A Photogrammetric Workflow for the Creation of a Forest Canopy Height Model from Small Unmanned Aerial System Imagery
The recent development of operational small unmanned aerial systems (UASs) opens the door for their extensive use in forest mapping, as both the spatial and temporal resolution of UAS imagery better suit local-scale investigation than traditional remote sensing tools. This article focuses on the use...
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Online Access: | http://www.mdpi.com/1999-4907/4/4/922 |
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doaj-30e235a7186b4b3eb73ce04edf6792bd2020-11-24T21:20:02ZengMDPI AGForests1999-49072013-11-014492294410.3390/f4040922A Photogrammetric Workflow for the Creation of a Forest Canopy Height Model from Small Unmanned Aerial System ImageryPhilippe LejeuneStéphanie BonnetMarc Pierrot-DeseillignyJonathan LiseinThe recent development of operational small unmanned aerial systems (UASs) opens the door for their extensive use in forest mapping, as both the spatial and temporal resolution of UAS imagery better suit local-scale investigation than traditional remote sensing tools. This article focuses on the use of combined photogrammetry and “Structure from Motion” approaches in order to model the forest canopy surface from low-altitude aerial images. An original workflow, using the open source and free photogrammetric toolbox, MICMAC (acronym for Multi Image Matches for Auto Correlation Methods), was set up to create a digital canopy surface model of deciduous stands. In combination with a co-registered light detection and ranging (LiDAR) digital terrain model, the elevation of vegetation was determined, and the resulting hybrid photo/LiDAR canopy height model was compared to data from a LiDAR canopy height model and from forest inventory data. Linear regressions predicting dominant height and individual height from plot metrics and crown metrics showed that the photogrammetric canopy height model was of good quality for deciduous stands. Although photogrammetric reconstruction significantly smooths the canopy surface, the use of this workflow has the potential to take full advantage of the flexible revisit period of drones in order to refresh the LiDAR canopy height model and to collect dense multitemporal canopy height series.http://www.mdpi.com/1999-4907/4/4/922canopy heightforestryphotogrammetryMICMACUnmanned Aerial SystemsUASUAVforest inventoryuneven-aged broadleaf stands |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Philippe Lejeune Stéphanie Bonnet Marc Pierrot-Deseilligny Jonathan Lisein |
spellingShingle |
Philippe Lejeune Stéphanie Bonnet Marc Pierrot-Deseilligny Jonathan Lisein A Photogrammetric Workflow for the Creation of a Forest Canopy Height Model from Small Unmanned Aerial System Imagery Forests canopy height forestry photogrammetry MICMAC Unmanned Aerial Systems UAS UAV forest inventory uneven-aged broadleaf stands |
author_facet |
Philippe Lejeune Stéphanie Bonnet Marc Pierrot-Deseilligny Jonathan Lisein |
author_sort |
Philippe Lejeune |
title |
A Photogrammetric Workflow for the Creation of a Forest Canopy Height Model from Small Unmanned Aerial System Imagery |
title_short |
A Photogrammetric Workflow for the Creation of a Forest Canopy Height Model from Small Unmanned Aerial System Imagery |
title_full |
A Photogrammetric Workflow for the Creation of a Forest Canopy Height Model from Small Unmanned Aerial System Imagery |
title_fullStr |
A Photogrammetric Workflow for the Creation of a Forest Canopy Height Model from Small Unmanned Aerial System Imagery |
title_full_unstemmed |
A Photogrammetric Workflow for the Creation of a Forest Canopy Height Model from Small Unmanned Aerial System Imagery |
title_sort |
photogrammetric workflow for the creation of a forest canopy height model from small unmanned aerial system imagery |
publisher |
MDPI AG |
series |
Forests |
issn |
1999-4907 |
publishDate |
2013-11-01 |
description |
The recent development of operational small unmanned aerial systems (UASs) opens the door for their extensive use in forest mapping, as both the spatial and temporal resolution of UAS imagery better suit local-scale investigation than traditional remote sensing tools. This article focuses on the use of combined photogrammetry and “Structure from Motion” approaches in order to model the forest canopy surface from low-altitude aerial images. An original workflow, using the open source and free photogrammetric toolbox, MICMAC (acronym for Multi Image Matches for Auto Correlation Methods), was set up to create a digital canopy surface model of deciduous stands. In combination with a co-registered light detection and ranging (LiDAR) digital terrain model, the elevation of vegetation was determined, and the resulting hybrid photo/LiDAR canopy height model was compared to data from a LiDAR canopy height model and from forest inventory data. Linear regressions predicting dominant height and individual height from plot metrics and crown metrics showed that the photogrammetric canopy height model was of good quality for deciduous stands. Although photogrammetric reconstruction significantly smooths the canopy surface, the use of this workflow has the potential to take full advantage of the flexible revisit period of drones in order to refresh the LiDAR canopy height model and to collect dense multitemporal canopy height series. |
topic |
canopy height forestry photogrammetry MICMAC Unmanned Aerial Systems UAS UAV forest inventory uneven-aged broadleaf stands |
url |
http://www.mdpi.com/1999-4907/4/4/922 |
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