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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:

Monthly composites from Sentinel-1 and Sentinel-2 images for regional major crop mapping with Google Earth Engine
Chong Luo, Huanjun Liu, Lü-ping LU, et al.
Journal of Integrative Agriculture (2021) Vol. 20, Iss. 7, pp. 1944-1957
Open Access | Times Cited: 77

Showing 1-25 of 77 citing articles:

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: 76
Early-Season Mapping of Winter Crops Using Sentinel-2 Optical Imagery
Haifeng Tian, Yongjiu Wang, Ting Chen, et al.
Remote Sensing (2021) Vol. 13, Iss. 19, pp. 3822-3822
Open Access | Times Cited: 78
Regional soil organic matter mapping models based on the optimal time window, feature selection algorithm and Google Earth Engine
Chong Luo, Xinle Zhang, Yihao Wang, et al.
Soil and Tillage Research (2022) Vol. 219, pp. 105325-105325
Closed Access | Times Cited: 52
Bridging optical and SAR satellite image time series via contrastive feature extraction for crop classification
Yuan Yuan, Lei Lin, Zeng-Guang Zhou, et al.
ISPRS Journal of Photogrammetry and Remote Sensing (2022) Vol. 195, pp. 222-232
Closed Access | Times Cited: 46
Crop classification based on phenology information by using time series of optical and synthetic-aperture radar images
Fatemeh Kordi, Hossein Yousefi
Remote Sensing Applications Society and Environment (2022) Vol. 27, pp. 100812-100812
Closed Access | Times Cited: 43
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 of soil organic matter in a typical black soil area using Landsat-8 synthetic images at different time periods
Chong Luo, Wenqi Zhang, Xinle Zhang, et al.
CATENA (2023) Vol. 231, pp. 107336-107336
Closed Access | Times Cited: 31
Mapping the soil organic matter content in a typical black-soil area using optical data, radar data and environmental covariates
Chong Luo, Wenqi Zhang, Xinle Zhang, et al.
Soil and Tillage Research (2023) Vol. 235, pp. 105912-105912
Open Access | Times Cited: 24
Artificial Intelligence in Agricultural Mapping: A Review
Ramón Espinel, Gricelda Herrera-Franco, José Luis Rivadeneira García, et al.
Agriculture (2024) Vol. 14, Iss. 7, pp. 1071-1071
Open Access | Times Cited: 11
Cropland and Crop Type Classification with Sentinel-1 and Sentinel-2 Time Series Using Google Earth Engine for Agricultural Monitoring in Ethiopia
Christina Eisfelder, Bruno Boemke, Ursula Geßner, et al.
Remote Sensing (2024) Vol. 16, Iss. 5, pp. 866-866
Open Access | Times Cited: 9
Systematic method for mapping fine-resolution water cover types in China based on time series Sentinel-1 and 2 images
Yang Li, Zhenguo Niu
International Journal of Applied Earth Observation and Geoinformation (2021) Vol. 106, pp. 102656-102656
Open Access | Times Cited: 47
Mapping Winter Wheat with Optical and SAR Images Based on Google Earth Engine in Henan Province, China
Changchun Li, Weinan Chen, Yilin Wang, et al.
Remote Sensing (2022) Vol. 14, Iss. 2, pp. 284-284
Open Access | Times Cited: 29
Multispectral UAV data for detection of weeds in a citrus farm using machine learning and Google Earth Engine: Case study of Morocco
Hajar Saad El Imanni, Abderrazak El Harti, El Mostafa Bachaoui, et al.
Remote Sensing Applications Society and Environment (2023) Vol. 30, pp. 100941-100941
Closed Access | Times Cited: 20
Crop type classification with combined spectral, texture, and radar features of time-series Sentinel-1 and Sentinel-2 data
Gang Cheng, Huan Ding, Jie Yang, et al.
International Journal of Remote Sensing (2023) Vol. 44, Iss. 4, pp. 1215-1237
Closed Access | Times Cited: 17
Predicting regional soil organic matter content utilizing conventional satellites: Assessing the influence of temporal, spatial, and spectral disparities
Wenqi Zhang, Chong Luo, Xiangtian Meng, et al.
CATENA (2024) Vol. 237, pp. 107821-107821
Closed Access | Times Cited: 7
Mapping annual 10-m soybean cropland with spatiotemporal sample migration
Hongchi Zhang, Zihang Lou, Dailiang Peng, et al.
Scientific Data (2024) Vol. 11, Iss. 1
Open Access | Times Cited: 7
Combining Multitemporal Optical and Radar Satellite Data for Mapping the Tatra Mountains Non-Forest Plant Communities
Marcin Kluczek, Bogdan Zagajewski, Marlena Kycko
Remote Sensing (2024) Vol. 16, Iss. 8, pp. 1451-1451
Open Access | Times Cited: 6
Research on remote sensing classification of fruit trees based on Sentinel-2 multi-temporal imageries
Xinxing Zhou, Yangyang Li, Yuan-Kai Luo, et al.
Scientific Reports (2022) Vol. 12, Iss. 1
Open Access | Times Cited: 24
Tree-fruits crop type mapping from Sentinel-1 and Sentinel-2 data integration in Egypt's New Delta project
Mohsen Nabil, Eslam Farg, Sayed M. Arafat, et al.
Remote Sensing Applications Society and Environment (2022) Vol. 27, pp. 100776-100776
Closed Access | Times Cited: 23
Mapping soil organic matter content using Sentinel-2 synthetic images at different time intervals in Northeast China
Chong Luo, Wenqi Zhang, Xinle Zhang, et al.
International Journal of Digital Earth (2023) Vol. 16, Iss. 1, pp. 1094-1107
Open Access | Times Cited: 15
Exploring the Effect of Balanced and Imbalanced Multi-Class Distribution Data and Sampling Techniques on Fruit-Tree Crop Classification Using Different Machine Learning Classifiers
Yingisani Chabalala, Elhadi Adam, Khalid Adem Ali
Geomatics (2023) Vol. 3, Iss. 1, pp. 70-92
Open Access | Times Cited: 13
Monitoring salinity in bare soil based on Sentinel-1/2 image fusion and machine learning
Yujie He, Zhitao Zhang, Ru Xiang, et al.
Infrared Physics & Technology (2023) Vol. 131, pp. 104656-104656
Closed Access | Times Cited: 13
ChinaSoyArea10m: a dataset of soybean-planting areas with a spatial resolution of 10 m across China from 2017 to 2021
Qinghang Mei, Zhao Zhang, Jichong Han, et al.
Earth system science data (2024) Vol. 16, Iss. 7, pp. 3213-3231
Open Access | Times Cited: 5
Understanding the potentials of early-season crop type mapping by using Landsat-8, Sentinel-1/2, and GF-1/6 data
Cong Wang, Xinyu Zhang, Wenjing Wang, et al.
Computers and Electronics in Agriculture (2024) Vol. 224, pp. 109239-109239
Closed Access | Times Cited: 4
Improving model performance in mapping black-soil resource with machine learning methods and multispectral features
Jianfang Hu, Yulei Tang, Jiapan Yan, et al.
Scientific Reports (2025) Vol. 15, Iss. 1
Open Access
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