Network Theory and Hiking
Source: http://www.sciencedirect.com/science/article/pii/S0143622814002124#
Walking and hiking are popular outdoor recreational activities and are shown to have beneficial effects on human health and well-being. In fact, it is recommended to walk thirty minutes daily to experience these benefits. This paper evaluates the use of hiking trails using network theory and mixed GPS tracking. The research involved two collections of data: the first one involves the structure of recreational trials in the portion of the Danube-Auen National Park in Vienna, Austria, while the second collection involved the paths visitors took through the park from any of the four major entrances. After gathering the data, the researches implemented a five-step process to analyze the data:
- Pre-processing of GPS data – this filtered out any unrealistic movements or buggy GPS data.
- Creating the structural network (undirected graph) – display network of all possible routes a hiker can take with the nodes representing the places where a hiker can choose to follow a different path and the edges represent the paths between two nodes.
- Creating the functional network (directed graph) – Use the GPS data of a hiker in the area to determine the paths the person took in the form of a directed graph. When compiled with data from all the other hikers, the network will determine the most popular routes or paths taken.
- Calculating the network connectivity indices – 3 different Kansky indices were used to evaluate network efficiency.
- Quantifying the importance of network nodes – This step involves calculating node centrality measures. For this paper, the researchers determined: input degree, output degree, degree all, closeness, and betweenness.
This paper discusses material mentioned at the very beginning of class as well as a little bit of material presented later in the class. The research involved the use of basic network theory which is evident in the creation of the structural network of the park in Step 2 of the data analysis procedure. The researchers simply compiled all the possible paths any hiker can take through the park. While early after the midterm we discussed directed graphs in Web pages, which is shown in Step 3, where, as I mentioned before, the researchers compiled GPS data of hikers traversing in the area. The paper provided some important figures also. The first figure shows how GPS data of a hiker in the park is converted into a functional network. In (A) the GPS was imported into a MATLAB environment and in (B), the resulting structural network is displayed. The second picture shows the structural network of the park, labeled (A), with numerically labeled node numbers and the functional network, labeled (B), where the more popular routes are shown with a more bolded arrow. In conclusion, using GPS data and network theory is an excellent to evaluate recreational trails, though there are faults to it such as possible interference of GPS signals with the environment.
