Preprint Article Version 1 This version is not peer-reviewed

Visualization of the Strain-rate State of a Data Cloud: Analysis of the Temporal Change of an Urban Multivariate Description

Version 1 : Received: 10 June 2019 / Approved: 13 June 2019 / Online: 13 June 2019 (08:18:30 CEST)

A peer-reviewed article of this Preprint also exists.

Salazar-Llano, L.; Bayona-Roa, C. Visualization of the Strain-Rate State of a Data Cloud: Analysis of the Temporal Change of an Urban Multivariate Description. Appl. Sci. 2019, 9, 2920. Salazar-Llano, L.; Bayona-Roa, C. Visualization of the Strain-Rate State of a Data Cloud: Analysis of the Temporal Change of an Urban Multivariate Description. Appl. Sci. 2019, 9, 2920.

Journal reference: Appl. Sci. 2019, 9, 2920
DOI: 10.3390/app9142920

Abstract

One challenging problem is the representation of three-dimensional datasets that vary with time. These datasets can be though as a cloud of points that gradually deforms. But point-wise variations lack of information about the overall deformation pattern, and more importantly, about the extreme deformation locations inside the cloud. The present article applies a technique in computational mechanics to derive the strain-rate state of a time-dependent and three-dimensional data distribution, by which one can characterize its main trends of shift. Indeed, the tensorial analysis methodology is able to determine the global deformation rates in the entire dataset. With the use of this technique, one can characterize the significant fluctuations in a reduced multivariate description of an urban system and identify the possible causes of those changes: calculating the strain-rate state of a PCA-based multivariate description of an urban system, we are able to describe the clustering and divergence patterns between the districts of the city and to characterize the temporal rate in which those variations happen.

Subject Areas

dimensionality reduction; pattern identification; three-dimensional data-cloud; strain-rate; Finite Element Method (FEM); trajectory visualization

Comments (0)

We encourage comments and feedback from a broad range of readers. See criteria for comments and our diversity statement.

Leave a public comment
Send a private comment to the author(s)
Views 0
Downloads 0
Comments 0
Metrics 0


×
Alerts
Notify me about updates to this article or when a peer-reviewed version is published.