Department news: summary of February 2018

Department news: summary of February 2018

February 28, 2018

image kindly provided by Marius Philipp

In February, the winter term 2017/18 ended, and here is a short summary on our teaching activities.

degree programms

courses given

students taught

The department is involved in 3 degree programs on geography at the University of Würzburg and in the “Global Change Ecology M.Sc.” graduate program of the Universities Bayreuth, Würzburg and Augsburg within the Elitenetwork of Bavaria.

Within the bachelor’s program “Geography”, 183 students visited our lecture on “Introduction to geographical Remote Sensing”. Our tutors Jana Maier, Florian Baumgartner, Patrick Horst and Jakob Rieser accompanied the lecture with weekly tutorials.

This term, 22 BSc students chose “Remote Sensing” as a minor. The course “Methods for Analysing Remote Sensing Data” essentially conveys methodological basics: data download, geometric and radiometric corrections, spatial and spectral filters, image enhancement, analysis of spectral profiles, information extraction (rationing, indices, transformations), classification of remote sensing imagery, accuracy assessment and change analysis. Learning about the joint usage of remote sensing data with other geoinformation in geographical information systems, the participants now can apply fundamental methods for the processing and analysis of optical EO data. They gave talks on different methods of data analysis and how to perform them in ENVI. Their tutor Leon Nill encouraged and supported the students and they are now busy carrying out change detection analysis on a topic of their choice using open geodata such as Landsat or Sentinel-2.

Within the master programes Applied Physical Geography and Applied Human Geography 13 students learned how to characterize the earth’s surface by assessing remotely sensed parameters. Landscape analysis with a focus on forests were performed and (inter)national assessment approaches, monitoring methods and programs were discussed.

For our 17 first year EAGLE students, the semester isn’t finished yet, too. Specialization courses on Remote Sensing in Urban Geography and Hyperspectral Remote Sensing have been held, a course on Remote Sensing Time Series is ongoing. We’d like to thank our EAGLE lecturers and colleagues from DLR Dr. Hannes Taubenböck, Dr. Martin Bachmann and Dr. Andreas Dietz for their contribution and diverse coursework!

The EAGLE students starting in winter term 2016/17 are scattered all over the world working as interns at different host institutions or carrying out their innovation Laboratory.

The summer term 2018 will start in April and we offer 12 lectures and seminars given by the members of our department and additional 4 seminars in the EAGLE programme held by Dr. Nikola Koglin, PD Dr. Claudia Künzer, Prof. Dr. Hartwig Frimmel and Dr. Tobias Ullmann. We are looking forward to interesting talks and discussions about remote sensing and geography!

you may also like:

A Glimpse into Our Research: Data on Display in the Foyer

A Glimpse into Our Research: Data on Display in the Foyer

Stepping into the foyer, visitors are now greeted by large, striking images that tell the story of our research through data. Each visual represents a unique scientific perspective – from the Arctic to the cultivated landscapes of Bavaria, and from forest canopies to...

Successful MSc defense by Sonja Maas

Successful MSc defense by Sonja Maas

Big congratulations to Sonja Maas, who successfully defended her Master thesis today on the highly relevant and increasingly pressing topic: LiDAR-Based Acquisition Strategies for Forest Management Planning in a Mature Beech Stand Supervised by Dr. Julian Fäth and...

Visit at the Institute for Geoinformatics (IFGI) at University of Münster

Visit at the Institute for Geoinformatics (IFGI) at University of Münster

Two days ago, our PostDoc Dr. Jakob Schwalb-Willmann visited the Institute for Geoinformatics at University of Münster to give a talk at IFGI’s GI Forum titled “Can animals be used to classify land use? Employing movement-tracked animals as environmental informants using deep learning”.