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
MSc defense by Katrin Hasenbein
Katrin Hasenbein will defend her M.Sc. thesis on Thursday 12am on "The potential to enhance land use mapping by leveraging processing methods of time series data". from the abstract: "With the launch of the twin satellites of Sentinel-2 time series data with a high...
2020 applications
We received again a high number of very good applicants and are currently working through all application files. We will invite all eligible applicants in the next weeks for an interview. In total we received 137 eligible applications from the EU as well as North and...
MSc idea presentation by Aida Taghavi
Aida will present on Friday, May 22nd at 2:30pm her MSc idea "Potentials of Cosmic-Ray Neutron Probes for Assessing and Mapping SAR-based Soil Moisture in a Mediterranean agro-forestry ecosystem by developing an integrated ground- and space-based Modelling Framework"....
Sebastian Buchelt successfully presented his MSc thesis
Sebastian Buchelt successfully presented his MSc thesis - congratulations! Read more about his research project here.
MSc defense by Sebastian Buchelt
Sebastian Buchelt will present his M.Sc. thesis "Analysis of High-Resolution Spatio-Temporal Patterns of Snowmelt using Orthorectified Photo Cameras, Sentinel-1 Time Series and Digital Elevation Data" in a virtual course room. From the abstract: " Snow is one of the...
Successful virtual MSc defense by Silvan Steiner
Congratulation to Silvan Steiner, our first EAGLE passing with a virtual MSc defense!
MSc defense by Silvan Steiner
On Thursday at 10am Silvan Steiner will present his M.Sc. thesis "Assessing the Potential of a Land Cover Dependent Snow Cover Detection Algorithm for the Global SnowPack". Due to the Covid19 situation his defense will be in a virtual course room. Everybody is invited...
Covid-19 situation and EAGLE
The Covid-19 situation is also challenging for the University as well as the EAGLE program. Even though we are all in the process to adapt to this new situation, the program itself is continuing as usual. All courses, exams, MSc thesis defense and so on will take...
new book by our lecturer “Intro to Spatial Data Analysis”
The upcoming book by our lecturer Jakob Schwalb-Willmann, Stefan Dech and Martin Wegmann on "Introduction to Spatial Data Analysis" with QGIS and first steps in R is available for pre-order - order now and get 30% discount. This textbook aims at students and...
M.Sc. defense by Benjamin Lee
Benjamin will defend his M.Sc. thesis " DEVELOPMENT OF A SEMI-ANALYTICAL MODEL FOR SEAGRASS MAPPING USING CLOUD-BASED COMPUTING AND OPEN SOURCED OPTICAL SATELLITE DATA" on Friday March 6th 10 am in room 1.009 OKW 86. from the abstract: "Seagrasses provide USD$2.28...