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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

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • 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