Biodiversity and Ecosystem Service Modeling
Anthropogenic pressure on the environment leads to a significant loss of biodiversity and impacts the capacity of ecosystems to provide ecosystem services – the benefits people obtain from nature.
This module addresses how Earth observation data and geoinformation can be used for mapping and modeling biodiversity and ecosystem services with the aim to support better informed management decisions.
An introduction to the theoretical background of biodiversity and ecosystem service modeling as well as an overview of the current state-of-the-art will be given, complemented by brief presentations of the participants on selected topics. Focusing on practical examples (ranging from species distribution modeling to provisioning, regulating and cultural ecosystem services), the participants will learn how to analyze and integrate different Earth observation products in such models. All methods introduced and applied during the course will be based on the programming language R and other open source tools. This course is based on the skills obtained in the “Spatial Modeling and Prediction” course.
General Course News and Updates
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
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