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Statistical Study Based on the Kriging Method and Geographic Mapping in Rigid Pavement Defects in Southern Chile


  • Diana Movilla-Quesada

    (Departamento de Construcción y Agronomía, Escuela Politécnica Superior de Zamora, Universidad de Salamanca, 49029 Zamora, Spain)

  • Julio Rojas-Mora

    (Departamento de Ingeniería Informática, Facultad de Ingeniería, Universidad Católica de Temuco, Temuco 4780000, Chile)

  • Aitor C. Raposeiras

    (Gi2V—Grupo de Investigación en Ingeniería Vial, Facultad de Ciencias de la Ingeniería, Instituto de Obras Civiles, Universidad Austral de Chile, Valdivia 5090000, Chile
    Departamento de Ingeniería Mecánica, Escuela Politécnica Superior de Zamora, Universidad de Salamanca, 49029 Zamora, Spain)


ASTM D6433 is used to assess the need for maintenance of pavement sections. Although the Pavement Condition Index (PCI) factor calculation method provides reliable values, this method analyzes sections and defects individually and indicates current maintenance needs, but it cannot be used to predict the occurrence of new defects. Therefore, it is necessary to complement this method by considering variables that influence the occurrence of faults, among which are the geospatial distribution and the specific characteristics of the slabs. This research focuses on the identification of multiple types of disturbances that exist in Portland Cement Pavements (PCC), located in a high traffic area in the city of Valdivia (Chile). A spatial geostatistical relationship is established through visual inspection using geographical maps, as well as distribution, using the kriging method. This technique makes use of variograms that allow quantifying the parameters used in this study, thus expressing the spatial autocorrelation of the faults analyzed. From the results obtained by spatial geostatistics and kriging, it is possible to generate a data correlation for the distribution and characteristics of the streets considered. In addition, a co-kriging method is established instead of an ordinary kriging method. The relationship between observed and predicted values improved from 0.3327 to 0.5770. The width of the slabs, as well as some streets, is shown in our analysis to be unimportant. For better model accuracy, the number of covariates associated with the type of vehicle traffic, the age and shape of the slabs, and the construction techniques used for the pavement needs to increase.

Suggested Citation

  • Diana Movilla-Quesada & Julio Rojas-Mora & Aitor C. Raposeiras, 2022. "Statistical Study Based on the Kriging Method and Geographic Mapping in Rigid Pavement Defects in Southern Chile," Sustainability, MDPI, vol. 14(1), pages 1-14, January.
  • Handle: RePEc:gam:jsusta:v:14:y:2022:i:1:p:585-:d:718598

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    References listed on IDEAS

    1. Oster, Clinton V. & Strong, John S., 2013. "Analyzing road safety in the United States," Research in Transportation Economics, Elsevier, vol. 43(1), pages 98-111.
    2. Niehaus, Markus & Galilea, Patricia & Hurtubia, Ricardo, 2016. "Accessibility and equity: An approach for wider transport project assessment in Chile," Research in Transportation Economics, Elsevier, vol. 59(C), pages 412-422.
    3. Hall, Stephen & Zegras, Christopher & Rojas, Henry Malbrán, 1994. "Transportation and energy in Santiago, Chile," Transport Policy, Elsevier, vol. 1(4), pages 233-243, October.
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