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:

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

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

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

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

Johannes:
“Tracking crop penology based on S1-Time series”

Sebastian:
“Solar power potential in Portugal”

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

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

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

New MSc thesis: Time series analysis in Colombian Orinoco Basin

New MSc thesis: Time series analysis in Colombian Orinoco Basin

Pilar Endara started her M.Sc. thesis on “Time series analysis of flooding and vegetation patterns in wetlands of the Colombian Orinoco Basin”

The ecosystems that are present within Colombian Orinoquia flooded savannas are currently being threatened by conversion of natural systems into intensive rangelands with introduced pastures, croplands and palm oil plantations. The loss of natural floodplain ecosystems has serious negative impacts on several important ecosystem services such as habitat quality for biodiversity, long-term carbon sequestration and water regulation.

In addition, this region’s natural vegetation endures strong intra-annual hydrological regimes, which in turn may affect the productivity, and consequently, the region’s carbon dynamics. Therefore, the objective of this thesis is to understand how, and if, the vegetation productivity in this area varies along the year, taking into account the strong hydrological variability.

The results of this thesis are going to be integrated with information from WWF Colombia to provide stakeholders and decisions-makers a tool that will allow them to assess for best practices of land use planning and land management.

First supervisor is Claudia Künzer, second supervisor is Martin Wegmann

Internship, Innovation Lab and MSc idea presentations

Internship, Innovation Lab and MSc idea presentations

The following students presented their innovation labs, internships and ideas for MSc. thesis:
Ahmed: ‎
Innovation Lab at DLR (team of Ursula Gessner) and Master Thesis Idea:
Title: Status of Agricultural Lands in Egypt using Earth Observation
Maninder (at DLR, Demmin):
Internship: To find a best fit model by comparing various Evapotranspiration  models using the weather station data for Toitz station, Germany
Thesis idea: comparing the performace of different crop growth models using synthetic remote sensing data at Demmin, Germany
Pilar:
Thesis idea: Time series analysis of flooding and vegetation patterns in wetlands of Colombian Orinoco Basin
MSc thesis started by Jakob Schwalb-Willmann

MSc thesis started by Jakob Schwalb-Willmann

Jakob Schwalb-Willmann just started his M.Sc. thesis titled “A deep learning movement prediction model using environmental data to identify movement anomalies”. He will combine animal movement and remote sensing data in order to develop a generic, data-driven DL-based model that predicts movements from movement history alongside environmental covariates in order to detect movement anomalies. He will establish simulated, controlled environments that allow precise adjustments of the model inputs to test the model’s feedbacks and its variability. It can be considered as a precursor study for the model’s deployment on real data and to only experimentally apply it on such due to the given constraints (time and content) of his M.Sc. thesis. The first supervisor is Dr. Martin Wegmann.

M.Sc. handed in on animal movement and remote sensing

M.Sc. handed in on animal movement and remote sensing

The M.Sc. thesis “Can animal movement and remote sensing data help to improve conservation efforts?” by Matthias Biber M.Sc. student within the Global Change Ecology program handed in his thesis. He explored the potential of remote sensing data to explain animal movement patterns and if these linkages can help to improve conservation efforts. He used Zebra as study animal in Southern and Eastern Africa. The first supervisor was Martin Wegmann, the second supervisor of his M.Sc. was Thomas Müller from BIK-F.

abstract:
Climate and land-use change have a growing influence on the world’s ecosystems, in particular in Africa, and increasingly threaten wildlife. The resulting habitat loss and fragmentation can impede animal movement, which is especially true for migratory species. Ungulate migration has declined in recent years, but its drivers are still unclear. Animal movement and remote sensing data was combined to analyse the influence of  various vegetation and water indices on the habitat selection of migratory plains zebras in Botswana’s Ngamiland. The study area experienced a more or less steady state in normalised difference vegetation index (NDVI) over the last 33 years. More than half of the study area was covered by PAs. NDVI increased stronger in PAs compared to areas that were not protected. NDVI was always higher in the Okavango Delta  compared to the Makgadikgadi Pans. Although zebras are thought to select for areas with high NDVI, they experienced a lower NDVI in the Makgadikgadi grasslands during wet season. Step selection functions (SSFs) showed that NDVI derived from Landsat as well as NDVI derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) were significant drivers of habitat selection across all individuals. Migration  seems to be driven by the high nutritional value of the Makgadikgadi grasslands and not seasonal resource limitation. Landsat imagery was shown to provide different environmental information compared to MODIS data. This highlights not only the importance of NDVI for explaining animal movement, but also the importance of Landsat imagery for monitoring habitat extent and fragmentation. Incorporating the animal’s  behavioural state and memory into SSFs will help to improve our ecological understanding of animal movement in the future.

MSc topic on wetland modeling

MSc topic on wetland modeling

M.Sc thesis (+ a two-month internship):

Agent-based modeling to understand Mediterranean wetland (former saltworks) dynamic based on multiple remote sensing data

UAV imagery over a portion of the study site. Image courtesy Cyril Fleurant (Uni Angers)

The Camargue’s former saltworks is a 6500-ha site located at the Mediterranean coast in southern France. The site has been recently purchased by the Conservatoire du Littoral, a public organization created in 1975 to ensure the protection of outstanding natural areas along the coast. The ongoing management of the area has been entrusted to the natural regional parc (PNR camargue), the national reserve of Camargue and the Tour du Valat. The site comprises a wide range of habitats. It has traditionally been home to the single colony of Flamingos nesting in France and is used by thousands of shorebirds during breeding and migration. Various construction works such as embankments (to control circulation of pumped sea-water through lagoons) and sea-front dike (to prevent uncontrolled flooding by the sea) together with salt exploitation and sea-level rise led to profound changes in the landscape that in turn call for the restoration of natural processes of coastal lagoon ecosystems. However, the conservation and management measures are restricted to be timely done as a result of difficult access for ground survey. Very high resolution remote sensing can introduce alternatives to this by providing continuous and objective surface coverage.

In this context, this M.Sc project aims at developing predictive tools on the basis of remote sensing data to follow habitat dynamics in order to help adaptive ecosystem management. The objective is to develop a method to understand the fast changes of the habitats using very high resolution remote sensing data. To this aim, LiDAR and very high resolution optical data (WorldView 2) and other GIS layers will be analyzed to produce spatially-continuous input for a state-of-the-art agent-based model. Few studies have applied this modeling approach to image analysis but the first results are promising .

Agent-based modeling will allow considering multiple non parametric factors that characterize the landscape dynamics. This approach will allow taking complex spatial and temporal processes as well as changing factors into account. The GAMA agent-based simulation platform (Taillandier et al. 2014, http://gama-platform.org/)  was initially developed to integrate GIS data in the  simulation. Within the envisaged M.Sc work this platform will be used for prediction based on the layers created from remote sensing data.

The M.Sc thesis is planned to be ideally started with a preliminary phase of two-month internship at the LETG, University of Angers . During the internship the M.Sc student will encompass a NetLogo and GAMA learning phase and gets to know the area and data.  A site visit at Tour du Valat research center may help to understand the management objective of the area. The second phase would be the M.Sc thesis, during which the candidate will spend time at both Universities of Würzburg (4 months) and Angers (2 months). The stay in Angers is supported by an existing ERASMUS agreement between the two universities.

Interested candidates are welcome to send an Email to Dr. Hooman Latifi (hooman.latifi@uni-wuerzburg.de).

Supervisors:

Dr. Aurélie Davranche (University of Angers, France)

Dr. Hooman Latifi (University of Würzburg)

Dr. Brigitte Poulin (Tour du Valat, France)