ForestMaps: A Computational Model and Visualization for Forest Utilization
We seek to compute utilization information for public spaces, in particular forests: which parts are used by how many people. Our contribution is threefold. First, we present a sound model for computing this information from publicly available data such a
- PDF / 6,573,061 Bytes
- 19 Pages / 439.363 x 666.131 pts Page_size
- 4 Downloads / 193 Views
Abstract. We seek to compute utilization information for public spaces, in particular forests: which parts are used by how many people. Our contribution is threefold. First, we present a sound model for computing this information from publicly available data such as road maps and population counts. Second, we present efficient algorithms for computing the desired utilization information according to this model. Third, we provide an experimental evaluation with respect to both efficiency and quality, as well as an interactive web application, that visualizes our result as a heatmap layer on top of OpenStreetMap data. The link to our web application can be found under http://forestmaps.informatik.uni-freiburg.de.
1
Introduction
Recreation is an important part of human life. Most people spent a significant fraction of their recreation time in public spaces such as forest, parks, or zoos. For the authorities of these public spaces, it is important to have utilization statistics about which parts of these spaces have been visited or are going to be visited by how many people. Such utilization statistics are useful for a number of purposes. For example, for the prioritization of maintenance works. Or for selecting proper locations for new construction works (e.g. a look-out or an inn) or facilities (e.g. litter bins). Forests, in particular, are also used for purposes other than recreation, most notably for logging and preservation. Here past and projected visitor information helps to find a meaningful assignment of the various parts of the forest to the various purposes. Indeed, the original motivation for this paper was a request from the German forest authorities for computing such usage statistics for exactly the named reasons. Our problem could be easily solved if we could track the movements of each visitor in the area of interest. But for a large number of visitors this is practically infeasible, and it would also be a major privacy issue. Instead, our approach is to come up with a computational model for how many people move through an area of interest on which paths. The input for this model should be publicly available data. Once computed, we visualize our usage statistics as a heat map, overlaid on top of a standard map.
D. Pfoser and K.-J. Li (Eds.): W2GIS 2014, LNCS 8470, pp. 115–133, 2014. c Springer-Verlag Berlin Heidelberg 2014
116
H. Bast, J. Sternisko, and S. Storandt
Extract population data for cities/counties (Wikipedia, GeoNames).
27 58
Map population data to vertices in the street graph.
35
Extract forest areas forest paths
Compute forest entry points.
Compute travel times from all vertices in the street graph to close-by entry points.
Determine popularity of entry points.
waters places of interest street data from OpenStreetMap.
Identify probable roundtours and tours through the forest.
FOREST UTILISATION HEAT MAP
Fig. 1. Overview of the complete pipeline for our utilization distribution generator on the example of public forest areas
1.1
Contribution
The contribution of this pape
Data Loading...
