Background

Data holds the answers to all manner of questions and analysis methods can extract those answers - linking the two is “data preparation”. Anyone interested in working with data will likely need to know at least some of the principles outlined.

Learning contents

An introduction to the preparation of data for analysis, beginning with the initial production or acquisition through to an analysis ready dataset. The specific case of image data will then be discussed in more detail using examples from satellite-based Earth Observation.

Learning objectives

An understanding of how to approach a new dataset and the typical steps that will be necessary in a variety of contexts. An insight into the preparation of image data and practical experience performing such tasks using Python.

Prior knowledge

Basic experience with programming on any language would be an advantage.

Technical requirements

• Own laptop

• Connection to Wifi via eduroam or equivalent access (see: https://www.uni-bremen.de/en/zfn/wifi/overview-wifi)

A software environment will be provided via the online tool Jupyther Hub; for local installation, participants will receive installation instructions prior to the workshop

The Lecturer(s)

Dr. Karl Kortum Karl Kortum is a Post-Doctoral Researcher at the German Aerospace Center (DLR).	Björn Tings Björn Tings Research Associate in the team of Synthetic Aperture Radar (SAR) oceanography at the Remote Sensing Technology Institute of German Aerospace Center (DLR) in Bremen.

Find out more about the Data Train lectures on our website.

This event is organized by