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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:

Agricultural cropland extent and areas of South Asia derived using Landsat satellite 30-m time-series big-data using random forest machine learning algorithms on the Google Earth Engine cloud
Murali Krishna Gumma, Prasad S. Thenkabail, Pardhasaradhi Teluguntla, et al.
GIScience & Remote Sensing (2019) Vol. 57, Iss. 3, pp. 302-322
Open Access | Times Cited: 135

Showing 1-25 of 135 citing articles:

Current and near-term advances in Earth observation for ecological applications
Susan L. Ustin, Elizabeth M. Middleton
Ecological Processes (2021) Vol. 10, Iss. 1
Open Access | Times Cited: 190
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: 155
Mapping croplands of Europe, Middle East, Russia, and Central Asia using Landsat, Random Forest, and Google Earth Engine
Aparna Phalke, Mutlu Özdoğan, Prasad S. Thenkabail, et al.
ISPRS Journal of Photogrammetry and Remote Sensing (2020) Vol. 167, pp. 104-122
Open Access | Times Cited: 154
Mapping of cropland, cropping patterns and crop types by combining optical remote sensing images with decision tree classifier and random forest
Aqil Tariq, Jianguo Yan, Alexandre S. Gagnon, et al.
Geo-spatial Information Science (2022) Vol. 26, Iss. 3, pp. 302-320
Open Access | Times Cited: 144
Estimation of surface-level NO2 and O3 concentrations using TROPOMI data and machine learning over East Asia
Yoojin Kang, Hyunyoung Choi, Jungho Im, et al.
Environmental Pollution (2021) Vol. 288, pp. 117711-117711
Closed Access | Times Cited: 140
Challenges to Use Machine Learning in Agricultural Big Data: A Systematic Literature Review
Ania Cravero, Sebastián Pardo, Samuel Sepúlveda, et al.
Agronomy (2022) Vol. 12, Iss. 3, pp. 748-748
Open Access | Times Cited: 85
A review of regional and Global scale Land Use/Land Cover (LULC) mapping products generated from satellite remote sensing
Yanzhao Wang, Yonghua Sun, X. L. Cao, et al.
ISPRS Journal of Photogrammetry and Remote Sensing (2023) Vol. 206, pp. 311-334
Closed Access | Times Cited: 65
Advancement of Remote Sensing for Soil Measurements and Applications: A Comprehensive Review
Mukhtar Iderawumi Abdulraheem, Wei Zhang, Shixin Li, et al.
Sustainability (2023) Vol. 15, Iss. 21, pp. 15444-15444
Open Access | Times Cited: 64
Evaluation of agriculture land transformations with socio-economic influences on wheat demand and supply for food sustainability
Danish Raza, Hong Shu, Muhsan Ehsan, et al.
Cogent Food & Agriculture (2025) Vol. 11, Iss. 1
Open Access | Times Cited: 4
From Data to Insights: Modeling Urban Land Surface Temperature Using Geospatial Analysis and Interpretable Machine Learning
Nhat‐Duc Hoang, Van-Duc Tran, Thanh‐Canh Huynh
Sensors (2025) Vol. 25, Iss. 4, pp. 1169-1169
Open Access | Times Cited: 2
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
Use and Adaptations of Machine Learning in Big Data—Applications in Real Cases in Agriculture
Ania Cravero, Samuel Sepúlveda
Electronics (2021) Vol. 10, Iss. 5, pp. 552-552
Open Access | Times Cited: 90
A new framework to map fine resolution cropping intensity across the globe: Algorithm, validation, and implication
Chong Liu, Qi Zhang, Shiqi Tao, et al.
Remote Sensing of Environment (2020) Vol. 251, pp. 112095-112095
Open Access | Times Cited: 86
A 30 m terrace mapping in China using Landsat 8 imagery and digital elevation model based on the Google Earth Engine
Bowen Cao, Le Yu, Victoria Naipal, et al.
Earth system science data (2021) Vol. 13, Iss. 5, pp. 2437-2456
Open Access | Times Cited: 71
Improved retrievals of aerosol optical depth and fine mode fraction from GOCI geostationary satellite data using machine learning over East Asia
Yoojin Kang, Miae Kim, Eunjin Kang, et al.
ISPRS Journal of Photogrammetry and Remote Sensing (2021) Vol. 183, pp. 253-268
Open Access | Times Cited: 66
Automated Mapping for Long-Term Analysis of Shifting Cultivation in Northeast India
Pulakesh Das, Sujoy Mudi, Mukunda Dev Behera, et al.
Remote Sensing (2021) Vol. 13, Iss. 6, pp. 1066-1066
Open Access | Times Cited: 57
Multiple agricultural cropland products of South Asia developed using Landsat-8 30 m and MODIS 250 m data using machine learning on the Google Earth Engine (GEE) cloud and spectral matching techniques (SMTs) in support of food and water security
Murali Krishna Gumma, Prasad S. Thenkabail, Pranay Panjala, et al.
GIScience & Remote Sensing (2022) Vol. 59, Iss. 1, pp. 1048-1077
Open Access | Times Cited: 44
Forecasting disruptions in global food value chains to tackle food insecurity: The role of AI and big data analytics – A bibliometric and scientometric analysis
Phemelo Tamasiga, El houssin Ouassou, Helen Onyeaka, et al.
Journal of Agriculture and Food Research (2023) Vol. 14, pp. 100819-100819
Open Access | Times Cited: 41
Towards sustainable transportation: A case study analysis of climate-responsive strategies in a developing nation
Rabiya Nasir, Hui Jun Meng, Sajid Rashid Ahmad, et al.
Case Studies in Thermal Engineering (2024) Vol. 55, pp. 104117-104117
Open Access | Times Cited: 13
Directions of land degradation in the greater Istanbul metropolitan area: A view from four decades
Selim Bayraktar, Katarzyna Cegielska, Eren Dağra Sökmen, et al.
Land Degradation and Development (2024) Vol. 35, Iss. 5, pp. 1656-1672
Open Access | Times Cited: 11
Assessment of Machine Learning Algorithms for Land Cover Classification in a Complex Mountainous Landscape
Gomal Amin, Iqra Imtiaz, Ehsan Haroon, et al.
Journal of Geovisualization and Spatial Analysis (2024) Vol. 8, Iss. 2
Open Access | Times Cited: 10
Using Bi-Temporal Lidar to Evaluate Canopy Structure and Ecotone Influence on Landsat Vegetation Index Trends Within a Boreal Wetland Complex
Farnoosh Aslami, Chris Hopkinson, L. Chasmer, et al.
Applied Sciences (2025) Vol. 15, Iss. 9, pp. 4653-4653
Open Access | Times Cited: 1
Challenges to Use Machine Learning in Agricultural Big Data: A Systematic Literature Review
Ania Cravero, Sebastián Pardo, Samuel Sepúlveda, et al.
(2022)
Open Access | Times Cited: 33
A method for reconstructing NDVI time-series based on envelope detection and the Savitzky-Golay filter
Xinkai Liu, Lingyun Ji, Chen Zhang, et al.
International Journal of Digital Earth (2022) Vol. 15, Iss. 1, pp. 553-584
Open Access | Times Cited: 30
Machine Learning-Driven Remote Sensing Applications for Agriculture in India—A Systematic Review
Shweta Pokhariyal, N. R. Patel, Ajit Govind
Agronomy (2023) Vol. 13, Iss. 9, pp. 2302-2302
Open Access | Times Cited: 22
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