Institute of Forest Resource Information Techniques
In research, Institute of Forest Resource Information Techniques stands highest in Physical Sciences (#6,966 of 12,888 worldwide) and Environmental Science (#2,165 of 3,551 worldwide), 2022–2025. Relative to its size it is most specialised in Environmental Science — Environmental Science is 12.8× its share of world research.
- World rank, 2022–2025
- #12,667 of 28,054 · #19,437 all time
- Rank in China
- #2,166 of 3,058
- Research works
- 471 ▼ 15% vs 2013–17
- Citations
- 5k 10.6 per fractional work
- Top-10% rate
- 29.8% record average 16.5%
- Open access
- 33% world 28%
What is Institute of Forest Resource Information Techniques known for in research?
The fields where it stands highest, 2022–2025, ranked among every institution above the floor in each field.
| Field | World rank | Where that sits | Top-10% rate | Works | All time |
|---|---|---|---|---|---|
| Physical SciencesDomain | #6,966 of 12,888 | 29.9% | 98 | #10866 | |
| Environmental ScienceField | #2,165 of 3,551 | 29.5% | 71 | #3238 |
Each strip is that field’s whole ranked pool, with the notch where Institute of Forest Resource Information Techniques sits in it, in the colour of the band that rank falls in. The track under the rate is the rate itself: it carries no world mark, because the world rate differs by field (from about 6% to 21% in this record).
What does Institute of Forest Resource Information Techniques specialise in?
Where its research is concentrated relative to its size: Environmental Science takes 12.8× the share of its output that it takes of world research.
- Environmental ScienceField · 70.7 works13×
Location quotient, a volume reading rather than an impact one. It surfaces small, lopsided specialities.
Field profile
Location quotient across every field it publishes in: outside the ring is more than an institution of this size would be expected to publish, inside it is less.
Rings at 0.5×, 1× and 2×. Widest outward: Environmental Science, 12.8×. Every wedge is a field page.
- Environmental Science 12.8×
- Earth and Planetary Sciences 4.4×
- Agricultural and Biological Sciences 1.9×
- Engineering 0.8×
- Computer Science 0.6×
- Chemistry 0.5×
- Mathematics 0.2×
- Biochemistry, Genetics and Molecular Biology 0.2×
- Nursing 0.1×
- Social Sciences 0.1×
- Economics, Econometrics and Finance 0.1×
- Physics and Astronomy 0.1×
- Health Professions 0.0×
- Materials Science 0.0×
- Psychology 0.0×
- Medicine 0.0×
Who are the top researchers at Institute of Forest Resource Information Techniques?
Ranked on the composite score, Zengyuan Li, Liyong Fu and Erxue Chen lead among researchers whose main affiliation is Institute of Forest Resource Information Techniques.
- 1 Zengyuan Li China · #700,907 worldwide 195 citations · 88 works
- 2 Liyong Fu China · #975,353 worldwide 76 citations · 24 works
- 3 Erxue Chen China · #999,762 worldwide 93 citations · 50 works
- 4 Lei Zhao China · #1,197,073 worldwide 40 citations · 25 works
- 5 Yuancai Lei China · #1,244,104 worldwide 36 citations · 16 works
- 6 Huaiqing Zhang China · #1,336,657 worldwide 41 citations · 23 works
- 7 Huiru Zhang China · #1,367,765 worldwide 14 citations · 20 works
- 8 Shouzheng Tang China · #1,389,231 worldwide 24 citations · 18 works
- 9 Qingwang Liu China · #1,519,066 worldwide 13 citations · 21 works
Which keywords describe research at Institute of Forest Resource Information Techniques?
By fractional works in 2022–2025, weighted toward what it does more of than the world: Biomass Estimation, Remote Sensing, Aboveground Biomass, Terrestrial Laser Scanning, Climate Change, Forest Carbon Stocks, Lidar Remote Sensing and Global Change.
- Habitat Fragmentation
- Hyperspectral Imaging
- Ecosystem
- Tree Mortality
- Invasive Species
- Sustainable Forest Management
- Support Vector Machines
- Hyperspectral
- Spatial Dynamics
- Urbanization
- Ecosystem Resilience
- Sustainability
- Land Use Change
- Carbon Stocks
- Biodiversity Conservation
- Phenology
- Lidar Remote Sensing
- Forest Carbon Stocks
- Climate Change
- Remote Sensing
- Biomass Estimation
- Aboveground Biomass
- Terrestrial Laser Scanning
- Global Change
- Machine Learning
- Vegetation Monitoring
- Allometric Models
- Tropical Forests
- Deep Learning
- Ecosystem Services
- Biodiversity
- Global Impact
- Forest Management
- Climate Change Impacts
- Forest Carbon Sequestration
- Urban Heat Island
- Drought
- Feature Extraction
- Ecosystem Functioning
- Change Detection
Size is fractional works in 2022–2025 in the topics tagged with each word; colour is the word's share of this institution's work against its share of the world's. The 40 words are chosen for being large and distinctive. Each links to the topic it comes from most.
All 40 words, with their numbers
- Biomass Estimation40▲ 239×3 topics
- Remote Sensing30▲ 22×22 topics
- Aboveground Biomass28▲ 278×2 topics
- Climate Change18▲ 6.2×33 topics
- Terrestrial Laser Scanning18▲ 129×2 topics
- Forest Carbon Stocks16▲ 238×1 topic
- Global Change16▲ 57×5 topics
- Lidar Remote Sensing16▲ 238×1 topic
- Machine Learning14▲ 3.9×11 topics
- Phenology13▲ 183×1 topic
- Vegetation Monitoring13▲ 183×1 topic
- Biodiversity Conservation12▲ 30×6 topics
- Allometric Models12▲ 215×2 topics
- Carbon Stocks11▲ 368×1 topic
- Tropical Forests11▲ 286×1 topic
- Land Use Change11▲ 32×7 topics
- Deep Learning8▲ 2.1×21 topics
- Sustainability8▲ 2.8×10 topics
- Ecosystem Services7▲ 17×6 topics
- Ecosystem Resilience6▲ 38×4 topics
- Biodiversity6▲ 7.2×6 topics
- Urbanization6▲ 13×2 topics
- Global Impact5▲ 27×1 topic
- Spatial Dynamics5▲ 50×1 topic
- Forest Management4▲ 65×4 topics
- Hyperspectral4▲ 43×2 topics
- Climate Change Impacts4▲ 31×2 topics
- Support Vector Machines4▲ 11×3 topics
- Forest Carbon Sequestration4▲ 168×1 topic
- Sustainable Forest Management4▲ 168×1 topic
- Urban Heat Island4▲ 37×2 topics
- Invasive Species4▲ 8.1×5 topics
- Drought4▲ 36×1 topic
- Tree Mortality4▲ 73×1 topic
- Feature Extraction4▲ 6.9×3 topics
- Ecosystem3▲ 28×2 topics
- Ecosystem Functioning3▲ 16×4 topics
- Hyperspectral Imaging3▲ 11×4 topics
- Change Detection3▲ 43×1 topic
- Habitat Fragmentation3▲ 14×2 topics
Which research topics does Institute of Forest Resource Information Techniques publish most on?
By volume in 2022–2025: Remote Sensing and LiDAR Applications, Remote Sensing in Agriculture, Forest ecology and management and Land Use and Ecosystem Services.
Area is fractional works; colour is the subfield each topic belongs to.
- 1 Remote Sensing and LiDAR Applications Environmental Engineering 16 works
- 2 Remote Sensing in Agriculture Ecology 13 works
- 3 Forest ecology and management Nature and Landscape Conservation 11 works
- 4 Land Use and Ecosystem Services Global and Planetary Change 5 works
- 5 Forest Management and Policy Global and Planetary Change 4 works
- 6 Plant Water Relations and Carbon Dynamics Global and Planetary Change 4 works
- 7 Remote-Sensing Image Classification Media Technology 3 works
- 8 Remote Sensing and Land Use Atmospheric Science 3 works
- 9 Ecology and Vegetation Dynamics Studies Nature and Landscape Conservation 3 works
- 10 Synthetic Aperture Radar (SAR) Applications and Techniques Aerospace Engineering 2 works
How open and international is its research?
Against the world’s own shares — the tick on each track. Both are shares of its output, so they sit on one scale and can be read against each other as well as against the world.
World: 28% of research is openly available.
World: 19% is written across borders.
How has Institute of Forest Resource Information Techniques's research output changed?
Output in 2018–2022 was 15% lower than in 2013–2017.
The same series as a ribbon — one cell per year, darker for more. The line above answers how much; this answers when.
Other research institutions in Beijing
- Chinese Academy of Sciences
- Tsinghua University
- Peking University
- University of Chinese Academy of Sciences
- Beihang University
- Beijing Institute of Technology
- Chinese Academy of Medical Sciences & Peking Union Medical College
- North China Electric Power University
Research measures only: rankings here say nothing about teaching, admissions or student experience. Comparable institutions and collaboration partners are in the interactive view on the map.