Application of KDE+ software to identify collective risk hotspots of ungulate-vehicle collisions in South Tyrol, Northern Italy
The result's identifiers
Result code in 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>
Result on the web
<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>
Alternative languages
Result language
angličtina
Original language name
Application of KDE+ software to identify collective risk hotspots of ungulate-vehicle collisions in South Tyrol, Northern Italy
Original language description
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.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
10619 - Biodiversity conservation
Result continuities
Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2018
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
EUROPEAN JOURNAL OF WILDLIFE RESEARCH
ISSN
1612-4642
e-ISSN
1439-0574
Volume of the periodical
64
Issue of the periodical within the volume
5
Country of publishing house
US - UNITED STATES
Number of pages
12
Pages from-to
"nestránkovano"
UT code for WoS article
000445753000001
EID of the result in the Scopus database
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