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Categorizing Wetland Vegetation by Airborne Laser Scanning on Lake Balaton and Kis-Balaton, Hungary

Authors: Norbert Pfeifer; Christian Briese; András Zlinszky; Werner Mücke; Hubert Lehner;

Categorizing Wetland Vegetation by Airborne Laser Scanning on Lake Balaton and Kis-Balaton, Hungary

Abstract

Outlining patches dominated by different plants in wetland vegetation provides information on species succession, microhabitat patterns, wetland health and ecosystem services. Aerial photogrammetry and hyperspectral imaging are the usual data acquisition methods but the application of airborne laser scanning (ALS) as a standalone tool also holds promises for this field since it can be used to quantify 3-dimensional vegetation structure. Lake Balaton is a large shallow lake in western Hungary with shore wetlands that have been in decline since the 1970s. In August 2010, an ALS survey of the shores of Lake Balaton was completed with 1 pt/m<sup>2</sup> discrete echo recording. The resulting ALS dataset was processed to several output rasters describing vegetation and terrain properties, creating a sufficient number of independent variables for each raster cell to allow for basic multivariate classification. An expert-generated decision tree algorithm was applied to outline wetland areas, and within these, patches dominated by <em>Typha</em> sp. <em>Carex</em> sp., and <em>Phragmites australis</em>. Reed health was mapped into four categories: healthy, stressed, ruderal and die-back. The output map was tested against a set of 775 geo-tagged ground photographs and had a user’s accuracy of > 97% for detecting non-wetland features (trees, artificial surfaces and low density <em>Scirpus</em> stands), > 72% for dominant genus detection and > 80% for most reed health categories (with 62% for one category). Overall classification accuracy was 82.5%, Cohen’s Kappa 0.80, which is similar to some hyperspectral or multispectral-ALS fusion studies. Compared to hyperspectral imaging, the processing chain of ALS can be automated in a similar way but relies directly on differences in vegetation structure and actively sensed reflectance and is thus probably more robust. The data acquisition parameters are similar to the national surveys of several European countries, suggesting that these existing datasets could be used for vegetation mapping and monitoring.

Subjects by Vocabulary

Microsoft Academic Graph classification: Vegetation classification Wetland Phragmites Ruderal species Remote sensing Shore geography geography.geographical_feature_category biology Hyperspectral imaging Vegetation biology.organism_classification Environmental science Physical geography Scirpus

Keywords

Science, wetlands, LIDAR, LIDAR; wetlands; <em>Phragmites australis</em>; <em>Carex</em>; <em>Typha</em>; ecosystem health; vegetation classification, vegetation classification, ecosystem health, &lt;em&gt;Carex&lt;/em&gt;, Q, General Earth and Planetary Sciences, &lt;em&gt;Phragmites australis&lt;/em&gt;, &lt;em&gt;Typha&lt;/em&gt;

99 references, page 1 of 10

Strayer, D.L.; Findlay, S.E.G. Ecology of freshwater shore zones. Aquat. Sci. 2010, 72, 127-163. [OpenAIRE]

Ostendorp, W. Schilf ALS Lebensraum. In Artenschutzsymposium Teichrohrsänger; Landesanstalt für Umweltschutz Baden-Württemberg, Karlsruhe, Germany, 1993; Volume 68, pp. 173-280. [OpenAIRE]

Vymazal, J. Enhancing ecosystem services on the landscape with created, constructed and restored wetlands. Ecol. Eng. 2011, 37, 1-5. [OpenAIRE]

Limnologica 2004, 34, 3-14.

Wetzel, R.G. Limnology, 3rd ed.; Academic Press: London, UK, 2001; p. 1066.

6. Segal, S. Principles on structure, zonation and succession of aquatic macrophytes. Hidrobiologia 1971, 12, 89-97.

7. van der Putten, W.H. Die-back of Phragmites australis in European wetlands: An overview of the European Research Programme on Reed Die-Back and Progression (1993-1994). Aquat. Bot. 1997, 59, 263-275.

8. Cizkova, H.; Brix, H.; Kopecky, J.; Lukavska, J. Organic acids in the sediments of wetlands dominated by Phragmites australis: Evidence of phytotoxic concentrations. Aquat. Bot. 1999, 64, 303-315. [OpenAIRE]

9. Weisner, S.E.B. Effects of an organic sediment on performance of young Phragmites australis clones at different water depth treatments. Hydrobiologia 1996, 330, 189-194.

10. Zlinszky, A. A Balatoni Nádpusztulás Légifelvételes Vizsgálata; Eötvös Loránd University, Budapest, Hungary, 2007.

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    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
52
Top 10%
Top 10%
Top 10%
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