remote Sensing of Boreal Wetlands 2: Methods for Evaluating Boreal Wetland Ecosystem State and Drivers of Change
L. Chasmer, Craig Mahoney, Koreen Millard, et al.
Remote Sensing (2020) Vol. 12, Iss. 8, pp. 1321-1321
Open Access | Times Cited: 60
Performance comparison of deep learning and machine learning methods in determining wetland water areas using EuroSAT dataset
Mehmet Akıf Günen
Environmental Science and Pollution Research (2021) Vol. 29, Iss. 14, pp. 21092-21106
Closed Access | Times Cited: 51
A novel classifier for improving wetland mapping by integrating image fusion techniques and ensemble machine learning classifiers
Javed Mallick, Swapan Talukdar, Shahfahad, et al.
Ecological Informatics (2021) Vol. 65, pp. 101426-101426
Closed Access | Times Cited: 45
A Training Sample Migration Method for Wetland Mapping and Monitoring Using Sentinel Data in Google Earth Engine
Erfan Fekri, Hooman Latifi, Meisam Amani, et al.
Remote Sensing (2021) Vol. 13, Iss. 20, pp. 4169-4169
Open Access | Times Cited: 42
Land use change and climate dynamics in the Rift Valley Lake Basin, Ethiopia
Ayenew D. Ayalew, Paul D. Wagner, Dejene Sahlu, et al.
Environmental Monitoring and Assessment (2022) Vol. 194, Iss. 11
Open Access | Times Cited: 38
Identification of Artificial Levees in the Contiguous United States
Richard L. Knox, Ryan R. Morrison, Ellen Wohl
Water Resources Research (2022) Vol. 58, Iss. 4
Open Access | Times Cited: 34
A satellite-based monitoring system for quantifying surface water and mesic vegetation dynamics in a semi-arid region
Nicholas E. Kolarik, Anand Roopsind, Amy Pickens, et al.
Ecological Indicators (2023) Vol. 147, pp. 109965-109965
Open Access | Times Cited: 22
Machine learning approaches for estimating apricot drying characteristics in various advanced and conventional dryers
Mohammad Kaveh, Necati Çetin, Esmail Khalife, et al.
Journal of Food Process Engineering (2023) Vol. 46, Iss. 12
Open Access | Times Cited: 18
Probabilistic coastal wetland mapping with integration of optical, SAR and hydro-geomorphic data through stacking ensemble machine learning model
Pankaj Prasad, Victor J. Loveson, Mahender Kotha
Ecological Informatics (2023) Vol. 77, pp. 102273-102273
Closed Access | Times Cited: 17
Classification of Crops, Pastures, and Tree Plantations along the Season with Multi-Sensor Image Time Series in a Subtropical Agricultural Region
Cecília Lira Melo de Oliveira Santos, Rubens Augusto Camargo Lamparelli, Gleyce Kelly Dantas Araújo Figueiredo, et al.
Remote Sensing (2019) Vol. 11, Iss. 3, pp. 334-334
Open Access | Times Cited: 48
Tracking the Land Use/Land Cover Change in an Area with Underground Mining and Reforestation via Continuous Landsat Classification
Jiaxin Mi, Yongjun Yang, Shaoliang Zhang, et al.
Remote Sensing (2019) Vol. 11, Iss. 14, pp. 1719-1719
Closed Access | Times Cited: 47
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