LFU:online

Understanding fundamental principles and applications of remote sensing time series
Ability to access, handle and process remote sensing time series
Knowledge and understanding of concepts and methods for information extraction from remote sensing time series (e.g., classification, machine learning, change detection)

The course covers the theoretical background and practical examples of methods used for information extraction from remote sensing time series. Using various datasets and applications, the entire processing chain is demonstrated and practised: From accessing and processing of multitemporal data to validation and accuracy assessment of the final products.

Analysis and processing methods of remote sensing
Scripting with Python
Use of e-learning material (with interactive tutorials)
Use of open-source software

Course examination according to § 7, statute section on "study-law regulations"

Lillesand, T. M., R. W. Kiefer, & J. W. Chipman (2015). Remote sensing and image interpretation. 7th ed., John Wiley & Sons.
Künzer, C., Dech, S., & Wagner, W. (2015). Remote sensing time series - Revealing land surface dynamics, Springer, https://doi.org/10.1007/978-3-319-15967-6

Recommended requirements:
Fundamental knowledge of geographic information systems and geoinformatics
Basic skills in scripting with Python (e.g., VU Python for Geographers)