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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:

Google Earth Engine for geo-big data applications: A meta-analysis and systematic review
Haifa Tamiminia, Bahram Salehi, Masoud Mahdianpari, et al.
ISPRS Journal of Photogrammetry and Remote Sensing (2020) Vol. 164, pp. 152-170
Closed Access | Times Cited: 945

Showing 1-25 of 945 citing articles:

Google Earth Engine Cloud Computing Platform for Remote Sensing Big Data Applications: A Comprehensive Review
Meisam Amani, Arsalan Ghorbanian, Seyed Ali Ahmadi, et al.
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (2020) Vol. 13, pp. 5326-5350
Open Access | Times Cited: 807
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: 441
Progress and Trends in the Application of Google Earth and Google Earth Engine
Qiang Zhao, Le Yu, Xuecao Li, et al.
Remote Sensing (2021) Vol. 13, Iss. 18, pp. 3778-3778
Open Access | Times Cited: 179
A practical approach to reconstruct high-quality Landsat NDVI time-series data by gap filling and the Savitzky–Golay filter
Yang Chen, Ruyin Cao, Jin Chen, et al.
ISPRS Journal of Photogrammetry and Remote Sensing (2021) Vol. 180, pp. 174-190
Closed Access | Times Cited: 174
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: 172
A review of Earth Artificial Intelligence
Ziheng Sun, L. Sandoval, Robert Crystal‐Ornelas, et al.
Computers & Geosciences (2022) Vol. 159, pp. 105034-105034
Open Access | Times Cited: 170
Land Use/Land Cover Changes and Their Driving Factors in the Northeastern Tibetan Plateau Based on Geographical Detectors and Google Earth Engine: A Case Study in Gannan Prefecture
Chenli Liu, Wenlong Li, Gaofeng Zhu, et al.
Remote Sensing (2020) Vol. 12, Iss. 19, pp. 3139-3139
Open Access | Times Cited: 169
A Systematic Review of Landsat Data for Change Detection Applications: 50 Years of Monitoring the Earth
Mohammadali Hemati, Mahdi Hasanlou, Masoud Mahdianpari, et al.
Remote Sensing (2021) Vol. 13, Iss. 15, pp. 2869-2869
Open Access | Times Cited: 151
Google Earth Engine and Artificial Intelligence (AI): A Comprehensive Review
Liping Yang, Joshua Driscol, Sarigai Sarigai, et al.
Remote Sensing (2022) Vol. 14, Iss. 14, pp. 3253-3253
Open Access | Times Cited: 150
Remote Sensing Big Data for Water Environment Monitoring: Current Status, Challenges, and Future Prospects
Jinyue Chen, Shuisen Chen, Rao Fu, et al.
Earth s Future (2022) Vol. 10, Iss. 2
Open Access | Times Cited: 129
Remote sensing of soil degradation: Progress and perspective
Jingzhe Wang, Jianing Zhen, Weifang Hu, et al.
International Soil and Water Conservation Research (2023) Vol. 11, Iss. 3, pp. 429-454
Open Access | Times Cited: 126
Evaluation and analysis of ecosystem service value based on land use/cover change in Dongting Lake wetland
Xiangren Long, Hui Lin, Xuexian An, et al.
Ecological Indicators (2022) Vol. 136, pp. 108619-108619
Open Access | Times Cited: 125
Quantitative spatial analysis of vegetation dynamics and potential driving factors in a typical alpine region on the northeastern Tibetan Plateau using the Google Earth Engine
Chenli Liu, Wenlong Li, Wenying Wang, et al.
CATENA (2021) Vol. 206, pp. 105500-105500
Closed Access | Times Cited: 116
Analysis of Land Use and Land Cover Using Machine Learning Algorithms on Google Earth Engine for Munneru River Basin, India
Kotapati Narayana Loukika, K. Venkata Reddy, Venkataramana Sridhar
Sustainability (2021) Vol. 13, Iss. 24, pp. 13758-13758
Open Access | Times Cited: 113
Comparison of Land Use Land Cover Classifiers Using Different Satellite Imagery and Machine Learning Techniques
Sana Basheer, Xiuquan Wang, Aitazaz A. Farooque, et al.
Remote Sensing (2022) Vol. 14, Iss. 19, pp. 4978-4978
Open Access | Times Cited: 112
Google Earth Engine for large-scale land use and land cover mapping: an object-based classification approach using spectral, textural and topographical factors
Hossein Shafizadeh‐Moghadam, Morteza Khazaei, Seyed Kazem Alavipanah, et al.
GIScience & Remote Sensing (2021) Vol. 58, Iss. 6, pp. 914-928
Open Access | Times Cited: 104
Spatiotemporal Change Analysis and Prediction of Future Land Use and Land Cover Changes Using QGIS MOLUSCE Plugin and Remote Sensing Big Data: A Case Study of Linyi, China
Rizwan Muhammad, Wenyin Zhang, Zaheer Abbas, et al.
Land (2022) Vol. 11, Iss. 3, pp. 419-419
Open Access | Times Cited: 103
Updated soil salinity with fine spatial resolution and high accuracy: The synergy of Sentinel-2 MSI, environmental covariates and hybrid machine learning approaches
Xiangyu Ge, Jianli Ding, Dexiong Teng, et al.
CATENA (2022) Vol. 212, pp. 106054-106054
Closed Access | Times Cited: 84
Bibliometric Analysis of Global NDVI Research Trends from 1985 to 2021
Yang Xu, Yaping Yang, Xiaona Chen, et al.
Remote Sensing (2022) Vol. 14, Iss. 16, pp. 3967-3967
Open Access | Times Cited: 74
Google Earth Engine: A Global Analysis and Future Trends
Andrés Velástegui-Montoya, Néstor Montalván-Burbano, Paúl Carrión-Mero, et al.
Remote Sensing (2023) Vol. 15, Iss. 14, pp. 3675-3675
Open Access | Times Cited: 73
Long-Term Landsat-Based Monthly Burned Area Dataset for the Brazilian Biomes Using Deep Learning
Ane Alencar, Vera L. S. Arruda, Wallace Vieira da Silva, et al.
Remote Sensing (2022) Vol. 14, Iss. 11, pp. 2510-2510
Open Access | Times Cited: 72
U-net-based semantic classification for flood extent extraction using SAR imagery and GEE platform: A case study for 2019 central US flooding
Zhouyayan Li, İbrahim Demir
The Science of The Total Environment (2023) Vol. 869, pp. 161757-161757
Open Access | Times Cited: 69
Mapping 21st Century Global Coastal Land Reclamation
Dhritiraj Sengupta, Young Rae Choi, Bo Tian, et al.
Earth s Future (2023) Vol. 11, Iss. 2
Open Access | Times Cited: 68
Artificial intelligence for geoscience: Progress, challenges and perspectives
Tianjie Zhao, Sheng Wang, Chaojun Ouyang, et al.
The Innovation (2024) Vol. 5, Iss. 5, pp. 100691-100691
Open Access | Times Cited: 51
Landscape fires disproportionally affect high conservation value temperate peatlands, meadows, and deciduous forests, but only under low moisture conditions
Máire Kirkland, Philip W. Atkinson, James W. Pearce‐Higgins, et al.
The Science of The Total Environment (2023) Vol. 884, pp. 163849-163849
Closed Access | Times Cited: 49
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