Assessment of error in air quality models using dynamic time warping

Jessica Lin; Guido Cervone; Pasquale Franzese

doi:10.1145/1869890.1869895

Assessment of error in air quality models using dynamic time warping

Jessica Lin, Guido Cervone, Pasquale Franzese

Geography

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

3 Scopus citations

Abstract

An estimate of the error between the mean concentration of a released pollutant simulated by an atmospheric dispersion model and the values measured at the ground is obtained using Dynamic Time Warping (DTW). The error measure is relevant to the application with iterative source detection algorithms based on forward numerical transport and dispersion simulations. The new proposed measure is compared with two established error functions commonly used in the literature. A sensitivity study of the error measure to wind direction was performed using real world data from the Prairie Grass field experiment. Whereas both standard measures found smallest error only with a few degrees of wind direction, DTW found the smallest error with a much larger range of wind directions, often as high as 20 degrees.

Original language	English (US)
Title of host publication	Proc. of the 1st ACM SIGSPATIAL Int. Workshop on Data Mining for Geoinformatics, DMG 2010, offered under the auspices of the 18th Int. Conference on Advances in Geographic Information Systems, ACMGIS
Pages	38-44
Number of pages	7
DOIs	https://doi.org/10.1145/1869890.1869895
State	Published - 2010
Event	1st ACM SIGSPATIAL International Workshop on Data Mining for Geoinformatics, DMG 2010, offered under the auspices of the 18th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, GIS'10 - San Jose, CA, United States Duration: Nov 2 2010 → Nov 2 2010

Publication series

Name	Proc. of the 1st ACM SIGSPATIAL Int. Workshop on Data Mining for Geoinformatics, DMG 2010, offered under the auspices of the 18th Int. Conference on Advances in Geographic Information Systems, ACMGIS

Other

Other	1st ACM SIGSPATIAL International Workshop on Data Mining for Geoinformatics, DMG 2010, offered under the auspices of the 18th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, GIS'10
Country/Territory	United States
City	San Jose, CA
Period	11/2/10 → 11/2/10

All Science Journal Classification (ASJC) codes

Computer Science Applications
Information Systems
Geography, Planning and Development

Access to Document

10.1145/1869890.1869895

Cite this

Lin, J., Cervone, G., & Franzese, P. (2010). Assessment of error in air quality models using dynamic time warping. In Proc. of the 1st ACM SIGSPATIAL Int. Workshop on Data Mining for Geoinformatics, DMG 2010, offered under the auspices of the 18th Int. Conference on Advances in Geographic Information Systems, ACMGIS (pp. 38-44). (Proc. of the 1st ACM SIGSPATIAL Int. Workshop on Data Mining for Geoinformatics, DMG 2010, offered under the auspices of the 18th Int. Conference on Advances in Geographic Information Systems, ACMGIS). https://doi.org/10.1145/1869890.1869895

Lin, Jessica ; Cervone, Guido ; Franzese, Pasquale. / Assessment of error in air quality models using dynamic time warping. Proc. of the 1st ACM SIGSPATIAL Int. Workshop on Data Mining for Geoinformatics, DMG 2010, offered under the auspices of the 18th Int. Conference on Advances in Geographic Information Systems, ACMGIS. 2010. pp. 38-44 (Proc. of the 1st ACM SIGSPATIAL Int. Workshop on Data Mining for Geoinformatics, DMG 2010, offered under the auspices of the 18th Int. Conference on Advances in Geographic Information Systems, ACMGIS).

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title = "Assessment of error in air quality models using dynamic time warping",

abstract = "An estimate of the error between the mean concentration of a released pollutant simulated by an atmospheric dispersion model and the values measured at the ground is obtained using Dynamic Time Warping (DTW). The error measure is relevant to the application with iterative source detection algorithms based on forward numerical transport and dispersion simulations. The new proposed measure is compared with two established error functions commonly used in the literature. A sensitivity study of the error measure to wind direction was performed using real world data from the Prairie Grass field experiment. Whereas both standard measures found smallest error only with a few degrees of wind direction, DTW found the smallest error with a much larger range of wind directions, often as high as 20 degrees.",

author = "Jessica Lin and Guido Cervone and Pasquale Franzese",

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doi = "10.1145/1869890.1869895",

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pages = "38--44",

booktitle = "Proc. of the 1st ACM SIGSPATIAL Int. Workshop on Data Mining for Geoinformatics, DMG 2010, offered under the auspices of the 18th Int. Conference on Advances in Geographic Information Systems, ACMGIS",

note = "1st ACM SIGSPATIAL International Workshop on Data Mining for Geoinformatics, DMG 2010, offered under the auspices of the 18th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, GIS'10 ; Conference date: 02-11-2010 Through 02-11-2010",

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Lin, J, Cervone, G & Franzese, P 2010, Assessment of error in air quality models using dynamic time warping. in Proc. of the 1st ACM SIGSPATIAL Int. Workshop on Data Mining for Geoinformatics, DMG 2010, offered under the auspices of the 18th Int. Conference on Advances in Geographic Information Systems, ACMGIS. Proc. of the 1st ACM SIGSPATIAL Int. Workshop on Data Mining for Geoinformatics, DMG 2010, offered under the auspices of the 18th Int. Conference on Advances in Geographic Information Systems, ACMGIS, pp. 38-44, 1st ACM SIGSPATIAL International Workshop on Data Mining for Geoinformatics, DMG 2010, offered under the auspices of the 18th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, GIS'10, San Jose, CA, United States, 11/2/10. https://doi.org/10.1145/1869890.1869895

Assessment of error in air quality models using dynamic time warping. / Lin, Jessica; Cervone, Guido; Franzese, Pasquale.
Proc. of the 1st ACM SIGSPATIAL Int. Workshop on Data Mining for Geoinformatics, DMG 2010, offered under the auspices of the 18th Int. Conference on Advances in Geographic Information Systems, ACMGIS. 2010. p. 38-44 (Proc. of the 1st ACM SIGSPATIAL Int. Workshop on Data Mining for Geoinformatics, DMG 2010, offered under the auspices of the 18th Int. Conference on Advances in Geographic Information Systems, ACMGIS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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AB - An estimate of the error between the mean concentration of a released pollutant simulated by an atmospheric dispersion model and the values measured at the ground is obtained using Dynamic Time Warping (DTW). The error measure is relevant to the application with iterative source detection algorithms based on forward numerical transport and dispersion simulations. The new proposed measure is compared with two established error functions commonly used in the literature. A sensitivity study of the error measure to wind direction was performed using real world data from the Prairie Grass field experiment. Whereas both standard measures found smallest error only with a few degrees of wind direction, DTW found the smallest error with a much larger range of wind directions, often as high as 20 degrees.

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Lin J, Cervone G, Franzese P. Assessment of error in air quality models using dynamic time warping. In Proc. of the 1st ACM SIGSPATIAL Int. Workshop on Data Mining for Geoinformatics, DMG 2010, offered under the auspices of the 18th Int. Conference on Advances in Geographic Information Systems, ACMGIS. 2010. p. 38-44. (Proc. of the 1st ACM SIGSPATIAL Int. Workshop on Data Mining for Geoinformatics, DMG 2010, offered under the auspices of the 18th Int. Conference on Advances in Geographic Information Systems, ACMGIS). doi: 10.1145/1869890.1869895

Assessment of error in air quality models using dynamic time warping

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