In wintery regions, it is critical to have a full understanding of how road surface conditions would change over space to make more informed decision on where (i.e., hot-spots such as historically cold spots that are likely to create slippery conditions) and how much of winter maintenance operations (i.e., salting and plowing) are of necessity. Thermal mapping has been a primary tool used to determine the hot-spots by identifying the variation pattern of measured pavement surface temperature along roadways. It, however, requires substantial amount of time and effort, particularly for cities that are in need of a large-scaled implementation, posing a significant limitation of its applicability at the regional level. Hence, this paper presents a standard framework to estimate road surface temperature (RST) variable using GIS and advanced geostatistical technique. A case study based on highway segments in Alberta is used to illustrate the distinct features of the proposed method and model estimation performance. The findings of the paper suggest that the proposed GIS-based approach provides a reliable solution posing a great possibility to replace the existing technique and further applied for determining the potential location of an RWIS station to promote more efficient and cost-effective winter maintenance operations.


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    Title :

    Modelling of winter road surface temperature (RST) — A GIS-based approach


    Contributors:
    Kwon, Tae J. (author) / Gu, Lian (author)


    Publication date :

    2017-08-01


    Size :

    455141 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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