Remote-Sensing Image Classification
Remote-Sensing Image Classification is a research topic within Media Technology. Science Explorer counts 38k research works in it since 1955. 26.3% of them reached the world's top 10% most cited for their field and year.
This cluster of papers focuses on the advances in hyperspectral image analysis, remote sensing, and classification. It covers topics such as deep learning, change detection, spectral unmixing, feature extraction, and object-based analysis for remote sensing applications.
- Hyperspectral
- Image Analysis
- Remote Sensing
- Classification
- Deep Learning
- Change Detection
- Spectral Unmixing
- Feature Extraction
- Object-Based Analysis
- Support Vector Machines
- Research works
- 38k fractional, since 1955
- In the world top 10%
- 10k per year above
- Top-10% rate
- 26.3% share of its works in the world top 10%
- Growth, 2013–17 → 2018–22
- +45% the tick is no change
Which countries lead Remote-Sensing Image Classification research?
By volume, China and India publish the most (5.9k and 1.1k works in 2022–2025).
By volume, 2022–2025
- 1 China 5.9k works
- 2 India 1.1k works
- 3 United States 546 works
- 4 Italy 209 works
- 5 Germany 180 works
- 6 France 172 works
- 7 Iran 149 works
- 8 Türkiye 142 works
- 9 United Kingdom 134 works
- 10 Japan 121 works
How concentrated that is
The same countries as shares of everything the list above accounts for. A node where two countries do two thirds of the work and one spread evenly across twelve read alike as a ranking and not at all alike here.
Shares of the rows listed above, not of the whole node.
Which institutions lead Remote-Sensing Image Classification research?
By volume in 2022–2025, Xidian University publishes the most Remote-Sensing Image Classification research, followed by Wuhan University and Chinese Academy of Sciences.
By volume, 2022–2025
- 1 Xidian UniversityChina 234 works
- 2 Wuhan UniversityChina 180 works
- 3 Chinese Academy of SciencesChina 157 works
- 4 Northwestern Polytechnical UniversityChina 130 works
- 5 China University of GeosciencesChina 114 works
- 6 Aerospace Information Research InstituteChina 97 works
- 7 Beijing Institute of TechnologyChina 96 works
- 8 National University of Defense TechnologyChina 81 works
- 9 Nanjing University of Science and TechnologyChina 81 works
- 10 Harbin Institute of TechnologyChina 76 works
Who are the leading researchers in Remote-Sensing Image Classification?
The most-cited researchers publishing on Remote-Sensing Image Classification include Li Fei-Fei, Wei Liu and Luc Van Gool.
- 1 Li Fei-Fei United States 17k citations
- 2 Wei Liu China 9.7k citations
- 3 Luc Van Gool Switzerland 8.5k citations
- 4 Xiaoou Tang Hong Kong 8k citations
- 5 Thomas S. Huang United States 7.4k citations
- 6 Anil K. Jain United States 6.3k citations
- 7 Dacheng Tao Australia 6.1k citations
Ranked by citations received across their whole record, among researchers with at least three works on this topic.
Where is Remote-Sensing Image Classification research done?
The largest centres of Remote-Sensing Image Classification research in 2022–2025 are Beijing (China), Xi'an (China), Wuhan (China) and Nanjing (China). Among places with at least 20 works in it, it is an unusually large share of all research in Starkville and Yantai.
Largest cities, 2022–2025
Where it is the local speciality
- StarkvilleUS · 31.4 works16×
- YantaiCN · 47.0 works8.0×
Location quotient: how much more of its research is in Remote-Sensing Image Classification than the world average.
Where is the best place to study Remote-Sensing Image Classification?
Among universities, judged by research, Xidian University, China University of Geosciences and Wuhan University score highest, combining excellence, specialisation, size, growth and international reach. Research strength is one signal when choosing where to study; it does not measure teaching.
One dot per university in the table below. The upper left is the interesting corner: small places doing unusually strong work.
| # | University | Score | Top 10% | Specialisation | Works | Growth |
|---|---|---|---|---|---|---|
| 1 | Xidian UniversityChina | 76.7 | 37.5% | 31.5× | 234 | +155.0% |
| 2 | China University of GeosciencesChina | 76.5 | 45.1% | 24.7× | 114 | +138.3% |
| 3 | Wuhan UniversityChina | 74.1 | 44.1% | 14.7× | 180 | +78.6% |
| 4 | Nanjing University of Information Science and TechnologyChina | 70.4 | 38.4% | 12.9× | 53 | +167.5% |
| 5 | Northwestern Polytechnical UniversityChina | 69.4 | 35.1% | 11.2× | 130 | +110.1% |
| 6 | Hunan UniversityChina | 68.8 | 47.9% | 7.2× | 51 | +233.7% |
| 7 | Aerospace Information Research InstituteChina | 65.6 | 38.2% | 81.3× | 97 | — |
| 8 | Mississippi State UniversityUnited States | 64.9 | 53.3% | 15.5× | 31 | +15.6% |
| 9 | Liaoning Normal UniversityChina | 64.9 | 42.4% | 17.8× | 16 | +199.6% |
| 10 | PLA Information Engineering UniversityChina | 64.1 | 35.4% | 32.9× | 34 | +176.0% |
Universities only. Score blends excellence (30%), specialisation (25%), size (20%), growth (15%) and international reach (10%), 2015–2022; growth compares 2010–14 with 2015–19.
Is Remote-Sensing Image Classification research growing?
Output in 2018–2022 was 45% higher than in 2013–2017, peaking in 2025. The fastest-growing topics are Remote-Sensing Image Classification.
The same series as a ribbon — one cell per year, darker for more. The line above answers how much; this answers when.
Which topics inside it are moving
Growth and decline on one axis around a shared zero. Two lists side by side hide the thing that matters: whether the growth dwarfs the decline, or the other way round.