Image Analysis to Monitor Experimental Trampling and Vegetation Recovery in Icelandic Plant Communities

• Main Authors: Micael C. Runnström, Rannveig Ólafsdóttir, Jan Blanke, Bastian Berlin
• Format: Article
• Language: English
• Published: MDPI AG 2019-08-01
• Series: Environments
• Subjects: monitoring; recreational trampling; experimental plots; nature-based tourism; image analysis; green chromatic coordinate (GCC); Maximum Likelihood Classification (MLC)
• Online Access: https://www.mdpi.com/2076-3298/6/9/99

With growing tourism in natural areas, monitoring recreational impacts is becoming increasingly important. This paper aims to evaluate how different trampling intensities affect 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.