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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:

Examining rice distribution and cropping intensity in a mixed single- and double-cropping region in South China using all available Sentinel 1/2 images
Yingli He, Jinwei Dong, Xiaoyong Liao, et al.
International Journal of Applied Earth Observation and Geoinformation (2021) Vol. 101, pp. 102351-102351
Open Access | Times Cited: 87

Showing 1-25 of 87 citing articles:

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
Annual paddy rice planting area and cropping intensity datasets and their dynamics in the Asian monsoon region from 2000 to 2020
Jichong Han, Zhao Zhang, Yuchuan Luo, et al.
Agricultural Systems (2022) Vol. 200, pp. 103437-103437
Closed Access | Times Cited: 104
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
Mapping the vegetation distribution and dynamics of a wetland using adaptive-stacking and Google Earth Engine based on multi-source remote sensing data
Xiangren Long, Xinyu Li, Hui Lin, et al.
International Journal of Applied Earth Observation and Geoinformation (2021) Vol. 102, pp. 102453-102453
Open Access | Times Cited: 74
High-Resolution Mapping of Paddy Rice Extent and Growth Stages across Peninsular Malaysia Using a Fusion of Sentinel-1 and 2 Time Series Data in Google Earth Engine
Fatchurrachman, Rudiyanto Rudiyanto, Norhidayah Che Soh, et al.
Remote Sensing (2022) Vol. 14, Iss. 8, pp. 1875-1875
Open Access | Times Cited: 42
Mapping upland crop–rice cropping systems for targeted sustainable intensification in South China
Bingwen Qiu, Linhai Yu, Peng Yang, et al.
The Crop Journal (2024) Vol. 12, Iss. 2, pp. 614-629
Open Access | Times Cited: 9
Comparison of Cloud-Mask Algorithms and Machine-Learning Methods Using Sentinel-2 Imagery for Mapping Paddy Rice in Jianghan Plain
Xinyi Gao, Hong Chi, Jinliang Huang, et al.
Remote Sensing (2024) Vol. 16, Iss. 7, pp. 1305-1305
Open Access | Times Cited: 9
A novel and robust method for large-scale single-season rice mapping based on phenology and statistical data
Maolin Yang, Bin Guo, Jianlin Wang
ISPRS Journal of Photogrammetry and Remote Sensing (2024) Vol. 213, pp. 14-32
Closed Access | Times Cited: 9
A general methodological framework for predicting and assessing heavy metal pollution in paddy soils using machine learning models
Unurnyam Jugnee, Le Jiao, Sainbayar Dalantai, et al.
Heliyon (2025), pp. e42619-e42619
Open Access | Times Cited: 1
Rice Mapping in a Subtropical Hilly Region Based on Sentinel-1 Time Series Feature Analysis and the Dual Branch BiLSTM Model
Chunling Sun, Hong Zhang, Ji Ge, et al.
Remote Sensing (2022) Vol. 14, Iss. 13, pp. 3213-3213
Open Access | Times Cited: 31
Improving grain yield prediction through fusion of multi-temporal spectral features and agronomic trait parameters derived from UAV imagery
Hongkui Zhou, Jianhua Yang, Weidong Lou, et al.
Frontiers in Plant Science (2023) Vol. 14
Open Access | Times Cited: 17
An automated sample generation method by integrating phenology domain optical-SAR features in rice cropping pattern mapping
Jingya Yang, Qiong Hu, Wenjuan Li, et al.
Remote Sensing of Environment (2024) Vol. 314, pp. 114387-114387
Closed Access | Times Cited: 7
Improved phenology-based rice mapping algorithm by integrating optical and radar data
Zizhang Zhao, Jinwei Dong, Geli Zhang, et al.
Remote Sensing of Environment (2024) Vol. 315, pp. 114460-114460
Closed Access | Times Cited: 7
Application of Artificial Neural Networks for Mangrove Mapping Using Multi-Temporal and Multi-Source Remote Sensing Imagery
Arsalan Ghorbanian, Seyed Ali Ahmadi, Meisam Amani, et al.
Water (2022) Vol. 14, Iss. 2, pp. 244-244
Open Access | Times Cited: 28
Mapping the Complex Crop Rotation Systems in Southern China Considering Cropping Intensity, Crop Diversity, and Their Seasonal Dynamics
Yuan Liu, Qiangyi Yu, Qingbo Zhou, et al.
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (2022) Vol. 15, pp. 9584-9598
Open Access | Times Cited: 25
A robust and unified land surface phenology algorithm for diverse biomes and growth cycles in China by using harmonized Landsat and Sentinel-2 imagery
Jilin Yang, Jinwei Dong, Luo Liu, et al.
ISPRS Journal of Photogrammetry and Remote Sensing (2023) Vol. 202, pp. 610-636
Closed Access | Times Cited: 16
A robust approach for large-scale cropping intensity mapping in smallholder farms from vegetation, brownness indices and SAR time series
Bingwen Qiu, Hu Xiang, Peng Yang, et al.
ISPRS Journal of Photogrammetry and Remote Sensing (2023) Vol. 203, pp. 328-344
Closed Access | Times Cited: 16
Mapping Diverse Paddy Rice Cropping Patterns in South China Using Harmonized Landsat and Sentinel-2 Data
Jie Hu, Yunping Chen, Zhiwen Cai, et al.
Remote Sensing (2023) Vol. 15, Iss. 4, pp. 1034-1034
Open Access | Times Cited: 14
Decline in Planting Areas of Double-Season Rice by Half in Southern China over the Last Two Decades
Wenchao Zhu, Xinqin Peng, Mingjun Ding, et al.
Remote Sensing (2024) Vol. 16, Iss. 3, pp. 440-440
Open Access | Times Cited: 6
Early Mapping Method for Different Planting Types of Rice Based on Planet and Sentinel-2 Satellite Images
Yunfei Yu, Linghua Meng, Chong Luo, et al.
Agronomy (2024) Vol. 14, Iss. 1, pp. 137-137
Open Access | Times Cited: 5
Determining Effective Temporal Windows for Rapeseed Detection Using Sentinel-1 Time Series and Machine Learning Algorithms
Saeideh Maleki, Nicolas Baghdadi, Sami Najem, et al.
Remote Sensing (2024) Vol. 16, Iss. 3, pp. 549-549
Open Access | Times Cited: 5
Large-scale and high-resolution paddy rice intensity mapping using downscaling and phenology-based algorithms on Google Earth Engine
Liangli Meng, Yunfei Li, Ruoque Shen, et al.
International Journal of Applied Earth Observation and Geoinformation (2024) Vol. 128, pp. 103725-103725
Open Access | Times Cited: 5
Novel Harmonic-Based Scheme for Mapping Rice-Crop Intensity at a Large Scale Using Time-Series Sentinel-1 and ERA5-Land Datasets
Ze He, Shihua Li, Minghui Chang, et al.
IEEE Transactions on Geoscience and Remote Sensing (2024) Vol. 62, pp. 1-23
Closed Access | Times Cited: 5
Pixel-level rice planting information monitoring in Fujin City based on time-series SAR imagery
Jiatai Pang, Rui Zhang, Bin Yu, et al.
International Journal of Applied Earth Observation and Geoinformation (2021) Vol. 104, pp. 102551-102551
Open Access | Times Cited: 31
Rapid and Automated Approach for Early Crop Mapping Using Sentinel-1 and Sentinel-2 on Google Earth Engine; A Case of a Highly Heterogeneous and Fragmented Agricultural Region
Hajar Saad El Imanni, Abderrazak El Harti, Mohammed Hssaisoune, et al.
Journal of Imaging (2022) Vol. 8, Iss. 12, pp. 316-316
Open Access | Times Cited: 20
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