Creating Quasi-Maps for Uncovering Space-Time Patterns
For a set of geographically referenced time series, we generate a matrix arrangement with rows corresponding to linearized geographical positions and columns to time steps. This matrix is treated as a background map suitable for application of common methods for thematic data visualization. 2D spatial positions are transformed to 1D ordering of the matrix rows by means of one of existing methods for dimensionality reduction. We illustrate the approach by representing the dynamics of the COVID-19 pandemic and population mobility levels throughout the provinces of Spain
- Published in:
Abstracts of the ICA - Type:
Article - Authors:
Andrienko, Natalia; Andrienko, Gennady - Year:
2024
Citation information
Andrienko, Natalia; Andrienko, Gennady: Creating Quasi-Maps for Uncovering Space-Time Patterns, Abstracts of the ICA, 2024, 8, 3, https://ica-abs.copernicus.org/articles/8/3/2024/, Andrienko.Andrienko.2024b,
@Article{Andrienko.Andrienko.2024b,
author={Andrienko, Natalia; Andrienko, Gennady},
title={Creating Quasi-Maps for Uncovering Space-Time Patterns},
journal={Abstracts of the ICA},
volume={8},
pages={3},
url={https://ica-abs.copernicus.org/articles/8/3/2024/},
year={2024},
abstract={For a set of geographically referenced time series, we generate a matrix arrangement with rows corresponding to linearized geographical positions and columns to time steps. This matrix is treated as a background map suitable for application of common methods for thematic data visualization. 2D spatial positions are transformed to 1D ordering of the matrix rows by means of one of existing methods...}}
