Coastline kriging: A Bayesian approach

Nada Abdalla, Sudipto Banerjee, Gurumurthy Ramachandran, Mark Stenzel, Patricia A. Stewart

Research output: Contribution to journalArticlepeer-review

1 Scopus citations


Statistical interpolation of chemical concentrations at new locations is an important step in assessing a worker's exposure level. When measurements are available from coastlines, as is the case in coastal clean-up operations in oil spills, one may need a mechanism to carry out spatial interpolation at new locations along the coast. In this article, we present a simple model for analyzing spatial data that is observed over a coastline. We demonstrate four different models using two different representations of the coast using curves. The four models were demonstrated on simulated data and one of them was also demonstrated on a dataset from the GuLF STUDY (Gulf Long-term Follow-up Study). Our contribution here is to offer practicing hygienists and exposure assessors with a simple and easy method to implement Bayesian hierarchical models for analyzing and interpolating coastal chemical concentrations.

Original languageEnglish (US)
Pages (from-to)818-827
Number of pages10
JournalAnnals of work exposures and health
Issue number7
StatePublished - Aug 13 2018


  • Coastal kriging
  • Gaussian process
  • Geostatistics
  • Hierarchical modeling
  • Kriging
  • Markov chain Monte Carlo

ASJC Scopus subject areas

  • Public Health, Environmental and Occupational Health


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