Image Analysis to Monitor Experimental Trampling and Vegetation Recovery in Icelandic Plant Communities
Autor: | Bastian Berlin, J. H. Blanke, Rannveig Ólafsdóttir, Micael Runnström |
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Přispěvatelé: | Líf- og umhverfisvísindadeild (HÍ), Faculty of Life and Environmental Sciences (UI), Verkfræði- og náttúruvísindasvið (HÍ), School of Engineering and Natural Sciences (UI), Háskóli Íslands, University of Iceland |
Jazyk: | angličtina |
Rok vydání: | 2019 |
Předmět: |
010504 meteorology & atmospheric sciences
Monitoring nature-based tourism Experimental plots Maximum likelihood classification Recreational trampling 01 natural sciences Natural (archaeology) lcsh:TD1-1066 Image analysis Recovery rate Maximum Likelihood Classification (MLC) image analysis 0502 economics and business Traðk Green chromatic coordinate (GCC) Gróðureyðing lcsh:Environmental technology. Sanitary engineering Recreation Ecology Evolution Behavior and Systematics 0105 earth and related environmental sciences General Environmental Science green chromatic coordinate (GCC) Resistance (ecology) Renewable Energy Sustainability and the Environment recreational trampling experimental plots 05 social sciences Ferðamennska Plant community Vegetation Nature-based tourism monitoring Environmental science Physical geography Trampling Umhverfismál 050212 sport leisure & tourism |
Zdroj: | Environments, Vol 6, Iss 9, p 99 (2019) Environments Volume 6 Issue 9 |
ISSN: | 2076-3298 |
Popis: | Publisher's version (útgefin grein) With growing tourism in natural areas, monitoring recreational impacts is becoming increasingly important. This paper aims to evaluate how di_erent trampling intensities a_ect some common Icelandic plant communities by using digital photographs to analyze and quantify vegetation in experimental plots and to monitor vegetation recovery rates over a consecutive three-year period. Additionally, it seeks to evaluate the use of image analysis for monitoring recreational impact in natural areas. Experimental trampling was conducted in two di_erent sites representing the lowlands and the highlands in 2014, and the experimental plots were revisited in 2015, 2016, and 2017. The results show that moss has the highest sensitivity to trampling, and furthermore has a slow recovery rate. Moss-heaths in the highlands also show higher sensitivity and slower recovery rates than moss-heaths in the lowlands, and grasslands show the highest resistance to trampling. Both methods tested, i.e., Green Chromatic Coordinate (GCC) and Maximum Likelihood Classification (MLC), showed significant correlation with the trampling impact. Using image analysis to quantify the status and define limits of use will likely be a valuable and vital element in managing recreational areas. Unmanned aerial vehicles (UAVs) will add a robust way to collect photographic data that can be processed into vegetation parameters to monitor recreational impacts in natural areas. This research was partly funded by the Icelandic Tourist Board. |
Databáze: | OpenAIRE |
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