Erstellung eines Kulturgut-Katasters zur Analyse von potenziell nachteiligen Folgen von Hochwasser | Cultural sites and floods

Please find below the announcement of a paid master thesis, supported be the Austrian Federal Ministry for Sustainability and Tourism, BMNT. The information is in German. The master thesis is preferred in German, but also possibel in English.
  

Die Hochwasserrichtlinie 2007/60/EG gibt einen Impuls zur Bewertung von nachteiligen Folgen von Hochwasser. Signifikante nachteilige Auswirkungen auf die menschliche Gesundheit, die Umwelt, wirtschaftliche Tätigkeiten und das Kulturerbe sollen dabei in die Bewertung des Hochwasserrisikos einfließen. Die Auswirkungsanalyse für Kulturgüter stellt in Österreich eine besondere Herausforderung dar, da keine flächendeckenden, räumlichen Daten zu Kulturgütern vorliegen.

Um detailliertere Aussagen zu potenziell betroffenen Kulturgütern (zB. Vom Weltkulturerbe Stadt Salzburg, bis hin zu Kleinobjekten/Marterl)  treffen zu können, soll ein Verfahren entwickelt werden, um die Kulturgut-Listen des Bundesdenkmalamtes (rund 40.000 Einträge für Österreich) zu verorten. Obwohl den Kulturgütern in den meisten Fällen Grundstücke zugeordnet sind, bestehen Unsicherheiten im räumlichen Bezug (teilweise kleine Objekte auf Grundstücken mit großer Fläche, teilweise Adresspunkte weitab vom eigentlich denkmalgeschützten Bauwerk/Struktur). Unter dem Einsatz verschiedener Datenquellen (DKM, OSM, Google API usw.) soll eine Methode zur Verortung und Qualitätssicherung entwickelt werden. Anschließend kann die räumliche Verteilung von nicht-mobilem Kulturgut analysiert werden. Der abgeleitete Basisdatensatz stellt eine Grundlage für die weitere Analyse von nachteiligen Folgen von Hochwasser für Kulturgüter dar, die über Verschneidungen mit Überflutungsflächen und Informationen zur Prozessausprägung (Wassertiefen und Fließgeschwindigkeiten) erreicht werden kann.

Die Kompetenzen der Kandidatin bzw. des Kandidaten liegen im Bereich der Erstellung von Skripten zur Automatisierung von Prozessen (Python im GIS-Kontext) sowie der Arbeit mit größeren Datensätzen und -mengen. Erfahrungen mit dem Bereich Hochwasser sind nicht zwingend erforderlich, der Wille zur Aneignung von Wissen in diesem Bereich reicht aus.

Die Master-These wird von der Abteilung Schutzwasserwirtschaft (Bundesministerium für Nachhaltigkeit und Tourismus - BMNT), die für die Umsetzung der Hochwasserrichtlinie in Österreich verantwortlich ist, mitbetreut und bietet die Möglichkeit einer praxisorientierten Arbeit im Bereich des Risikomanagements. Die entwickelten Ergebnisse leisten einen wichtigen Beitrag zum Umgang mit Hochwasser. Der erfolgreiche Abschluss der Arbeit wird mit 2.000€ honoriert, etwaige Reisekosten werden abgegolten. Die Arbeit kann in Deutsch aber auch bei Bedarf in Englisch verfasst werden.

Rückfragehinweis

Martin Wenk

E-Mail: martin.wenk@bmnt.gv.at

Stefan Kienberger

E-Mail: stefan.kienberger@sbg.ac.at

Identifying Urban Neighbourhoods from Social Media Posts

Urban Neighbourhood Definition beyond Administrative Boundaries

Suggested by: Bernd Resch

Short description: Predicting epidemiological spreads in space and time is challenging because official health data is oftentimes not publicly available and partly outdated and often limited in its spatial and temporal resolution. Thus, this thesis will develop methods for identifying spatio-temporal patterns in dengue and chikungunya cases. The developed methodology will identify hot spots in space and time based on user-generated data (e.g., Twitter) and correlate the results with official and ancillary data (e.g. socio-economic & environmental data). Depending on the progress of the thesis, additional goals comprise the implementation of a tool for dynamic visualisation and the development of a method for forecasting the further spread of a disease, and investigating relationships with socio-economic information. The results can potentially support health institutions in planning vaccination and preparing for a rapidly spreading epidemic. The thesis has extraordinary practical relevance as chikungunya epidemic is currently spreading over South, Middle and North America, and Dengue fever is prevalent in many tropical and sub-tropical regions across the globe and increasingly impacts urban agglomerations.

Literature:

Anselin, L. and Williams, S. (2016) Digital Neighborhoods. Journal of Urbanism: International Research on Placemaking and Urban Sustainability, 9(4), pp. 305-328.
Resch, B., Usländer, F. and Havas, C. (2018) Combining Machine-learning Topic Models and Spatiotemporal Analysis of Social Media Data for Disaster Footprint and Damage Assessment. Cartography and Geographic Information Science, 45(4), pp. 362-376.
Bernardo, F., & Palma-Oliveira, J. M. (2016) Urban Neighbourhoods and Intergroup Relations: The Importance of Place Identity. Journal of Environmental Psychology, 45, pp. 239-251.

Start date: ASAP

Prerequisites/qualifications: experience with geospatial analysis, data visualisation, and urban research

Spatio-temporal Patterns in Epidemiological Spread of Dengue and Chikungunya

Correlating User-generated Data with Public Health Data

Suggested by: Bernd Resch

Short description: Urban neighbourhoods are inherently spatial and oftentimes defined through adminstrative districts. These neighbourhoods also represent urban places that are increasingly important units of focus in urban planning processes. Neighbourhoods are multi-dimensional in their nature, defined by physical, personal, political, organisational, socially enacted, and symbolic properties.
This thesis project aims to develop a new methodology for defining urban neighbourhoods through uncovering dynamic phenomena of pattern formation. Therefore, the analysis of social media posts has the potential of defining neighbourhoods through social interaction and interests, going beyond previous administrative definitions. This will lead to a new understanding of urban structures, potentially supporting urban planning through serving the needs of homogeneous communities with similar interests.

The master thesis will be carried out together with Harvard University’s School of Public Health (HSPH) and the Center for Geographic Analysis (CGA).

Literature:

Hagenlocher, M., Delmelle, E., Casas, I., and Kienberger, S. (2013) Assessing socioeconomic vulnerability to dengue fever in Cali, Colombia: statistical vs expert-based modeling. International journal of health geographics, 12(1), 36.

Jaenisch, T. and Patz, J. (2002) Assessment of Associations between Climate and Infectious Diseases; a Comparison of the Reports of the Intergovernmental Panel on Climate Change (IPCC), the National Research Council (NRC), and United States Global Change Research Program (USGCRP). Global Change & Human Health 2002, Volume 3(1), 2-7.

Resch, B. (2013) People as Sensors and Collective Sensing - Contextual Observations Complementing Geo-Sensor Network Measurements. In: Krisp, J. (2013) Advances in Location-Based Services, ISBN 978-3-642-34202-8, Springer, Berlin Heidelberg, pp. 391-406.

Start date: ASAP

Prerequisites/qualifications: experience with analysing VGI, data visualisation, and spatio-temporal pattern detection

VGI in Disaster Management - Fusing Remote Sensing Data with User-generated Data

Suggested by: Bernd Resch

Short description: Disaster events like floods, tsunamis or large-scale industrial accidents pose two central challenges to disaster management: first, availability of data and information for decision support; and second, communication before, during and after a disaster – bi-directionally between all involved actors: public authorities, action forces, and citizens. The theses outlined below aim to explore the enhancement of remote sensing methods by making use of social media, human sensors and in-situ sensors in disaster management in three areas (one thesis will cover one area with leveraging potential synergies to the others):

1.) Data Fusion: enhancement and validation of established remote sensing-based processes through the use of user-generated data and in-situ sensor data.

2.) Communication and Coordination: design and prototypical realisation of a social media-based platform to enable communication between the above-mentioned actors, including the coordination of ad-hoc forces.

3.) Citizen Sensing: data acquisition by citizens throughout and after a disaster event by making use of the “human sensor” concept in the form of a smartphone and/or web app.

The master students will have the opportunity (non-mandatory) to spend part of or the full duration of the thesis at the German Aerospace Center (DLR) in Oberpfaffenhofen, Germany in the frame of the Center for Satellite-based Crisis Information (ZKI).

Literature:

Goodchild, M. F. and Glennon, J. A. (2010) Crowdsourcing Geographic Information for Disaster Response: A Research Frontier. International Journal of Digital Earth, 3(3), pp. 231-241.

Harvard Humanitarian Initiative (2011): Disaster Relief 2.0 - The Future of Information Sharing in Humanitarian Emergencies, Washington, D.C. and Berkshire, UK: UN Foundation-Vodafone Foundation Partnership, 72 S.

Resch, B. (2013) People as Sensors and Collective Sensing - Contextual Observations Complementing Geo-Sensor Network Measurements. In: Krisp, J. (2013) Advances in Location-Based Services, ISBN 978-3-642-34202-8, Springer, Berlin Heidelberg, pp. 391-406.

Start date: ASAP

Prerequisites/qualifications: experience with analysing VGI, preferably background in data fusion, remote sensing and smartphone app design