A Photogrammetric Workflow for the Creation of a Forest Canopy Height Model from Small Unmanned Aerial System Imagery
Top Cited Papers
Open Access
- 6 November 2013
- Vol. 4 (4), 922-944
- https://doi.org/10.3390/f4040922
Abstract
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.Keywords
This publication has 48 references indexed in Scilit:
- Lightweight unmanned aerial vehicles will revolutionize spatial ecologyFrontiers in Ecology and the Environment, 2013
- Small area estimations of proportion of forest and timber volume combining Lidar data and stereo aerial images with terrestrial dataScandinavian Journal of Forest Research, 2013
- Unmanned Aircraft Systems in Remote Sensing and Scientific Research: Classification and Considerations of UseRemote Sensing, 2012
- Dawn of Drone Ecology: Low-Cost Autonomous Aerial Vehicles for ConservationTropical Conservation Science, 2012
- An Automated Technique for Generating Georectified Mosaics from Ultra-High Resolution Unmanned Aerial Vehicle (UAV) Imagery, Based on Structure from Motion (SfM) Point CloudsRemote Sensing, 2012
- Remote Sensing of Vegetation Structure Using Computer VisionRemote Sensing, 2010
- Area-based lidar-assisted estimation of forest standing volumeCanadian Journal of Forest Research, 2008
- High‐quality image matching and automated generation of 3D tree modelsInternational Journal of Remote Sensing, 2008
- Modeling the World from Internet Photo CollectionsInternational Journal of Computer Vision, 2007
- Predicting forest stand characteristics with airborne scanning laser using a practical two-stage procedure and field dataRemote Sensing of Environment, 2001