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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:

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: 723

Showing 1-25 of 723 citing articles:

Sentinel-2 Data for Land Cover/Use Mapping: A Review
Darius Phiri, Matamyo Simwanda, Serajis Salekin, et al.
Remote Sensing (2020) Vol. 12, Iss. 14, pp. 2291-2291
Open Access | Times Cited: 588
Toward Global Soil Moisture Monitoring With Sentinel-1: Harnessing Assets and Overcoming Obstacles
Bernhard Bauer-Marschallinger, Vahid Freeman, Senmao Cao, et al.
IEEE Transactions on Geoscience and Remote Sensing (2018) Vol. 57, Iss. 1, pp. 520-539
Open Access | Times Cited: 401
A review of remote sensing applications in agriculture for food security: Crop growth and yield, irrigation, and crop losses
L. Karthikeyan, Ila Chawla, Ashok K. Mishra
Journal of Hydrology (2020) Vol. 586, pp. 124905-124905
Closed Access | Times Cited: 401
Agricultural land systems importance for supporting food security and sustainable development goals: A systematic review
Cláudia M. Viana, Dulce Freire, Patrícia Abrantes, et al.
The Science of The Total Environment (2021) Vol. 806, pp. 150718-150718
Open Access | Times Cited: 339
Sensitivity of Sentinel-1 Backscatter to Vegetation Dynamics: An Austrian Case Study
Mariëtte Vreugdenhil, Wolfgang Wagner, Bernhard Bauer-Marschallinger, et al.
Remote Sensing (2018) Vol. 10, Iss. 9, pp. 1396-1396
Open Access | Times Cited: 325
Mapping cropping intensity in China using time series Landsat and Sentinel-2 images and Google Earth Engine
Luo Liu, Xiangming Xiao, Yuanwei Qin, et al.
Remote Sensing of Environment (2019) Vol. 239, pp. 111624-111624
Closed Access | Times Cited: 312
Dual polarimetric radar vegetation index for crop growth monitoring using sentinel-1 SAR data
Dipankar Mandal, Vineet Kumar, Debanshu Ratha, et al.
Remote Sensing of Environment (2020) Vol. 247, pp. 111954-111954
Closed Access | Times Cited: 302
Estimating leaf area index and aboveground biomass of grazing pastures using Sentinel-1, Sentinel-2 and Landsat images
Jie Wang, Xiao Xiangming, Rajen Bajgain, et al.
ISPRS Journal of Photogrammetry and Remote Sensing (2019) Vol. 154, pp. 189-201
Open Access | Times Cited: 261
Mapping of crop types and crop sequences with combined time series of Sentinel-1, Sentinel-2 and Landsat 8 data for Germany
Lukas Blickensdörfer, Marcel Schwieder, Dirk Pflugmacher, et al.
Remote Sensing of Environment (2021) Vol. 269, pp. 112831-112831
Open Access | Times Cited: 246
Examining earliest identifiable timing of crops using all available Sentinel 1/2 imagery and Google Earth Engine
Nanshan You, Jinwei Dong
ISPRS Journal of Photogrammetry and Remote Sensing (2020) Vol. 161, pp. 109-123
Closed Access | Times Cited: 237
Mapping coastal wetlands of China using time series Landsat images in 2018 and Google Earth Engine
Xinxin Wang, Xiangming Xiao, Zhenhua Zou, et al.
ISPRS Journal of Photogrammetry and Remote Sensing (2020) Vol. 163, pp. 312-326
Open Access | Times Cited: 235
Synergistic Use of Radar Sentinel-1 and Optical Sentinel-2 Imagery for Crop Mapping: A Case Study for Belgium
Kristof Van Tricht, Anne Gobin, Sven Gilliams, et al.
Remote Sensing (2018) Vol. 10, Iss. 10, pp. 1642-1642
Open Access | Times Cited: 221
Tracking annual changes of coastal tidal flats in China during 1986–2016 through analyses of Landsat images with Google Earth Engine
Xinxin Wang, Xiangming Xiao, Zhenhua Zou, et al.
Remote Sensing of Environment (2018) Vol. 238, pp. 110987-110987
Open Access | Times Cited: 219
Automated Extraction of Surface Water Extent from Sentinel-1 Data
Wenli Huang, Ben DeVries, Chengquan Huang, et al.
Remote Sensing (2018) Vol. 10, Iss. 5, pp. 797-797
Open Access | Times Cited: 213
Deep learning-based fusion of Landsat-8 and Sentinel-2 images for a harmonized surface reflectance product
Zhenfeng Shao, Jiajun Cai, Peng Fu, et al.
Remote Sensing of Environment (2019) Vol. 235, pp. 111425-111425
Open Access | Times Cited: 199
High-resolution digital mapping of soil organic carbon and soil total nitrogen using DEM derivatives, Sentinel-1 and Sentinel-2 data based on machine learning algorithms
Tao Zhou, Yajun Geng, Jie Chen, et al.
The Science of The Total Environment (2020) Vol. 729, pp. 138244-138244
Closed Access | Times Cited: 199
Mapping Winter Crops in China with Multi-Source Satellite Imagery and Phenology-Based Algorithm
Haifeng Tian, Ni Huang, Zheng Niu, et al.
Remote Sensing (2019) Vol. 11, Iss. 7, pp. 820-820
Open Access | Times Cited: 193
Comparison of Satellite and UAV-Based Multispectral Imagery for Vineyard Variability Assessment
Aleem Khaliq, Lorenzo Comba, Alessandro Biglia, et al.
Remote Sensing (2019) Vol. 11, Iss. 4, pp. 436-436
Open Access | Times Cited: 189
From parcel to continental scale – A first European crop type map based on Sentinel-1 and LUCAS Copernicus in-situ observations
Raphaël d’Andrimont, Astrid Verhegghen, Guido Lemoine, et al.
Remote Sensing of Environment (2021) Vol. 266, pp. 112708-112708
Open Access | Times Cited: 186
Uniting remote sensing, crop modelling and economics for agricultural risk management
Elinor Benami, Zhenong Jin, Michael R. Carter, et al.
Nature Reviews Earth & Environment (2021) Vol. 2, Iss. 2, pp. 140-159
Closed Access | Times Cited: 185
Status of Phenological Research Using Sentinel-2 Data: A Review
Gourav Misra, Fiona Cawkwell, Astrid Wingler
Remote Sensing (2020) Vol. 12, Iss. 17, pp. 2760-2760
Open Access | Times Cited: 180
Sentinel SAR-optical fusion for crop type mapping using deep learning and Google Earth Engine
Jarrett Adrian, Vasit Sagan, Maitiniyazi Maimaitijiang
ISPRS Journal of Photogrammetry and Remote Sensing (2021) Vol. 175, pp. 215-235
Open Access | Times Cited: 176
Crop Monitoring Using Sentinel-1 Data: A Case Study from The Netherlands
Saeed Khabbazan, Paul Vermunt, Susan Steele‐Dunne, et al.
Remote Sensing (2019) Vol. 11, Iss. 16, pp. 1887-1887
Open Access | Times Cited: 159
Garlic and Winter Wheat Identification Based on Active and Passive Satellite Imagery and the Google Earth Engine in Northern China
Haifeng Tian, Jie Pei, Jianxi Huang, et al.
Remote Sensing (2020) Vol. 12, Iss. 21, pp. 3539-3539
Open Access | Times Cited: 149
Early-season mapping of winter wheat in China based on Landsat and Sentinel images
Jie Dong, Yangyang Fu, Jingjing Wang, et al.
Earth system science data (2020) Vol. 12, Iss. 4, pp. 3081-3095
Open Access | Times Cited: 144
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