Naoto Yokoya

14.9k total citations · 13 hit papers
173 papers, 10.9k citations indexed

About

Naoto Yokoya is a scholar working on Media Technology, Computer Vision and Pattern Recognition and Atmospheric Science. According to data from OpenAlex, Naoto Yokoya has authored 173 papers receiving a total of 10.9k indexed citations (citations by other indexed papers that have themselves been cited), including 108 papers in Media Technology, 61 papers in Computer Vision and Pattern Recognition and 44 papers in Atmospheric Science. Recurrent topics in Naoto Yokoya's work include Remote-Sensing Image Classification (95 papers), Advanced Image Fusion Techniques (57 papers) and Remote Sensing and Land Use (42 papers). Naoto Yokoya is often cited by papers focused on Remote-Sensing Image Classification (95 papers), Advanced Image Fusion Techniques (57 papers) and Remote Sensing and Land Use (42 papers). Naoto Yokoya collaborates with scholars based in Japan, China and Germany. Naoto Yokoya's co-authors include Jocelyn Chanussot, Akira Iwasaki, Danfeng Hong, Pedram Ghamisi, Takehisa Yairi, Wei He, Junshi Xia, Jing Yao, Bing Zhang and Xiao Xiang Zhu and has published in prestigious journals such as Nature Communications, SHILAP Revista de lepidopterología and IEEE Transactions on Pattern Analysis and Machine Intelligence.

In The Last Decade

Naoto Yokoya

164 papers receiving 10.7k citations

Hit Papers

More Diverse Means Better: Multim... 2011 2026 2016 2021 2020 2011 2017 2015 2017 250 500 750 1000
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. More Diverse Means Better: Multimodal Deep Learning Meets Remote-Sensing Imagery Classification
    2020 1.1k citations Danfeng Hong, Naoto Yokoya et al. IEEE Transactions on Geoscience and Remote Sensing profile →
  2. Coupled Nonnegative Matrix Factorization Unmixing for Hyperspectral and Multispectral Data Fusion
    2011 852 citations Naoto Yokoya et al. IEEE Transactions on Geoscience and Remote Sensing profile →
  3. Advances in Hyperspectral Image and Signal Processing: A Comprehensive Overview of the State of the Art
    2017 647 citations Pedram Ghamisi, Naoto Yokoya et al. IEEE Geoscience and Remote Sensing Magazine profile →
  4. Pan-sharpening Hyperspectral : revue
    2015 613 citations Laëtitia Loncan, Luı́s B. Almeida et al. profile →
  5. Hyperspectral and Multispectral Data Fusion: A comparative review of the recent literature
    2017 512 citations Naoto Yokoya, Jocelyn Chanussot et al. IEEE Geoscience and Remote Sensing Magazine profile →
  6. SpectralGPT: Spectral Remote Sensing Foundation Model
    2024 467 citations Danfeng Hong, Bing Zhang et al. IEEE Transactions on Pattern Analysis and Machine Intelligence profile →
  7. Multisource and Multitemporal Data Fusion in Remote Sensing: A Comprehensive Review of the State of the Art
    2019 418 citations Pedram Ghamisi, Richard Gloaguen et al. IEEE Geoscience and Remote Sensing Magazine profile →
  8. Invariant Attribute Profiles: A Spatial-Frequency Joint Feature Extractor for Hyperspectral Image Classification
    2020 263 citations Danfeng Hong, Pedram Ghamisi et al. IEEE Transactions on Geoscience and Remote Sensing profile →
  9. Advanced Multi-Sensor Optical Remote Sensing for Urban Land Use and Land Cover Classification: Outcome of the 2018 IEEE GRSS Data Fusion Contest
    2019 255 citations Naoto Yokoya, Ronny Hänsch et al. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing profile →
  10. Remote Sensing Approaches for Monitoring Mangrove Species, Structure, and Biomass: Opportunities and Challenges
    2019 235 citations Tien Dat Pham, Naoto Yokoya et al. Remote Sensing profile →
  11. Endmember-Guided Unmixing Network (EGU-Net): A General Deep Learning Framework for Self-Supervised Hyperspectral Unmixing
    2021 178 citations Danfeng Hong, Jing Yao et al. profile →
  12. Decoupled-and-Coupled Networks: Self-Supervised Hyperspectral Image Super-Resolution With Subpixel Fusion
    2023 156 citations Danfeng Hong, Jing Yao et al. IEEE Transactions on Geoscience and Remote Sensing profile →
  13. Multimodal artificial intelligence foundation models: Unleashing the power of remote sensing big data in earth observation
    2024 65 citations Danfeng Hong, Chenyu Li et al. profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Naoto Yokoya Japan 52 7.3k 4.6k 2.3k 1.7k 1.3k 173 10.9k
Lianru Gao China 53 9.1k 1.3× 4.1k 0.9× 4.1k 1.8× 1.3k 0.8× 807 0.6× 277 12.2k
Bing Zhang China 53 7.9k 1.1× 3.6k 0.8× 3.8k 1.7× 1.7k 1.0× 907 0.7× 320 13.1k
Qiangqiang Yuan China 52 5.5k 0.8× 5.3k 1.1× 2.0k 0.9× 1.1k 0.6× 2.1k 1.7× 241 10.5k
Danfeng Hong China 59 10.2k 1.4× 5.7k 1.2× 4.0k 1.7× 1.4k 0.9× 1.0k 0.8× 247 15.3k
Lefei Zhang China 47 5.7k 0.8× 5.0k 1.1× 2.8k 1.2× 842 0.5× 557 0.4× 195 10.3k
Zhenwei Shi China 47 5.3k 0.7× 4.8k 1.0× 2.0k 0.9× 1.1k 0.6× 546 0.4× 271 9.8k
Yanfei Zhong China 66 8.9k 1.2× 4.8k 1.0× 4.4k 1.9× 2.5k 1.5× 1.5k 1.2× 403 13.3k
Weiwei Sun China 52 4.9k 0.7× 2.1k 0.5× 3.1k 1.3× 1.3k 0.8× 838 0.7× 330 8.8k
Devis Tuia Switzerland 53 5.4k 0.7× 3.7k 0.8× 2.5k 1.1× 2.2k 1.3× 1.6k 1.3× 251 11.0k
Hongyan Zhang China 49 6.0k 0.8× 5.0k 1.1× 2.1k 0.9× 894 0.5× 489 0.4× 324 9.9k

Countries citing papers authored by Naoto Yokoya

Since Specialization
Citations

This map shows the geographic impact of Naoto Yokoya'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 Naoto Yokoya with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Naoto Yokoya more than expected).

Fields of papers citing papers by Naoto Yokoya

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Naoto Yokoya. 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 Naoto Yokoya. The network helps show where Naoto Yokoya may publish in the future.

Co-authorship network of co-authors of Naoto Yokoya

This figure shows the co-authorship network connecting the top 25 collaborators of Naoto Yokoya. A scholar is included among the top collaborators of Naoto Yokoya 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 Naoto Yokoya. Naoto Yokoya 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.
Chen, Hongruixuan, Jian Song, Junjue Wang, et al.. (2025). Bright: a globally distributed multimodal building damage assessment dataset with very-high-resolution for all-weather disaster response. Earth system science data. 17(11). 6217–6253. 5 indexed citations
2.
Ding, Lei, Danfeng Hong, Hongruixuan Chen, et al.. (2025). A Survey of Sample-Efficient Deep Learning for Change Detection in Remote Sensing: Tasks, strategies, and challenges. IEEE Geoscience and Remote Sensing Magazine. 13(3). 164–189. 7 indexed citations
3.
Xia, Junshi, et al.. (2025). Generating national very high-resolution land cover product of France without any labels: A comparative study. Remote Sensing Applications Society and Environment. 38. 101542–101542. 1 indexed citations
4.
Wang, Junjue, Hongruixuan Chen, Zhuo Zheng, et al.. (2025). CityVLM: Towards sustainable urban development via multi-view coordinated vision–language model. ISPRS Journal of Photogrammetry and Remote Sensing. 232. 62–74.
5.
Callejo, Miguel Ángel Manso, et al.. (2024). Impact of Tile Size and Tile Overlap on the Prediction Performance of Convolutional Neural Networks Trained for Road Classification. Remote Sensing. 16(15). 2818–2818. 1 indexed citations
6.
Hong, Danfeng, Bing Zhang, Xuyang Li, et al.. (2024). SpectralGPT: Spectral Remote Sensing Foundation Model. IEEE Transactions on Pattern Analysis and Machine Intelligence. 46(8). 5227–5244. 467 indexed citations breakdown →
7.
Ahmadi, Seyed Ali, Ali Mohammadzadeh, Naoto Yokoya, & Arsalan Ghorbanian. (2023). BD-SKUNet: Selective-Kernel UNets for Building Damage Assessment in High-Resolution Satellite Images. Remote Sensing. 16(1). 182–182. 14 indexed citations
8.
Li, Zhuohong, Hongyan Zhang, Jiayi Li, et al.. (2022). The Outcome of the 2021 IEEE GRSS Data Fusion Contest—Track MSD: Multitemporal Semantic Change Detection. SHILAP Revista de lepidopterología. 24 indexed citations
9.
Huang, Ting‐Zhu, et al.. (2022). An Iterative Regularization Method Based on Tensor Subspace Representation for Hyperspectral Image Super-Resolution. IEEE Transactions on Geoscience and Remote Sensing. 60. 1–16. 53 indexed citations
10.
Schmitt, Michael, Pedram Ghamisi, Naoto Yokoya, & Ronny Hänsch. (2022). EOD: The IEEE GRSS Earth Observation Database. IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium. 5365–5368. 10 indexed citations
11.
Yokoya, Naoto, Pedram Ghamisi, Ronny Hänsch, et al.. (2021). 2021 Data Fusion Contest: Geospatial Artificial Intelligence for Social Good [Technical Committees]. IEEE Geoscience and Remote Sensing Magazine. 9(1). 287–C3. 10 indexed citations
12.
Xia, Yu, Qi Huang, Hongyan Zhang, et al.. (2021). The Outcome of the 2021 IEEE GRSS Data Fusion Contest - Track DSE: Detection of Settlements Without Electricity. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 14. 12375–12385. 11 indexed citations
13.
Le, Nga Nhu, et al.. (2021). Learning from multimodal and multisensor earth observation dataset for improving estimates of mangrove soil organic carbon in Vietnam. International Journal of Remote Sensing. 42(18). 6866–6890. 18 indexed citations
14.
Hong, Danfeng, Naoto Yokoya, Jocelyn Chanussot, Jian Xu, & Xiao Xiang Zhu. (2020). Joint and Progressive Subspace Analysis (JPSA) With Spatial–Spectral Manifold Alignment for Semisupervised Hyperspectral Dimensionality Reduction. IEEE Transactions on Cybernetics. 51(7). 3602–3615. 92 indexed citations
15.
Chen, Yong, Ting‐Zhu Huang, Wei He, Naoto Yokoya, & Xi-Le Zhao. (2020). Hyperspectral Image Compressive Sensing Reconstruction Using Subspace-Based Nonlocal Tensor Ring Decomposition. IEEE Transactions on Image Processing. 29. 6813–6828. 58 indexed citations
16.
Pham, Tien Dat, Naoto Yokoya, Dieu Tien Bui, Kunihiko Yoshino, & Daniel A. Friess. (2019). Remote Sensing Approaches for Monitoring Mangrove Species, Structure, and Biomass: Opportunities and Challenges. Remote Sensing. 11(3). 230–230. 235 indexed citations breakdown →
17.
Chen, Yong, Wei He, Naoto Yokoya, & Ting‐Zhu Huang. (2019). Hyperspectral Image Restoration Using Weighted Group Sparsity-Regularized Low-Rank Tensor Decomposition. IEEE Transactions on Cybernetics. 50(8). 3556–3570. 182 indexed citations
18.
Ghamisi, Pedram, Richard Gloaguen, Peter M. Atkinson, et al.. (2019). Multisource and Multitemporal Data Fusion in Remote Sensing: A Comprehensive Review of the State of the Art. IEEE Geoscience and Remote Sensing Magazine. 7(1). 6–39. 418 indexed citations breakdown →
19.
Zheng, Hongrui, Peijun Du, Jike Chen, et al.. (2017). Performance Evaluation of Downscaling Sentinel-2 Imagery for Land Use and Land Cover Classification by Spectral-Spatial Features. Remote Sensing. 9(12). 1274–1274. 90 indexed citations
20.
Loncan, Laëtitia, Luı́s B. Almeida, José M. Bioucas‐Dias, et al.. (2015). Hyperspectral Pansharpening: A Review. IEEE Geoscience and Remote Sensing Magazine. 3(3). 27–46. 17 indexed citations

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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