Application of KDE+ software to identify collective risk hotspots of ungulate-vehicle collisions in South Tyrol, Northern Italy

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F44994575%3A_____%2F18%3AN0000031" target="_blank" >RIV/44994575:_____/18:N0000031 - isvavai.cz</a>

Výsledek na webu

<a href="https://link.springer.com/article/10.1007/s10344-018-1214-x" target="_blank" >https://link.springer.com/article/10.1007/s10344-018-1214-x</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/s10344-018-1214-x" target="_blank" >10.1007/s10344-018-1214-x</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Application of KDE+ software to identify collective risk hotspots of ungulate-vehicle collisions in South Tyrol, Northern Italy

Popis výsledku v původním jazyce

This paper is the first dealing with animal-vehicle collisions (AVC) with red and roe deer in South Tyrol, Northern Italy. The Autonomous Province of Bolzano (South Tyrol) has been collecting AVC data since 2012 on the entire provincial road network. Each year, AVC data accounted for more than 700 cases per year, with several socioeconomic and ecological implications. The aim of this research is to identify the locations where AVC occur more frequently than expected (hotspots) and better outline subsequent implementation of mitigation measures. For an effective identification of AVC hotspots, we applied a combined methodology of temporal and spatial analysis on AVC data collected on the South Tyrol road network in the years 2012–2014. AVC data enabled the identification of the temporal patterns, which showed different behaviors of the two target species in close proximity of the road network and throughout the 12 months. The KDE+ software applied to the 2012–2014 AVC database allowed for spatial analysis and the identification of hotspots, i.e., the road sections having the highest risk for drivers. The integration of the results, coming from the abovementioned methodologies, contributes to a detailed assessment of roads that would allow the identification of the local contributing factors and a base-line of potential problematic areas that will highlight the need for further investigation to assess whether the risk-rank is accurate and allocate effectively limited resources to a feasible number of identified hotspots and reduce the current degree of AVC in the South Tyrolean road network.

Název v anglickém jazyce

Application of KDE+ software to identify collective risk hotspots of ungulate-vehicle collisions in South Tyrol, Northern Italy

Popis výsledku anglicky

This paper is the first dealing with animal-vehicle collisions (AVC) with red and roe deer in South Tyrol, Northern Italy. The Autonomous Province of Bolzano (South Tyrol) has been collecting AVC data since 2012 on the entire provincial road network. Each year, AVC data accounted for more than 700 cases per year, with several socioeconomic and ecological implications. The aim of this research is to identify the locations where AVC occur more frequently than expected (hotspots) and better outline subsequent implementation of mitigation measures. For an effective identification of AVC hotspots, we applied a combined methodology of temporal and spatial analysis on AVC data collected on the South Tyrol road network in the years 2012–2014. AVC data enabled the identification of the temporal patterns, which showed different behaviors of the two target species in close proximity of the road network and throughout the 12 months. The KDE+ software applied to the 2012–2014 AVC database allowed for spatial analysis and the identification of hotspots, i.e., the road sections having the highest risk for drivers. The integration of the results, coming from the abovementioned methodologies, contributes to a detailed assessment of roads that would allow the identification of the local contributing factors and a base-line of potential problematic areas that will highlight the need for further investigation to assess whether the risk-rank is accurate and allocate effectively limited resources to a feasible number of identified hotspots and reduce the current degree of AVC in the South Tyrolean road network.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

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OECD FORD obor

10619 - Biodiversity conservation

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

2018

Kód důvěrnosti údajů

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

Název periodika

EUROPEAN JOURNAL OF WILDLIFE RESEARCH

ISSN

1612-4642

e-ISSN

1439-0574

Svazek periodika

64

Číslo periodika v rámci svazku

5

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

12

Strana od-do

"nestránkovano"

Kód UT WoS článku

000445753000001

EID výsledku v databázi Scopus

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