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Topic · Ocean Engineering

Automated Road and Building Extraction

Automated Road and Building Extraction is a research topic within Ocean Engineering. Science Explorer counts 7.9k research works in it since 1966. 21.4% of them reached the world's top 10% most cited for their field and year.

This cluster of papers focuses on the automatic extraction of road networks from remote sensing images, utilizing techniques such as deep learning, high-resolution imagery, and GPS traces. The research covers areas such as GIS update, aerial images, urban road networks, and map inference, with a particular emphasis on the application of these methods to road extraction.

  • Road Extraction
  • Remote Sensing
  • Deep Learning
  • High-Resolution Imagery
  • GIS Update
  • Aerial Images
  • GPS Traces
  • Urban Road Networks
  • SAR Imagery
  • Map Inference
Research works
7.9k
fractional, since 1966
In the world top 10%
1.7k
per year above
Top-10% rate
21.4%
share of its works in the world top 10%
Growth, 2013–17 → 2018–22
+65%
the tick is no change

Which countries lead Automated Road and Building Extraction research?

By volume, China and India publish the most (1.2k and 232 works in 2022–2025).

By volume, 2022–2025

  1. 1 China 1.2k works
  2. 2 India 232 works
  3. 3 United States 175 works
  4. 4 Germany 68 works
  5. 5 Türkiye 49 works
  6. 6 Japan 48 works
  7. 7 United Kingdom 43 works
  8. 8 South Korea 42 works
  9. 9 France 38 works
  10. 10 Canada 35 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.

China: 62.2%India: 12.0%United States: 9.0%Germany: 3.5%6 others listed: 13.2%62%largest
China1,202 · 62.2%India232 · 12.0%United States175 · 9.0%Germany68 · 3.5%6 others listed255 · 13.2%

Shares of the rows listed above, not of the whole node.

Which institutions lead Automated Road and Building Extraction research?

By volume in 2022–2025, Wuhan University publishes the most Automated Road and Building Extraction research, followed by China University of Geosciences and Chinese Academy of Sciences.

By volume, 2022–2025

  1. 1 Wuhan UniversityChina 46 works
  2. 2 China University of GeosciencesChina 23 works
  3. 3 Chinese Academy of SciencesChina 23 works
  4. 4 National University of Defense TechnologyChina 17 works
  5. 5 University of Electronic Science and Technology of ChinaChina 17 works
  6. 6 State Key Laboratory of Information Engineering in Surveying Mapping and Remote SensingChina 17 works
  7. 7 Xidian UniversityChina 16 works
  8. 8 Aerospace Information Research InstituteChina 15 works
  9. 9 Sun Yat-sen UniversityChina 15 works
  10. 10 Tsinghua UniversityChina 14 works

Where is Automated Road and Building Extraction research done?

The largest centres of Automated Road and Building Extraction research in 2022–2025 are Beijing (China), Wuhan (China), Nanjing (China) and Xi'an (China). Among places with at least 20 works in it, it is an unusually large share of all research in Wuhan, Zhengzhou and Xi'an.

Largest cities, 2022–2025

  1. 1 Beijing China 247 works
  2. 2 Wuhan China 126 works
  3. 3 Nanjing China 83 works
  4. 4 Xi'an China 66 works
  5. 5 Shanghai China 49 works
  6. 6 Chengdu China 43 works
  7. 7 Changsha China 37 works
  8. 8 Hangzhou China 37 works
  9. 9 Guangzhou China 36 works
  10. 10 Zhengzhou China 26 works

Where it is the local speciality

  1. WuhanCN · 125.7 works6.5×
  2. ZhengzhouCN · 26.2 works4.0×
  3. Xi'anCN · 65.7 works3.5×
  4. NanjingCN · 82.6 works3.4×
← less than its size predicts1×more →

Location quotient: how much more of its research is in Automated Road and Building Extraction than the world average.

See Automated Road and Building Extraction on the map

Where is the best place to study Automated Road and Building Extraction?

Among universities, judged by research, China University of Geosciences, Wuhan University and Nanjing University of Information Science and Technology 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.

0%20%40%mean 27.65%fractional works in this node (log) →share in the world top 10% →China University of Geosciences: 23, 35.0%Wuhan University: 46, 32.6%Nanjing University of Information Science and Technology: 11, 30.3%PLA Information Engineering University: 13, 23.1%Chang'an University: 9, 25.6%University of Electronic Science and Technology of China: 17, 24.4%Xidian University: 16, 21.9%Hong Kong Polytechnic University: 10, 35.9%Aerospace Information Research Institute: 15, 20.5%Sun Yat-sen University: 15, 27.2%China University of …Wuhan UniversityNanjing University o…PLA Information Engi…
above the meannear itbelow it

One dot per university in the table below. The upper left is the interesting corner: small places doing unusually strong work.

#UniversityScoreTop 10%SpecialisationWorksGrowth
1 China University of GeosciencesChina 80.835.0%21.2×23 +183.6%
2 Wuhan UniversityChina 77.732.6%15.8×46 +63.2%
3 Nanjing University of Information Science and TechnologyChina 66.730.3%11.4×11 +170.0%
4 PLA Information Engineering UniversityChina 60.723.1%52.8×13 +263.5%
5 Chang'an UniversityChina 60.125.6%9.9×9 +333.3%
6 University of Electronic Science and Technology of ChinaChina 55.024.4%6.2×17 +240.8%
7 Xidian UniversityChina 54.621.9%8.9×16 +120.7%
8 Hong Kong Polytechnic UniversityHong Kong 53.135.9%4.8×10 +27.9%
9 Aerospace Information Research InstituteChina 52.320.5%52.9×15 —
10 Sun Yat-sen UniversityChina 49.127.2%3.9×15 +249.1%

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 Automated Road and Building Extraction research growing?

Output in 2018–2022 was 65% higher than in 2013–2017, peaking in 2025. The fastest-growing topics are Automated Road and Building Extraction.

19801990200020102020
grewheldshrank

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.