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Increased accuracy of geostatistical prediction of nitrogen dioxide in the United Kingdom with secondary data

Increased accuracy of geostatistical prediction of nitrogen dioxide in the United Kingdom with secondary data
Increased accuracy of geostatistical prediction of nitrogen dioxide in the United Kingdom with secondary data
Five techniques were used to map nitrogen dioxide (NO2) concentrations in the United Kingdom. The methods used to predict from point data, collected as part of the UK NO2 diffusion tube network, were local linear regression (LR), inverse distance weighting (IDW), ordinary kriging (OK), simple kriging with a locally varying mean (SKlm) and kriging with an external drift (KED). These techniques may be divided into two groups: (i) those that use only a single variable in the prediction process (IDW, OK) and (ii) those that make use of additional variables as a part of prediction (LR, SKlm and KED). Nitrous oxides emission data were used as secondary data with LR, SKlm and KED. It was concluded that SKlm provided the most accurate predictions based on the summary statistics of prediction errors from cross-validation.
NO2 mapping, NOx emissions, local regression, kriging
0303-2434
293-305
Lloyd, C.D.
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Atkinson, P.M.
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Lloyd, C.D.
2d3bd538-2045-4fbb-900c-9f77c386bbc9
Atkinson, P.M.
aaaa51e4-a713-424f-92b0-0568b198f425

Lloyd, C.D. and Atkinson, P.M. (2004) Increased accuracy of geostatistical prediction of nitrogen dioxide in the United Kingdom with secondary data. International Journal of Applied Earth Observation and Geoinformation, 5 (4), 293-305. (doi:10.1016/j.jag.2004.07.004).

Record type: Article

Abstract

Five techniques were used to map nitrogen dioxide (NO2) concentrations in the United Kingdom. The methods used to predict from point data, collected as part of the UK NO2 diffusion tube network, were local linear regression (LR), inverse distance weighting (IDW), ordinary kriging (OK), simple kriging with a locally varying mean (SKlm) and kriging with an external drift (KED). These techniques may be divided into two groups: (i) those that use only a single variable in the prediction process (IDW, OK) and (ii) those that make use of additional variables as a part of prediction (LR, SKlm and KED). Nitrous oxides emission data were used as secondary data with LR, SKlm and KED. It was concluded that SKlm provided the most accurate predictions based on the summary statistics of prediction errors from cross-validation.

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Published date: 2004
Keywords: NO2 mapping, NOx emissions, local regression, kriging

Identifiers

Local EPrints ID: 15771
URI: http://eprints.soton.ac.uk/id/eprint/15771
ISSN: 0303-2434
PURE UUID: 015ef3f1-b473-4c28-a5d3-983ad8b0f95b

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Date deposited: 01 Jun 2005
Last modified: 15 Mar 2024 05:43

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Contributors

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

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