Upon successful completion of the requirements for this course, students will be able to:
- describe fundamental concepts, statistical models and techniques (e.g. autocorrelations) in temporal and spatiotemporal data analysis,
- implement solutions to real-world temporal and spatiotemporal analysis problems,
- describe and evaluate widely used temporal and spatiotemporal analysis algorithms,
- use existing functions and software packages (e.g. statsmodels) and develop their own code to automatically analyze time series and spatiotemporal data.
In pursuit of the “why” questions, the “when” and “where” questions often arise. Spatial data specify “where” and temporal instances specify “when” data is collected. The demand for spatiotemporal analysis is increasing due to the rapid growth and widespread collection of spatiotemporal data across various disciplines. Spatiotemporal analysis can illuminate any unusual patterns and interesting information or allow the study of persistence of patterns over time. |
This course is an introduction to the challenges and techniques to analyse spatiotemporal data, This course aims to provide students with the fundamental knowledge of spatiotemporal modelling. It will cover the similarities and differences in spatial and temporal data, techniques to visualize spatiotemporal data, linear methods to interpolate, extrapolate and smooth temporal and spatiotemporal data and linear generative models such as autoregression. Additional topics may include Markov and hidden Markov models.
Lectures will be complemented with interactive demonstrations and hands-on exercises to provide students with practical experience in spatiotemporal data analysis.
Students are required to submit at least 4 out of 6 resulting scripts from the practical session worksheets. These scripts will not be graded.
Individual Take Home Assignment:
The individual assignment counts for 40% of the grade
The final exam counts for 60% of the grade
“Due to limited capacity, this course is currently not open for external students.”