Coastline Kriging: A Bayesian Approach. Issue 7 (23rd July 2018)

• Record Type: Journal Article
• Authors: Abdalla, Nada; Banerjee, Sudipto; Ramachandran, Gurumurthy; Stenzel, Mark; Stewart, Patricia A
• Is Part Of: Annals of work exposures and health. Volume 62:Issue 7(2018)
• Page Start: 818
• Page End: 827
• Publication Date: 2018-07-23
• Subjects: coastal kriging -- Gaussian process -- geostatistics -- hierarchical modeling -- kriging -- Markov chain Monte Carlo; Medicine, Industrial -- Periodicals; Industrial hygiene -- Periodicals; 613.6205
• DOI: 10.1093/annweh/wxy058
• Languages: English
• ISSNs: 2398-7316

Abstract

Abstract: 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.