Mathias I. Disney

Ecology · 2013–2020

A researcher in the Science corpus: 11 papers; trusts 16 researchers and is trusted by 1 researcher here, as inferred from the citation graph.

Subfields

• Ecology — 53 citations into it
• Environmental Engineering — 49 citations into it; #5,233 of 5,479 by trust here, #1,082 by citations
• Global and Planetary Change — 41 citations into it
• Nature and Landscape Conservation — 40 citations into it
• Plant Science — 36 citations into it
• Geology — 9 citations into it
• Computational Mechanics — 7 citations into it
• Computer Vision and Pattern Recognition — 7 citations into it

Whom Mathias I. Disney trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Craig Macfarlane
2. Sylvain G. Leblanc
3. Pasi Raumonen
4. Nathalie Bréda
5. Huiquan Bi
6. Kim Calders
7. Youngryel Ryu
8. Jan Pisek
9. Richard A. Fournier
10. Chuong B. Do

Who trusts Mathias I. Disney overall

1. Kim Calders

Papers from Mathias I. Disney's perspective

Ordered by how strongly the researchers Mathias I. Disney trusts endorse each paper. Same corpus, a different order for every researcher.

1. Review of methods for in situ leaf area index determination Part I. Theories, sensors and hemispherical photography
2. A Method for Registration of 3-D Shapes
3. Automatic Stem Mapping Using Single-Scan Terrestrial Laser Scanning (IEEE Transactions on Geoscience and Remote Sensing)
4. Estimating tree and stand variables in a Corsican Pine woodland from terrestrial laser scanner data
5. Fast Automatic Precision Tree Models from Terrestrial Laser Scanner Data (Remote Sensing)
6. A Simplex Method for Function Minimization
7. Automatic forest inventory parameter determination from terrestrial laser scanner data
8. Forests and Climate Change: Forcings, Feedbacks, and the Climate Benefits of Forests (Science)
9. Improved allometric models to estimate the aboveground biomass of tropical trees (Global Change Biology)
10. Knowledge and heuristic-based modeling of laser-scanned trees (TOGS)

Their papers

• Tree species classification using structural features derived from terrestrial laser scanning (2020) — 88 citations
• Time for a Plant Structural Economics Spectrum (2019) — 68 citations
• Leaf and wood classification framework for terrestrial LiDAR point clouds (2019) — 170 citations
• New estimates of leaf angle distribution from terrestrial LiDAR: Comparison with measured and modelled estimates from nine broadleaf tree species (2019) — 75 citations
• Variability and bias in active and passive ground-based measurements of effective plant, wood and leaf area index (2018) — 70 citations
• Quantifying the impact of woody material on leaf area index estimation from hemispherical photography using 3D canopy simulations (2016) — 55 citations
• Nondestructive estimates of above‐ground biomass using terrestrial laser scanning (2015) — 626 citations
• Waveform lidar over vegetation: An evaluation of inversion methods for estimating return energy (2015) — 76 citations
• An improved theoretical model of canopy gap probability for Leaf Area Index estimation in woody ecosystems (2015) — 48 citations
• SimpleTree —An Efficient Open Source Tool to Build Tree Models from TLS Clouds (2015) — 331 citations
• Fast Automatic Precision Tree Models from Terrestrial Laser Scanner Data (2013) — 788 citations