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“.
General Course News and Updates
courses on permafrost earth observation
What is the relevance of permafrost? What effects does the degradation of permafrost have on Arctic environments? How can satellite earth observation be utilized to monitor and quantify these effects? Addressing these questions was the focus of a recent hackathon week...
EAGLE applications and student statistics
We get constantly increasing number of applications and of course we are interested who is applying and who is actually starting our international Earth Observation MSc. program. The percentage of women in our study program did rise to around 80% while men...
Animal Movement and Remote Sensing course
How do animals move through the environment they live in? Which behavioural patterns can be observed when tracking an animals' movements for weeks, months or even years? Which spaces do they utilize and why? And how can remote sensing be used to predict the...
On Tuesday, March 28th at 13:00 p.m. Wilmer Fabián Montién Tique will present on his internship "Topographic and hydrographic factors for flood susceptibility analysis. By using WhiteboxTools geospatial data in Nigeria" at DLR via Zoom. On Tuesday, March 28th at...
Msc Defense by Reagan Okoth
On Monday, March 27th at 10:00 a.m. Ronald Reagan Okoth will present his M.Sc. theses “Fusing Remote Sensing Data: Application in Soil Temperature Prediction” in room 1.005 (Zentrales Hörsaal- und Seminargebäude). From the abstract: Understanding soil temperature (ST)...
Msc Proposal Presentation
On February 28th at 12:00 pm (room 1.005 Bib. Geb.) Rutendo Tadiwa Mukaratirwa will present her Msc proposal "Modelling the Spatio-temporal suitability of urban environments for Aedes Aegypti mosquitoes based on their bio-ecological characteristics in Rio de Janeiro"...
On February 28th at 13:00 (room 1.005 Bib. Geb.) Jyoti Biswas will present on her internship at the DLR: "Urbanization" Supervisor: Prof. Dr. Hannes Taubenböck
On February 24th at 10 a.m. (room 1.003 Z6 ) Ina Schulz, Caroline Göhner, and Svenja Dobelmann will present on their internship at the Kruger National Park/South Africa. Supervisors: Dr. Mirjana Bevanda and Dr. Martin Wegmann
MSc defense by Kemeng Liu
On Tuesday March 21st at 10 a.m. (room 1.003 Z6 ) Kemeng will present her M.Sc. thesis "Mapping Spatial-Temporal Development of Coastal Aquaculture Ponds using Landsat Archive". From the abstract: Aquaculture has become the global principal supply source of fish,...
Internship and Inno Lab Presentations
On Tuesday, 31st of January at 13 p.m. we will have the following presentations: Moritz Roesch: Spectral compositing for mapping bare soil areas and soil organic carbon estimation in Germany - Internship at RSS GmbH Lallu Nikerthil Prathapan: Landuse/ building type...