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
Our new EAGLEs arrived! We welcomed our new international EAGLE students from the US, Ecuador, Bangladesh, Ruanda or Germany for the upcoming winter term and introduced the lectures as well as the courses. In the evening we had a joint dinner to get to...read more
On Monday, 24th of September from 1:30 onwards the following EAGLE students will present their M.Sc. idea. Everybody is welcome to join their presentations and to provide feedback: Julia: "Time-Series Analysis of Sentinel-1 and Sentinel-2...read more
On Monday, 24th of September, at 1pm the following internship reports will be presented: Bharath: "Installation and Characterization of an imaging Spectrometer for the UAV-based remote sensing" Johannes: "Crop classification based on S1/S2 in...read more
Pilar Endara started her M.Sc. thesis on "Time series analysis of flooding and vegetation patterns in wetlands of the Colombian Orinoco Basin" The ecosystems that are present within Colombian Orinoquia flooded savannas are currently being threatened by conversion of...read more
The following students presented their innovation labs, internships and ideas for MSc. thesis: Ahmed: Innovation Lab at DLR (team of Ursula Gessner) and Master Thesis Idea: Title: Status of Agricultural Lands in Egypt using Earth Observation Maninder (at DLR,...read more
Our 2018 EAGLE summer dialogue took place last Friday, 22nd of June and was a great place to meet all students, lectures, staff of the department and quite some external guests from all around Europe.read more
Today some of our EAGLE students presented their internship and innovation laboratory projects. Very interesting topics and they obviously applied and deepened their remote sensing knowledge a lot. Julia Sauerbrey: Prediction of Organic Matter Content from Sentinel-2...read more
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