Benoît St-Onge

According to our database1, Benoît St-Onge authored at least 13 papers between 2000 and 2022.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Links

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Bibliography

2022
Effects of Viewing Geometry on Multispectral Lidar-Based Needle-Leaved Tree Species Identification.
Remote. Sens., December, 2022

A Comparison of Three Airborne Laser Scanner Types for Species Identification of Individual Trees.
Sensors, 2022

2019
Estimating the Height and Basal Area at Individual Tree and Plot Levels in Canadian Subarctic Lichen Woodlands Using Stereo WorldView-3 Images.
Remote. Sens., 2019

2018
Integrating macro and micro scale approaches in the agent-based modeling of residential dynamics.
Int. J. Appl. Earth Obs. Geoinformation, 2018

Towards a Generalized Method for Tree Species Classification Using Multispectral Airborne Laser Scanning in Ontario, Canada.
Proceedings of the 2018 IEEE International Geoscience and Remote Sensing Symposium, 2018

2017
Modeling the Effect of the Spatial Pattern of Airborne Lidar Returns on the Prediction and the Uncertainty of Timber Merchantable Volume.
Remote. Sens., 2017

2016
Canopy Height Model (CHM) Derived From a TanDEM-X InSAR DSM and an Airborne Lidar DTM in Boreal Forest.
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2016

2014
Mapping forest canopy height using TanDEM-X DSM and airborne LiDAR DTM.
Proceedings of the 2014 IEEE Geoscience and Remote Sensing Symposium, 2014

2012
A GEOBIA framework to estimate forest parameters from lidar transects, Quickbird imagery and machine learning: A case study in Quebec, Canada.
Int. J. Appl. Earth Obs. Geoinformation, 2012

2011
A multiscale geographic object-based image analysis to estimate lidar-measured forest canopy height using Quickbird imagery.
Int. J. Geogr. Inf. Sci., 2011

2009
Development of a pit filling algorithm for LiDAR canopy height models.
Comput. Geosci., 2009

2004
L'altimétrie laser à balayage.
Rev. Int. Géomatique, 2004

2000
Cellular neural network for automated detection of geological lineaments on Radarsat images.
IEEE Trans. Geosci. Remote. Sens., 2000


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