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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:

Implementation of machine-learning classification in remote sensing: an applied review
Aaron E. Maxwell, Timothy A. Warner, Fang Fang
International Journal of Remote Sensing (2018) Vol. 39, Iss. 9, pp. 2784-2817
Open Access | Times Cited: 1538

Showing 1-25 of 1538 citing articles:

Land-Use Land-Cover Classification by Machine Learning Classifiers for Satellite Observations—A Review
Swapan Talukdar, Pankaj Singha, Susanta Mahato, et al.
Remote Sensing (2020) Vol. 12, Iss. 7, pp. 1135-1135
Open Access | Times Cited: 887
A Brief Review of Random Forests for Water Scientists and Practitioners and Their Recent History in Water Resources
Hristos Tyralis, Georgia Papacharalampous, Andreas Langousis
Water (2019) Vol. 11, Iss. 5, pp. 910-910
Open Access | Times Cited: 571
Land cover and land use classification performance of machine learning algorithms in a boreal landscape using Sentinel-2 data
Abdulhakim M. Abdi
GIScience & Remote Sensing (2019) Vol. 57, Iss. 1, pp. 1-20
Open Access | Times Cited: 495
Land Cover Classification using Google Earth Engine and Random Forest Classifier—The Role of Image Composition
Thanh Noi Phan, Verena Kuch, Lukas Lehnert
Remote Sensing (2020) Vol. 12, Iss. 15, pp. 2411-2411
Open Access | Times Cited: 446
Improved land cover map of Iran using Sentinel imagery within Google Earth Engine and a novel automatic workflow for land cover classification using migrated training samples
Arsalan Ghorbanian, Mohammad Kakooei, Meisam Amani, et al.
ISPRS Journal of Photogrammetry and Remote Sensing (2020) Vol. 167, pp. 276-288
Closed Access | Times Cited: 270
Recent Applications of Landsat 8/OLI and Sentinel-2/MSI for Land Use and Land Cover Mapping: A Systematic Review
Michel Eustáquio Dantas Chaves, Michelle Cristina Araújo Picoli, Ieda Del’Arco Sanches
Remote Sensing (2020) Vol. 12, Iss. 18, pp. 3062-3062
Open Access | Times Cited: 259
Evaluation of Sampling and Cross-Validation Tuning Strategies for Regional-Scale Machine Learning Classification
Christopher A. Ramezan, Timothy A. Warner, Aaron E. Maxwell
Remote Sensing (2019) Vol. 11, Iss. 2, pp. 185-185
Open Access | Times Cited: 250
Machine learning in modelling land-use and land cover-change (LULCC): Current status, challenges and prospects
Junye Wang, Michael Bretz, M. Ali Akber Dewan, et al.
The Science of The Total Environment (2022) Vol. 822, pp. 153559-153559
Closed Access | Times Cited: 244
Remote Sensing Approaches for Monitoring Mangrove Species, Structure, and Biomass: Opportunities and Challenges
Tien Dat Pham, Naoto Yokoya, Dieu Tien Bui, et al.
Remote Sensing (2019) Vol. 11, Iss. 3, pp. 230-230
Open Access | Times Cited: 242
A review of machine learning in processing remote sensing data for mineral exploration
Hojat Shirmard, Ehsan Farahbakhsh, R. Dietmar Müller, et al.
Remote Sensing of Environment (2021) Vol. 268, pp. 112750-112750
Open Access | Times Cited: 242
Ecosystem service value assessment of a natural reserve region for strengthening protection and conservation
Srikanta Sannigrahi, Suman Chakraborti, P. K. Joshi, et al.
Journal of Environmental Management (2019) Vol. 244, pp. 208-227
Closed Access | Times Cited: 204
Accuracy Assessment in Convolutional Neural Network-Based Deep Learning Remote Sensing Studies—Part 1: Literature Review
Aaron E. Maxwell, Timothy A. Warner, Luis Andrés Guillén
Remote Sensing (2021) Vol. 13, Iss. 13, pp. 2450-2450
Open Access | Times Cited: 204
Crop type classification using a combination of optical and radar remote sensing data: a review
Aiym Orynbaikyzy, Ursula Geßner, Christopher Conrad
International Journal of Remote Sensing (2019) Vol. 40, Iss. 17, pp. 6553-6595
Closed Access | Times Cited: 197
Lessons learned implementing an operational continuous United States national land change monitoring capability: The Land Change Monitoring, Assessment, and Projection (LCMAP) approach
J. F. Brown, H. Tollerud, Christopher Barber, et al.
Remote Sensing of Environment (2019) Vol. 238, pp. 111356-111356
Open Access | Times Cited: 194
Comparing Deep Neural Networks, Ensemble Classifiers, and Support Vector Machine Algorithms for Object-Based Urban Land Use/Land Cover Classification
Shahab Jozdani, Brian Johnson, Dongmei Chen
Remote Sensing (2019) Vol. 11, Iss. 14, pp. 1713-1713
Open Access | Times Cited: 178
Machine Learning Classification of Mediterranean Forest Habitats in Google Earth Engine Based on Seasonal Sentinel-2 Time-Series and Input Image Composition Optimisation
Salvatore Praticò, Francesco Solano, Salvatore Di Fazio, et al.
Remote Sensing (2021) Vol. 13, Iss. 4, pp. 586-586
Open Access | Times Cited: 176
Advances in Machine Learning Modeling Reviewing Hybrid and Ensemble Methods
Sina Ardabili, Amir Mosavi, Annamária R. Várkonyi-Kóczy
Lecture notes in networks and systems (2020), pp. 215-227
Closed Access | Times Cited: 171
Evaluation of machine learning algorithms for forest stand species mapping using Sentinel-2 imagery and environmental data in the Polish Carpathians
Ewa Grabska‐Szwagrzyk, David Frantz, Katarzyna Ostapowicz
Remote Sensing of Environment (2020) Vol. 251, pp. 112103-112103
Closed Access | Times Cited: 171
A New Deep Generative Network for Unsupervised Remote Sensing Single-Image Super-Resolution
Juan M. Haut, Rubén Fernández-Beltran, Mercedes E. Paoletti, et al.
IEEE Transactions on Geoscience and Remote Sensing (2018) Vol. 56, Iss. 11, pp. 6792-6810
Open Access | Times Cited: 167
City-descriptive input data for urban climate models: Model requirements, data sources and challenges
Valéry Masson, Wieke Heldens, Erwan Bocher, et al.
Urban Climate (2019) Vol. 31, pp. 100536-100536
Open Access | Times Cited: 162
Evaluation of Sentinel-2 time-series for mapping floodplain grassland plant communities
Sébastien Rapinel, Cendrine Mony, Lucie Lecoq, et al.
Remote Sensing of Environment (2019) Vol. 223, pp. 115-129
Open Access | Times Cited: 161
Land Use and Land Cover Mapping Using Sentinel-2, Landsat-8 Satellite Images, and Google Earth Engine: A Comparison of Two Composition Methods
Vahid Nasiri, Azade Deljouei, Fardin Moradi, et al.
Remote Sensing (2022) Vol. 14, Iss. 9, pp. 1977-1977
Open Access | Times Cited: 147
Sensors, Features, and Machine Learning for Oil Spill Detection and Monitoring: A Review
Rami Al‐Ruzouq, Mohamed Barakat A. Gibril, Abdallah Shanableh, et al.
Remote Sensing (2020) Vol. 12, Iss. 20, pp. 3338-3338
Open Access | Times Cited: 146
Land use/cover classification in an arid desert-oasis mosaic landscape of China using remote sensed imagery: Performance assessment of four machine learning algorithms
Genbatu Ge, Zhongjie Shi, Yuanjun Zhu, et al.
Global Ecology and Conservation (2020) Vol. 22, pp. e00971-e00971
Open Access | Times Cited: 142
Mapping temperate forest tree species using dense Sentinel-2 time series
Jan Hemmerling, Dirk Pflugmacher, Patrick Hostert
Remote Sensing of Environment (2021) Vol. 267, pp. 112743-112743
Closed Access | Times Cited: 141
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