Determining tree height and crown diameter from high-resolution UAV imagery

Advances in computer vision and the parallel development of unmanned aerial vehicles (UAVs) allow for the extensive use of UAV in forest inventory and in indirect measurements of tree features. We used UAV-sensed high-resolution imagery through photogrammetry and Structure from Motion (SfM) to estim...

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Vydané v:	International journal of remote sensing Ročník 38; číslo 8-10; s. 2392 - 2410
Hlavní autori:	Panagiotidis, Dimitrios, Abdollahnejad, Azadeh, Surový, Peter, Chiteculo, Vasco
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	London Taylor & Francis 19.05.2017 Taylor & Francis Ltd
Predmet:	Accuracy Betula pendula Birch trees Canopies canopy Computer vision Coniferous trees Evergreen trees forest inventory Geographic information systems High resolution Image resolution Image segmentation Imagery Larix decidua Motion perception Photogrammetry Picea abies Pine Pine trees Pinus sylvestris remote sensing Satellite navigation systems Smoothing Species composition species diversity Trees Unmanned aerial vehicles watersheds Workflow Norway
ISSN:	0143-1161, 1366-5901, 1366-5901
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Abstract	Advances in computer vision and the parallel development of unmanned aerial vehicles (UAVs) allow for the extensive use of UAV in forest inventory and in indirect measurements of tree features. We used UAV-sensed high-resolution imagery through photogrammetry and Structure from Motion (SfM) to estimate tree heights and crown diameters. We reconstructed 3D structures from 2D image sequences for two study areas (25 × 25 m). Species composition for Plot 1 included Norway spruce (Picea abies L.) together with European larch (Larix decidua Mill.) and Scots pine (Pinus sylvestris L.), whereas Plot 2 was mainly Norway spruce and Scots pine together with scattered individuals of European larch and Silver birch (Betula pendula Roth.). The involved workflow used canopy height models (CHMs) for the extraction of height, the smoothing of raster images for the determination of the local maxima, and Inverse Watershed Segmentation (IWS) for the estimation of the crown diameters with the help of a geographical information system (GIS). Finally, we validated the accuracies of the two methods by comparing the UAV results with ground measurements. The results showed higher agreement between field and remote-sensed data for heights than for crown diameters based on RMSE%, which were in the range 11.42-12.62 for height and 14.29-18.56 for crown diameter. Overall, the accuracy of the results was acceptable and showed that the methods were feasible for detecting tree heights and crown diameter.
AbstractList	Advances in computer vision and the parallel development of unmanned aerial vehicles (UAVs) allow for the extensive use of UAV in forest inventory and in indirect measurements of tree features. We used UAV-sensed high-resolution imagery through photogrammetry and Structure from Motion (SfM) to estimate tree heights and crown diameters. We reconstructed 3D structures from 2D image sequences for two study areas (25 × 25 m). Species composition for Plot 1 included Norway spruce (Picea abies L.) together with European larch (Larix decidua Mill.) and Scots pine (Pinus sylvestris L.), whereas Plot 2 was mainly Norway spruce and Scots pine together with scattered individuals of European larch and Silver birch (Betula pendula Roth.). The involved workflow used canopy height models (CHMs) for the extraction of height, the smoothing of raster images for the determination of the local maxima, and Inverse Watershed Segmentation (IWS) for the estimation of the crown diameters with the help of a geographical information system (GIS). Finally, we validated the accuracies of the two methods by comparing the UAV results with ground measurements. The results showed higher agreement between field and remote-sensed data for heights than for crown diameters based on RMSE%, which were in the range 11.42–12.62 for height and 14.29–18.56 for crown diameter. Overall, the accuracy of the results was acceptable and showed that the methods were feasible for detecting tree heights and crown diameter. Advances in computer vision and the parallel development of unmanned aerial vehicles (UAVs) allow for the extensive use of UAV in forest inventory and in indirect measurements of tree features. We used UAV-sensed high-resolution imagery through photogrammetry and Structure from Motion (SfM) to estimate tree heights and crown diameters. We reconstructed 3D structures from 2D image sequences for two study areas (25 × 25 m). Species composition for Plot 1 included Norway spruce (Picea abies L.) together with European larch (Larix decidua Mill.) and Scots pine (Pinus sylvestris L.), whereas Plot 2 was mainly Norway spruce and Scots pine together with scattered individuals of European larch and Silver birch (Betula pendula Roth.). The involved workflow used canopy height models (CHMs) for the extraction of height, the smoothing of raster images for the determination of the local maxima, and Inverse Watershed Segmentation (IWS) for the estimation of the crown diameters with the help of a geographical information system (GIS). Finally, we validated the accuracies of the two methods by comparing the UAV results with ground measurements. The results showed higher agreement between field and remote-sensed data for heights than for crown diameters based on RMSE%, which were in the range 11.42-12.62 for height and 14.29-18.56 for crown diameter. Overall, the accuracy of the results was acceptable and showed that the methods were feasible for detecting tree heights and crown diameter. Advances in computer vision and the parallel development of unmanned aerial vehicles (UAVs) allow for the extensive use of UAV in forest inventory and in indirect measurements of tree features. We used UAV-sensed high-resolution imagery through photogrammetry and Structure from Motion (SfM) to estimate tree heights and crown diameters. We reconstructed 3D structures from 2D image sequences for two study areas (25 25 m). Species composition for Plot 1 included Norway spruce (Picea abies L.) together with European larch (Larix decidua Mill.) and Scots pine (Pinus sylvestris L.), whereas Plot 2 was mainly Norway spruce and Scots pine together with scattered individuals of European larch and Silver birch (Betula pendula Roth.). The involved workflow used canopy height models (CHMs) for the extraction of height, the smoothing of raster images for the determination of the local maxima, and Inverse Watershed Segmentation (IWS) for the estimation of the crown diameters with the help of a geographical information system (GIS). Finally, we validated the accuracies of the two methods by comparing the UAV results with ground measurements. The results showed higher agreement between field and remote-sensed data for heights than for crown diameters based on RMSE%, which were in the range 11.42-12.62 for height and 14.29-18.56 for crown diameter. Overall, the accuracy of the results was acceptable and showed that the methods were feasible for detecting tree heights and crown diameter.
Author	Chiteculo, Vasco Panagiotidis, Dimitrios Surový, Peter Abdollahnejad, Azadeh
Author_xml	– sequence: 1 givenname: Dimitrios surname: Panagiotidis fullname: Panagiotidis, Dimitrios email: panagiotidis@fld.czu.cz organization: Department of Forest Management, Czech University of Life Sciences – sequence: 2 givenname: Azadeh surname: Abdollahnejad fullname: Abdollahnejad, Azadeh organization: Department of Forest Management, Czech University of Life Sciences – sequence: 3 givenname: Peter surname: Surový fullname: Surový, Peter organization: Department of Forest Management, Czech University of Life Sciences – sequence: 4 givenname: Vasco surname: Chiteculo fullname: Chiteculo, Vasco organization: Department of Forest Management, Czech University of Life Sciences
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Snippet	Advances in computer vision and the parallel development of unmanned aerial vehicles (UAVs) allow for the extensive use of UAV in forest inventory and in...
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SubjectTerms	Accuracy Betula pendula Birch trees Canopies canopy Computer vision Coniferous trees Evergreen trees forest inventory Geographic information systems High resolution Image resolution Image segmentation Imagery Larix decidua Motion perception Photogrammetry Picea abies Pine Pine trees Pinus sylvestris remote sensing Satellite navigation systems Smoothing Species composition species diversity Trees Unmanned aerial vehicles watersheds Workflow
Title	Determining tree height and crown diameter from high-resolution UAV imagery
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