Internship and M.Sc. idea presentations

Internship and M.Sc. idea presentations

on Thursday, December 13th, at 12:30 we will have the following presentations in the student working room (Josef Martin Weg 52, 3rd floor):

internship presentations:

Johni Miah
“Remote Sensing and Geographic Information System for Decision Making”
Benjamin Lee
“Quantifying intertidal areas in the East Asian-Australasian Flyway”
Marina Reiter
“Computation of sewer system in Ulm”

M.Sc. idea presentations:

Marina Reiter
“Analysis of urban green areas in German cities”
Fowad Ahmed
“Drought Monitoring in the University Forest Sailershausen”
New 2018 EAGLE students now online

New 2018 EAGLE students now online

Web presence of you new EAGLE students is online. Our new 2018 EAGLE students created their own webspace in order to present the group and each student individually.

Have a look who started EAGLE this year, read about their background and interests – and especially have a look at their funny “on hover” picture animations!

2018 EAGLE Students

M.Sc. graduation by Jakob Schwalb-Willmann

M.Sc. graduation by Jakob Schwalb-Willmann

Congratulation to Jakob Schwalb-Willmann who successfully graduated today! His M.Sc. topic was “A deep learning movement prediction framework for identifying anomalies in animal-environment interactions” aiming to explore the potential of animal movement analysis for informing remote sensing data analysis. 

The M.Sc. was conducted in collaboration with the Max-Planck-Institute of Ornithology and supervised by Martin Wegmann and Kamran Safi.

From the abstract: “The environmental conditions that animals are exposed to infuence their movement throughout the landscape. A variety of modeling approaches aim to quantify the relationships between animal movement trajectories and environmental variables, e.g. acquired through satellite remote sensing. However, many of such approaches are designed for species-specifc movement modeling and often rely on a priori assumptions, knowledge-based parameterization or the selection of features. In this study, the use of representation learning for predicting animal-environment interactions in a non-parametric, species-independent framework is investigated to enable the unsupervised detection of anomalies. It is shown that a Long Short-Term Memory (LSTM) network is capable of learning generalized representations of the interactions between location and raw environmental features in movement sequences which had been simulated under an agent-based resource selection regime unknown to the network. Thus, the network is able to reconstruct such movement sequences that show similar feature interaction characteristics to the ones the network had learned. On the contrary, the reconstruction of sequences containing patterns that are novel to the network results in a reconstruction error response that was utilized to detect anomalies in movement sequences. It is discussed, how the proposed framework may be applicable for the analysis of animal movement, e.g. for outlier detection, behavioral segmentation or movement simulation. In addition, its potential for supporting environmental research on an inter-species scale, e.g. by detecting phenological indicators from animal movement, is examined.

EAGLE welcome 2018

EAGLE welcome 2018

Our new EAGLEs arrived!

We welcomed our new international EAGLE students from the US, Ecuador, Bangladesh, Ruanda or Germany for the upcoming winter term and introduced the lectures as well as the courses. In the evening we had a joint dinner to get to know each other. The first course started on Tuesday morning at 9 am on fundamentals of Earth Observation by Claudia Kuenzer.

EAGLE M.Sc. idea presentations

EAGLE M.Sc. idea presentations

On Monday, 24th of September from 1:30 onwards the following EAGLE students will present their M.Sc. idea. Everybody is welcome to join their presentations and to provide feedback:

“Time-Series Analysis of Sentinel-1 and Sentinel-2 Imagery for Detection of active Morphodynamics in the Atacama Desert, Chile”

Risk assessment for flood events based on remote sensing data – a case study for North-Rhine Westfalia, Germany

“Remote sensing of water quality using Sentinel-2 towards a potential separation of harmful algal blooms from other Algae”

“Assessing the development of circular irrigation in South Africa since 19*”

“Tracking crop penology based on S1-Time series”

“Solar power potential in Portugal”

“An approach to optimize object-based classification: Mapping dead trees and gaps in Białowieża Forest”

“Deep learning for Instance Segmentation and a comparison to a Conventional Segmentation on historical aerial images of the Second World War”

“Drought Monitoring in University Forest with Hyper-Spectral And In-Situ Data”