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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:

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

Showing 1-25 of 36 citing articles:

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 mapping using supervised machine learning and deep learning: a systematic literature review
Mouad Alami Machichi, Loubna El Mansouri, Yasmina Imani, et al.
International Journal of Remote Sensing (2023) Vol. 44, Iss. 8, pp. 2717-2753
Open Access | Times Cited: 26
Interseasonal transfer learning for crop mapping using Sentinel-1 data
Miloš Pandžić, Dejan Pavlović, Predrag Matavulj, et al.
International Journal of Applied Earth Observation and Geoinformation (2024) Vol. 128, pp. 103718-103718
Open Access | Times Cited: 11
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
A generalized model for mapping sunflower areas using Sentinel-1 SAR data
Abdul Qadir, Sergii Skakun, Nataliia Kussul, et al.
Remote Sensing of Environment (2024) Vol. 306, pp. 114132-114132
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
Improving Land Use/Cover Classification Accuracy from Random Forest Feature Importance Selection Based on Synergistic Use of Sentinel Data and Digital Elevation Model in Agriculturally Dominated Landscape
Saad Eddin Ibrahim
Agriculture (2022) Vol. 13, Iss. 1, pp. 98-98
Open Access | Times Cited: 24
Crop type classification with combined spectral, texture, and radar features of time-series Sentinel-1 and Sentinel-2 data
Gang Cheng, Huan Ding, Jie Yang, et al.
International Journal of Remote Sensing (2023) Vol. 44, Iss. 4, pp. 1215-1237
Closed Access | Times Cited: 17
Spatially transferable machine learning wind power prediction models: v−logit random forests
Mario E. Arrieta-Prieto, Kristen R. Schell
Renewable Energy (2024) Vol. 223, pp. 120066-120066
Open Access | Times Cited: 5
Temporally transferable crop mapping with temporal encoding and deep learning augmentations
Vu-Dong Pham, Gideon Okpoti Tetteh, Fabian Thiel, et al.
International Journal of Applied Earth Observation and Geoinformation (2024) Vol. 129, pp. 103867-103867
Open Access | Times Cited: 4
Transferability of Machine Learning Models for Crop Classification in Remote Sensing Imagery Using a New Test Methodology: A Study on Phenological, Temporal, and Spatial Influences
Hauke Hoppe, Peter Dietrich, Philip Marzahn, et al.
Remote Sensing (2024) Vol. 16, Iss. 9, pp. 1493-1493
Open Access | Times Cited: 4
Selecting Relevant Features for Random Forest-Based Crop Type Classifications by Spatial Assessments of Backward Feature Reduction
Talha Mahmood, Muhammad Usman, Christopher Conrad
PFG – Journal of Photogrammetry Remote Sensing and Geoinformation Science (2025)
Open Access
Sentinel-1 (S1) time series alignment method for rapeseed fields mapping
Saeideh Maleki, Nicolas Baghdadi, Sami Najem, et al.
Frontiers in Remote Sensing (2025) Vol. 5
Open Access
Advancements in crop mapping through remote sensing: A comprehensive review of concept, data sources, and procedures over four decades
Iman Khosravi
Remote Sensing Applications Society and Environment (2025), pp. 101527-101527
Closed Access
Enhancing Crop Type Mapping in Data-Scarce Regions Through Transfer Learning: A Case Study of the Hexi Corridor
Juliane Mai, Qisheng Feng, Shuai Fu, et al.
Remote Sensing (2025) Vol. 17, Iss. 9, pp. 1494-1494
Open Access
Crop Type Prediction: A Statistical and Machine Learning Approach
Bikram Pratim Bhuyan, Ravi Tomar, Thipendra P. Singh, et al.
Sustainability (2022) Vol. 15, Iss. 1, pp. 481-481
Open Access | Times Cited: 16
Crop classification based on G-CNN using multi-scale remote sensing images
Mengmeng Meng, Kaixin Zhang, Yabo Huang, et al.
Remote Sensing Letters (2024) Vol. 15, Iss. 9, pp. 941-950
Closed Access | Times Cited: 3
Crop Classification Based on GDSSM-CNN Using Multi-Temporal RADARSAT-2 SAR with Limited Labeled Data
Heping Li, Jing Lu, Guixiang Tian, et al.
Remote Sensing (2022) Vol. 14, Iss. 16, pp. 3889-3889
Open Access | Times Cited: 13
Synergy of Sentinel-1 and Sentinel-2 Imagery for Crop Classification Based on DC-CNN
Kaixin Zhang, Da Yuan, Huijin Yang, et al.
Remote Sensing (2023) Vol. 15, Iss. 11, pp. 2727-2727
Open Access | Times Cited: 8
Towards an Improved Large-Scale Gridded Population Dataset: A Pan-European Study on the Integration of 3D Settlement Data into Population Modelling
Daniela Palacios‐Lopez, Thomas Esch, Kytt MacManus, et al.
Remote Sensing (2022) Vol. 14, Iss. 2, pp. 325-325
Open Access | Times Cited: 11
Exploring Transferable Techniques to Retrieve Crop Biophysical and Biochemical Variables Using Sentinel-2 Data
Mahlatse Kganyago, Clement Adjorlolo, Paidamwoyo Mhangara
Remote Sensing (2022) Vol. 14, Iss. 16, pp. 3968-3968
Open Access | Times Cited: 11
In-Depth Analysis and Characterization of a Hazelnut Agro-Industrial Context through the Integration of Multi-Source Satellite Data: A Case Study in the Province of Viterbo, Italy
Francesco Lodato, Giorgio Pennazza, Marco Santonico, et al.
Remote Sensing (2024) Vol. 16, Iss. 7, pp. 1227-1227
Open Access | Times Cited: 2
Improving the crop classification performance by unlabeled remote sensing data
Hengbin Wang, Zijing Ye, Yan Wang, et al.
Expert Systems with Applications (2023) Vol. 236, pp. 121283-121283
Closed Access | Times Cited: 5
Crop Classification using Sentinel-1 and Sentinel-2: A Machine Learning Method
Sourav, Navneet Kaur, Bobbinpreet Kaur
(2024), pp. 1-6
Closed Access | Times Cited: 1
Crop Classification Using Multi-Temporal RADARSAT Constellation Mission Compact Polarimetry SAR Data
Ramin Farhadiani, Saeid Homayouni, Avik Bhattacharya, et al.
Canadian Journal of Remote Sensing (2024) Vol. 50, Iss. 1
Open Access | Times Cited: 1
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