The University of Southampton
University of Southampton Institutional Repository

Assessing uncertainty in estimates with ordinary and indicator kriging

Assessing uncertainty in estimates with ordinary and indicator kriging
Assessing uncertainty in estimates with ordinary and indicator kriging
The objective of this paper is to examine the applicability of three geostatistical approaches, ordinary kriging (OK), kriging with a trend model (KT), and indicator kriging (IK), to the assessment of uncertainty in estimates. This paper uses the OK and KT standard error and the conditional standard error of the conditional cumulative distribution function (ccdf) derived through IK to assess uncertainty in estimates of elevation. The mean OK and KT standard error and mean IK standard error, using data sampled from a remotely sensed digital terrain model (DTM), were used to ascertain the uncertainty in estimates. The estimates of elevation were assessed with reference to the complete DTM. Judgement on the success of the three approaches was made on the basis of the difference between the standard error of estimates and the mean kriging standard error. The mean OK and KT standard errors represent the standard error of estimation more accurately than the mean IK standard error, and OK (or KT) estimates of elevation values were more accurate than those for IK. Furthermore, IK may be significantly more costly to implement than OK (or KT) in terms of expenditure of time and effort. Also, the implementation of IK was demonstrated to be problematic in the presence of a low-frequency trend. A modified form of IK was also employed whereby the thresholds for estimation of the ccdfs were adapted locally in the basis of the available observations. This approach markedly reduced the problems encountered with IK employing fixed (global) thresholds. IK with locally adaptive indicator thresholds provided a more accurate guide to uncertainty on a local basis than OK or KT. It is suggested that IK recommended for the assessment of uncertainty in estimates locally where the estimation of accuracy of a specified will need to be implemented with a trend model to further improve results.
929-937
Lloyd, C.D.
2d3bd538-2045-4fbb-900c-9f77c386bbc9
Atkinson, P.M.
aaaa51e4-a713-424f-92b0-0568b198f425
Lloyd, C.D.
2d3bd538-2045-4fbb-900c-9f77c386bbc9
Atkinson, P.M.
aaaa51e4-a713-424f-92b0-0568b198f425

Lloyd, C.D. and Atkinson, P.M. (2001) Assessing uncertainty in estimates with ordinary and indicator kriging. Computers & Geosciences, 27 (8), 929-937. (doi:10.1016/S0098-3004(00)00132-1).

Record type: Article

Abstract

The objective of this paper is to examine the applicability of three geostatistical approaches, ordinary kriging (OK), kriging with a trend model (KT), and indicator kriging (IK), to the assessment of uncertainty in estimates. This paper uses the OK and KT standard error and the conditional standard error of the conditional cumulative distribution function (ccdf) derived through IK to assess uncertainty in estimates of elevation. The mean OK and KT standard error and mean IK standard error, using data sampled from a remotely sensed digital terrain model (DTM), were used to ascertain the uncertainty in estimates. The estimates of elevation were assessed with reference to the complete DTM. Judgement on the success of the three approaches was made on the basis of the difference between the standard error of estimates and the mean kriging standard error. The mean OK and KT standard errors represent the standard error of estimation more accurately than the mean IK standard error, and OK (or KT) estimates of elevation values were more accurate than those for IK. Furthermore, IK may be significantly more costly to implement than OK (or KT) in terms of expenditure of time and effort. Also, the implementation of IK was demonstrated to be problematic in the presence of a low-frequency trend. A modified form of IK was also employed whereby the thresholds for estimation of the ccdfs were adapted locally in the basis of the available observations. This approach markedly reduced the problems encountered with IK employing fixed (global) thresholds. IK with locally adaptive indicator thresholds provided a more accurate guide to uncertainty on a local basis than OK or KT. It is suggested that IK recommended for the assessment of uncertainty in estimates locally where the estimation of accuracy of a specified will need to be implemented with a trend model to further improve results.

Text
Lloyd_&_Atkinson_C&G_2001.pdf - Other
Restricted to Registered users only
Download (262kB)

More information

Published date: 2001

Identifiers

Local EPrints ID: 16175
URI: http://eprints.soton.ac.uk/id/eprint/16175
PURE UUID: 14330d73-f5ac-4e9c-8da6-c7bfff4fdb40

Catalogue record

Date deposited: 06 Jul 2005
Last modified: 15 Mar 2024 05:46

Export record

Altmetrics

Contributors

Author: C.D. Lloyd
Author: P.M. Atkinson

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×