Benchmarking Knowledge-assisted Kriging for Automated Spatial Interpolation of Wind Measurements


Zlatev, Zlatko, Middleton, Stuart and Veres, Galina (2010) Benchmarking Knowledge-assisted Kriging for Automated Spatial Interpolation of Wind Measurements. In, Fusion 2010, Edinburgh, (Submitted).

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Description/Abstract

Abstract - We have benchmarked a novel knowledge-assisted kriging algorithm that allows regions of spatial cohesion to be specified and variograms calculated for each region. The variogram calculation itself is automated and spatial regions are created via offline automated segmentation of either expert-drawn Google Earth polygons or NASA altitude data. Our use-case is to create wind interpolation grids for input into a bathing water quality model of microbial contamination. We benchmark our knowledge-assisted kriging algorithm against 7 other algorithms on UK met-office wind data (189 sensors). Our wind estimation results are comparable, but not better than ordinary kriging, but the kriging error maps are much sharper and reflect the known spatial features better. These results are very promising when considering it is an automated approach and allows on-demand datasets to be selected and thus real-time interpolation of previously unknown measurements. Automation is important in progressing towards a pan-European interpolation service capability.

Item Type: Conference or Workshop Item (Paper)
Additional Information: Event Dates: July 2010
ISBNs: 9780982443811
Keywords: Data Fusion, Kriging, Spatial Interpolation, Wind Speed, Wind Direction, OGC, WPS
Divisions: Faculty of Physical Sciences and Engineering > Electronics and Computer Science
Faculty of Physical Sciences and Engineering > Electronics and Computer Science > IT Innovation Centre
ePrint ID: 272320
Date Deposited: 24 May 2011 12:48
Last Modified: 27 Mar 2014 20:18
Further Information:Google Scholar
URI: http://eprints.soton.ac.uk/id/eprint/272320

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