Identification of local factors causing clustering of animal vehicle collisions

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14310%2F18%3A00102612" target="_blank" >RIV/00216224:14310/18:00102612 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1002/jwmg.21467" target="_blank" >http://dx.doi.org/10.1002/jwmg.21467</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1002/jwmg.21467" target="_blank" >10.1002/jwmg.21467</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Identification of local factors causing clustering of animal vehicle collisions

Popis výsledku v původním jazyce

Effective measures reducing risk of animal vehicle collisions (AVC) require defining high risk locations on roads where AVCs occur. Previous studies examined factors explaining locations of individual AVCs; however, some AVCs can form hotspots (i.e., clusters of AVCs) that can be explained by local factors. We therefore applied a novel kernel density estimation (KDE) method to AVCs for the Czech Republic from October 2006 to December 2011 to identify AVCs hotspots along roads. Our main goal was to identify local factors and their effect on the non random (clustered) occurrence of AVCs. The remaining solitary AVCs occurred randomly and are likely induced by other human factors on the global scale. The hotspot identification method followed by the selected data mining methods (KDE methods) identified factors causing local clustering of AVCs.

Název v anglickém jazyce

Identification of local factors causing clustering of animal vehicle collisions

Popis výsledku anglicky

Effective measures reducing risk of animal vehicle collisions (AVC) require defining high risk locations on roads where AVCs occur. Previous studies examined factors explaining locations of individual AVCs; however, some AVCs can form hotspots (i.e., clusters of AVCs) that can be explained by local factors. We therefore applied a novel kernel density estimation (KDE) method to AVCs for the Czech Republic from October 2006 to December 2011 to identify AVCs hotspots along roads. Our main goal was to identify local factors and their effect on the non random (clustered) occurrence of AVCs. The remaining solitary AVCs occurred randomly and are likely induced by other human factors on the global scale. The hotspot identification method followed by the selected data mining methods (KDE methods) identified factors causing local clustering of AVCs.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10600 - Biological sciences

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach<br>I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2018

Kód důvěrnosti údajů

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

Název periodika

Journal of Wildlife Management

ISSN

0022-541X

e-ISSN

—

Svazek periodika

82

Číslo periodika v rámci svazku

5

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

8

Strana od-do

940-947

Kód UT WoS článku

000435816100008

EID výsledku v databázi Scopus

2-s2.0-85048989701