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 thesis defense by Nestor Gualsaqui
On March 8th at 10:30 Nestor will present his M.Sc. thesis "Pre-crop emergence weed mapping using high satellite imagery". From the abstract: "During the last decades, the growth of the world population has been increasing and weather fluctuations around the world...
MSc defense Nils Karges
Nils Karges will present his M.Sc. thesis "Exploring spatial relationships of soundscape variables in urban areas. " on 15th of February at 9:30. From the abstract: "This work describes the relationship between soundscape and the underlying landscape in an urban...
MSc defense Camilo Zamora
On Friday 11th of February at 9am Camilo Zamora will present his M.Sc. thesis "Deforestation dynamics in the Dry Chaco ecoregion: a three decades of change detection and fragmentation study analysis". From the abtract: "Tropical forests represent 52% of global forests...
MSc idea and interesting presentations
on Friday 18th of February at 9am we will have the following presentations: Jakob Rieser - Thesis Idea: "A Synergistic Use of Optical and SAR Remote Sensing Data for the Long-term Evolution of Biocrusts and their Activity across diverse Dryland Ecosystems"....
Internship, inno lab and MSc. idea
On Monday 17th of January at 9am we will have the following presentations: Luisa Pflumm (MSc. idea presentation): "Assess silver-backed chevrotaindistribution in Nui Chua NP (Vietnam).", supervisors: Insa Otte, Andreas Wilting (IZW) Christopher Chan (Msc. idea...
Our EAGLEs featured on the University page
Our EAGLEs Sofia, Annika, Antonio, Andreas and Nils are featured on the University webpage with their UrbanSens idea of combining mobile IoT sensors and Earth Observation data for urban climate monitoring. Their success winning the DLR Copernicus challenge rewarded...
MSc defense by Yomna Eid
Yomna will present her M.Sc. thesis "Assessment of ESA CCI+ and NASA MODIS-LST in Ecological Transects of Australia" on January 14th 2022 at 10am. From the abstract: "Identifying the best-performing MODIS LST products available for scientific analysis is instrumental...
MSc defense by Marius Witt
Marius Witt will present his M.Sc. thesis "Investigating discharge dynamics at catchment level usingremote sensing timeseries" on Friday 14th of January 2022 at 9am. From the abstract: The anthropogenic induced climate change is one of the foremost challenges of the...
Our students won the DLR Copernicus challenge 2021!
Great to see again our EAGLE students winning the DLR Copernicus challenge. Last year Henrik Fisser won with his truck detection approach, this year our EAGLE students Sofia Garcia, Annika Ludwig, Nils Karges, Andreas Bury and Antonio Castaneda won the DLR Copernicus...
Great dashboard by our EAGLE students
our EAGLE students created various informative remote sensing and spatial environmental data dashboards and learned a lot how to communicate their Earth Observation research in an interactive online platform. One example by our student Ronald Okoth is shown below and...