World's Best Scientists 2026 revealed!

D-Index & Metrics

Environmental Sciences

D-Index
61
Citations
15963
World Ranking
2735
National Ranking
213

Research.com Recognitions

  • 2015 - National Institutes of Health Director's Pioneer Award

Overview

Mathias Disney is affiliated with University College London in the United Kingdom. Their research primarily focuses on environmental science, with a strong emphasis on subfields such as environmental engineering, nature and landscape conservation, global and planetary change, ecology, and insect science.

The core topics of Mathias Disney's work include:

  • Remote Sensing and LiDAR Applications
  • Forest ecology and management
  • Remote Sensing in Agriculture
  • Plant Water Relations and Carbon Dynamics
  • Forest Ecology and Biodiversity Studies
  • Ecology and Vegetation Dynamics Studies
  • 3D Surveying and Cultural Heritage

The scientist has collaborated frequently with several researchers, among whom are:

  • Phil Wilkes
  • Kim Calders
  • Andrew Burt
  • Yadvinder Malhi
  • Hans Verbeeck

Mathias Disney has published numerous papers in several notable publication venues. The top venues by the number of publications include:

  • Zenodo (CERN European Organization for Nuclear Research)
  • bioRxiv (Cold Spring Harbor Laboratory)
  • Remote Sensing in Ecology and Conservation
  • Remote Sensing of Environment
  • Methods in Ecology and Evolution

Recent papers authored or co-authored by Mathias Disney include:

  • Terrestrial laser scanning in forest ecology: Expanding the horizon (2020), Remote Sensing of Environment
  • Estimating forest above-ground biomass with terrestrial laser scanning: Current status and future directions (2022), Methods in Ecology and Evolution
  • Quantifying tropical forest structure through terrestrial and UAV laser scanning fusion in Australian rainforests (2022), Remote Sensing of Environment
  • Tree species classification using structural features derived from terrestrial laser scanning (2020), ISPRS Journal of Photogrammetry and Remote Sensing
  • Laser scanning reveals potential underestimation of biomass carbon in temperate forest (2022), Ecological Solutions and Evidence

Mathias Disney has also contributed to book publications, including the work published by Ghent University titled Aboveground Woody Biomass Product Validation Good Practices Protocol (2021).

In 2015, Mathias Disney received the National Institutes of Health Director's Pioneer Award, reflecting recognition within their field of study.

Best Publications

  • First operational BRDF, albedo nadir reflectance products from MODIS

    Crystal B Schaaf;Feng Gao;Alan H Strahler;Wolfgang Lucht

  • Fast Automatic Precision Tree Models from Terrestrial Laser Scanner Data

    Pasi Raumonen;Mikko Kaasalainen;Markku Åkerblom;Sanna Kaasalainen

  • Nondestructive estimates of above‐ground biomass using terrestrial laser scanning

    Kim Calders;Glenn Newnham;Andrew Burt;Simon Murphy

  • Hyperspectral remote sensing of foliar nitrogen content.

    Yuri Knyazikhin;Mitchell A. Schull;Pauline Stenberg;Matti Mõttus

  • Terrestrial laser scanning in forest ecology: Expanding the horizon

    Kim Calders;Jennifer Adams;John Armston;Harm Bartholomeus

  • Data acquisition considerations for Terrestrial Laser Scanning of forest plots

    Phil Wilkes;Alvaro Lau;Mathias Disney;Kim Calders;Kim Calders

  • SimpleTree —An Efficient Open Source Tool to Build Tree Models from TLS Clouds

    Jan Hackenberg;Heinrich Spiecker;Kim Calders;Mathias Disney

  • Third Radiation Transfer Model Intercomparison (RAMI) exercise: Documenting progress in canopy reflectance models

    Jean-Luc Widlowski;Malcolm Taberner;Bernard Pinty;Véronique Bruniquel-Pinel

  • Can we measure terrestrial photosynthesis from space directly, using spectral reflectance and fluorescence?

    J Grace;C Nichol;M Disney;P Lewis

  • Terrestrial Laser Scanning for Plot-Scale Forest Measurement

    Glenn J. Newnham;John D. Armston;Kim Calders;Kim Calders;Mathias I. Disney

  • Estimation of above-ground biomass of large tropical trees with Terrestrial LiDAR

    Jose Gonzalez de Tanago;Jose Gonzalez de Tanago;Alvaro Lau;Alvaro Lau;Harm Bartholomeus;Martin Herold

  • The fourth phase of the radiative transfer model intercomparison (RAMI) exercise: Actual canopy scenarios and conformity testing

    Jean Luc Widlowski;Corrado Mio;Mathias Disney;Jennifer Adams

  • Radiation Transfer Model Intercomparison (RAMI) exercise: Results from the second phase

    B. Pinty;J.-L. Widlowski;M. Taberner;N. Gobron

  • 3d modelling of forest canopy structure for remote sensing simulations in the optical and microwave domains

    M. Disney;P. Lewis;P. Saich

  • Monte Carlo ray tracing in optical canopy reflectance modelling

    M.I. Disney;P. Lewis;P.R.J. North

  • Extracting individual trees from lidar point clouds using treeseg

    Andrew Burt;Mathias Disney;Mathias Disney;Kim Calders

  • Weighing trees with lasers: advances, challenges and opportunities.

    M. I. Disney;M. Boni Vicari;A. Burt;K. Calders

  • Highly Accurate Tree Models Derived from Terrestrial Laser Scan Data: A Method Description

    Jan Hackenberg;Christopher Morhart;Jonathan Sheppard;Heinrich Spiecker

  • Canopy spectral invariants for remote sensing and model applications

    Dong Huang;Yuri Knyazikhin;Robert Earl Dickinson;Miina Rautiainen

  • The Importance of Consistent Global Forest Aboveground Biomass Product Validation

    L. Duncanson;J. Armston;M. Disney;V. Avitabile

  • An assessment of the MODIS collection 5 leaf area index product for a region of mixed coniferous forest

    MG De Kauwe;MI Disney;Tristan Quaife;P Lewis

  • Assimilating canopy reflectance data into an ecosystem model with an Ensemble Kalman Filter

    Tristan Quaife;Philip Lewis;Martin De Kauwe;Mathew Williams

Frequent Co-Authors

Philip Lewis
Philip Lewis University College London
Kim Calders
Kim Calders Ghent University
John Armston
John Armston University of Maryland, College Park
Tristan Quaife
Tristan Quaife University of Reading
Mathew Williams
Mathew Williams University of Edinburgh
Martin Herold
Martin Herold Wageningen University & Research
Yadvinder Malhi
Yadvinder Malhi University of Oxford
Alexander Shenkin
Alexander Shenkin Northern Arizona University
Crystal B. Schaaf
Crystal B. Schaaf University of Massachusetts Boston
Patrick Meir
Patrick Meir University of Edinburgh

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