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Image analysis to monitor experimental trampling and vegetation recovery in Icelandic plant communities

Runnström, Micael C. LU ; Ólafsdóttir, Rannveig LU ; Blanke, Jan LU and Berlin, Bastian LU (2019) In Environments - MDPI 6(9).
Abstract

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 different 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,... (More)

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 different 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.

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author
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Experimental plots, Green chromatic coordinate (GCC), Image analysis, Maximum Likelihood Classification (MLC), Monitoring, Nature-based tourism, Recreational trampling
in
Environments - MDPI
volume
6
issue
9
article number
99
external identifiers
  • scopus:85073573081
ISSN
2076-3298
DOI
10.3390/environments6090099
language
English
LU publication?
yes
id
b1462b1c-0ad0-47c6-8952-ebb8dd88ad8b
date added to LUP
2019-10-29 10:55:57
date last changed
2020-01-13 02:29:32
@article{b1462b1c-0ad0-47c6-8952-ebb8dd88ad8b,
  abstract     = {<p>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 different 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.</p>},
  author       = {Runnström, Micael C. and Ólafsdóttir, Rannveig and Blanke, Jan and Berlin, Bastian},
  issn         = {2076-3298},
  language     = {eng},
  number       = {9},
  series       = {Environments - MDPI},
  title        = {Image analysis to monitor experimental trampling and vegetation recovery in Icelandic plant communities},
  url          = {http://dx.doi.org/10.3390/environments6090099},
  doi          = {10.3390/environments6090099},
  volume       = {6},
  year         = {2019},
}