Remote Sensing in Biodiversity and Conservation Science
project work in the Steigerwald
Within this course different options for continuous data acquisition for biodiversity research and conservation using remote sensing are covered. New and established methods and data sets are introduced and student can explore them on their own. The whole course will take place in the Nationalpark Bavarian Forest or the Steigerwald.
Different field sampling strategies will be practically experienced such as LCCS, hemispherical measurements or LAI, as well as existing zoological and botanical data sets explored and linked to remote sensing data sets. Especially LiDAR and hyperspectral data sets, beside multispectral remote sensing data are used to explain the spatial patterns of the biodiversity data. Students will need to develop their own research plan including questions and hypothesis and have to present it on the last day of the course. The course covers several consecutive days in the study area where all remote sensing data analysis, statistical modeling and field work need to be achieved. This courses requires a sounds knowledge of programming and modeling which are covered by previous courses. The course will be tightly linked to a parallel course for biologists and joint projects as well as interdisciplinary discussions and challenges are envisioned.
learning how to collect field data
learning how to plan field work.
learn how to apply coding for your specific research question
present your research findings to your fellow students
General Course News and Updates
the application deadline for our next term of the international M.Sc. program EAGLE “applied Earth Observation and Geoanalysis of the Living Environment” is approaching. Application for the upcoming winter term are accepted until May 15thread more
The course "from field work to spatial data" by Tobias Ullmann and Martin Wegmann is covering the whole range of field campaign planning and especially training all necessary methods such as GPS handling, coordinate systems, setting waypoints or finding locations. In...read more
Jakob Schwalb-Willmann just started his M.Sc. thesis titled "A deep learning movement prediction model using environmental data to identify movement anomalies". He will combine animal movement and remote sensing data in order to develop a generic, data-driven DL-based...read more
Today our EAGLE students applied data munging, pipes, plotting and statistics using colour distribution of sweets. They specifically used the dplyr, ggplot, kableExtra and others to compute derivatives, rearrange the data, plot it and run statistics on colour...read more
Last week Steven Hill and Thorsten Dahms gave a course that introduced EAGLE students to Python-based spatial data analysis. The advantages and challenges of different python libraries, data sets and methods were covered in hands-on exercises and also discussed...read more
The Bavarian Forest and the Bohemian Forest together form the largest contiguous forest area in central Europe, which is of an extraordinary importance for the protection and maintenance of biological diversity. Since 1970, a large area of the forest is protected as a...read more
In the past few weeks various block courses by colleagues from DLR have taken place. Divers topics how remote sensing can be used, which methods have to be applied and how to put it into practice were covered by our colleagues Hannes Taubenböck, Martin Bachmann and...read more
Hannes Taubenböck from DLR discussed with our EAGLE students the application of remote sensing applications within urban research.read more