Detection and Segmentation of Small Trees in the Forest-Tundra Ecotone Using Airborne Laser Scanning

Due to expected climate change and increased focus on forests as a potential carbon sink, it is of interest to map and monitor even marginal forests where trees exist close to their tolerance limits, such as small pioneer trees in the forest-tundra ecotone. Such small trees might indicate tree line...

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Main Authors: Marius Hauglin, Erik Næsset
Format: Article
Language:English
Published: MDPI AG 2016-05-01
Series:Remote Sensing
Subjects:
Online Access:http://www.mdpi.com/2072-4292/8/5/407
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author Marius Hauglin
Erik Næsset
author_facet Marius Hauglin
Erik Næsset
author_sort Marius Hauglin
collection DOAJ
description Due to expected climate change and increased focus on forests as a potential carbon sink, it is of interest to map and monitor even marginal forests where trees exist close to their tolerance limits, such as small pioneer trees in the forest-tundra ecotone. Such small trees might indicate tree line migrations and expansion of the forests into treeless areas. Airborne laser scanning (ALS) has been suggested and tested as a tool for this purpose and in the present study a novel procedure for identification and segmentation of small trees is proposed. The study was carried out in the Rollag municipality in southeastern Norway, where ALS data and field measurements of individual trees were acquired. The point density of the ALS data was eight points per m2, and the field tree heights ranged from 0.04 to 6.3 m, with a mean of 1.4 m. The proposed method is based on an allometric model relating field-measured tree height to crown diameter, and another model relating field-measured tree height to ALS-derived height. These models are calibrated with local field data. Using these simple models, every positive above-ground height derived from the ALS data can be related to a crown diameter, and by assuming a circular crown shape, this crown diameter can be extended to a crown segment. Applying this model to all ALS echoes with a positive above-ground height value yields an initial map of possible circular crown segments. The final crown segments were then derived by applying a set of simple rules to this initial “map” of segments. The resulting segments were validated by comparison with field-measured crown segments. Overall, 46% of the field-measured trees were successfully detected. The detection rate increased with tree size. For trees with height >3 m the detection rate was 80%. The relatively large detection errors were partly due to the inherent limitations in the ALS data; a substantial fraction of the smaller trees was hit by no or just a few laser pulses. This prevents reliable detection of changes at an individual tree level, but monitoring changes on an area level could be a possible application of the method. The results further showed that some variation must be expected when the method is used for repeated measurements, but no significant differences in the mean number of segmented trees were found over an intensively measured test area of 11.4 ha.
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spelling doaj.art-045cb91a05694a5b8f3f2850f291ed262022-12-22T04:06:18ZengMDPI AGRemote Sensing2072-42922016-05-018540710.3390/rs8050407rs8050407Detection and Segmentation of Small Trees in the Forest-Tundra Ecotone Using Airborne Laser ScanningMarius Hauglin0Erik Næsset1Norwegian University of Life Sciences, Department of Ecology and Natural Resource Management, P.O. Box 5003, N-1432 Ås, NorwayNorwegian University of Life Sciences, Department of Ecology and Natural Resource Management, P.O. Box 5003, N-1432 Ås, NorwayDue to expected climate change and increased focus on forests as a potential carbon sink, it is of interest to map and monitor even marginal forests where trees exist close to their tolerance limits, such as small pioneer trees in the forest-tundra ecotone. Such small trees might indicate tree line migrations and expansion of the forests into treeless areas. Airborne laser scanning (ALS) has been suggested and tested as a tool for this purpose and in the present study a novel procedure for identification and segmentation of small trees is proposed. The study was carried out in the Rollag municipality in southeastern Norway, where ALS data and field measurements of individual trees were acquired. The point density of the ALS data was eight points per m2, and the field tree heights ranged from 0.04 to 6.3 m, with a mean of 1.4 m. The proposed method is based on an allometric model relating field-measured tree height to crown diameter, and another model relating field-measured tree height to ALS-derived height. These models are calibrated with local field data. Using these simple models, every positive above-ground height derived from the ALS data can be related to a crown diameter, and by assuming a circular crown shape, this crown diameter can be extended to a crown segment. Applying this model to all ALS echoes with a positive above-ground height value yields an initial map of possible circular crown segments. The final crown segments were then derived by applying a set of simple rules to this initial “map” of segments. The resulting segments were validated by comparison with field-measured crown segments. Overall, 46% of the field-measured trees were successfully detected. The detection rate increased with tree size. For trees with height >3 m the detection rate was 80%. The relatively large detection errors were partly due to the inherent limitations in the ALS data; a substantial fraction of the smaller trees was hit by no or just a few laser pulses. This prevents reliable detection of changes at an individual tree level, but monitoring changes on an area level could be a possible application of the method. The results further showed that some variation must be expected when the method is used for repeated measurements, but no significant differences in the mean number of segmented trees were found over an intensively measured test area of 11.4 ha.http://www.mdpi.com/2072-4292/8/5/407airborne laser scanningtreelinemonitoring
spellingShingle Marius Hauglin
Erik Næsset
Detection and Segmentation of Small Trees in the Forest-Tundra Ecotone Using Airborne Laser Scanning
Remote Sensing
airborne laser scanning
treeline
monitoring
title Detection and Segmentation of Small Trees in the Forest-Tundra Ecotone Using Airborne Laser Scanning
title_full Detection and Segmentation of Small Trees in the Forest-Tundra Ecotone Using Airborne Laser Scanning
title_fullStr Detection and Segmentation of Small Trees in the Forest-Tundra Ecotone Using Airborne Laser Scanning
title_full_unstemmed Detection and Segmentation of Small Trees in the Forest-Tundra Ecotone Using Airborne Laser Scanning
title_short Detection and Segmentation of Small Trees in the Forest-Tundra Ecotone Using Airborne Laser Scanning
title_sort detection and segmentation of small trees in the forest tundra ecotone using airborne laser scanning
topic airborne laser scanning
treeline
monitoring
url http://www.mdpi.com/2072-4292/8/5/407
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AT eriknæsset detectionandsegmentationofsmalltreesintheforesttundraecotoneusingairbornelaserscanning