Leaderboards/Tree Root and Stability Studies

Tree Root and Stability Studies

Last updated July 7, 2026

Rising Stars

New and hot

Rising Stars Researchers

1
Wantong Li
University of California, Berkeley
2
Moziihrii Ado
North Eastern Hill University
3
Si Chen
Chinese Academy of Fishery Sciences
4
Wenjie Liao
Southwest Jiaotong University
5
Tiancheng Yuan
Zhejiang A & F University
6
Zhaozhao Li
Anhui University of Science and Technology
7
Trung Nghia Phan
Hanoi University
8
Alec S. Baird
University of Bern
9
Shahrzad Nikoobakht
Yazd University
10
Itzhak Khait
Tel Aviv University

Rising Stars Papers

1
Regulation of the global carbon and water cycles through vegetation structural and physiological dynamics
Environmental Research Letters|2024
31 cit.
2
Modelling root decomposition effects on root reinforcement and slope stability
Computers and Geotechnics|2024
16 cit.
3
Renewable bamboo-based composites for electromagnetic and thermal applications
Journal of Cleaner Production|2025
16 cit.
4
A clean and convenient way to utilize naturally air-dried bamboo tubes and increase their economic value
Journal of Cleaner Production|2025
14 cit.
5
A Comprehensive Study on Young Roots of <i>Acacia mangium</i> Willd. Species for Soil Bioengineering
Land Degradation and Development|2024
12 cit.
6
Magnetic particle decorated hierarchical porous carbon with adjustable electromagnetic wave absorption and excellent Joule thermal response
Industrial Crops and Products|2025
12 cit.
7
Disentangling Effects of Vegetation Structure and Physiology on Land–Atmosphere Coupling
Global Change Biology|2025
11 cit.
8
Bamboo-derived fire-retardant porous carbon with excellent adjustable electromagnetic wave absorption performance
Industrial Crops and Products|2025
11 cit.
9
Resolving the contrasting leaf hydraulic adaptation of <scp>C<sub>3</sub></scp> and <scp>C<sub>4</sub></scp> grasses
New Phytologist|2025
9 cit.
10
Research on the changes of cell structure and micro-mechanical properties in different parts of bamboo under saturated steam treatment
Construction and Building Materials|2025
8 cit.

Emerging Leaders

Gaining momentum

Emerging Leaders Researchers

1
Zizheng Guo
Hebei University of Technology
2
Yutian Ke
California Institute of Technology
3
Paraskevas Tsangaratos
National Technical University of Athens
4
Zohre Sadat Pourtaghi
Yazd University
5
Li Zhu
Nanjing University of Chinese Medicine
6
Yifei Cui
Tsinghua University
7
Haijia Wen
Chongqing University of Technology
8
Faming Huang
Ministry of Natural Resources
9
Yunchao Tang
Dongguan University of Technology
10
Wenlong Wang
Chinese Academy of Sciences

Emerging Leaders Papers

1
3D vision technologies for a self-developed structural external crack damage recognition robot
Automation in Construction|2024
274 cit.
2
Fruit detection and positioning technology for a Camellia oleifera C. Abel orchard based on improved YOLOv4-tiny model and binocular stereo vision
Expert Systems with Applications|2022
250 cit.
3
Regional rainfall-induced landslide hazard warning based on landslide susceptibility mapping and a critical rainfall threshold
Geomorphology|2022
207 cit.
4
Novel visual crack width measurement based on backbone double-scale features for improved detection automation
Engineering Structures|2022
204 cit.
5
Slope stability prediction based on a long short-term memory neural network: comparisons with convolutional neural networks, support vector machines and random forest models
International Journal of Coal Science & Technology|2023
144 cit.
6
Automatic classification of asphalt pavement cracks using a novel integrated generative adversarial networks and improved VGG model
Engineering Structures|2023
137 cit.
7
Exploring temperature-resilient recycled aggregate concrete with waste rubber: An experimental and multi-objective optimization analysis
REVIEWS ON ADVANCED MATERIALS SCIENCE|2023
117 cit.
8
Uncertainties of landslide susceptibility prediction considering different landslide types
Journal of Rock Mechanics and Geotechnical Engineering|2023
110 cit.
9
Transforming unmanned pineapple picking with spatio-temporal convolutional neural networks
Computers and Electronics in Agriculture|2023
102 cit.
10
Seismic performance evaluation of recycled aggregate concrete-filled steel tubular columns with field strain detected via a novel mark-free vision method
Structures|2022
97 cit.

Current Senior Leaders

Established & currently active

Current Senior Leaders Researchers

1
Alexia Stokes
Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement
2
Biswajeet Pradhan
University of Technology Sydney
3
Ghislain Vieilledent
Université de Montpellier
4
Stephen D. Davis
Pepperdine University
5
Helena Pereira
University of Lisbon
6
Peter Niemz
ETH Zurich
7
Saro Lee
Korea Institute of Geoscience and Mineral Resources
8
John S. Sperry
University of Utah
9
Dani Or
ETH Zurich
10
C. P. Stark
National Institute of Hydrology

Current Senior Leaders Papers

1
Improved allometric models to estimate the aboveground biomass of tropical trees
Global Change Biology|2014
3k cit.
2
Vulnerability of Xylem to Cavitation and Embolism
Annual Review of Plant Physiology and Plant Molecular Biology|1989
1.6k cit.
3
The rainfall intensity–duration control of shallow landslides and debris flows: an update
Landslides|2007
1.6k cit.
4
Unsaturated Soil Mechanics.
Vadose Zone Journal|2005
1.3k cit.
5
Rainfall thresholds for the initiation of landslides in central and southern Europe
Meteorology and Atmospheric Physics|2007
1.3k cit.
6
A comparative study on the predictive ability of the decision tree, support vector machine and neuro-fuzzy models in landslide susceptibility mapping using GIS
Computers & Geosciences|2012
1.2k cit.
7
A method for measuring hydraulic conductivity and embolism in xylem
Plant Cell & Environment|1988
1.1k cit.
8
The limits to tree height
Nature|2004
1.1k cit.
9
Landslide hazard mapping at Selangor, Malaysia using frequency ratio and logistic regression models
Landslides|2006
1.1k cit.
10
Landslide susceptibility assessment and factor effect analysis: backpropagation artificial neural networks and their comparison with frequency ratio and bivariate logistic regression modelling
Environmental Modelling & Software|2009
956 cit.

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