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November 2003 Spatial Statistics in the Presence of Location Error with an Application to Remote Sensing of the Environment
Noel Cressie, John Kornak
Statist. Sci. 18(4): 436-456 (November 2003). DOI: 10.1214/ss/1081443228

Abstract

Techniques for the analysis of spatial data have, to date, tended to ignore any effect caused by error in specifying the spatial locations at which measurements are recorded. This paper reviews the methods for adjusting spatial inference in the presence of data-location error, particularly for data that have a continuous spatial index (geostatistical data). New kriging equations are developed and evaluated based on a simulation experiment. They are also applied to remote-sensing data from the Total Ozone Mapping Spectrometer instrument on the Nimbus-7 satellite, where the location error is caused by assignment of the data to their nearest grid-cell centers. The remote-sensing data measure total column ozone (TCO), which is important for protecting the Earth's surface from ultraviolet and other radiation.

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Noel Cressie. John Kornak. "Spatial Statistics in the Presence of Location Error with an Application to Remote Sensing of the Environment." Statist. Sci. 18 (4) 436 - 456, November 2003. https://doi.org/10.1214/ss/1081443228

Information

Published: November 2003
First available in Project Euclid: 8 April 2004

zbMATH: 1055.62104
MathSciNet: MR2059325
Digital Object Identifier: 10.1214/ss/1081443228

Rights: Copyright © 2003 Institute of Mathematical Statistics

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Vol.18 • No. 4 • November 2003
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