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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:

Improved Mapping Results of 10 m Resolution Land Cover Classification in Guangdong, China Using Multisource Remote Sensing Data With Google Earth Engine
Ying Tu, Wei Lang, Le Yu, et al.
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (2020) Vol. 13, pp. 5384-5397
Open Access | Times Cited: 35

Showing 1-25 of 35 citing articles:

How does urban expansion interact with cropland loss? A comparison of 14 Chinese cities from 1980 to 2015
Ying Tu, Бин Чэн, Le Yu, et al.
Landscape Ecology (2020) Vol. 36, Iss. 1, pp. 243-263
Closed Access | Times Cited: 102
Ecosystem health assessment of East Kolkata Wetlands, India: Implications for environmental sustainability
Pawan Kumar Yadav, Priyanka Jha, Md Saharik Joy, et al.
Journal of Environmental Management (2024) Vol. 366, pp. 121809-121809
Closed Access | Times Cited: 14
Random Forest for rice yield mapping and prediction using Sentinel-2 data with Google Earth Engine
Komal Choudhary, Wenzhong Shi, Dong Yu, et al.
Advances in Space Research (2022) Vol. 70, Iss. 8, pp. 2443-2457
Closed Access | Times Cited: 28
Google Earth Engine: empowering developing countries with large-scale geospatial data analysis—a comprehensive review
S Vijayakumar, R Saravanakumar, Mariadoss Arulanandam, et al.
Arabian Journal of Geosciences (2024) Vol. 17, Iss. 4
Closed Access | Times Cited: 6
National-Scale Cropland Mapping Based on Phenological Metrics, Environmental Covariates, and Machine Learning on Google Earth Engine
Abdelaziz Htitiou, Abdelghani Boudhar, Abdelghani Chehbouni, et al.
Remote Sensing (2021) Vol. 13, Iss. 21, pp. 4378-4378
Open Access | Times Cited: 37
A 10 m resolution land cover map of the Tibetan Plateau with detailed vegetation types
Huang Xingyi, Yuwei Yin, Luwei Feng, et al.
Earth system science data (2024) Vol. 16, Iss. 7, pp. 3307-3332
Open Access | Times Cited: 5
A Deep Learning Approach to an Enhanced Building Footprint and Road Detection in High-Resolution Satellite Imagery
Christian Ayala, R. Sesma, C. Aranda, et al.
Remote Sensing (2021) Vol. 13, Iss. 16, pp. 3135-3135
Open Access | Times Cited: 28
Surface energy balance-based surface urban heat island decomposition at high resolution
Fengxiang Guo, Jiayue Sun, Die Hu
Remote Sensing of Environment (2024) Vol. 315, pp. 114447-114447
Closed Access | Times Cited: 4
Assessment of forest cover dynamics for the detection of deforestation in the Hindu Kush Himalayan region using geospatial and machine learning approaches
Laxmi Gupta, Jagabandhu Dixit, Prem Chandra Pandey, et al.
Earth Science Informatics (2025) Vol. 18, Iss. 1
Closed Access
Attribute-guided feature fusion network with knowledge-inspired attention mechanism for multi-source remote sensing classification
Xiao Pan, Changzhe Jiao, Bo Yang, et al.
Neural Networks (2025) Vol. 187, pp. 107332-107332
Closed Access
Spatial Stratification Method for the Sampling Design of LULC Classification Accuracy Assessment: A Case Study in Beijing, China
Shiwei Dong, Hui Guo, Ziyue Chen, et al.
Remote Sensing (2022) Vol. 14, Iss. 4, pp. 865-865
Open Access | Times Cited: 17
A change type determination method based on knowledge of spectral changes in land cover types
Linye Zhu, Huaqiao Xing, Longfei Zhao, et al.
Earth Science Informatics (2023) Vol. 16, Iss. 2, pp. 1265-1279
Closed Access | Times Cited: 9
Wetland Mapping in Great Lakes Using Sentinel-1/2 Time-Series Imagery and DEM Data in Google Earth Engine
Farzane Mohseni, Meisam Amani, Pegah Mohammadpour, et al.
Remote Sensing (2023) Vol. 15, Iss. 14, pp. 3495-3495
Open Access | Times Cited: 9
A temporal-spectral value and shape change detection method integrating thematic index information and spectral band information
Linye Zhu, Xiaoyi Jiang, Longfei Zhao, et al.
Environmental Science and Pollution Research (2023) Vol. 30, Iss. 16, pp. 47408-47421
Closed Access | Times Cited: 8
Forest Tree Species Classification Based on Sentinel-2 Images and Auxiliary Data
Haotian You, Yuanwei Huang, Zhigang Qin, et al.
Forests (2022) Vol. 13, Iss. 9, pp. 1416-1416
Open Access | Times Cited: 12
Uncovering the Nature of Urban Land Use Composition Using Multi-Source Open Big Data with Ensemble Learning
Ying Tu, Бин Чэн, Wei Lang, et al.
Remote Sensing (2021) Vol. 13, Iss. 21, pp. 4241-4241
Open Access | Times Cited: 14
Applying machine learning classifiers to Sentinel-2 imagery for early identification of cotton fields to advance boll weevil eradication
Chenghai Yang, Charles P.‐C. Suh
Computers and Electronics in Agriculture (2023) Vol. 213, pp. 108268-108268
Closed Access | Times Cited: 4
Comparison of Algorithms and Optimal Feature Combinations for Identifying Forest Type in Subtropical Forests Using GF-2 and UAV Multispectral Images
Guowei He, Shun Li, Chao Huang, et al.
Forests (2024) Vol. 15, Iss. 8, pp. 1327-1327
Open Access | Times Cited: 1
How the characteristics of land cover changes affect vegetation greenness in Guangdong, a rapid urbanization region of China during 2001–2022
Yuzhen Wu, Xinxin Qiu, Dongmei Liang, et al.
Environmental Monitoring and Assessment (2024) Vol. 196, Iss. 11
Closed Access | Times Cited: 1
A Cloud-Based Global Land Cover Clustering Framework Using Sentinel-1 And Sentinel-2 Data
Abhinav Verma, Sandeep Kumar, Avik Bhattacharya
(2023), pp. 1-4
Closed Access | Times Cited: 2
A 10 m resolution land cover map of the Tibetan Plateau with detailed vegetation types
Huang Xingyi, Yuwei Yin, Luwei Feng, et al.
(2023)
Open Access | Times Cited: 2
A review of paddy rice mapping with remote sensing technology
Xinyi Gao, Hong Chi, Jinliang Huang, et al.
National Remote Sensing Bulletin (2023), pp. 1-27
Open Access | Times Cited: 2
Una revisión del uso de imágenes Sentinel-2 para el monitoreo de la cobertura boscosa a nivel global
Ronald Puerta, José Iannacone‍, Manuel Reategui-Inga
Ingeniería y Competitividad (2023) Vol. 25, Iss. 3
Open Access | Times Cited: 2
Comment on essd-2023-327
Huang Xingyi, Yuwei Yin, Luwei Feng, et al.
(2024)
Open Access
Reply on RC1
Huang Xingyi
(2024)
Open Access
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