Spatial Modelling and Prediction

04-GEO-OMA1

Lecturer

Martin Wegmann

ECTS

5 ECTS

 

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

Coding examples and individual project work

Software

Various software programs will be used, but mainly OpenSource software such as R and GRASS.

Techniques

Different techniques will be introduced and practically applied such as randomForest, GAM or MaxEnt
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Content

The theory and practice of spatial modeling with a focus on ecology and conservation

General Course News and Updates

[spotlight] Lecturer Spotlight: Martin Wegmann

[spotlight] Lecturer Spotlight: Martin Wegmann

If you've ever sat in a Würzburg classroom learning how to wrangle satellite data, there's a good chance Martin Wegmann was the one standing at the front. He's been the driving force behind the EAGLE MSc program, the Applied Earth Observation degree at the University...

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EAGLE Internship Presentation: Svalbard

EAGLE Internship Presentation: Svalbard

On July 07, 2026, Aoibhin Murphy and Marlene Sehrbrock will present her internship results on " Svalbard" at 12:00 in seminar room 3, John-Skilton-Str. 4a. From the abstract: Using thermal and RGB imagery collected via UAVs, we investigated the potential of thermal...

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Successful MSc Defense by Anna Bischof

Successful MSc Defense by Anna Bischof

We congratulate Anna Bischof on the successful defense of her MSc thesis, "Feasibility of Unoccupied Aerial System-Based Active Fire Monitoring in African Savannas." Anna's research addressed one of the key challenges in fire ecology and remote sensing: understanding...

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