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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:

Transfer Learning for Crop classification with Cropland Data Layer data (CDL) as training samples
Pengyu Hao, Liping Di, Chen Zhang, et al.
The Science of The Total Environment (2020) Vol. 733, pp. 138869-138869
Open Access | Times Cited: 120

Showing 1-25 of 120 citing articles:

Early- and in-season crop type mapping without current-year ground truth: Generating labels from historical information via a topology-based approach
Chenxi Lin, Liheng Zhong, Xiao‐Peng Song, et al.
Remote Sensing of Environment (2022) Vol. 274, pp. 112994-112994
Open Access | Times Cited: 89
Towards automation of in-season crop type mapping using spatiotemporal crop information and remote sensing data
Chen Zhang, Liping Di, Li Lin, et al.
Agricultural Systems (2022) Vol. 201, pp. 103462-103462
Open Access | Times Cited: 78
An unsupervised domain adaptation deep learning method for spatial and temporal transferable crop type mapping using Sentinel-2 imagery
Yumiao Wang, Luwei Feng, Zhou Zhang, et al.
ISPRS Journal of Photogrammetry and Remote Sensing (2023) Vol. 199, pp. 102-117
Closed Access | Times Cited: 51
EARice10: a 10 m resolution annual rice distribution map of East Asia for 2023
Mingyang Song, Lu Xu, Ji Ge, et al.
Earth system science data (2025) Vol. 17, Iss. 2, pp. 661-683
Open Access | Times Cited: 2
A new attention-based CNN approach for crop mapping using time series Sentinel-2 images
Yumiao Wang, Zhou Zhang, Luwei Feng, et al.
Computers and Electronics in Agriculture (2021) Vol. 184, pp. 106090-106090
Open Access | Times Cited: 97
Large-scale rice mapping under different years based on time-series Sentinel-1 images using deep semantic segmentation model
Pengliang Wei, Dengfeng Chai, Tao Lin, et al.
ISPRS Journal of Photogrammetry and Remote Sensing (2021) Vol. 174, pp. 198-214
Closed Access | Times Cited: 94
Satellite-based data fusion crop type classification and mapping in Rio Grande do Sul, Brazil
Luan Pierre Pott, Telmo Jorge Carneiro Amado, Raí Augusto Schwalbert, et al.
ISPRS Journal of Photogrammetry and Remote Sensing (2021) Vol. 176, pp. 196-210
Closed Access | Times Cited: 75
Rapid in-season mapping of corn and soybeans using machine-learned trusted pixels from Cropland Data Layer
Chen Zhang, Liping Di, Pengyu Hao, et al.
International Journal of Applied Earth Observation and Geoinformation (2021) Vol. 102, pp. 102374-102374
Open Access | Times Cited: 67
Validation and refinement of cropland data layer using a spatial-temporal decision tree algorithm
Li Lin, Liping Di, Chen Zhang, et al.
Scientific Data (2022) Vol. 9, Iss. 1
Open Access | Times Cited: 48
Mapping corn dynamics using limited but representative samples with adaptive strategies
Yanan Wen, Xuecao Li, Haowei Mu, et al.
ISPRS Journal of Photogrammetry and Remote Sensing (2022) Vol. 190, pp. 252-266
Open Access | Times Cited: 46
Exploring the potential of multi-source unsupervised domain adaptation in crop mapping using Sentinel-2 images
Yumiao Wang, Luwei Feng, Weiwei Sun, et al.
GIScience & Remote Sensing (2022) Vol. 59, Iss. 1, pp. 2247-2265
Closed Access | Times Cited: 41
Remote Sensing Based Crop Type Classification Via Deep Transfer Learning
Krishna Karthik Gadiraju, Ranga Raju Vatsavai
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (2023) Vol. 16, pp. 4699-4712
Open Access | Times Cited: 26
Vegetation Classification and Evaluation of Yancheng Coastal Wetlands Based on Random Forest Algorithm from Sentinel-2 Images
Yongjun Wang, Shuanggen Jin, Gino Dardanelli
Remote Sensing (2024) Vol. 16, Iss. 7, pp. 1124-1124
Open Access | Times Cited: 16
Performance of GEDI data combined with Sentinel-2 images for automatic labelling of wall-to-wall corn mapping
Ziqian Li, Xuan Fu, Yi Dong, et al.
International Journal of Applied Earth Observation and Geoinformation (2024) Vol. 127, pp. 103643-103643
Open Access | Times Cited: 13
Interseasonal transfer learning for crop mapping using Sentinel-1 data
Miloš Pandžić, Dejan Pavlović, Predrag Matavulj, et al.
International Journal of Applied Earth Observation and Geoinformation (2024) Vol. 128, pp. 103718-103718
Open Access | Times Cited: 11
Plot-Rice v1.0: A global plot-based rice benchmark dataset with spatiotemporal heterogeneity for scientific deep learning
Ji Ge, Hong Zhang, Wenjiang Huang, et al.
International Journal of Applied Earth Observation and Geoinformation (2025) Vol. 140, pp. 104569-104569
Closed Access | Times Cited: 1
Transferable deep learning model based on the phenological matching principle for mapping crop extent
Shuang Ge, Jinshui Zhang, Yaozhong Pan, et al.
International Journal of Applied Earth Observation and Geoinformation (2021) Vol. 102, pp. 102451-102451
Open Access | Times Cited: 45
An adaptive adversarial domain adaptation approach for corn yield prediction
Yuchi Ma, Zhou Zhang, H. Lexie Yang, et al.
Computers and Electronics in Agriculture (2021) Vol. 187, pp. 106314-106314
Open Access | Times Cited: 44
Seamless and automated rapeseed mapping for large cloudy regions using time-series optical satellite imagery
Hongyan Zhang, Wenbin Liu, Liangpei Zhang
ISPRS Journal of Photogrammetry and Remote Sensing (2021) Vol. 184, pp. 45-62
Closed Access | Times Cited: 44
Developing High-Resolution Crop Maps for Major Crops in the European Union Based on Transductive Transfer Learning and Limited Ground Data
Yuchuan Luo, Zhao Zhang, Liangliang Zhang, et al.
Remote Sensing (2022) Vol. 14, Iss. 8, pp. 1809-1809
Open Access | Times Cited: 38
Spatial Transferability of Random Forest Models for Crop Type Classification Using Sentinel-1 and Sentinel-2
Aiym Orynbaikyzy, Ursula Geßner, Christopher Conrad
Remote Sensing (2022) Vol. 14, Iss. 6, pp. 1493-1493
Open Access | Times Cited: 36
Smallholder Crop Type Mapping and Rotation Monitoring in Mountainous Areas with Sentinel-1/2 Imagery
Tingting Ren, Hongtao Xu, Xiumin Cai, et al.
Remote Sensing (2022) Vol. 14, Iss. 3, pp. 566-566
Open Access | Times Cited: 33
Rice mapping based on Sentinel-1 images using the coupling of prior knowledge and deep semantic segmentation network: A case study in Northeast China from 2019 to 2021
Pengliang Wei, Dengfeng Chai, Ran Huang, et al.
International Journal of Applied Earth Observation and Geoinformation (2022) Vol. 112, pp. 102948-102948
Open Access | Times Cited: 32
Improvement Of In-season Crop Mapping For Illinois Cropland Using Multiple Machine Learning Classifiers
Hui Li, Liping Di, Chen Zhang, et al.
(2022), pp. 1-6
Closed Access | Times Cited: 32
Large-Scale Rice Mapping Using Multi-Task Spatiotemporal Deep Learning and Sentinel-1 SAR Time Series
Zhixian Lin, Renhai Zhong, Xingguo Xiong, et al.
Remote Sensing (2022) Vol. 14, Iss. 3, pp. 699-699
Open Access | Times Cited: 31
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