Roadside vegetation influences clustering of ungulate vehicle collisions

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F44994575%3A_____%2F19%3AN0000021" target="_blank" >RIV/44994575:_____/19:N0000021 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/60460709:41320/19:80190 RIV/60460709:41330/19:80190

Výsledek na webu

<a href="https://www.sciencedirect.com/science/article/pii/S1361920918311659" target="_blank" >https://www.sciencedirect.com/science/article/pii/S1361920918311659</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.trd.2019.07.013" target="_blank" >10.1016/j.trd.2019.07.013</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Roadside vegetation influences clustering of ungulate vehicle collisions

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

Roadside vegetation influences clustering of ungulate vehicle collisions

Popis výsledku anglicky

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.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

40102 - Forestry

Projekt

Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2019

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Transportation Research Part D: Transport and Environment

ISSN

1361-9209

e-ISSN

—

Svazek periodika

73

Číslo periodika v rámci svazku

2019

Stát vydavatele periodika

NL - Nizozemsko

Počet stran výsledku

10

Strana od-do

381-390

Kód UT WoS článku

999

EID výsledku v databázi Scopus

—