Aim:
Within this course different methods to analyse point pattern statistically and conduct a spatial prediction are covered. Students will learn how to design such analysis, how to avoid caveats, troubleshoot errors and interpret the results.
Content
Different statistical methods will be applied for analysing spatial point patterns, such as vegetation samples or biodiversity related information. These results will be statistically predicted using methods such as GLM, GAM, Random Forest or MaxEnt. Implications of spatial point patterns as well as chosen environmental parameters will be discussed. All methods will be practically applied during the course using the programming language R. The needed pre-requisites are covered in the course “Applied Programming for Remote Sensing and GIS“.
Coding
Software
Techniques
Content
General Course News and Updates
EAGLE students learn remote sensing field work
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...
MSc thesis started by Jakob Schwalb-Willmann
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...
EAGLE students coding with sweets
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...
Final presentations of the remote sensing programming course
The final project presentations of the spatial coding course by the EAGLE students revealed quite some impressive analysis achieved within the last couple of months. All analysis were done using R and presentations created within R using knitr. The aim was to run a...
internship and innovation laboratory presentations
The following internship and innovation laboratory projects were presented today: Karsten Wiertz did his internship at the Białowieza national park on "Spatio-temporal analysis of tree mortality and gaps in the Białowieza Forest using high resolution imagery". Jakob...
Spatial Python block course
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...
Interdisciplinary course in the Bavarian Forest
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...
One week courses on hyperspectral and time-series analysis
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...
Urban Geography Course by Hannes Taubenböck
Hannes Taubenböck from DLR discussed with our EAGLE students the application of remote sensing applications within urban research.
Scientific Presentation of Earth Observation Applications
As every term our students could participated in a scientific presentation course where they learned how to prepare, design and defend a scientific talk. Beside the theoretical part many practical exercises were part of this course and a final presentation in a large...