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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. 10.0% 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%
784
per year above
Top-10% rate
10.0%
share of its works in the world top 10%
Growth, 2018-21 → 2022-25
+52%
the tick is no change
Largest producer
China
63% of the 10 largest, 2022-now
Automated Road and Building Extraction

Which countries lead Automated Road and Building Extraction research?

By volume, China and India publish the most (1.4k and 269 works in 2022-now).

By volume, 2022-now

  1. 1 China 1.4k works
  2. 2 India 269 works
  3. 3 United States 206 works
  4. 4 Germany 76 works
  5. 5 Türkiye 52 works
  6. 6 Japan 52 works
  7. 7 United Kingdom 50 works
  8. 8 South Korea 48 works
  9. 9 France 41 works
  10. 10 Canada 41 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: 63.2%India: 11.8%United States: 9.1%Germany: 3.3%6 others listed: 12.5%63%largest
China1,438 · 63.2%India269 · 11.8%United States206 · 9.1%Germany76 · 3.3%6 others listed285 · 12.5%

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

Which institutions lead Automated Road and Building Extraction research?

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

By volume, 2022-now

  1. 1 Chinese Academy of SciencesChina 67 works
  2. 2 Wuhan UniversityChina 54 works
  3. 3 China University of GeosciencesChina 26 works
  4. 4 National University of Defense TechnologyChina 19 works
  5. 5 State Key Laboratory of Information Engineering in Surveying Mapping and Remote SensingChina 19 works
  6. 6 Xidian UniversityChina 19 works
  7. 7 University of Electronic Science and Technology of ChinaChina 18 works
  8. 8 Sun Yat-sen UniversityChina 16 works
  9. 9 Tsinghua UniversityChina 16 works
  10. 10 Beijing Institute of TechnologyChina 15 works

Who are the leading researchers in Automated Road and Building Extraction?

The most-cited researchers publishing on Automated Road and Building Extraction include Yoshua Bengio, Geoffrey E. Hinton and Xiaogang Wang.

  1. 1 Yoshua Bengio Canada 476k citations
  2. 2 Geoffrey E. Hinton Canada 454k citations
  3. 3 Xiaogang Wang China 260k citations
  4. 4 Li Fei-Fei United States 225k citations
  5. 5 Luc Van Gool Switzerland 177k citations
  6. 6 Anil Kumar Jain United States 160k citations
  7. 7 Philip S. Yu United States 141k citations

Ranked by citations received across their whole record, among researchers with at least three works on this topic.

What are the most cited papers in Automated Road and Building Extraction?

The most cited paper in Automated Road and Building Extraction is "The R*-tree: an efficient and robust access method for points and rectangles" (Norbert Beckmann, Hans‐Peter Kriegel, Ralf Schneider et al., 1990), with 4,188 citations. Next come "Road Extraction by Deep Residual U-Net" (3,178) and "Remote Sensing Image Scene Classification: Benchmark and State of the Art" (2,701).

Most cited papers
#PaperReleasedCitations
1 The R*-tree: an efficient and robust access method for points and rectangles Norbert Beckmann, Hans‐Peter Kriegel, Ralf Schneider et al. Conference paperOpen access May 1990 4,188
2 Road Extraction by Deep Residual U-Net Zhengxin Zhang, Qingjie Liu, Yunhong Wang · IEEE Geoscience and Remote Sensing Letters Open access 8 Mar 2018 3,178
3 Remote Sensing Image Scene Classification: Benchmark and State of the Art Gong Cheng, Junwei Han, Xiaoqiang Lu · Proceedings of the IEEE Open access 3 Apr 2017 2,701
4 Simultaneous localization and mapping (SLAM): part II T.E.R. Bailey, Hugh F Durrant-Whyte · IEEE Robotics & Automation Magazine 23 Aug 2006 2,559
5 Deep Learning for Remote Sensing Data: A Technical Tutorial on the State of the Art Liangpei Zhang, Lefei Zhang, Bo Du · IEEE Geoscience and Remote Sensing Magazine Jun 2016 2,237
All 99 most cited papers, with filters and sorting

Where is Automated Road and Building Extraction research done?

The largest centres of Automated Road and Building Extraction research in 2022-now 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-now

  1. 1 BeijingChina 285 works
  2. 2 WuhanChina 144 works
  3. 3 NanjingChina 94 works
  4. 4 Xi'anChina 78 works
  5. 5 ShanghaiChina 58 works
  6. 6 ChengduChina 49 works
  7. 7 ChangshaChina 44 works
  8. 8 HangzhouChina 43 works
  9. 9 GuangzhouChina 40 works
  10. 10 ZhengzhouChina 30 works

Where it is the local speciality

  1. WuhanCN · 144.1 works6.5×
  2. ZhengzhouCN · 30.4 works3.9×
  3. Xi'anCN · 78.0 works3.6×
  4. NanjingCN · 93.6 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, Wuhan University, China University of Geosciences 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%10%20%mean 17.93%fractional works in this field (log) →share of work in the world top 10% →Nanjing University o…China University of …Wuhan UniversityHong Kong Polytechni…
above the meannear itbelow it

One dot per university in the first ten of the table below, at the default weights. The upper left is the interesting corner: small places doing unusually strong work.

Excellenceshare of its work in the world top 10%, 2022-now and all time averaged
40%
Specialisationhow much of its work is in this field, counted up to 10× the world share
10%
Sizeits output in this field, on a log scale
30%
Growthoutput growth, counted from -20% to +20%
10%
Internationalshare of its work with a co-author abroad
10%
Each slider sets a weight; the share it gets of the score is beside it.
#UniversityScoreTop 10%SpecialisationWorksGrowth
1Wuhan UniversityChina 80.318.6%15.4×54 +14.2%
2China University of GeosciencesChina 79.920.3%23.2×26 +80.0%
3Nanjing University of Information Science and TechnologyChina 69.621.1%12.5×12 +171.4%
4Hong Kong Polytechnic UniversityChina 66.017.8%5.5×12 +52.5%
5Sun Yat-sen UniversityChina 64.318.1%3.1×16 +151.2%
6Xidian UniversityChina 59.615.2%10.4×19 +108.4%
7Northwestern Polytechnical UniversityChina 57.317.9%4.7×13 +94.7%
8National University of Defense TechnologyChina 53.115.1%10.1×19 +90.2%
9Beijing Normal UniversityChina 49.615.8%5.7×11 +62.1%
10Peking UniversityChina 47.819.4%2.0×10 +38.5%

Universities only. The score blends excellence (40%), size (30%), specialisation (10%), growth (10%), international reach (10%), 2022-now; growth compares 2018-21 with 2022-25 and counts up to +20%, since a jump from a small base is mostly noise.

Every institution in Automated Road and Building Extraction, country by country

Is Automated Road and Building Extraction research growing?

Output in 2022-2025 was 52% higher than in 2018-2021, peaking in 2025. The fastest-growing topics are Automated Road and Building Extraction.

still counting19801990200020102020
grewheldshrank

The same series as a ribbon: one cell per year, darker for more. The line above answers how much; this answers when.

Its share of all research

Growing output can still be a shrinking share: all of science grows. This is Automated Road and Building Extraction as a percentage of every work published that year, 0.012% in 2024.

still counting0.0050%0.010%0.015%Automated Road and Building Extraction0.013% in 202519801990200020102020

Fractional works of Automated Road and Building Extraction over all fractional works that year. How the balance of science has shifted.

How much of it reaches the world top 10%

Year by year.

still counting5%10%15%Automated Road and Building Extraction9.9% in 2025200020102020

Of each year's works in it, the share that reached the world's 10% most cited for their field and year. A field is the world for its own topics, so there is no other line to hold it against.

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.

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