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:

Large-scale crop type and crop area mapping across Brazil using synthetic aperture radar and optical imagery
Olaniyi A. Ajadi, Jeremiah Barr, Sang-Zi Liang, et al.
International Journal of Applied Earth Observation and Geoinformation (2021) Vol. 97, pp. 102294-102294
Open Access | Times Cited: 41

Showing 1-25 of 41 citing articles:

Mapping corn dynamics using limited but representative samples with adaptive strategies
Yanan Wen, Xuecao Li, Haowei Mu, et al.
ISPRS Journal of Photogrammetry and Remote Sensing (2022) Vol. 190, pp. 252-266
Open Access | Times Cited: 46
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: 40
Applications, Challenges and Perspectives for Monitoring Agricultural Dynamics in the Brazilian Savanna with Multispectral Remote Sensing
Taya Cristo Parreiras, Édson Luís Bolfe, Paulo Roberto Mendes Pereira, et al.
Remote Sensing Applications Society and Environment (2025) Vol. 37, pp. 101448-101448
Open Access | Times Cited: 1
Transferable deep learning model based on the phenological matching principle for mapping crop extent
Shuang Ge, Jinshui Zhang, Yaozhong Pan, et al.
International Journal of Applied Earth Observation and Geoinformation (2021) Vol. 102, pp. 102451-102451
Open Access | Times Cited: 45
Spatial Transferability of Random Forest Models for Crop Type Classification Using Sentinel-1 and Sentinel-2
Aiym Orynbaikyzy, Ursula Geßner, Christopher Conrad
Remote Sensing (2022) Vol. 14, Iss. 6, pp. 1493-1493
Open Access | Times Cited: 36
Deep learning in cropland field identification: A review
Fan Xu, Xiaochuang Yao, Kangxin Zhang, et al.
Computers and Electronics in Agriculture (2024) Vol. 222, pp. 109042-109042
Closed Access | Times Cited: 8
Evaluating the spatial–temporal transferability of models for agricultural land cover mapping using Landsat archive
Jayan Wijesingha, Ilze Dzene, M. Wachendorf
ISPRS Journal of Photogrammetry and Remote Sensing (2024) Vol. 213, pp. 72-86
Open Access | Times Cited: 7
Mapping Maize Area in Heterogeneous Agricultural Landscape with Multi-Temporal Sentinel-1 and Sentinel-2 Images Based on Random Forest
Yansi Chen, Jinliang Hou, Chunlin Huang, et al.
Remote Sensing (2021) Vol. 13, Iss. 15, pp. 2988-2988
Open Access | Times Cited: 33
Spatial-aware SAR-optical time-series deep integration for crop phenology tracking
Wenzhi Zhao, Yang Qu, Liqiang Zhang, et al.
Remote Sensing of Environment (2022) Vol. 276, pp. 113046-113046
Closed Access | Times Cited: 26
Rapid and Automated Mapping of Crop Type in Jilin Province Using Historical Crop Labels and the Google Earth Engine
Feng Zhi, Zhenhua Dong, Suri Guga, et al.
Remote Sensing (2022) Vol. 14, Iss. 16, pp. 4028-4028
Open Access | Times Cited: 22
National high-resolution cropland classification of Japan with agricultural census information and multi-temporal multi-modality datasets
Junshi Xia, Naoto Yokoya, Bruno Adriano, et al.
International Journal of Applied Earth Observation and Geoinformation (2023) Vol. 117, pp. 103193-103193
Open Access | Times Cited: 13
Mapping Integrated Crop–Livestock Systems Using Fused Sentinel-2 and PlanetScope Time Series and Deep Learning
J. P. S. Werner, Mariana Belgiu, Inácio Thomaz Bueno, et al.
Remote Sensing (2024) Vol. 16, Iss. 8, pp. 1421-1421
Open Access | Times Cited: 4
Winter Wheat Mapping in Shandong Province of China with Multi-Temporal Sentinel-2 Images
Yongyu Feng, Bingyao Chen, Wei Liu, et al.
Applied Sciences (2024) Vol. 14, Iss. 9, pp. 3940-3940
Open Access | Times Cited: 4
Lightweight Deep Learning Model, ConvNeXt-U: An Improved U-Net Network for Extracting Cropland in Complex Landscapes from Gaofen-2 Images
Sijie Liu, Cao Shi, Lu Xia, et al.
Sensors (2025) Vol. 25, Iss. 1, pp. 261-261
Open Access
Mixing Data Cube Architecture and Geo-Object-Oriented Time Series Segmentation for Mapping Heterogeneous Landscapes
Michel Eustáquio Dantas Chaves, L.A.A. Soares, G. O. V. de Barros, et al.
AgriEngineering (2025) Vol. 7, Iss. 1, pp. 19-19
Open Access
A SAM-adapted weakly-supervised semantic segmentation method constrained by uncertainty and transformation consistency
Yinxia Cao, Xin Huang, Qihao Weng
International Journal of Applied Earth Observation and Geoinformation (2025) Vol. 137, pp. 104440-104440
Closed Access
Assessing the Impact of Cloud Removal and Reconstruction Through Sar-Optical Data Fusion on Crop Mapping Accuracy
Chenxi Duan, Mariana Belgiu, Alfred Stein
(2025)
Closed Access
Modifying NISAR’s Cropland Area Algorithm to Map Cropland Extent Globally
Kaylee G. Sharp, Jordan R. Bell, H. G. Pankratz, et al.
Remote Sensing (2025) Vol. 17, Iss. 6, pp. 1094-1094
Open Access
A robust framework for mapping complex cropping patterns: The first national-scale 10 m map with 10 crops in China using Sentinel 1/2 images
Bingwen Qiu, Fangzheng Wu, Xiang Hu, et al.
ISPRS Journal of Photogrammetry and Remote Sensing (2025) Vol. 224, pp. 361-381
Closed Access
Mapping Agricultural Intensification in the Brazilian Savanna: A Machine Learning Approach Using Harmonized Data from Landsat Sentinel-2
Édson Luís Bolfe, Taya Cristo Parreiras, Lucas Augusto Pereira da Silva, et al.
ISPRS International Journal of Geo-Information (2023) Vol. 12, Iss. 7, pp. 263-263
Open Access | Times Cited: 9
National-scale 10 m annual maize maps for China and the contiguous United States using a robust index from Sentinel-2 time series
Yingze Huang, Bingwen Qiu, Peng Yang, et al.
Computers and Electronics in Agriculture (2024) Vol. 221, pp. 109018-109018
Closed Access | Times Cited: 3
Phenological normalization can improve in-season classification of maize and soybean: A case study in the central US Corn Belt
Hannah Kerner, Ritvik Sahajpal, Dhruv Pai, et al.
Science of Remote Sensing (2022) Vol. 6, pp. 100059-100059
Closed Access | Times Cited: 13
Monitoring Maize Growth and Calculating Plant Heights with Synthetic Aperture Radar (SAR) and Optical Satellite Images
İbrahim Arslan, Mehmet Topakçı, Nusret Demir
Agriculture (2022) Vol. 12, Iss. 6, pp. 800-800
Open Access | Times Cited: 12
Hierarchical Classification of Soybean in the Brazilian Savanna Based on Harmonized Landsat Sentinel Data
Taya Cristo Parreiras, Édson Luís Bolfe, Michel Eustáquio Dantas Chaves, et al.
Remote Sensing (2022) Vol. 14, Iss. 15, pp. 3736-3736
Open Access | Times Cited: 12
Rice Mapping Using a BiLSTM-Attention Model from Multitemporal Sentinel-1 Data
Chunling Sun, Hong Zhang, Lu Xu, et al.
Agriculture (2021) Vol. 11, Iss. 10, pp. 977-977
Open Access | Times Cited: 16
Page 1 - Next Page

Scroll to top