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Remote Sensing and Land Use

Remote Sensing and Land Use is a research topic within Atmospheric Science. Science Explorer counts 65k research works in it since 1950. 9.7% of them reached the world's top 10% most cited for their field and year.

This cluster of papers focuses on the applications of remote sensing technology in geoscience, agriculture, and environmental monitoring. It covers topics such as hyperspectral imaging, geohazards induced by earthquakes, urban heat island effects, vegetation classification, and the impact of land use change. Additionally, it explores the use of remote sensing for assessing earthquake damage, monitoring medicinal plants, and analyzing spatial patterns in various environments.

  • Remote Sensing
  • Hyperspectral Imaging
  • Geohazards
  • Earthquake Damage
  • Urban Heat Island
  • Vegetation Classification
  • Medicinal Plants
  • Land Use Change
  • Object-Oriented Analysis
  • Spatial Pattern Analysis
Research works
65k
fractional, since 1950
In the world top 10%
6.4k
per year above
Top-10% rate
9.7%
share of its works in the world top 10%
Growth, 2018-21 → 2022-25
+52%
the tick is no change
Largest producer
China
76% of the 10 largest, 2022-now

Which countries lead Remote Sensing and Land Use research?

By volume, China and India publish the most (6.2k and 778 works in 2022-now).

By volume, 2022-now

  1. 1 China 6.2k works
  2. 2 India 778 works
  3. 3 United States 332 works
  4. 4 Indonesia 192 works
  5. 5 Japan 160 works
  6. 6 Italy 121 works
  7. 7 South Korea 109 works
  8. 8 ?? 99 works
  9. 9 Vietnam 93 works
  10. 10 Iran 92 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: 75.7%India: 9.6%United States: 4.1%Indonesia: 2.4%6 others listed: 8.3%76%largest
China6,153 · 75.7%India778 · 9.6%United States332 · 4.1%Indonesia192 · 2.4%6 others listed674 · 8.3%

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

Which institutions lead Remote Sensing and Land Use research?

By volume in 2022-now, Chinese Academy of Sciences publishes the most Remote Sensing and Land Use research, followed by Wuhan University and Beijing Normal University.

Who are the leading researchers in Remote Sensing and Land Use?

The most-cited researchers publishing on Remote Sensing and Land Use include Simon Iain Hay, Jun Wang and Martin McKee.

  1. 1 Simon Iain Hay United States 452k citations
  2. 2 Jun Wang China 340k citations
  3. 3 Martin McKee United Kingdom 270k citations
  4. 4 Xiaogang Wang China 260k citations
  5. 5 Philippe Ciais France 237k citations
  6. 6 Kai You Wang China 224k citations
  7. 7 Hua Zhang Singapore 196k citations
  8. 8 Luc Van Gool Switzerland 177k 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 Land Use?

The most cited paper in Remote Sensing and Land Use is "The energetic basis of the urban heat island" (T. R. Oke, 1982), with 4,665 citations. Next come "Object based image analysis for remote sensing" (4,539) and "Local Climate Zones for Urban Temperature Studies" (4,473).

Most cited papers
#PaperReleasedCitations
1 The energetic basis of the urban heat island T. R. Oke · Quarterly Journal of the Royal Meteorological Society 1982 4,665
2 Object based image analysis for remote sensing Thomas Blaschke · ISPRS Journal of Photogrammetry and Remote Sensing Open access 29 Aug 2009 4,539
3 Local Climate Zones for Urban Temperature Studies Iain D. Stewart, T. R. Oke · Bulletin of the American Meteorological Society 25 May 2012 4,473
4 Classification of hyperspectral remote sensing images with support vector machines Farid Melgani, Lorenzo Bruzzone · IEEE Transactions on Geoscience and Remote Sensing Aug 2004 4,440
5 Review Article Digital change detection techniques using remotely-sensed data Ashbindu Singh · International Journal of Remote Sensing Open access Jun 1989 3,870
All 99 most cited papers, with filters and sorting

Where is Remote Sensing and Land Use research done?

The largest centres of Remote Sensing and Land Use 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 Fuxin and Jiaozuo.

Largest cities, 2022-now

  1. 1 BeijingChina 1.4k works
  2. 2 WuhanChina 371 works
  3. 3 NanjingChina 337 works
  4. 4 Xi'anChina 313 works
  5. 5 ShanghaiChina 196 works
  6. 6 GuangzhouChina 191 works
  7. 7 ChengduChina 167 works
  8. 8 HarbinChina 156 works
  9. 9 ChangshaChina 136 works
  10. 10 KunmingChina 121 works

Where it is the local speciality

  1. FuxinCN · 25.2 works16×
  2. JiaozuoCN · 41.6 works14×
← less than its size predicts1×more →

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

See Remote Sensing and Land Use on the map

Where is the best place to study Remote Sensing and Land Use?

Among universities, judged by research, Wuhan University, Xidian University and Beijing Normal 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 21.6%fractional works in this field (log) →share of work in the world top 10% →Wuhan UniversityXidian UniversityChina University of …Beijing Normal Unive…
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 71.126.0%8.6×98 +19.1%
2Xidian UniversityChina 70.822.2%13.1×77 +28.8%
3Beijing Normal UniversityChina 66.913.1%13.6×88 +30.5%
4China University of GeosciencesChina 62.419.1%16.9×63 +36.5%
5University of Chinese Academy of SciencesChina 60.716.7%5.1×68 +14.2%
6Nanjing University of Information Science and TechnologyChina 59.615.4%16.6×54 +103.5%
7China Agricultural UniversityChina 58.118.0%10.1×45 +62.2%
8Mississippi State UniversityUnited States 57.543.4%8.2×13 -19.5%
9University of Hong KongChina 56.123.6%1.6×12 +114.0%
10Sun Yat-sen UniversityChina 54.818.5%2.4×41 +86.1%

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 Land Use, country by country

Is Remote Sensing and Land Use research growing?

Output in 2022-2025 was 52% higher than in 2018-2021, peaking in 2011. The fastest-growing topics are Remote Sensing and Land Use.

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 Land Use as a percentage of every work published that year, 0.060% in 2024.

still counting0.10%0.20%Remote Sensing and Land Use0.045% in 202519801990200020102020

Fractional works of Remote Sensing and Land Use 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 Land Use10.0% 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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