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Mapping and monitoring of vegetation using airborne laser scanning

Nyström, Mattias (2014). Mapping and monitoring of vegetation using airborne laser scanning. Diss. (sammanfattning/summary) Umeå : Sveriges lantbruksuniv., Acta Universitatis Agriculturae Sueciae, 1652-6880 ; 2014:9
ISBN 978-91-576-7966-6
eISBN 978-91-576-7967-3
[Doctoral thesis]

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In this thesis, the utility of airborne laser scanning (ALS) for monitoring vegetation of relevance for the environmental sector was investigated. The vegetation characteristics studied include measurements of biomass, biomass change and vegetation classification in the forest-tundra ecotone; afforestation of grasslands; and detection of windthrown trees. Prediction of tree biomass for mountain birch (Betula pubescens ssp. czerepanovii) using sparse (1.4 points/m²) and dense (6.1 points/m²) ALS data was compared for a site at the forest-tundra ecotone near Abisko in northern Sweden (Lat. 68° N, Long. 19° E). The predictions using the sparse ALS data provided almost as good results (RMSE 21.2%) as the results from the dense ALS data (18.7%) despite the large difference in point densities. A new algorithm was developed to compensate for uneven distribution of the laser points without decimating the data; use of this algorithm reduced the RMSE for biomass prediction from 19.9% to 18.7% for the dense ALS data. Additional information about vegetation height and density from ALS data improved a satellite data classification of alpine vegetation, in particular for the willow and mountain birch classes. Histogram matching was shown to be effective for relative calibration of metrics from two ALS acquisitions collected over the same area using different scanners and flight parameters. Thus the difference between histogram-matched ALS metrics from different data acquisitions can be used to locate areas with unusual development of the vegetation.

The height of small trees (0.3–2.6 m tall) in former pasture land near the Remnings¬torp test site in southern Sweden (Lat. 58° N, Long. 13° E) could be measured with high precision (standard deviation 0.3 m) using high point density ALS data (54 points/m2). When classifying trees taller than 1 m into the two classes of changed and unchanged, the overall classification accuracy was 88%. A new method to automatically detect windthrown trees in forested areas was developed and evaluated at the Remningstorp test site. The overall detection rate was 38% on tree-level, but when aggregating to 40 m square grid cells, at least one windthrown tree was detected in 77% of the cells that according to field data contained windthrown trees.

In summary, this thesis has shown the high potential for ALS to be a future tool to map and monitor vegetation for several applications of interest for the environmental sector.

Authors/Creators:Nyström, Mattias
Title:Mapping and monitoring of vegetation using airborne laser scanning
Series Name/Journal:Acta Universitatis Agriculturae Sueciae
Year of publishing :21 February 2014
Number of Pages:72
I.Nyström, M., Holmgren, J., & Olsson, H. (2012). Prediction of tree biomass in the forest–tundra ecotone using airborne laser scanning. Remote Sensing of Environment 123, 271-279.
II.Reese, H., Nyström, M., Nordkvist, K., & Olsson, H. (2014). Combining airborne laser scanning data and optical satellite data for classification of alpine vegetation. International Journal of Applied Earth Observation and Geoinformation 27, 81-90.
III.Nyström, M., Holmgren, J., & Olsson, H. (2013). Change detection of mountain birch using multi-temporal ALS point clouds. Remote Sensing Letters 4, 190-199.
IV.Nyström, M., Holmgren, J., & Olsson, H. (2013). Detecting afforestation at individual tree level using ALS (manuscript).
V.Nyström, M., Holmgren, J., Fransson, J. E. S., & Olsson, H. Detection of windthrown trees using airborne laser scanning. Accepted for publication in International Journal of Applied Earth Observation and Geoinformation.
Place of Publication:Umeå
Publisher:Dept. of Forest Resource Management, Swedish University of Agricultural Sciences
Associated Programs and Other Stakeholders:SLU - Agricultural Sciences for Global Development > Land use and climate change
ISBN for printed version:978-91-576-7966-6
ISBN for electronic version:978-91-576-7967-3
Publication Type:Doctoral thesis
Full Text Status:Public
Agris subject categories.:K Forestry > K10 Forestry production
U Auxiliary disciplines > U40 Surveying methods
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
Agrovoc terms:remote sensing, lasers, aerial surveying, sensors, forest trees, tundra, vegetation, biomass, storms, wind damage, afforestation, monitoring, sweden
Keywords:airborne laser scanning, ALS, LiDAR, windthrown trees, storm damaged forest, afforestation, tree line, biomass, forest-tundra ecotone, change detection, alpine vegetation
Permanent URL:
ID Code:10982
Faculty:S - Faculty of Forest Sciences
Department:(S) > Dept. of Forest Resource Management
(NL, NJ) > Dept. of Forest Resource Management
External funders:Swedish Environmental Protection Agency and Swedish National Space Board
Deposited By: Dr Mattias Nyström
Deposited On:21 Jan 2014 14:22
Metadata Last Modified:14 Dec 2014 08:44

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