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Spatio-temporal Data Analysis

Summary

The aim of this course is to present the processing of spatiotemporal data. The introductory part of the course presents the problems of time series and selected methods of their visualization, analysis and modeling (decomposition, regression models, exponential models, ARIMA and SARIMA). Furthermore, key aspects of spatiotemporal data and methods of their exploratory analysis are presented. Methods of analysis of spatiotemporal data and spatiotemporal clustering are presented, which form a key part of this course. Lectures are also devoted to the issue of visualization of spatiotemporal data.

Literature

KULLDORFF, M. SaTScan User Guide. 2021. 119 p. http://www.satscan.org/
SHMUELI, G., LICHTENDAHL, K.C. Practical Time Series Forecasting with R: A Hands-On Guide, Axelrod Schnall Publishers, 2nd edition, 2016, ISBN 978-0997847918 .
SHI, Z., PUN-CHENG, L.S.C. Spatiotemporal Data Clustering: A Survey of Methods. ISPRS International Journal of Geo-Information, 2019, 8, 112; doi:10.3390/ijgi8030112.
ROGERSON, P., YAMADA, I. Statistical Detection and Surveillance of Geographic Clusters. Chapman and Hall/CRC, 2008, 324 p.

Advised literature

CRESSIE, N., WINKLE, C.K. Statistics for Spatio-Temporal Data. Wiley, 2011, 624 p.
SHERMAN, M. Spatial Statistics and Spatio-Temporal Data: Covariance Functions and Directional Properties. Wiley, 2010, 294 p.
LEVINE, N. CrimeStat: A Spatial Statistics Program for the Analysis of Crime Incident Locations (v 4.02). Ned Levine & Associates, Houston, Texas, and the National Institute of Justice, Washington, D.C. August. 2015.
ANSARI, M.Y., AHMAD, A., KHAN, S.S., BHUSHAN, G., MAINUDDIN. Spatiotemporal clustering: a review. Artificial Intelligence Review, 2020, 53:2381–2423, https://doi.org/10.1007/s10462-019-09736-1.


Language of instruction čeština, angličtina
Code 548-0952
Abbreviation CSAD
Course title Spatio-temporal Data Analysis
Coordinating department Department of Geoinformatics
Course coordinator prof. Ing. Igor Ivan, Ph.D.