Coastline Kriging: A Bayesian Approach

Details

• Personal Author:
  Abdalla N ; Banerjee S ; Ramachandran G ; Stenzel M ; Stewart PA
• Description:
  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. [Description provided by NIOSH]
• Subjects:
  Mining Occupational Health Safety Vibration
• Keywords:
  Algorithms Analytical Models Author Keywords: Coastal Kriging Chemical Analysis Chemicals Databases Data Processing Environmental Contamination Exposure Assessment Exposure Levels Gaussian Process Geostatistics Hierarchical Modeling Information Retrieval Systems Information Systems Kriging Markov Chain Monte Carlo Mathematical Models Models Oil Spills Regression Analysis Statistical Analysis

  More +
• ISSN:
  2398-7308
• Document Type:
  Text
• Funding:
  Grant
• Genre:
  Journal Article
• Place as Subject:
  California ; Maryland ; OSHA Region 3 ; OSHA Region 9 ; Virginia
• CIO:
  National Institute for Occupational Safety and Health (NIOSH)
• Topic:
  Workplace Safety & Health
• Location:
  North America
• Volume:
  62
• Issue:
  7
• NIOSHTIC Number:
  nn:20052161
• Citation:
  Ann Work Expo Health 2018 Aug; 62(7):818-827
• Contact Point Address:
  Sudipto Banerjee, Department of Biostatistics, University of California-Los Angeles, 650 Charles E. Young Drive South, Los Angeles, CA 91302, USA
• Email:
  sudipto@ucla.edu
• Federal Fiscal Year:
  2018
• Performing Organization:
  University of California, Los Angeles
• Peer Reviewed:
  True
• Start Date:
  20130901
• Source Full Name:
  Annals of Work Exposures and Health
• End Date:
  20170831
• Collection(s):
  National Institute for Occupational Safety and Health
• Main Document Checksum:
  urn:sha-512:a6725db809972124788774787be605e8c2ab67b04225dfa815119dfa8b88a28b14eb8c0490bf8462faf66a6b11edb810cd18a75d5020f4f13dbb03b27041928d
• Download URL:
  https://stacks.cdc.gov/view/cdc/211750/cdc_211750_DS1.pdf
• File Type:
  [PDF - 1.16 MB ]