Theses

Thema: Im Rahmen der gemeinsamen IFGIcopter und ILÖK UAV Initiative werden  kontinuierlich vegetationsspezifische Fernerkundungsdaten unterschiedlichster UAV-Sensoren (Drohnen) aufgenommen und ausgewertet. Besondere Schwerpunkte sind die Erfassung und Analyse von Vegetationsmustern, Vitalitätsparametern und inversiver Arten mittels multispektraler UAS Daten. In diesem Kontext spielen die Datenverarbeitung und Visualisierung (auch 3D) mittels verschiedenster geoinformatischer Werkzeuge (GIS, kommerzielle Software, Web-Tools und Eigenprogrammierungen etc.) eine große Rolle. Wer Interesse an einer interdisziplinären Fragestellung in diesem Bereich hat, wende sich an die beiden Ansprechpartner [2017].

Ansprechpartner: Torsten Prinz / Jan Lehmann

Contact: Torsten Prinz

gdalcubes ist eine am ifgi entwickelte C++ Bibliothek zur effizienten Erstellung und Verarbeitung von raumzeitlichen Data-Cubes aus größeren Satellitenbildsammlungen. Zur einfacheren Nutzbarkeit durch Datenwissenschaftler existiert zur Zeit lediglich eine Schnitstelle als R Paket. Ziel dieser Arbeit ist es, eine prototypische Schnittstelle zwischen gdalcubes und Python zu entwickeln. Dabei sollen verschiedene existierende Ansätze zur Verküpfung von Python und C++ (zum Beispiel pybind11, Cython, SWIG, Boost.Python) evaluiert werden. Schwerpunkte der Arbeit können nach Interesse besprochen werden.

Contact: Marius Appel

Copernicus is a European Earth observation programme with the goal “to provide accurate, timely and easily accessible information to improve the management of the environment, understand and mitigate the effects of climate change and en-sure civil security” (ESA 2015). Within Copernicus, a series of new satellite mis-sions will be executed to gather new satellite data. The first mission acquiring ra-dar data, called Sentinel-1, and the second mission gathering multi-spectral high-resolution data have already been launched.
In order to derive higher-level information products, the data needs to be pro-cessed, e.g. by using segmentation algorithms. In former times, the workflow in-cluded downloading the data, pre-processing it by selecting the spatial and/or temporal extent, and then running the actual segmentation process. The idea of rich data interfaces is that these processing facillities for deriving new information products are directly provided with the data in order to avoid downloading large raw datasets.
The aim of this bachelor thesis is to investigate how the OGC Web Processing Service (WPS) standard (Mueller & Pross, 2015), which defines a web service in-terface for geoprocessing functionality, can be utilized for such a rich data inter-face for the Copernicus. The expected outcomes are
(i) architecture patterns for coupling WPSs with copernicus data interfaces (ii) a prototypical implementation (iii) an evaluation of the concepts developed.
In order to successfully work on the thesis, good knowledge in Web technologies and Java programming is required as well as interest in remote sensing and EO-analysis. The work will be done in cooperation with the 52°North Open Source ini-tiative.
Literature:
Mueller, Matthias, and B. Pross. “OGC WPS 2.0 Interface Standard”. OpenGIS Implementation Standard, Version 2.0, OGC 14-065. (2014).
ESA. “Overview/Copernicus”. Available online at http://www.esa.int/Our_Activities/Observing_the_Earth/Copernicus/Overview3. (2015) Accessed 29/05/2015.
Contact:
Prof. Dr. Albert Remke (a.remke@52north.org) Dr. Christoph Stasch (c.stasch@52north.org)

Contact: Prof. Dr. Albert Remke

Die openSenseMap ist eine Plattform für Umweltsensordaten von Messstationen jeglicher Art. Zur Zeit werden nur Rohdaten von senseBoxen gespeichert und die Daten können sich nur pro senseBox angezeigt werden lassen. Zudem gibt es die Möglichkeit sich die gesammelten Daten für einen Zeitpunkt interpoliert darstellen zu lassen.

Ziel der Arbeit ist es, für die openSenseMap ein Portal zu entwicklen, in dem der Benutzer die Möglichkeit hat mehrere senseBoxen und Sensoren mit statistischen Methoden zu vergleichen und externe Datenquellen, wie zB. vom DWD, einzubinden.

Contact: Thomas Bartoschek

In der Arbeit soll untersucht werden, inwieweit Qualitätssicherung von crowd-sourced Sensordaten in einem Sensornetzwerk automatisierbar ist. Dies ist ein neues und hoch relevantes Forschungsfeld: große Datenmengen erlauben die Anwendung statistischer oder machine learning-Verfahren. Traditionelle Verfahren sind häufig nicht nutzbar, da die Daten in Echtzeit vorliegen müssen. Zudem stellen crowd-sourced Daten eine spezielle Herausforderungen dar, da nicht davon ausgegangen werden kann, dass alle Daten mit korrekten bzw. konsistenten Messverfahren erhoben wurden. Schließlich haben low-cost-Sensoren selbst Messfehler, die von professionellen Sensoren stark abweichen. oder Messstationen sind von Citizen Scientists schlecht montiert. Das Ziel ist, die Einflussfaktoren auf die Datenqualität und die Messgenauigkeit der Sensoren zu erforschen, Verfahren zur automatisierten Identifikation fehlerhafter Daten und möglicher Fehlerquellen zu entwickeln sowie automatisiert Entscheidungen über Möglichkeit zur Korrektur der Daten (bspw. über Nachkalibrierung der Sensoren) oder Ausschluss bestimmter Daten zu treffen.

Contact: Thomas Bartoschek

Contact: Thomas Bartoschek

Learning Analytics is a method to collect, measure, analyze and visualize data about learners and their context. It enables the understaning of the learning process and allows an adaption of learning pathes based on the collected data. It also gives feedback to the learner and teacher about the learning process.

Contact: Thomas Bartoschek

Im Rahmen dieser Bachelorarbeit sollen neue Sensorkomponenten für Umweltphänomene (z.B. Wind, Wasser, Radioaktivität o.ä.) für die senseBox identifiziert und in das senseBox Ökosystem aus Open Source Hardware, openSenseMap Geodateninfrastruktur, Blockly-Programmierumgebung integriert und evaluiert werden. 

Contact: Thomas Bartoschek

For decades, sketchmaps have been used as a tool for measuring spatial knowledge - i.e., for estimating how well participants know and understand some areas. However, evidence from psychological memory studies demonstrates, that drawing something can also be a good strategy to memorise a set of object. For instance, if you need to memorise the setting of a room, drawing the room as you see it is a better memorisation strategy than repeating the names of the objects verbally or in your head. This thesis will test whether drawing a sketch map is a good memorisation strategy for spatial environments and how this approach can be implemented in a gamified app. The problem is relevant for situations in which people must learn new spatial environments, e.g. to become taxi/delivery drivers, or when they move to a new city.
The thesis can be completed with focus on one of two aspects:
**Computational focus:** You will design a teaching app that (a) records the user's trajectory together with a list of landmarks that were visible along the route, and (b) after a delay, asks users to draw the area that they have travelled. Here the key problem may be to select routes and landmarks that the user should be asked to draw (based on the recorded trajectories).
**Evaluation focus:** You will design and conduct an experiment to evaluate the following research question: does drawing a sketchmap help people memorise the environment better, compared to alternative strategies? This does not require creating an app, and can be conducted as an in-situ experiment, or inside our Virtual Reality lab.

Contact: Jakub Krukar

Current search engines return results in almost a fraction of a second to any query submitted by users. This often comes with the drawback of users navigating through a number of irrelevant results. This thesis will explore the impact of adding query disambiguation steps of overall user satisfaction during search, and investigate the extent to which users are willing to trade response time with quality of results. Tasks envisioned include:

1. Data preparation

2. Development of a prototypical search engine, which (a) asks users which place they mean when homonyms are available (e.g. Berlin, USA vs Berlin, Germany), (b) offer disambiguation functionalities before the display of results using e.g. the Geonames API 

3. Development of a prototypical search engine, which simulates the functionalities of the current state of the art offered by search engines

The evaluation will involve A/B testing, and gathering of participants’ feedback during a user study.

Contact: Auriol Degbelo

Annotations of visualizations is a useful task during exploratory data analysis. As illustrated in [1,2], users may want to record trends, clusters, distributions or outliers found on components of a geovisualization during a data analysis session. A key challenge here is that of summarizing the annotations produced by various users during their exploration activities. This thesis will look into computational and/or graphical means of producing these summaries. Tasks include: 

Prototyping: design of a web-based or mobile prototype to record annotations of web maps graphically.

Data collection: here graphical annotation of web-maps will be generated. These annotations could be synthetic or real, depending on the scope of the thesis. 

Summarization: this design, implementation and evaluation of summary approaches. 

References

[1] Heer, J., Viégas, F. B. and Wattenberg, M. (2009) ‘Voyagers and voyeurs: supporting asynchronous collaborative visualization’, Communications of the ACM, 52(1), pp. 87–97. doi: 10.1145/1435417.1435439.

[2] Lai, P.-C. and Degbelo, A. (2021) ‘A comparative study of typing and speech for map metadata creation’, in Partsinevelos, P., Kyriakidis, P., and Kavouras, M. (eds) Proceedings of the 24th AGILE Conference on Geographic Information Science (AGILE 2021), pp. 1–12. doi: 10.5194/agile-giss-2-7-2021.

Contact: Auriol Degbelo

Thema: Im Rahmen der gemeinsamen IFGIcopter und ILÖK UAV Initiative werden  kontinuierlich vegetationsspezifische Fernerkundungsdaten unterschiedlichster UAV-Sensoren (Drohnen) aufgenommen und ausgewertet. Besondere Schwerpunkte sind die Erfassung und Analyse von Vegetationsmustern, Vitalitätsparametern und inversiver Arten mittels multispektraler UAS Daten. In diesem Kontext spielen die Datenverarbeitung und Visualisierung (auch 3D) mittels verschiedenster geoinformatischer Werkzeuge (GIS, kommerzielle Software, Web-Tools und Eigenprogrammierungen etc.) eine große Rolle. Wer Interesse an einer interdisziplinären Fragestellung in diesem Bereich hat, wende sich an die beiden Ansprechpartner [2017].

Ansprechpartner: Torsten Prinz / Jan Lehmann

Contact: Torsten Prinz

The mapping of biotope types plays an essential role in the assessment and monitoring of ecosystems. Since an extensive collection of the required parameters in the field is not feasible, remote sensing (mainly high-resolution RGB and NIR data) is commonly used. Usually the data is analyzed manually through visual interpretation by trained analysts. The aim of this project is to develop and evaluate methods for an automated segmentation (delineation) and classification of relevant biotope types at the spatial scale of established classification schemes.

Guiding questions include:

• What are the identifiable features (e.g. spatial, spectral, temporal patterns) that are commonly used in the visual interpretation of remote sensing images to detect and classify biotope types, and can these features be integrated in models for an automatic classification?
• How can deep learning and “classical” machine learning support the automation of classifying biotope types in remote sensing images?
• What are the main features that are learned by well-trained machine learning models for identifying biotope types as compared to the features used in the visual interpretation by human analysts?
• Which biotope types can or cannot be reliably classified, what are the main difficulties and which additional data might be helpful in increasing classification accuracy?

The data basis consists of high-resolution remote sensing images (10 cm, color infrared and RGB) as well as freely available medium resolution satellite data (especially Sentinel). A comprehensive reference data set of manually digitized biotope types is available for model training and validation. The practical work is expected to be conducted reproducibly in R.  

The research will be conducted through two master theses (geoinformatics and landscape ecology) in close collaboration. The specific tasks and research questions of both theses will be discussed between the students and supervisors.

Supervisors: Christian Knoth (ifgi), Hanna Meyer and Jan Lehman (ILÖK),   Reinhard Silvers (Hansa Luftbild)

Contact: Christian Knoth

IVE is a panoramic video footage that is displayed on large screens in a cave like environment that creates a sense of physical presence and enables people to better interact and intervene the image of their surroundings. However, the forms of interactions are very limited - yet needed - when users need to create objects on the screen as video overlays and interact with them (e.g., adding and scaling a tree, modifying a building façade etc.).

This study aims to explore the forms of interactions on IVE for effective creation and interaction of the overlays. The student will work with the IVE system in the Sitcom Lab at Ifgi. The study will cover the following steps: creating a video footage and overlays for IVE, exploration of the tools (e.g., smart phone, HTC Vive controllers, touch pad), design of the forms (e.g., adding, removing, scaling, rotating, placing the overlays) of interaction and the UI component.

Contact: Simge Özdal Oktay

Buildings of the future will have to be much more flexible than they are now. One envisioned possibility is that building interiors will change their shapes depending on the current context of use, personal preference of their users, or tasks that the occupants have to perform within them at the given moment. While this may sound like a distant vision of the future, Virtual Reality equipment already allows us to study such scenarios today.

In this thesis, you will design a Virtual Reality building that participants will explore in Head-Mounted Displays. The VR system will monitor spatio-temporal data of the building user, and create the remaining (yet unvisited) parts of the building in response to this data, before the user gets there.

The specific context of this thesis can be adjusted based on your interests. One possibility would be to detect navigational confusion based on the occupant's walking trajectory, and - in response - provide a navigationally simplified space in the next room that the occupant is going to visit. Another possibility is to detect loss of attention in a virtual museum gallery, and - in response - provide the user with a more exciting space in the next room. The application should be evaluated in a simple user study.

Contact: Jakub Krukar and Chris Kray

OriGami is a GeoGame fostering spatial literacy: The player has to solve several wayfinding tasks to various locations and answer questions at these locations. At the current state, it is a single-player game.

As part of this thesis, you would have to extend the concept of OriGami for a multi-player version, where players can compete or work together to solve tasks. After the conceptual development, you should implement a user management + implement the collaborative games and evaluate your game.

More information on OriGami can be found on our project website http://enable-project.eu/origami/.

Requirements:

You should have some experience in android programming and interest in location-based games.

Contact: Thomas Bartoschek, Angela Schwering

In der Arbeit soll untersucht werden, inwieweit Qualitätssicherung von crowd-sourced Sensordaten in einem Sensornetzwerk automatisierbar ist. Dies ist ein neues und hoch relevantes Forschungsfeld: große Datenmengen erlauben die Anwendung statistischer oder machine learning-Verfahren. Traditionelle Verfahren sind häufig nicht nutzbar, da die Daten in Echtzeit vorliegen müssen. Zudem stellen crowd-sourced Daten eine spezielle Herausforderungen dar, da nicht davon ausgegangen werden kann, dass alle Daten mit korrekten bzw. konsistenten Messverfahren erhoben wurden. Schließlich haben low-cost-Sensoren selbst Messfehler, die von professionellen Sensoren stark abweichen. oder Messstationen sind von Citizen Scientists schlecht montiert. Das Ziel ist, die Einflussfaktoren auf die Datenqualität und die Messgenauigkeit der Sensoren zu erforschen, Verfahren zur automatisierten Identifikation fehlerhafter Daten und möglicher Fehlerquellen zu entwickeln sowie automatisiert Entscheidungen über Möglichkeit zur Korrektur der Daten (bspw. über Nachkalibrierung der Sensoren) oder Ausschluss bestimmter Daten zu treffen.

Contact: Thomas Bartoschek

Learning Analytics ist eine Methode zur Erfassung, Messung, Analyse und Visualisierung von Daten über Lernende und ihren Kontext, die es ermöglicht den Lernfortschritt zu verstehen und Lernpfade zu optimieren, um dem Lernenden aber auch Lehrenden Feedback zum Lernprozess zu geben. Learning Analytics lässt sich besonders gut in digitale Lernplattformen einbinden. Blockly für die senseBox ermöglicht es Anfängern in die Mikrocontrollerprogrammierung einzusteigen.Trotzdem können Fehler im "Code" entstehen, wodurch das Programm nicht kompilierbar ist. 

Ziel der Arbeit ist die Entwicklung einer Learning Analytics Komponente, die dem Nutzer Feedback zum selbst programmierten Code gibt, Hinweise bei Fehlern und Lernfortschritte trackt.

Contact: Thomas Bartoschek

Learning Analytics is a method to collect, measure, analyze and visualize data about learners and their context. It enables the understanding of the learning process and allows an adaption of learning paths based on the collected data. It also gives feedback to the learner and teacher about the learning process.

WebGIS NRW is a prototypical WebGIS for educational purposes (webgis.nrw) based on MapBox GL.

In this thesis you should investigate the possibilities of learning analytics for the work with webGIS, i.e. cartography, map design, data analysis. A prototypical implementation of learning analytics components for webgis.nrw is part of the work.

Contact: Thomas Bartoschek

When people draw sketch maps, they generalise information compared to the ground-truth information they perceived in the world. For example:

- many buildings belonging to university campus are drawn as a single polygon labelled "campus",

- a complex roundabout is drawn as a few crossing lines,

- 10 side streets from the main road are drawn as a few random lines, only to indicate that "some side streets" are there. 

This is a challenge for analysing sketch maps because this information is not wrong, yet a computer system for automated analysis would interpret it as such.

In the paper linked below we presented a classification of generalisation types in sketch maps, and many other examples. We also also have a working software prototype for analysing generalisation in sketch maps.

This thesis topic can be concerned with the software implementation of different algorithms for detecting generalised spatial information (e.g., in a comparison between a sketch map and OpenStreetMap data), and/or with theoretical studies of how people generalise information.

Examples of potential research questions:

- What affects the level of specific generalisations, e.g., when people perform stronger vs weaker forms of "amalgamation" generalisation?

- What are common ways to schematise complex spatial structures (e.g., roundabout), and how people do it spontaneously in drawings?

- How to detect and algoirthmically differentiate the >lack of some object< (e.g., a missing streets in an area) from their generalisation?

Contact: Jakub Krukar

For decades, sketchmaps have been used as a tool for measuring spatial knowledge - i.e., for estimating how well participants know and understand some areas. However, evidence from psychological memory studies demonstrates, that drawing something can also be a good strategy to memorise a set of object. For instance, if you need to memorise the setting of a room, drawing the room as you see it is a better memorisation strategy than repeating the names of the objects verbally or in your head. This thesis will test whether drawing a sketch map is a good memorisation strategy for spatial environments and how this approach can be implemented in a gamified app. The problem is relevant for situations in which people must learn new spatial environments, e.g. to become taxi/delivery drivers, or when they move to a new city.
The thesis can be completed with focus on one of two aspects:
**Computational focus:** You will design a teaching app that (a) records the user's trajectory together with a list of landmarks that were visible along the route, and (b) after a delay, asks users to draw the area that they have travelled. Here the key problem may be to select routes and landmarks that the user should be asked to draw (based on the recorded trajectories).
**Evaluation focus:** You will design and conduct an experiment to evaluate the following research question: does drawing a sketchmap help people memorise the environment better, compared to alternative strategies? This does not require creating an app, and can be conducted as an in-situ experiment, or inside our Virtual Reality lab.

Contact: Jakub Krukar

Finding the optimal trajectory in an 3D space is an ongoing research topic with applications such as optimizing an underwater route for a submarine robot or a flight route for drones. The problem becomes challenging as soon as the 3D space has barriers like danger zones or protected spaces. Those barriers can be modelled as features in GIS. A research gap to be closed is to combine the trajectory optimization techniques with GIS-modelled 3D barriers. Namely, the produced 3D-routes from the optimization techniques need a validation process to ensure that no barriers are crossed. Since many validations are necessary, one requirement is a fast computation.

The aim of this thesis is to solve the trajectory optimization problem with the artificial inteligence technique called "Genetic Programming" (GP). The produced trajectories are to be converted into geographical lines, which are tested for any interference with GIS-modelled 3D barriers. 

Contact: Moritz Hildemann, Judith Verstegen

Evaluative images of cities (i.e. composite maps capturing citizens’ perceptions of areas in the cities) are a rich source of qualitative data that can be used by urban planners to understand how people relate to neighborhoods of their cities. They were proposed by Nasar (1990), who suggested deriving them through interviews. Recently Barros et al (2022) proposed a web-mapping approach to create city images computationally, with promising results. This thesis will build upon this and explore techniques to compare two evaluative city images computationally. Tasks include:

Data collection: collect data about how people perceive areas of a city (e.g. Münster) concerning the five dimensions originally suggested by Nasar (i.e. naturalness, upkeep, openness, historical significance, and openness).

Development of a comparison module for evaluative city images: at least two directions are possible.

• A) The module helps assess and visually communicate similarities/differences between two evaluative city images. Possible applications of the comparison module include: assessment of the temporal variability (collection of two evaluative city images at different points in time), the spatial variability (comparison of evaluative city images from two different neighborhoods, or cities), the statements made by the city images about the mapped regions, and the (spatial) accuracies of the city images.

• B) The module relates an evaluative city image (qualitative data) with quantitative data available about the mapped neighbourhoods to identify conflicting statements and converging evidence for urban facts.

Evaluation: aspects to be evaluated could include the computational performance (how the module performs as the areas mapped by participants grow), the effectiveness of the visual communication of differences (how easy it is for users to perceive similarities and differences), or the usefulness of the comparison module for urban planners (what experts say about integrating the module into their workflows).

Readings

Barros, M. S., Degbelo, A. and Filomena, G. (2022) ‘Evaluative image 2.0: A web mapping approach to capture people’s perceptions of a city’, Transactions in GIS, 26(2), pp. 1116–1139. doi: 10.1111/tgis.12867.

Nasar, J. L. (1990) ‘The evaluative image of the city’, Journal of the American Planning Association, 56(1), pp. 41–53. doi: 10.1080/01944369008975742.

Demos

eImage Canvas: https://www.youtube.com/watch?v=z8dtaum_Xu0

eImage Viewer: https://www.youtube.com/watch?v=J-MDp9YItnc

Contact

Auriol Degbelo (auriol.degbelo@uni-muenster.de )

Simge Oktay (soezdalo@uni-muenster.de )   

Contact: Auriol Degbelo

"Replication" refers to the process of re-creating an experiment published by other researchers in an effort of obtaining results pointing to the same conclusion. A "replication crisis" showed that many published research is not replicable. We can distinguish two types of replication:

- an "exact replication" is the attempt of recreating every detail of the original experiment

- a "conceptual replication" is the attempt of creating a similar experiment, with similar hypotheses, but perhaps with a different stimuli, instructions, or groups of participants.

This thesis focuses on a "conceptual replication" of navigation research.

Navigation research is usually performed in very specific spatial context (such as the city in which the paper's authors are based or the virtual environment that they have created). This introduces a challenge to generalizability and replicability of navigation research because we do not know whether classic research findings would be equally applicable in different spatial contexts (e.g., a different city).

This thesis focuses on replicating an existing wayfinding paper (to be chosen by the student) in Münster, or in a virtual environment available at ifgi.

The key challenge is finding a way to make the new spatial context (of Münster) comparable to that of the original paper.

Thesis co-supervised by Daniel Nüst (with technical support w.r.t. replicability).

Examples of papers that can be replicated:

https://doi.org/10.1080/17470218.2014.963131

https://doi.org/10.1016/j.cognition.2011.06.005

Contact: Jakub Krukar

WI-FI is a promising technique to monitor traffic in different scenarios. As discussed in [2], WiFi sensing is beneficial because 1) low-cost, 2) not intrusive and 3) sensitive to lighting conditions. First tests done in [1] in Münster have yielded encouraging results for the monitoring of cars, but much is still needed to grasp the potential of the technique.  The aim of this thesis is to advance our understanding of the benefits and costs of WI-FI sensing for city traffic monitoring.

Tasks include:

• Scenario definition, system setup and data collection
• Prototype implementation for automated vehicle detection and classification
• Evaluation of the classification accuracies

Possible directions include (non-exhaustive list)

• Detection of vehicles on multiple lanes using Wi-Fi (e.g. two lanes, one direction; two lanes, two directions)
• Effect of the spatial distance between sending/receiving units on the classification accuracy

• Effect of the temporal resolution of the measurements on the classification accuracy
• Effect of the use of channel state information (CSI) on the classification accuracy
• Measurement of velocity and direction of vehicles (e.g. through the addition of additional sender/receiving units)
• WIFI-Sensing for real-time traffic monitoring
• Designing and developing prototype for real life implementation.

References

[1] Gupta, S., Hamzin, A. and Degbelo, A. (2018) ‘A low-cost open hardware system for collecting traffic data using Wi-Fi signal strength’, Sensors, 18(11), p. 3623. doi: 10.3390/s18113623.

[2] Ma, Y., Zhou, G. and Wang, S. (2019) ‘WiFi sensing with channel state information’, ACM Computing Surveys, 52(3), pp. 1–36. doi: 10.1145/3310194.

Contact: Auriol Degbelo

Annotations of visualizations is a useful task during exploratory data analysis. As illustrated in [1,2], users may want to record trends, clusters, distributions or outliers found on components of a geovisualization during a data analysis session. A key challenge here is that of summarizing the annotations produced by various users during their exploration activities. This thesis will look into computational and/or graphical means of producing these summaries. Tasks include: 

Prototyping: design of a web-based or mobile prototype to record annotations of web maps graphically.

Data collection: here graphical annotation of web-maps will be generated. These annotations could be synthetic or real, depending on the scope of the thesis. 

Summarization: this design, implementation and evaluation of summary approaches. 

References

[1] Heer, J., Viégas, F. B. and Wattenberg, M. (2009) ‘Voyagers and voyeurs: supporting asynchronous collaborative visualization’, Communications of the ACM, 52(1), pp. 87–97. doi: 10.1145/1435417.1435439.

[2] Lai, P.-C. and Degbelo, A. (2021) ‘A comparative study of typing and speech for map metadata creation’, in Partsinevelos, P., Kyriakidis, P., and Kavouras, M. (eds) Proceedings of the 24th AGILE Conference on Geographic Information Science (AGILE 2021), pp. 1–12. doi: 10.5194/agile-giss-2-7-2021.

Contact: Auriol Degbelo

Visualizations of spatial data on large displays could be very useful during the exploration of large spatial datasets. A key issue in this context is the design of natural interaction (e.g. interaction with freehand gestures and/or speech-based interaction) to support exploratory data analysis tasks (e.g. panning, zooming, selection, aggregation, annotation). This thesis aims to explore strategies to facilitate the interaction with spatial data on large displays using freehand gestures. Tasks include:

Task 1: implementation of a software module to reliably map the position of users’ hands to the screen’s positions.

Task 2: implementation of a software module that enables panning and zooming with maps via freehand gestures on a large display.

Task 3: evaluation of the software modules (e.g. performance, usability, usefulness).

The immersive video environment will serve as a prototypical large display during the study. Programming skills (C++, C# or VB.NET) will be an advantage.

Contact

Auriol Degbelo (auriol.degbelo@uni-muenster.de)

Samuel Navas Medrano (s.navas@uni-muenster.de)

Readings

Bartoschek, T., Pape, G., Kray, C., Jones, J. and Kauppinen, T. (2014) ‘Gestural interaction with spatiotemporal linked open data’, OSGeo Journal, 13(1), pp. 60–67.

Nancel, M., Wagner, J., Pietriga, E., Chapuis, O. and Mackay, W. (2011) ‘Mid-air pan-and-zoom on wall-sized displays’, in Tan, D. S., Amershi, S., Begole, B., Kellogg, W. A., and Tungare, M. (eds) Proceedings of the 2011 annual conference on Human factors in computing systems - CHI ’11. Vancouver, Canada: ACM Press, pp. 177–186. doi: 10.1145/1978942.1978969.

Contact: Auriol Degbelo

Cloud-computing services for analyzing larger collections of satellite imagery typically have a complex architecture, include strong requirements on the infrastructure, and are difficult to deploy for others, even if the underlying libraries are open-source. To facilitate reproducing analyses on smaller scale, a lightweight Earth observation platform that is easy to deploy and directly works on cloud computing platforms containing freely available satellite imagery such as Amazon web services, Google cloud platform, or Microsoft Azure would be needed.

This thesis aims at developing such a platform by interfacing the gdalcubes R package [1] and the openEO API [2]. The gdalcubes R package is a lightweight library to create and analyse on-demand data cubes from satellite image collections. Among others, it can be used to run user-defined R functions on data cubes and reading data from cloud storage directly. The openEO project in contrast provides a standardized REST-like API that makes analyses interoperable even among different cloud services.

Important questions for the thesis may include:

• How can gdalcubes functions be mapped to openEO processes?
• How to make the deployment as easy as possible?
• How to interface the backend with available STAC API endpoints?
• How to publish results as interactive web-service?
• How to run user-defined R functions on data cubes?

Do not hesitate to contact Marius Appel or Edzer Pebesma if interested.

Contact: Marius Appel