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Extraction of Spectral Information from Airborne 3D Data for Assessment of Tree Species Proportions

Bohlin, Jonas and Wallerman, Jörgen and Fransson, Johan (2021). Extraction of Spectral Information from Airborne 3D Data for Assessment of Tree Species Proportions. Remote Sensing. 13 , 720
[Research article]

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Abstract

With the rapid development of photogrammetric software and accessible camera technology, land surveys and other mapping organizations now provide various point cloud and digital surface model products from aerial images, often including spectral information. In this study, methods for colouring the point cloud and the importance of different metrics were compared for tree species-specific estimates at a coniferous hemi-boreal test site in southern Sweden. A total of three different data sets of aerial image-based products and one multi-spectral lidar data set were used to estimate tree species-specific proportion and stem volume using an area-based approach. Metrics were calculated for 156 field plots (10 m radius) from point cloud data and used in a Random Forest analysis. Plot level accuracy was evaluated using leave-one-out cross-validation. The results showed small differences in estimation accuracy of species-specific variables between the colouring methods. Simple averages of the spectral metrics had the highest importance and using spectral data from two seasons improved species prediction, especially deciduous proportion. Best tree species-specific proportion was estimated using multi-spectral lidar with 0.22 root mean square error (RMSE) for pine, 0.22 for spruce and 0.16 for deciduous. Corresponding RMSE for aerial images was 0.24, 0.23 and 0.20 for pine, spruce and deciduous, respectively. For the species-specific stem volume at plot level using image data, the RMSE in percent of surveyed mean was 129% for pine, 60% for spruce and 118% for deciduous.

Authors/Creators:Bohlin, Jonas and Wallerman, Jörgen and Fransson, Johan
Title:Extraction of Spectral Information from Airborne 3D Data for Assessment of Tree Species Proportions
Series Name/Journal:Remote Sensing
Year of publishing :2021
Volume:13
Article number:720
Number of Pages:12
Publisher:MDPI
Language:English
Publication Type:Research article
Article category:Scientific peer reviewed
Version:Published version
Copyright:Creative Commons: Attribution 4.0
Full Text Status:Public
Subjects:(A) Swedish standard research categories 2011 > 2 Engineering and Technology > 207 Environmental Engineering > Remote Sensing
(A) Swedish standard research categories 2011 > 4 Agricultural Sciences > 401 Agricultural, Forestry and Fisheries > Forest Science
Keywords:aerial images, multi-spectral lidar, Optec Titan, photogrammetry, species-specific proportion, stem volume, UltraCam
URN:NBN:urn:nbn:se:slu:epsilon-p-111374
Permanent URL:
http://urn.kb.se/resolve?urn=urn:nbn:se:slu:epsilon-p-111374
Additional ID:
Type of IDID
DOI10.3390/rs13040720
Web of Science (WoS)000624440400001
ID Code:23250
Faculty:S - Faculty of Forest Sciences
Department:(S) > Dept. of Forest Resource Management
(NL, NJ) > Dept. of Forest Resource Management
Deposited By: SLUpub Connector
Deposited On:12 Apr 2021 11:57
Metadata Last Modified:12 Apr 2021 12:01

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