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Soil Moisture and Remote Sensing

Soil Moisture and Remote Sensing is a research topic within Environmental Engineering. Science Explorer counts 26k research works in it since 1950. 21.6% of them reached the world's top 10% most cited for their field and year.

This cluster of papers focuses on the remote sensing of soil moisture using satellite observations, data assimilation techniques, and hydrological modeling. It explores the spatial variability, temporal dynamics, and validation of soil moisture measurements at global scales. The research aims to improve our understanding of soil moisture patterns and their implications for water resource management.

  • Remote Sensing
  • Soil Moisture
  • Satellite Observations
  • Data Assimilation
  • Hydrological Modeling
  • Global Monitoring
  • Microwave Retrieval
  • Spatial Variability
  • Temporal Dynamics
  • Validation
Research works
26k
fractional, since 1950
In the world top 10%
5.7k
per year above
Top-10% rate
21.6%
share of its works in the world top 10%
Growth, 2013–17 → 2018–22
+20%
the tick is no change

Which countries lead Soil Moisture and Remote Sensing research?

By volume, China and the United States publish the most (1.6k and 920 works in 2022–2025).

By volume, 2022–2025

  1. 1 China 1.6k works
  2. 2 United States 920 works
  3. 3 India 316 works
  4. 4 Germany 184 works
  5. 5 Italy 174 works
  6. 6 France 152 works
  7. 7 Japan 103 works
  8. 8 Canada 101 works
  9. 9 United Kingdom 100 works
  10. 10 Australia 88 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: 42.1%United States: 24.9%India: 8.6%Germany: 5.0%6 others listed: 19.4%42%largest
China1,552 · 42.1%United States920 · 24.9%India316 · 8.6%Germany184 · 5.0%6 others listed718 · 19.4%

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

Which institutions lead Soil Moisture and Remote Sensing research?

By volume in 2022–2025, Lawrence Berkeley National Laboratory publishes the most Soil Moisture and Remote Sensing research, followed by Chinese Academy of Sciences and Wuhan University.

Who are the leading researchers in Soil Moisture and Remote Sensing?

The most-cited researchers publishing on Soil Moisture and Remote Sensing include Martinus Th. van Genuchten, Philippe Ciais and Patricia de Rosnay.

  1. 1 Martinus Th. van Genuchten United States 5.1k citations
  2. 2 Philippe Ciais France 4k citations
  3. 3 Patricia de Rosnay United Kingdom 3.8k citations

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

Where is Soil Moisture and Remote Sensing research done?

The largest centres of Soil Moisture and Remote Sensing research in 2022–2025 are Beijing (China), Berkeley (United States), Nanjing (China) and Wuhan (China). Among places with at least 20 works in it, it is an unusually large share of all research in Greenbelt, Berkeley and Pasadena.

Largest cities, 2022–2025

  1. 1 Beijing China 508 works
  2. 2 Berkeley United States 206 works
  3. 3 Nanjing China 125 works
  4. 4 Wuhan China 102 works
  5. 5 Xi'an China 68 works
  6. 6 Shanghai China 62 works
  7. 7 Chengdu China 59 works
  8. 8 Paris France 51 works
  9. 9 Changsha China 44 works
  10. 10 Tokyo Japan 42 works

Where it is the local speciality

  1. GreenbeltUS · 21.4 works48×
  2. BerkeleyUS · 205.8 works34×
  3. PasadenaUS · 39.5 works19×
← less than its size predictsmore →

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

See Soil Moisture and Remote Sensing on the map

Where is the best place to study Soil Moisture and Remote Sensing?

Among universities, judged by research, Memorial University of Newfoundland, Northwest A&F University and Aerospace Information Research Institute 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 28.2%fractional works in this node (log) →share in the world top 10% →Memorial University of Newfoundland: 9, 36.9%Northwest A&F University: 16, 34.2%Aerospace Information Research Institute: 25, 30.2%Wuhan University: 41, 29.4%Hohai University: 30, 20.7%Nanjing University of Information Science and Technology: 30, 13.2%Chang'an University: 12, 24.6%Indian Institute of Technology Bombay: 16, 23.2%TU Wien: 10, 32.5%China University of Geosciences: 13, 37.1%Memorial University …Northwest A&F Univer…Aerospace Informatio…Wuhan University
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 Memorial University of NewfoundlandCanada 69.136.9%9.4×9 +171.0%
2 Northwest A&F UniversityChina 67.834.2%8.7×16 +197.6%
3 Aerospace Information Research InstituteChina 61.930.2%44.6×25
4 Wuhan UniversityChina 60.529.4%7.2×41 +114.7%
5 Hohai UniversityChina 54.520.7%11.6×30 +18.2%
6 Nanjing University of Information Science and TechnologyChina 53.713.2%15.7×30 +86.5%
7 Chang'an UniversityChina 53.624.6%6.9×12 +259.0%
8 Indian Institute of Technology BombayIndia 50.423.2%7.7×16 +97.9%
9 TU WienAustria 48.732.5%7.0×10 -22.9%
10 China University of GeosciencesChina 46.837.1%6.0×13 -54.8%

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 Soil Moisture and Remote Sensing research growing?

Output in 2018–2022 was 20% higher than in 2013–2017, peaking in 2025. The fastest-growing topics are Soil Moisture and Remote Sensing.

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.