Hamid Ebrahimy

604 total citations
20 papers, 436 citations indexed

About

Hamid Ebrahimy is a scholar working on Ecology, Media Technology and Atmospheric Science. According to data from OpenAlex, Hamid Ebrahimy has authored 20 papers receiving a total of 436 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Ecology, 7 papers in Media Technology and 6 papers in Atmospheric Science. Recurrent topics in Hamid Ebrahimy's work include Remote Sensing in Agriculture (9 papers), Remote-Sensing Image Classification (7 papers) and Oil Spill Detection and Mitigation (3 papers). Hamid Ebrahimy is often cited by papers focused on Remote Sensing in Agriculture (9 papers), Remote-Sensing Image Classification (7 papers) and Oil Spill Detection and Mitigation (3 papers). Hamid Ebrahimy collaborates with scholars based in Iran, China and United States. Hamid Ebrahimy's co-authors include Mohsen Azadbakht, Meisam Amani, Ali Akbar Matkan, Zhou Zhang, Bakhtiar Feizizadeh, Amin Naboureh, Babak Mirbagheri, Hossein Azadi, Sahel Mahdavi and Jinhu Bian and has published in prestigious journals such as IEEE Transactions on Geoscience and Remote Sensing, Sensors and Remote Sensing.

In The Last Decade

Hamid Ebrahimy

19 papers receiving 428 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Hamid Ebrahimy Iran 12 183 171 134 120 54 20 436
Mar Bisquert Spain 12 232 1.3× 295 1.7× 158 1.2× 145 1.2× 34 0.6× 16 475
Fulvio Capodici Italy 15 219 1.2× 162 0.9× 134 1.0× 110 0.9× 27 0.5× 50 579
Qu Zhou United States 11 176 1.0× 103 0.6× 199 1.5× 64 0.5× 70 1.3× 23 525
Claudio Navacchi Austria 10 222 1.2× 219 1.3× 119 0.9× 163 1.4× 40 0.7× 17 478
Andrea Vallario Italy 10 131 0.7× 105 0.6× 120 0.9× 51 0.4× 89 1.6× 15 376
Enrico Cadau Italy 12 170 0.9× 219 1.3× 239 1.8× 125 1.0× 93 1.7× 34 524
Uwe Müller-Wilm Germany 5 170 0.9× 190 1.1× 303 2.3× 77 0.6× 110 2.0× 9 481
Medhavy Thankappan Australia 11 145 0.8× 219 1.3× 220 1.6× 97 0.8× 70 1.3× 33 493
Frieke M.B. Van Coillie Belgium 9 158 0.9× 252 1.5× 186 1.4× 135 1.1× 110 2.0× 16 493
Íñigo Molina Spain 12 209 1.1× 92 0.5× 100 0.7× 138 1.1× 61 1.1× 35 460

Countries citing papers authored by Hamid Ebrahimy

Since Specialization
Citations

This map shows the geographic impact of Hamid Ebrahimy's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Hamid Ebrahimy with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hamid Ebrahimy more than expected).

Fields of papers citing papers by Hamid Ebrahimy

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Hamid Ebrahimy. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Hamid Ebrahimy. The network helps show where Hamid Ebrahimy may publish in the future.

Co-authorship network of co-authors of Hamid Ebrahimy

This figure shows the co-authorship network connecting the top 25 collaborators of Hamid Ebrahimy. A scholar is included among the top collaborators of Hamid Ebrahimy based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Hamid Ebrahimy. Hamid Ebrahimy is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
2.
Ebrahimy, Hamid, Tong Yu, & Zhou Zhang. (2025). Developing a spatiotemporal fusion framework for generating daily UAV images in agricultural areas using publicly available satellite data. ISPRS Journal of Photogrammetry and Remote Sensing. 220. 413–427. 2 indexed citations
3.
Ebrahimy, Hamid, et al.. (2025). Integrating Proximal and Remote Sensing with Machine Learning for Pasture Biomass Estimation. Sensors. 25(7). 1987–1987. 3 indexed citations
4.
Naboureh, Amin, Ainong Li, Jinhu Bian, et al.. (2025). Accuracies, discrepancies, and challenges of the 10 m global land cover products in mountains. GIScience & Remote Sensing. 62(1). 2 indexed citations
5.
Ebrahimy, Hamid, et al.. (2024). Bayesian Joint Adaptation Network for Crop Mapping in the Absence of Mapping Year Ground-Truth Samples. IEEE Transactions on Geoscience and Remote Sensing. 62. 1–20. 3 indexed citations
6.
Ebrahimy, Hamid, Yi Wang, & Zhou Zhang. (2023). Utilization of synthetic minority oversampling technique for improving potato yield prediction using remote sensing data and machine learning algorithms with small sample size of yield data. ISPRS Journal of Photogrammetry and Remote Sensing. 201. 12–25. 25 indexed citations
7.
Ebrahimy, Hamid & Zhou Zhang. (2023). Per-pixel accuracy as a weighting criterion for combining ensemble of extreme learning machine classifiers for satellite image classification. International Journal of Applied Earth Observation and Geoinformation. 122. 103390–103390. 12 indexed citations
8.
Amani, Meisam, Soroosh Mehravar, Reza Mohammadi Asiyabi, et al.. (2022). Ocean Remote Sensing Techniques and Applications: A Review (Part II). Water. 14(21). 3401–3401. 22 indexed citations
9.
Ebrahimy, Hamid, Babak Mirbagheri, Ali Akbar Matkan, & Mohsen Azadbakht. (2022). Effectiveness of the integration of data balancing techniques and tree-based ensemble machine learning algorithms for spatially-explicit land cover accuracy prediction. Remote Sensing Applications Society and Environment. 27. 100785–100785. 12 indexed citations
10.
Amani, Meisam, Armin Moghimi, S. Mohammad Mirmazloumi, et al.. (2022). Ocean Remote Sensing Techniques and Applications: A Review (Part I). Water. 14(21). 3400–3400. 24 indexed citations
11.
Amani, Meisam, Farzane Mohseni, Seyed Ali Ahmadi, et al.. (2022). Remote Sensing Systems for Ocean: A Review (Part 2: Active Systems). IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 15. 1421–1453. 22 indexed citations
12.
Ebrahimy, Hamid, Hossein Aghighi, Mohsen Azadbakht, et al.. (2021). Downscaling MODIS Land Surface Temperature Product Using an Adaptive Random Forest Regression Method and Google Earth Engine for a 19-Years Spatiotemporal Trend Analysis Over Iran. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 14. 2103–2112. 50 indexed citations
13.
Ebrahimy, Hamid, Amin Naboureh, Bakhtiar Feizizadeh, Jagannath Aryal, & Omid Ghorbanzadeh. (2021). Integration of Sentinel-1 and Sentinel-2 Data with the G-SMOTE Technique for Boosting Land Cover Classification Accuracy. Applied Sciences. 11(21). 10309–10309. 8 indexed citations
14.
Naboureh, Amin, Ainong Li, Hamid Ebrahimy, et al.. (2021). Assessing the effects of irrigated agricultural expansions on Lake Urmia using multi-decadal Landsat imagery and a sample migration technique within Google Earth Engine. International Journal of Applied Earth Observation and Geoinformation. 105. 102607–102607. 28 indexed citations
15.
Amani, Meisam, et al.. (2021). Oil Spill Detection Using Satellite Imagery. 2(4). 1–9. 8 indexed citations
16.
17.
Ebrahimy, Hamid, Babak Mirbagheri, Ali Akbar Matkan, & Mohsen Azadbakht. (2020). Per-pixel land cover accuracy prediction: A random forest-based method with limited reference sample data. ISPRS Journal of Photogrammetry and Remote Sensing. 172. 17–27. 42 indexed citations
18.
Naboureh, Amin, Hamid Ebrahimy, Mohsen Azadbakht, Jinhu Bian, & Meisam Amani. (2020). RUESVMs: An Ensemble Method to Handle the Class Imbalance Problem in Land Cover Mapping Using Google Earth Engine. Remote Sensing. 12(21). 3484–3484. 29 indexed citations
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Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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