Assessment of reed structure based on ULS data

The reed belt surrounding Neusiedler See is the largest Phragmites Australis (Common Reed) reed belt in Central Europe, spanning approximately 180 square kilometers. Most of the area is protected as part of the Neusiedler See-Seewinkel National Park. Reduced reed harvesting in recent years, due to warmer winters, has led to the formation of aging and degrading reed stands. Fire management has been proposed as a method to rejuvenate reed stands by eliminating the broken reed layer. To evaluate this method, Land Burgenland conducted a controlled fire experiment on 9 January 2024, accompanied by UAV-based LiDAR and RGB data acquisition before, immediately and several months post-fire.This thesis estimates reed parameters and the structural influence of fire management by computation of topographic models. Further analysis included the vertical point distribution to assess reed parameters, such as the thickness of the broken reed layer and reed density. In-situ data collected by the University of Vienna and BOKU Vienna supported further analysis. A reduction in the thickness of the broken reed layer was quantified using difference DTMs. Validation of the broken reed layer reduction was performed using In-Situ data, collected prior to the fire experiment. In addition, fire-affected areas were successfully quantified, providing further planning data for future fire management campaigns. Reed density assessment was performed using normalized point density values above a height threshold of 100 cm, in an attempt to distinguish dense and sparse reed patches. The absence of In-situ validation data for dense and sparse patches limits the certainty of these classifications. The potential of UAV LiDAR systems for assessing and monitoring reed parameters has been demonstrated.

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Publication Details

Journal
reposiTUm (TU Wien)
Published
2024-12-01
DOI
https://doi.org/10.34726/hss.2024.122550
Primary Topic
Fire effects on ecosystems
Type
article
Field-Weighted Citation Impact
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article

Assessment of reed structure based on ULS data

reposiTUm (TU Wien)
Fire effects on ecosystems
article

Assessment of reed structure based on ULS data

article en

Abstract

The reed belt surrounding Neusiedler See is the largest Phragmites Australis (Common Reed) reed belt in Central Europe, spanning approximately 180 square kilometers. Most of the area is protected as part of the Neusiedler See-Seewinkel National Park. Reduced reed harvesting in recent years, due to warmer winters, has led to the formation of aging and degrading reed stands. Fire management has been proposed as a method to rejuvenate reed stands by eliminating the broken reed layer. To evaluate this method, Land Burgenland conducted a controlled fire experiment on 9 January 2024, accompanied by UAV-based LiDAR and RGB data acquisition before, immediately and several months post-fire.This thesis estimates reed parameters and the structural influence of fire management by computation of topographic models. Further analysis included the vertical point distribution to assess reed parameters, such as the thickness of the broken reed layer and reed density. In-situ data collected by the University of Vienna and BOKU Vienna supported further analysis. A reduction in the thickness of the broken reed layer was quantified using difference DTMs. Validation of the broken reed layer reduction was performed using In-Situ data, collected prior to the fire experiment. In addition, fire-affected areas were successfully quantified, providing further planning data for future fire management campaigns. Reed density assessment was performed using normalized point density values above a height threshold of 100 cm, in an attempt to distinguish dense and sparse reed patches. The absence of In-situ validation data for dense and sparse patches limits the certainty of these classifications. The potential of UAV LiDAR systems for assessing and monitoring reed parameters has been demonstrated.

reposiTUm (TU Wien)
TU Wien (AT)
Sustainable cities and communities
Openalex Percentile: Top 70%
Fire effects on ecosystems
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