Hyperspectral Remote Sensing
field spectroscopy and image analysis
Spectroscopy and hyperspectral remote sensing enables to retrieve very detailed spectral information about a certain surface in dense bandwith intervalls. Information on the “spectral fingerprints” of surfaces is then available in a near-continuous manner. This allows for the differentiation of materials, such different geologic surfaces, different urban materials, or plants of different composition and vigor. Especially field- and laboratory spectroscopy has shown many benefits, as measurements can be carried out in a controlled environment, and can be directly visualized and explained. This course provides you insights into practical experiments using a field spectrometer, and subsequent data analysis to assess key environmental parameters such as plant health, soil moisture content, and geologic composition.
The content of this course includes both the theoretical background of field and imaging spectroscopy, as well as practical experiments and subsequent data analysis. In particular, we will adress: the theoretical background of field and imaging spectroscopy / general reflectance and transmittance properties of plant leaves, canopies and soils / the quantification of biophysical and biochemical properties using spectroscopic measurements, feature parametrization and regression analysis / the advantages and challenges of existing and planned hyperspectral spaceborne sensors
Coding examples and individual work will be covered
Various software programs will be used, but mainly OpenSource software such as R.
Different techniques will be introduced and practically applied.
The content of scientific with regard to the audience will be discussed.
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