Science Explorer Back to mapMap
Discussion
Topic · Environmental Engineering

Remote Sensing and LiDAR Applications

Remote Sensing and LiDAR Applications is a research topic within Environmental Engineering. Science Explorer counts 44k research works in it since 1950. 9.9% of them reached the world's top 10% most cited for their field and year.

This cluster of papers focuses on the use of Lidar remote sensing technology for mapping and assessing various forest attributes such as carbon stocks, aboveground biomass, tree height, and canopy structure at global and regional scales. The papers cover techniques like airborne and terrestrial laser scanning, data fusion, individual tree detection, and biomass estimation, highlighting the importance of Lidar in sustainable forest management and ecological research.

  • Lidar Remote Sensing
  • Forest Carbon Stocks
  • Aboveground Biomass
  • Tree Height Estimation
  • Global Forest Mapping
  • Airborne Laser Scanning
  • Terrestrial Laser Scanning
  • Forest Inventory
  • Biomass Estimation
  • Canopy Structure
Research works
44k
fractional, since 1950
In the world top 10%
4.4k
per year above
Top-10% rate
9.9%
share of its works in the world top 10%
Growth, 2018-21 → 2022-25
+41%
the tick is no change
Largest producer
China
55% of the 10 largest, 2022-now
Remote Sensing and LiDAR Applications

Which countries lead Remote Sensing and LiDAR Applications research?

By volume, China and the United States publish the most (5.6k and 1.5k works in 2022-now).

By volume, 2022-now

  1. 1 China 5.6k works
  2. 2 United States 1.5k works
  3. 3 India 564 works
  4. 4 Germany 556 works
  5. 5 Italy 471 works
  6. 6 Japan 349 works
  7. 7 Canada 327 works
  8. 8 Spain 315 works
  9. 9 South Korea 306 works
  10. 10 United Kingdom 305 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: 54.7%United States: 14.2%India: 5.5%Germany: 5.4%6 others listed: 20.2%55%largest
China5,622 · 54.7%United States1,463 · 14.2%India564 · 5.5%Germany556 · 5.4%6 others listed2,074 · 20.2%

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

Which institutions lead Remote Sensing and LiDAR Applications research?

By volume in 2022-now, Chinese Academy of Sciences publishes the most Remote Sensing and LiDAR Applications research, followed by Wuhan University and Centre National de la Recherche Scientifique.

By volume, 2022-now

  1. 1 Chinese Academy of SciencesChina 335 works
  2. 2 Wuhan UniversityChina 146 works
  3. 3 Centre National de la Recherche ScientifiqueFrance 86 works
  4. 4 University of Chinese Academy of SciencesChina 69 works
  5. 5 Helmholtz Association of German Research CentresGermany 67 works
  6. 6 Beijing Forestry UniversityChina 67 works
  7. 7 Beijing Normal UniversityChina 66 works
  8. 8 United States Department of AgricultureUnited States 65 works
  9. 9 Northeast Forestry UniversityChina 61 works
  10. 10 Tongji UniversityChina 61 works

Who are the leading researchers in Remote Sensing and LiDAR Applications?

The most-cited researchers publishing on Remote Sensing and LiDAR Applications include Yoshua Bengio, Geoffrey E. Hinton and Simon Iain Hay.

  1. 1 Yoshua Bengio Canada 476k citations
  2. 2 Geoffrey E. Hinton Canada 454k citations
  3. 3 Simon Iain Hay United States 452k citations
  4. 4 Martin McKee United Kingdom 270k citations
  5. 5 Xiaogang Wang China 260k citations
  6. 6 Andrew Zisserman United Kingdom 255k citations
  7. 7 Philippe Ciais France 237k citations
  8. 8 Kai You Wang China 224k citations
  9. 9 Trevor J. Darrell United States 206k citations
  10. 10 Peter B. Reich United States 189k 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 Remote Sensing and LiDAR Applications?

The most cited paper in Remote Sensing and LiDAR Applications is "Overview of the radiometric and biophysical performance of the MODIS vegetation indices" (ALFREDO R. HUETE, Kamel Didan, Tomoaki Miura et al., 2002), with 9,991 citations. Next come "Modification of normalised difference water index (NDWI) to enhance open water features in remotely sensed imagery" (6,019) and "CONDENSATION—Conditional Density Propagation for Visual Tracking" (4,900).

Most cited papers
#PaperReleasedCitations
1 Overview of the radiometric and biophysical performance of the MODIS vegetation indices ALFREDO R. HUETE, Kamel Didan, Tomoaki Miura et al. · Remote Sensing of Environment Nov 2002 9,991
2 Modification of normalised difference water index (NDWI) to enhance open water features in remotely sensed imagery Hanqiu Xu · International Journal of Remote Sensing Open access 7 Jul 2006 6,019
3 CONDENSATION—Conditional Density Propagation for Visual Tracking Michael Isard, Andrew Blake · International Journal of Computer Vision Aug 1998 4,900
4 Remote Sensing And Image Interpretation THOMAS M. LILLESAND, Ralph W. Kiefer, Jonathan Chipman Open access 1979 4,476
5 ScanNet: Richly-Annotated 3D Reconstructions of Indoor Scenes Angela Dai, Anne Lynn S. Chang, Manolis Savva et al. Conference paper Jul 2017 4,270
All 100 most cited papers, with filters and sorting

Where is Remote Sensing and LiDAR Applications research done?

The largest centres of Remote Sensing and LiDAR Applications research in 2022-now are Beijing (China), Wuhan (China), Nanjing (China) and Shanghai (China). Among places with at least 20 works in it, it is an unusually large share of all research in Kirkkonummi and Lin’an Shi.

Largest cities, 2022-now

  1. 1 BeijingChina 1.3k works
  2. 2 WuhanChina 405 works
  3. 3 NanjingChina 357 works
  4. 4 ShanghaiChina 289 works
  5. 5 Xi'anChina 202 works
  6. 6 GuangzhouChina 194 works
  7. 7 HarbinChina 161 works
  8. 8 ChengduChina 160 works
  9. 9 ChangshaChina 156 works
  10. 10 HangzhouChina 142 works

Where it is the local speciality

  1. KirkkonummiFI · 20.1 works149×
  2. Lin’an ShiCN · 25.0 works11×
← less than its size predicts1×more →

Location quotient: how much more of its research is in Remote Sensing and LiDAR Applications than the world average.

See Remote Sensing and LiDAR Applications on the map

Where is the best place to study Remote Sensing and LiDAR Applications?

Among universities, judged by research, University of Hong Kong, Wuhan University and Nanjing Agricultural 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.

0%20%40%mean 22.35%fractional works in this field (log) →share of work in the world top 10% →Nanjing Agricultural…University of Hong K…Hong Kong University…Wuhan University
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
1University of Hong KongChina 67.129.9%2.0×23 +111.4%
2Wuhan UniversityChina 66.214.6%8.3×146 +41.4%
3Nanjing Agricultural UniversityChina 63.631.0%3.2×15 +21.3%
4Hong Kong University of Science and TechnologyChina 62.726.5%2.9×15 +144.4%
5Nanjing Forestry UniversityChina 62.019.0%9.5×53 +80.1%
6Nanyang Technological UniversitySingapore 61.625.0%2.4×24 +162.0%
7Hong Kong Polytechnic UniversityChina 61.519.0%3.2×34 +36.1%
8Beijing Normal UniversityChina 61.416.8%6.7×66 +23.7%
9China Agricultural UniversityChina 61.023.6%5.0×35 +110.3%
10China University of GeosciencesChina 60.918.1%8.6×48 +112.6%

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 Remote Sensing and LiDAR Applications, country by country

Is Remote Sensing and LiDAR Applications research growing?

Output in 2022-2025 was 41% higher than in 2018-2021, peaking in 2024. The fastest-growing topics are Remote Sensing and LiDAR Applications.

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 Remote Sensing and LiDAR Applications as a percentage of every work published that year, 0.069% in 2024.

still counting0.025%0.050%0.075%Remote Sensing and LiDAR Applications0.061% in 202519801990200020102020

Fractional works of Remote Sensing and LiDAR Applications 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%Remote Sensing and LiDAR Applications9.9% 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.

Discussion

Ask a question or share a note about Remote Sensing and LiDAR Applications. Posts are plain text and can be reported.