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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:

Assessment of an Operational System for Crop Type Map Production Using High Temporal and Spatial Resolution Satellite Optical Imagery
Jordi Inglada, Marcela Arias, Benjamin Tardy, et al.
Remote Sensing (2015) Vol. 7, Iss. 9, pp. 12356-12379
Open Access | Times Cited: 348

Showing 1-25 of 348 citing articles:

First Experience with Sentinel-2 Data for Crop and Tree Species Classifications in Central Europe
Markus Immitzer, Francesco Vuolo, Clement Atzberger
Remote Sensing (2016) Vol. 8, Iss. 3, pp. 166-166
Open Access | Times Cited: 803
Understanding the temporal behavior of crops using Sentinel-1 and Sentinel-2-like data for agricultural applications
Amanda Veloso, Stéphane Mermoz, Alexandre Bouvet, et al.
Remote Sensing of Environment (2017) Vol. 199, pp. 415-426
Open Access | Times Cited: 717
Assessing the robustness of Random Forests to map land cover with high resolution satellite image time series over large areas
Charlotte Pelletier, Silvia Valero, Jordi Inglada, et al.
Remote Sensing of Environment (2016) Vol. 187, pp. 156-168
Closed Access | Times Cited: 525
Temporal Convolutional Neural Network for the Classification of Satellite Image Time Series
Charlotte Pelletier, Geoffrey I. Webb, François Petitjean
Remote Sensing (2019) Vol. 11, Iss. 5, pp. 523-523
Open Access | Times Cited: 462
Operational High Resolution Land Cover Map Production at the Country Scale Using Satellite Image Time Series
Jordi Inglada, Arthur Vincent, Marcela Arias, et al.
Remote Sensing (2017) Vol. 9, Iss. 1, pp. 95-95
Open Access | Times Cited: 422
Nominal 30-m Cropland Extent Map of Continental Africa by Integrating Pixel-Based and Object-Based Algorithms Using Sentinel-2 and Landsat-8 Data on Google Earth Engine
Jun Xiong, Prasad S. Thenkabail, James C. Tilton, et al.
Remote Sensing (2017) Vol. 9, Iss. 10, pp. 1065-1065
Open Access | Times Cited: 362
Near real-time agriculture monitoring at national scale at parcel resolution: Performance assessment of the Sen2-Agri automated system in various cropping systems around the world
Pierre Defourny, Sophie Bontemps, Nicolas Bellemans, et al.
Remote Sensing of Environment (2018) Vol. 221, pp. 551-568
Open Access | Times Cited: 349
Crop type mapping without field-level labels: Random forest transfer and unsupervised clustering techniques
Sherrie Wang, George Azzari, David B. Lobell
Remote Sensing of Environment (2019) Vol. 222, pp. 303-317
Closed Access | Times Cited: 329
Smallholder maize area and yield mapping at national scales with Google Earth Engine
Zhenong Jin, George Azzari, Calum You, et al.
Remote Sensing of Environment (2019) Vol. 228, pp. 115-128
Open Access | Times Cited: 304
Landsat-8 vs. Sentinel-2: examining the added value of sentinel-2’s red-edge bands to land-use and land-cover mapping in Burkina Faso
Gerald Forkuor, Kangbéni Dimobe, Idriss Sermé, et al.
GIScience & Remote Sensing (2017) Vol. 55, Iss. 3, pp. 331-354
Closed Access | Times Cited: 291
Using the 500 m MODIS land cover product to derive a consistent continental scale 30 m Landsat land cover classification
Hankui K. Zhang, David P. Roy
Remote Sensing of Environment (2017) Vol. 197, pp. 15-34
Open Access | Times Cited: 286
How much does multi-temporal Sentinel-2 data improve crop type classification?
Francesco Vuolo, Martin Neuwirth, Markus Immitzer, et al.
International Journal of Applied Earth Observation and Geoinformation (2018) Vol. 72, pp. 122-130
Closed Access | Times Cited: 283
A comparison of global agricultural monitoring systems and current gaps
Steffen Fritz, Linda See, Juan Carlos Laso Bayas, et al.
Agricultural Systems (2018) Vol. 168, pp. 258-272
Open Access | Times Cited: 262
The 10-m crop type maps in Northeast China during 2017–2019
Nanshan You, Jinwei Dong, Jianxi Huang, et al.
Scientific Data (2021) Vol. 8, Iss. 1
Open Access | Times Cited: 260
Recent Applications of Landsat 8/OLI and Sentinel-2/MSI for Land Use and Land Cover Mapping: A Systematic Review
Michel Eustáquio Dantas Chaves, Michelle Cristina Araújo Picoli, Ieda Del’Arco Sanches
Remote Sensing (2020) Vol. 12, Iss. 18, pp. 3062-3062
Open Access | Times Cited: 258
Deep Recurrent Neural Network for Agricultural Classification using multitemporal SAR Sentinel-1 for Camargue, France
Emile Ndikumana, Dinh Ho Tong Minh, Nicolas Baghdadi, et al.
Remote Sensing (2018) Vol. 10, Iss. 8, pp. 1217-1217
Open Access | Times Cited: 241
Improved Early Crop Type Identification By Joint Use of High Temporal Resolution SAR And Optical Image Time Series
Jordi Inglada, Arthur Vincent, Marcela Arias, et al.
Remote Sensing (2016) Vol. 8, Iss. 5, pp. 362-362
Open Access | Times Cited: 239
Estimating wheat yields in Australia using climate records, satellite image time series and machine learning methods
Elisa Kamir, François Waldner, Zvi Hochman
ISPRS Journal of Photogrammetry and Remote Sensing (2019) Vol. 160, pp. 124-135
Closed Access | Times Cited: 235
Weakly Supervised Deep Learning for Segmentation of Remote Sensing Imagery
Sherrie Wang, William Chen, Sang Michael Xie, et al.
Remote Sensing (2020) Vol. 12, Iss. 2, pp. 207-207
Open Access | Times Cited: 214
A Combined Random Forest and OBIA Classification Scheme for Mapping Smallholder Agriculture at Different Nomenclature Levels Using Multisource Data (Simulated Sentinel-2 Time Series, VHRS and DEM)
Valentine Lebourgeois, Stéphane Dupuy, Élodie Vintrou, et al.
Remote Sensing (2017) Vol. 9, Iss. 3, pp. 259-259
Open Access | Times Cited: 194
Crop type classification using a combination of optical and radar remote sensing data: a review
Aiym Orynbaikyzy, Ursula Geßner, Christopher Conrad
International Journal of Remote Sensing (2019) Vol. 40, Iss. 17, pp. 6553-6595
Closed Access | Times Cited: 192
Effect of Training Class Label Noise on Classification Performances for Land Cover Mapping with Satellite Image Time Series
Charlotte Pelletier, Silvia Valero, Jordi Inglada, et al.
Remote Sensing (2017) Vol. 9, Iss. 2, pp. 173-173
Open Access | Times Cited: 188
DeepCropMapping: A multi-temporal deep learning approach with improved spatial generalizability for dynamic corn and soybean mapping
Jinfan Xu, Yue Zhu, Renhai Zhong, et al.
Remote Sensing of Environment (2020) Vol. 247, pp. 111946-111946
Closed Access | Times Cited: 182
Effects of Training Set Size on Supervised Machine-Learning Land-Cover Classification of Large-Area High-Resolution Remotely Sensed Data
Christopher A. Ramezan, Timothy A. Warner, Aaron E. Maxwell, et al.
Remote Sensing (2021) Vol. 13, Iss. 3, pp. 368-368
Open Access | Times Cited: 137
Towards interpreting multi-temporal deep learning models in crop mapping
Jinfan Xu, Jie Yang, Xingguo Xiong, et al.
Remote Sensing of Environment (2021) Vol. 264, pp. 112599-112599
Closed Access | Times Cited: 126
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