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Images from unmanned aircraft systems for surveying aquatic and riparian vegetation

Husson, Eva (2016). Images from unmanned aircraft systems for surveying aquatic and riparian vegetation. Diss. (sammanfattning/summary) Uppsala : Sveriges lantbruksuniv., Acta Universitatis Agriculturae Sueciae, 1652-6880 ; 2016:115
ISBN 978-91-576-8733-3
eISBN 978-91-576-8734-0
[Doctoral thesis]

[img] PDF (Summary part of the thesis - "kappan")
[img] PDF (Errata)


Aquatic and riparian vegetation in lakes, streams, and wetlands has important ecological and regulatory functions and should be monitored to detect ecosystem changes. Field surveys are often tedious and in countries with numerous lakes and streams a nationwide assessment is difficult to achieve. Remote sensing with unmanned aircraft systems (UASs) provides aerial images with high spatial resolution and offers a potential data source for detailed vegetation surveys. The overall objective of this thesis was to evaluate the potential of sub-decimetre resolution true-colour digital images acquired with a UAS for surveying non-submerged (i.e., floating-leaved and emergent) aquatic and riparian vegetation at a high level of thematic detail.

At two streams and three lakes in northern Sweden we applied several image analysis methods: Visual interpretation, manual mapping, manual mapping in combination with GPS-based field surveys, and automated object-based image analysis and classification of both 2D images and 3D point data. The UAS-images allowed for high taxonomic resolution, mostly at the species level, with high taxa identification accuracy (>80%) also in mixed-taxa stands. UAS-images in combination with ground-based vegetation surveys allowed for the extrapolation of field sampling results, like biomass measurement, to areas larger than the sampled sites. In automatically produced vegetation maps some fine-scale information detectable with visual interpretation was lost, but time-efficiency increased which is important when larger areas need to be covered. Based on spectral and textural features and height data the automated classification accuracy of non-submerged aquatic vegetation was ~80% for all test sites at the growth-form level and for four out of five test sites at the dominant-taxon level.

The results indicate good potential of UAS-images for operative mapping and monitoring of aquatic, riparian, and wetland vegetation. More case studies are needed to fully assess the added value of UAS-technology in terms of invested labour and costs compared to other survey methods. Especially the rapid technical development of multi- and hyperspectral lightweight sensors needs to be taken into account.

Authors/Creators:Husson, Eva
Title:Images from unmanned aircraft systems for surveying aquatic and riparian vegetation
Series Name/Journal:Acta Universitatis Agriculturae Sueciae
Year of publishing :2016
Depositing date:3 November 2016
Number of Pages:53
IHusson, E., Hagner, O., & Ecke, F. (2014). Unmanned aircraft systems help to map aquatic vegetation. Applied Vegetation Science 17(3), 567-577.
IIHusson, E., Lindgren, F., & Ecke, F. (2014). Assessing biomass and metal contents in riparian vegetation along a pollution gradient using an unmanned aircraft system. Water, Air, & Soil Pollution 225(6), Article number: 1957.
IIIHusson, E., Ecke, F., & Reese, H. (2016). Comparison of manual mapping and automated object-based image analysis of non-submerged aquatic vegetation from very-high-resolution UAS images. Remote Sensing 8(9), Article number: 724.
IVHusson, E., Reese, H., & Ecke, F. Combining spectral data and a DSM from UAS-images for improved classification of non-submerged aquatic vegetation. Manuscript.
Place of Publication:Uppsala
Publisher:Department of Aquatic Sciences and Assessment, Swedish University of Agricultural Sciences
ISBN for printed version:978-91-576-8733-3
ISBN for electronic version:978-91-576-8734-0
Publication Type:Doctoral thesis
Full Text Status:Public
Agris subject categories.:M Aquatic sciences and fisheries > M40 Aquatic ecology
P Natural resources > P01 Nature conservation and land resources
U Auxiliary disciplines > U40 Surveying methods
Subjects:Obsolete subject words > TECHNOLOGY > Information technology > Image analysis
(A) Swedish standard research categories 2011 > 1 Natural sciences > 105 Earth and Related Environmental Sciences > Environmental Sciences (social aspects to be 507)
(A) Swedish standard research categories 2011 > 2 Engineering and Technology > 207 Environmental Engineering > Remote Sensing
Obsolete subject words > NATURAL SCIENCES > Biology > Terrestrial, freshwater and marine ecology > Freshwater ecology
Agrovoc terms:riparian vegetation, aquatic environment, determination of species, remote sensing, aerial surveying, image analysis, cartography, environmental monitoring, sweden
Keywords:aquatic vegetation, drone, DSM (digital surface model), OBIA (Object-based image analysis), riparian vegetation, species identification, UAS (unmanned aircraft system), UAV (Unmanned aerial vehicle), RPAS (remotely piloted aircraft system), sub-decimetre spatial resolution, vegetation mapping
Permanent URL:
ID Code:13816
Faculty:NJ - Fakulteten för naturresurser och jordbruksvetenskap
Department:(NL, NJ) > Dept. of Aquatic Sciences and Assessment
Deposited By: Eva Husson
Deposited On:03 Nov 2016 09:23
Metadata Last Modified:10 Sep 2020 13:41

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