Citation

Keken Z, Sedoník J, Kušta T, Andrasik R, Bíl M. Transp. Res. D Trans. Environ. 2019; 73: 381-390.

Copyright

(Copyright © 2019, Elsevier Publishing)

DOI

10.1016/j.trd.2019.07.013

PMID

unavailable

Abstract

The aim of this study was to identify landscape-related factors which could explain the concentration of traffic crashes with large ungulates in a forest environment. We worked with ungulate-vehicle collisions which took place on the Czech road network in the period 2014-2016 using the application Srazenazver.cz. With the KDE+ method, we chose the most significant hotspots with linkage to forest. For comparison we randomly selected control localities outside the KDE+ hotspots (i.e., with very low level of ungulate-vehicle collisions) but still in the forest area. A set of photos were taken at each hotspot and control locality (2 orthophotos and 4 driver views). Each set of images was then visually analysed by two independent evaluators. They did not know which set of images were for hotspots and which set of images were for control localities. From the point of view of the overall score, it cannot be said that these two groups of locations differ (p-value 0.3575, Kolmogorov-Smirnov test). The only attribute that demonstrated a difference between hotspots and randomly selected locations was "attractiveness (quality food source and cover) of the immediate vicinity of the transport infrastructure for the ungulates" (p-value 0.0016, Kolmogorov-Smirnov test).

RESULTS confirm the importance of landscape management in the surroundings of transport infrastructure, especially in its immediate vicinity. However, they did not confirm the possibility that the most dangerous locations from the UVC point of view could be identified on the basis of landscape composition and the overall state of vegetation around transport infrastructure.

Language: en

Keywords

Collision risk; Google Street Views, views of drivers; Road ecology; Road management; Wildlife