Coastline Kriging: A Bayesian Approach

TL;DR

This paper introduces a Bayesian hierarchical model for spatial interpolation of chemical concentrations along coastlines, aiding exposure assessment in coastal clean-up operations, demonstrated on simulated and real data.

Contribution

It provides a simple, practical Bayesian method for analyzing and interpolating coastal chemical concentrations, tailored for exposure assessment.

Findings

Four models demonstrated on simulated data

One model applied to GuLF STUDY dataset

Method offers an easy implementation for practitioners

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 paper 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. 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.