Open Access Helper

OpenAlex Citation Counts

OpenAlex Citations Logo

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:

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

Showing 1-25 of 221 citing articles:

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
Combining Sentinel-1 and Sentinel-2 Satellite Image Time Series for land cover mapping via a multi-source deep learning architecture
Dino Ienco, Roberto Interdonato, Raffaele Gaetano, et al.
ISPRS Journal of Photogrammetry and Remote Sensing (2019) Vol. 158, pp. 11-22
Open Access | Times Cited: 257
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
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
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
Multi-modal temporal attention models for crop mapping from satellite time series
Vivien Sainte Fare Garnot, Loïc Landrieu, Nesrine Chehata
ISPRS Journal of Photogrammetry and Remote Sensing (2022) Vol. 187, pp. 294-305
Open Access | Times Cited: 75
Development of a 10-m resolution maize and soybean map over China: Matching satellite-based crop classification with sample-based area estimation
Haijun Li, Xiao‐Peng Song, Matthew C. Hansen, et al.
Remote Sensing of Environment (2023) Vol. 294, pp. 113623-113623
Closed Access | Times Cited: 57
Crop monitoring by multimodal remote sensing: A review
Priyabrata Karmakar, Shyh Wei Teng, Manzur Murshed, et al.
Remote Sensing Applications Society and Environment (2023) Vol. 33, pp. 101093-101093
Open Access | Times Cited: 52
National tree species mapping using Sentinel-1/2 time series and German National Forest Inventory data
Lukas Blickensdörfer, Katja Oehmichen, Dirk Pflugmacher, et al.
Remote Sensing of Environment (2024) Vol. 304, pp. 114069-114069
Open Access | Times Cited: 36
Detecting flowering phenology in oil seed rape parcels with Sentinel-1 and -2 time series
Raphaël d’Andrimont, Matthieu Taymans, Guido Lemoine, et al.
Remote Sensing of Environment (2020) Vol. 239, pp. 111660-111660
Open Access | Times Cited: 135
Mapping paddy rice by the object-based random forest method using time series Sentinel-1/Sentinel-2 data
Yaotong Cai, Hui Lin, Meng Zhang
Advances in Space Research (2019) Vol. 64, Iss. 11, pp. 2233-2244
Closed Access | Times Cited: 131
High-resolution satellite imagery applications in crop phenotyping: An overview
Chongyuan Zhang, Afef Marzougui, Sindhuja Sankaran
Computers and Electronics in Agriculture (2020) Vol. 175, pp. 105584-105584
Open Access | Times Cited: 117
Crop Type Classification Using Fusion of Sentinel-1 and Sentinel-2 Data: Assessing the Impact of Feature Selection, Optical Data Availability, and Parcel Sizes on the Accuracies
Aiym Orynbaikyzy, Ursula Geßner, Benjamin Mack, et al.
Remote Sensing (2020) Vol. 12, Iss. 17, pp. 2779-2779
Open Access | Times Cited: 99
Crop Classification Based on Temporal Signatures of Sentinel-1 Observations over Navarre Province, Spain
M. Arias, Miguel Ángel Campo‐Bescós, Jesús Álvarez‐Mozos
Remote Sensing (2020) Vol. 12, Iss. 2, pp. 278-278
Open Access | Times Cited: 95
Combined use of Sentinel-1 and Sentinel-2 data for improving above-ground biomass estimation
Narissara Nuthammachot, Askar Askar, Dimitris Stratoulias, et al.
Geocarto International (2020) Vol. 37, Iss. 2, pp. 366-376
Closed Access | Times Cited: 95
Land Use Land Cover Classification with U-Net: Advantages of Combining Sentinel-1 and Sentinel-2 Imagery
Jonathan V. Solórzano, Jean‐François Mas, Yan Gao, et al.
Remote Sensing (2021) Vol. 13, Iss. 18, pp. 3600-3600
Open Access | Times Cited: 95
Deeply synergistic optical and SAR time series for crop dynamic monitoring
Wenzhi Zhao, Yang Qu, Jiage Chen, et al.
Remote Sensing of Environment (2020) Vol. 247, pp. 111952-111952
Closed Access | Times Cited: 90
Application of Google Earth Engine Cloud Computing Platform, Sentinel Imagery, and Neural Networks for Crop Mapping in Canada
Meisam Amani, Mohammad Kakooei, Armin Moghimi, et al.
Remote Sensing (2020) Vol. 12, Iss. 21, pp. 3561-3561
Open Access | Times Cited: 86
Integrating Multitemporal Sentinel-1/2 Data for Coastal Land Cover Classification Using a Multibranch Convolutional Neural Network: A Case of the Yellow River Delta
Quanlong Feng, Jianyu Yang, Dehai Zhu, et al.
Remote Sensing (2019) Vol. 11, Iss. 9, pp. 1006-1006
Open Access | Times Cited: 85
Evaluation of Using Sentinel-1 and -2 Time-Series to Identify Winter Land Use in Agricultural Landscapes
Julien Denize, Laurence Hubert‐Moy, Julie Betbeder, et al.
Remote Sensing (2018) Vol. 11, Iss. 1, pp. 37-37
Open Access | Times Cited: 84
The impact of conflict-driven cropland abandonment on food insecurity in South Sudan revealed using satellite remote sensing
Victor Mackenhauer Olsen, Rasmus Fensholt, Pontus Olofsson, et al.
Nature Food (2021) Vol. 2, Iss. 12, pp. 990-996
Open Access | Times Cited: 81
Comparing Sentinel-1 and -2 Data and Indices for Agricultural Land Use Monitoring
Ann-Kathrin Holtgrave, Norbert Röder, Andrea Ackermann, et al.
Remote Sensing (2020) Vol. 12, Iss. 18, pp. 2919-2919
Open Access | Times Cited: 77
CNN-based burned area mapping using radar and optical data
Miguel A. Belenguer-Plomer, Mihai A. Tanase, Emilio Chuvieco, et al.
Remote Sensing of Environment (2021) Vol. 260, pp. 112468-112468
Open Access | Times Cited: 74
Page 1 - Next Page

Scroll to top