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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:

An evaluation of Landsat, Sentinel-2, Sentinel-1 and MODIS data for crop type mapping
Xiao‐Peng Song, Wenli Huang, Matthew C. Hansen, et al.
Science of Remote Sensing (2021) Vol. 3, pp. 100018-100018
Open Access | Times Cited: 110

Showing 1-25 of 110 citing articles:

A systematic review on hyperspectral imaging technology with a machine and deep learning methodology for agricultural applications
Atiya Khan, Amol D. Vibhute, Shankar Mali, et al.
Ecological Informatics (2022) Vol. 69, pp. 101678-101678
Closed Access | Times Cited: 220
Early- and in-season crop type mapping without current-year ground truth: Generating labels from historical information via a topology-based approach
Chenxi Lin, Liheng Zhong, Xiao‐Peng Song, et al.
Remote Sensing of Environment (2022) Vol. 274, pp. 112994-112994
Open Access | Times Cited: 84
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
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: 53
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: 63
Mapping Crop Types and Cropping Systems in Nigeria with Sentinel-2 Imagery
Esther Shupel Ibrahim, Philippe Rufin, Leon Nill, et al.
Remote Sensing (2021) Vol. 13, Iss. 17, pp. 3523-3523
Open Access | Times Cited: 59
Evaluating the efficiency of coarser to finer resolution multispectral satellites in mapping paddy rice fields using GEE implementation
Mirza Waleed, Muhammad Mubeen, Ashfaq Ahmad, et al.
Scientific Reports (2022) Vol. 12, Iss. 1
Open Access | Times Cited: 50
Improving remote sensing estimation of Secchi disk depth for global lakes and reservoirs using machine learning methods
Yibo Zhang, Kun� Shi, Xiao Sun, et al.
GIScience & Remote Sensing (2022) Vol. 59, Iss. 1, pp. 1367-1383
Open Access | Times Cited: 41
A novel Greenness and Water Content Composite Index (GWCCI) for soybean mapping from single remotely sensed multispectral images
Hui Chen, Huapeng Li, Zhao Liu, et al.
Remote Sensing of Environment (2023) Vol. 295, pp. 113679-113679
Open Access | Times Cited: 36
Early Crop Classification via Multi-Modal Satellite Data Fusion and Temporal Attention
Frank Weilandt, Robert Behling, Romulo Gonçalves, et al.
Remote Sensing (2023) Vol. 15, Iss. 3, pp. 799-799
Open Access | Times Cited: 23
Common Practices and Taxonomy in Deep Multiview Fusion for Remote Sensing Applications
Francisco Mena, Diego Arenas, Marlon Nuske, et al.
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (2024) Vol. 17, pp. 4797-4818
Open Access | Times Cited: 10
Deep learning with multi-scale temporal hybrid structure for robust crop mapping
Pengfei Tang, Jocelyn Chanussot, Shanchuan Guo, et al.
ISPRS Journal of Photogrammetry and Remote Sensing (2024) Vol. 209, pp. 117-132
Closed Access | Times Cited: 9
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
Time-Series-Based Spatiotemporal Fusion Network for Improving Crop Type Mapping
Wenfang Zhan, Feng Luo, Heng Luo, et al.
Remote Sensing (2024) Vol. 16, Iss. 2, pp. 235-235
Open Access | Times Cited: 6
Evaluation of soil texture classification from orthodox interpolation and machine learning techniques
Lei Feng, Umer Khalil, Bilal Aslam, et al.
Environmental Research (2023) Vol. 246, pp. 118075-118075
Open Access | Times Cited: 15
Accurate vegetation destruction detection using remote sensing imagery based on the three-band difference vegetation index (TBDVI) and dual-temporal detection method
Chuanwu Zhao, Yaozhong Pan, Shoujia Ren, et al.
International Journal of Applied Earth Observation and Geoinformation (2024) Vol. 127, pp. 103669-103669
Open Access | Times Cited: 5
Spectral-temporal traits in Sentinel-1 C-band SAR and Sentinel-2 multispectral remote sensing time series for 61 tree species in Central Europe
Christian Schulz, Michael Förster, Stenka Vulova, et al.
Remote Sensing of Environment (2024) Vol. 307, pp. 114162-114162
Open Access | Times Cited: 5
Predictive Modeling of Above-Ground Biomass in Brachiaria Pastures from Satellite and UAV Imagery Using Machine Learning Approaches
César Iván Álvarez Mendoza, Diego Guzman, Jorge Casas, et al.
Remote Sensing (2022) Vol. 14, Iss. 22, pp. 5870-5870
Open Access | Times Cited: 22
Large-area mapping of active cropland and short-term fallows in smallholder landscapes using PlanetScope data
Philippe Rufin, Adia Bey, Michelle Cristina Araújo Picoli, et al.
International Journal of Applied Earth Observation and Geoinformation (2022) Vol. 112, pp. 102937-102937
Open Access | Times Cited: 20
Assessing fire severity in Turkey’s forest ecosystems using spectral indices from satellite images
Coşkun Okan Güney, Ahmet Mert, Serkan Gülsoy
Journal of Forestry Research (2023) Vol. 34, Iss. 6, pp. 1747-1761
Open Access | Times Cited: 12
Annual Field-Scale Maps of Tall and Short Crops at the Global Scale Using GEDI and Sentinel-2
Stefania Di Tommaso, Sherrie Wang, Vivek Vajipey, et al.
Remote Sensing (2023) Vol. 15, Iss. 17, pp. 4123-4123
Open Access | Times Cited: 11
AgriCarbon-EO v1.0.1: large-scale and high-resolution simulation of carbon fluxes by assimilation of Sentinel-2 and Landsat-8 reflectances using a Bayesian approach
Taeken Wijmer, Ahmad Al Bitar, Ludovic Arnaud, et al.
Geoscientific model development (2024) Vol. 17, Iss. 3, pp. 997-1021
Open Access | Times Cited: 4
Optimizing Riparian Habitat Conservation: A Spatial Approach Using Aerial and Space Technologies
Ravindra Nath Tripathi, Aishwarya Ramachandran, Vikas Tripathi, et al.
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (2024) Vol. 17, pp. 16932-16943
Open Access | Times Cited: 4
Evaluation of Deep Learning Methods for Forecasting Turbidity in River Networks Using Sentinel-2 Remote Sensing Data
Victor Rocha Santos, Paulo Alexandre Costa Rocha, Jesse Van Griensven Thé, et al.
(2025)
Closed Access
Deep learning in multi-sensor agriculture and crop management
Darwin Alexis Arrechea-Castillo, Yady Tatiana Solano‐Correa
Elsevier eBooks (2025), pp. 335-379
Closed Access
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