Spatial Modeling and Prediction
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.
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 examples and individual project work
Various software programs will be used, but mainly OpenSource software such as R and GRASS.
Different techniques will be introduced and practically applied such as randomForest, GAM or MaxEnt
The theory and practice of spatial modeling with a focus on ecology and conservation
General Course News and Updates
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
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...read more
Our 2017 EAGLEs spend a great day at DLR-EOC close to Munich and learnt a lot about applied remote sensing. Beside talks about a variety of topics did the EAGLE students also have the chance to discuss in small groups with DLR scientists their research or...read more
Dr. Christian Hüttich started working in October as lecturer at the Department of Remote Sensing at the University of Würzburg. Christian is teaching applied Earth observation and digital image analyses & GIS in the EAGLE graduate program. Christian is further...read more
While the "old" EAGLEs are spending their 3rd term doing internships or innovation laboratories in Italy, Portugal, Poland or Burkina Faso at various research organizations or companies, the new EAGLEs for the winter term 2017/2018 will be welcomed next week. The...read more
The EAGLE course "Remote Sensing in Biodiversity and Conservation Science" took place in the last week of the summer term at the field research station in Fabrik Schleichach, Steigerwald. 20 biology and EAGLE students worked and lived together for one week and...read more