A point-cloud classification method to assess biases in tLiDAR-based forest canopy gap fraction estimates - Inria - Institut national de recherche en sciences et technologies du numérique Access content directly
Poster Communications Year : 2016

A point-cloud classification method to assess biases in tLiDAR-based forest canopy gap fraction estimates

Romain Rombourg
  • Function : Author
  • PersonId : 993807
Capture and Analysis of Shapes in Motion
Eric Casella
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  • PersonId : 940653
Centre for Sustainable Forestry and Climate Change
Franck Hétroy-Wheeler
Capture and Analysis of Shapes in Motion
CV
Helen Mckay
  • Function : Author
Centre for Sustainable Forestry and Climate Change

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Signal and Image Processing Environmental Engineering

Franck Hétroy-Wheeler  : Connect in order to contact the contributor

https://inria.hal.science/hal-01399489

Submitted on : Friday, November 18, 2016-11:11:38 PM

Last modification on : Saturday, April 27, 2024-3:10:38 AM

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hal-01399489 , version 1 (18-11-2016)

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  • HAL Id : hal-01399489 , version 1

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Romain Rombourg, Eric Casella, Franck Hétroy-Wheeler, Helen Mckay. A point-cloud classification method to assess biases in tLiDAR-based forest canopy gap fraction estimates. International Conference on Functional-Structural Plant Growth Modeling, Simulation, Visualization and Applications (FSPMA), Nov 2016, Qingdao, China. 2016. ⟨hal-01399489⟩

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