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 Moritz Rösch
On Tuesday, November 27 at 12:00 a.m., 2023 Moritz Rösch will present his MSc defense “Daily spread prediction of European wildfires based on historical burned area time series from Earth observation data using spatio-temporal graph neural networks” in the seminar...
Internship Report
On Tuesday, December 12, 2023 at 12:00 a.m. Sunniva McKeever, Maximilian Merzdorf, and Isabella Metz will present their internship report on their internship at the Kruger National Park, South Africa in seminar room 3 in John-Skilton-Str. 4a/ground floor Subject: "Our...
Internship Report by Christobal Tobbin
On Tuesday, November 28, 2023 at 13:00 Christobal Tobbin will present his internship report on his internship at DLR “The CONCERT Project” in seminar room 3 in John-Skilton-Str. 4a/ground floor. From the abstract: The CONCERT project with the Agriculture and...
Successful MSc defense by Giovanni Matabishi
Giovanni presented his MSc thesis “Modelling Bat Distribution and Diversity with Artificial light as a Focal Predictor in South Tyrol” today within our EAGLE colloquium and passed successfully. He presented very interesting approaches of remote sensing for modelling...
EAGLE 8th generation – first course by Claudia Kuenzer
Our new EAGLEs just spend the whole week learning about all Earth Observation sensors, physics of remote sensing, newest advances and upcoming methods in earth observation. Beside the lecture and getting to know all these crucial information they also had plenty of...
Internship Report by Janik Hoffmann and Lena Jäger
On Tuesday, December 19, 2023 at 12:00 Janik Hoffmann and Lena Jäger will present their internship report on their internship at the University Centre on Svalbard/Norway "Our Arctic Adventure – Northernmost internship on Svalbard" in seminar room 3 in...
welcome of new EAGLE generation
Today we welcomed the new generation of Earth Observation EAGLE students and are happy to see such a diverse and highly motivated group of students again. Students from Nepal, India, Ruanda or Turkey joint our study program among many other countries and already in...
MSc defense by Vanessa Rittlinger
On Friday,October 24, 2023 at 10:00 a.m. Vanessa Rittllinger will present her master thesis on “Detection of landslides in space and time using optical remote sensing data – A case study in South Tyrol” From the abstract: Landslides as a natural hazard cause damage...
EAGLE MSc students working in the Arctic
From August to November, two EAGLE students had the opportunity to do their internship at the University Centre in Svalbard (UNIS), working in the department of Arctic Biology. Their tasks included regular drone flights in Adventdalen, a valley close to the world’s...
MSc defense by Narges Mohammadi Khoshouei
On October 06, 2023, Narges Mohammadi Khoshouei (Sanaz) successfully defended her master’s thesis entitled “Short-term forecast of water reservoir dynamics by integrating earth observation and hydrological modeling for dam management” at the Earth Observation Research...