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:

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

Showing 1-25 of 186 citing articles:

The impact of Russia-Ukraine conflict on global food security
Faqin Lin, Xuecao Li, Ningyuan Jia, et al.
Global Food Security (2022) Vol. 36, pp. 100661-100661
Closed Access | Times Cited: 234
Challenges and opportunities in remote sensing-based crop monitoring: a review
Bingfang Wu, Miao Zhang, Hongwei Zeng, et al.
National Science Review (2022) Vol. 10, Iss. 4
Open Access | Times Cited: 117
Environmental and human health at risk – Scenarios to achieve the Farm to Fork 50% pesticide reduction goals
Vera Silva, Xiaomei Yang, Luuk Fleskens, et al.
Environment International (2022) Vol. 165, pp. 107296-107296
Open Access | Times Cited: 71
A review of regional and Global scale Land Use/Land Cover (LULC) mapping products generated from satellite remote sensing
Yanzhao Wang, Yonghua Sun, X. L. Cao, et al.
ISPRS Journal of Photogrammetry and Remote Sensing (2023) Vol. 206, pp. 311-334
Closed Access | Times Cited: 64
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
Quantifying war-induced crop losses in Ukraine in near real time to strengthen local and global food security
Klaus Deininger, Daniel Ayalew Ali, Nataliia Kussul, et al.
Food Policy (2023) Vol. 115, pp. 102418-102418
Open Access | Times Cited: 52
Application of precision agriculture technologies in Central Europe-review
Bojana Petrović, Roman Bumbálek, Tomáš Zoubek, et al.
Journal of Agriculture and Food Research (2024) Vol. 15, pp. 101048-101048
Open Access | Times Cited: 31
A 30 m annual cropland dataset of China from 1986 to 2021
Ying Tu, Shengbiao Wu, Бин Чэн, et al.
Earth system science data (2024) Vol. 16, Iss. 5, pp. 2297-2316
Open Access | Times Cited: 23
CROPGRIDS: a global geo-referenced dataset of 173 crops
Fiona H. M. Tang, Thu Ha Nguyen, Giulia Conchedda, et al.
Scientific Data (2024) Vol. 11, Iss. 1
Open Access | Times Cited: 22
Crop Type Mapping from Optical and Radar Time Series Using Attention-Based Deep Learning
Stella Ofori-Ampofo, Charlotte Pelletier, Stefan Lang
Remote Sensing (2021) Vol. 13, Iss. 22, pp. 4668-4668
Open Access | Times Cited: 65
Policy implications of multiple concurrent soil erosion processes in European farmland
Pasquale Borrelli, Panos Panagos, Christine Alewell, et al.
Nature Sustainability (2022) Vol. 6, Iss. 1, pp. 103-112
Closed Access | Times Cited: 63
Monitoring changes in global soil organic carbon stocks from space
José Padarian, Uta Stockmann, Budiman Minasny, et al.
Remote Sensing of Environment (2022) Vol. 281, pp. 113260-113260
Closed Access | Times Cited: 61
Designing a European-Wide Crop Type Mapping Approach Based on Machine Learning Algorithms Using LUCAS Field Survey and Sentinel-2 Data
Babak Ghassemi, Aleksandar Dujakovic, Mateusz Żółtak, et al.
Remote Sensing (2022) Vol. 14, Iss. 3, pp. 541-541
Open Access | Times Cited: 46
Cloud-based storage and computing for remote sensing big data: a technical review
Chen Xu, Xiaoping Du, Xiangtao Fan, et al.
International Journal of Digital Earth (2022) Vol. 15, Iss. 1, pp. 1417-1445
Open Access | Times Cited: 44
Mapping Crop Types of Germany by Combining Temporal Statistical Metrics of Sentinel-1 and Sentinel-2 Time Series with LPIS Data
Sarah Asam, Ursula Geßner, Roger Almengor González, et al.
Remote Sensing (2022) Vol. 14, Iss. 13, pp. 2981-2981
Open Access | Times Cited: 40
Crop Type Maps for Operational Global Agricultural Monitoring
Inbal Becker‐Reshef, B. Barker, A. K. Whitcraft, et al.
Scientific Data (2023) Vol. 10, Iss. 1
Open Access | Times Cited: 33
WorldCereal: a dynamic open-source system for global-scale, seasonal, and reproducible crop and irrigation mapping
Kristof Van Tricht, Jeroen Degerickx, Sven Gilliams, et al.
Earth system science data (2023) Vol. 15, Iss. 12, pp. 5491-5515
Open Access | Times Cited: 32
Remote Sensing Data for Digital Soil Mapping in French Research—A Review
Anne C Richer-De-Forges, Qianqian Chen, Nicolas Baghdadi, et al.
Remote Sensing (2023) Vol. 15, Iss. 12, pp. 3070-3070
Open Access | Times Cited: 27
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: 27
From regional to parcel scale: A high-resolution map of cover crops across Europe combining satellite data with statistical surveys
Arthur Nicolaus Fendrich, Francis Matthews, Elise Van Eynde, et al.
The Science of The Total Environment (2023) Vol. 873, pp. 162300-162300
Open Access | Times Cited: 24
Satellite Imagery in Precision Agriculture
Joel Segarra
Springer eBooks (2024), pp. 325-340
Closed Access | Times Cited: 13
Boosting crop classification by hierarchically fusing satellite, rotational, and contextual data
Valentin Barrière, Martin Claverie, Maja Schneider, et al.
Remote Sensing of Environment (2024) Vol. 305, pp. 114110-114110
Open Access | Times Cited: 12
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: 11
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
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: 1
Page 1 - Next Page

Scroll to top