Available Master’s Thesis Projects

Here you will find a list of master thesis topics at CUSP. If none of the topics below interest you, you are welcome to reach out to any members of the centre for exploring other opportunities, whether in collaboration with external organisations or developing research questions together.

Shaping the role of municipalities in climate change adaptation: community building for decarbonisation

Energy Modelling and Spatial Data Science Climate Change

The responsibility of decarbonising urban regions is increasingly framed as an individual burden. Even progressive cities around the world that assume the role of supporting the transformation of consumption patterns to more sustainable pathways, merely focus on piecemeal and reactive policymaking. This process of public administration usually entails offering subsidies in renovation of building stock and adoption of solar energy, tax deductions for reconsidering energy or transit use, or providing financial incentives for new market-based development initiatives? The burden of understanding, translating or even accessing such policy solutions is often disregarded. Because of multiple vulnerabilities, people who have lower access to education, live in fragmented and segregated social networks, and are not digitally oriented, are not able to effectively adopt such policy solutions in the long-term. The idea of individual responsibility does not intersect with how we build livelihoods in cities, where people seek social networks for work and innovation, and build collective living spaces. The role of citizens in their communities is never taken into account in developing policy solutions.

To facilitate decarbonisation that is just, effective and encompasses all needs, muncipalities must shift from offering solutions to brokering citizen communities that are capable of adopting solutions on larger scales. To understand the role of communities in decarbonisation, and illustrate this hypothesis, this project will develop a multi-modelling framework that can flexibly adapt to the level of communal engagment muncipalities have the capacity to foster. You will develop decarbonisation scenarios on a spectrum of engagment from individual to beehive, and measure realistic gains in decarbonisation for each scenario. Several models will be neccessary: for example, spatial modelling and clustering analysis to estimate social vulnerability, network analysis to scope engagment processes, machine learning for measuring or estimating energy usage and decarbonisation potential of various solutions, and dynamical systems modelling for measuring solar radiation or other technical phenomenon. As a particiopant in this project, you will be part of a large team, where others will contribute with several models or datasets and analysis. The role of a master thesis student will primarily be to conceptualise the multi-modelling framework, make datasets interoperable with multiple modelling techniques, and make the framework modular. You are flexible to choose one decarbonisation scenario, like adoption of renewable energy solutions (e.g., a combination of solar panels, heat pumps, district heating and renovation subsidies). Based on the averarching concept, you will then combine/develop models and translate them into outputs. The outputs should strongly be focused on visualisation to initiate a dialogue with muncipalities on their role as brokers of citizen engagment.

The outcomes will be situated in the broader discussions of spatial and social justice, such that communal engagement can be shaped in a meaningful way, where communities who are disadvantaged are not left behind in any decarbonisation process. We expect that municpailities can incorporate such a framework into their spatial data landscapes to model different kinds of scenarios (e.g., solar adoption, heat pumps, district heating, etc.). You will have access to several stakeholders but also several datasets and models. Data can come from the city of Glasgow (where a dashboard is also being developed professionally to start incorporating such ideas in the long-term), The Hague (extensive amount of climate related datasets are available) and Rotterdam (besides data, we also have extensive relationships with community organisations).

If you are interested in this topic in any capacity (MSc, internship (credits or paid)), please contact Dr. Trivik Verma [t.verma@tudelft.nl] with the email subject [MSc – Climate Change Brokering] and a CV (max 2 pages). This project will provide a lot of exposure in theory development/conceptualisation, programming and model building, data analysis and visualisation.

Modelling and measuring spatial accumulation of inequalities for people in cities

Urban Inequalities Modelling and Spatial Data Science

Studies of inequalities usually focus on identifying specific relations among urban sub-systems Meerow et al., 2016 using case-studies that uncover associations and in some cases, causal links among urban processes that shape inequalities. For example, some frontiers that emerged in the recent decade expand the notion of inequalities in specific domains (e.g., energy Robinson, 2019), highlighting hidden vulnerabilities among various populations associated with gender, age, race or disability and providing specific guidance to policymakers in making the distributional outcomes of their practice fair and inclusive. Evidence from different disciplines put together highlights the interplay among different factors in society, showing how inequalities scale superlinearly with size of populations or urban spaces, the benefits of investments are distributed unequally across income groups Sarkar, 2018, and such conditions continue to amplify across generations depending on one’s social networks Tóth et al., 2021. Despite the broader insights generated through empirical place-based studies in individual disciplines, so far the field is lacking a systematic analysis of the interlinked, intersectional and systemic accumulations of inequalities spanning dimensions of well-being across various urban systems (e.g., energy, water, transport, labour, housing, etc.) and spatial scales (e.g., household, neighbourhood and functional areas of movement).

The data-driven analysis in this research will focus on the cumulative, spatial and differential impact of inequalities associated with a person across three scales of living and movement: at home, within a neighbourhood, and while moving through the city. Using developments at CUSP on the conceptualisation of inequalities, we will develop, for the first time, a new empirical base of evidence on accumulation of multidimensional inequalities. First, we will set up several realisable hypotheses drawing associations of multiscalar and multidimensional vulnerabilities prevalent among certain social groups, and how might those be related with age and gender, markers of health, or the ability of an individual to participate in institutional and legal processes in the city. For example, older populations living on pension in peripheral neighbourhoods may be facing several deprivations: poorly built living environments, energy or transport poverty, inadequate access to important services, and in extreme cases be additionally vulnerable to impacts of climate change such as heat stress, sagging and flooding. Of this population, women and other non-male genders particularly face the maximum impact of all climate related vulnerabilities Neumayer et al., 2007, and such injustices are compounded by their under-representation in the labour force, indicating informality embedded in culturally sustained work like unpaid care Sudarshan et al., 2009. To account for such intersectional burdens Crenshaw, 2017 in the analysis, we will design a cross-scale spatial data landscape using geographic space as an anchor for information gathering and processing Franklin, et al., 2022. We will curate and embed the case-study’s (The Hague) specific datasets into this landscape, and subsequently analyse the nonlinear interdependencies in inequalities among its dimensions and across spatial scales to discern the implications it has for people and places in a city. Such an analyses can be used to answer questions of the sort: how do inequalities in accessibility to mobility infrastructure disadvantage a person on the basis of their income, home-ownership, gender identity and disability, specifically under different configurations of amenity distribution in urban space?

Scales of movement and inequalities.
Scales of movement and inequalities.

By building this landscape, and analysing the linkages among the different dimensions of inequalities across scales, this RL will bring novel insights into accumulation of inequalities among communities. However, any spatially-explicit measurements focus on administrative or arbitrary spatial boundaries. To standardise measurements delineating urban space and enable a spatially reasonable comparison, we will explore the nature of inequalities in an experimentation process across 3 sizes of spatial units (e.g., administrative boundaries of local authorities can be replaced with hexagons, and functional areas can be identified either as cities’ administrative boundaries or clustered by daily movement of people in and out of commuter zones.

If you are interested in this topic, please contact Dr. Trivik Verma [t.verma@tudelft.nl] with the email subject [MSc – accumulation of inequalities].

Defining, mapping and analysing the systemic and interconnected nature of inequalities

Theory and Co-creation Inequalities Well-being Indicators

Inequalities are shaped by a combination of several structural social, economic, environmental, and political factors, and a fragmented approach across disciplines and development of policy acts as a barrier for effectively dealing with their consequences. Transformative developments in the field of studying inequalities have largely been through systematic literature reviews Nijman and Wei, 2020, development of box-and-arrow frameworks around concepts essential to studying inequalities (ex. accessibility Geurs and van Wee, 2004, transport poverty Lucas et al., 2016 or energy poverty Robinson, 2019), empirical approaches in developing indicators [Xu et al., 2020, Lowe et al., 2022], moving beyond an economic lens to understand the distribution of infrastructure capabilities Pereira et al., 2017, and incorporating notions of equity and justice in evaluating social exclusion van Wee and Geurs, 2011. While excellent in their work, none of these frameworks support the view of how inequalities are systemically linked. Having a systemic view of the multifaceted phenomenon of inequalities will situate case-studies under appropriate systemic relationships and identify linkages across dimensions and scales of inequalities.

Thus, this thesis you will tackle the question: what are the different dimensions of inequalities that people face in an urban environment and how are they related to each other? In this thesis, through the lens of urban systems-thinking Meerow et al., 2016, you will co-create Lang et al., 2012 an integrated framework built upon the theory of social impact assessment (SIA) Vanclay, 2002. The SIA framework, when adjusted to an urban issue, constitutes the different social aspects of impact that might be faced by an urban population. These include, but are not limited to, health and well-being, quality of built-environment, economic and material well-being, cultural aspects, community relations, institutional and legal aspects, and gender relations. The research will draw on other case and place based studies of indicators measuring various forms of inequalities and identify how they fall into or expand the categories of SIA. To acquire knowledge about other forms of inequalities that do not fit into theoretical or empirical evidence bases, you will co-create and extend this framework to incorporate knowledge from stakeholders associated with the problem of inequality: namely by hosting participatory workshops for 3 case-studies in The Hague, The Netherlands; Delhi, India; and Sao Paolo, Brazil. (these can also be 3 cities in The Netherlands for ease of managing stakeholder participation). The goal is to use the framework as a deliberative tool - a boundary object Star et al., 1989 that becomes a point of focus for exchange of multiple social realities and perspectives - for eliciting knowledge crucial to every actor Dany et al., 2016, simultaneously staying well-defined yet adaptive. Your focus will be on The Hague where we will facilitate stakeholder deliberation workshops with policymakers in different sectors of mobility, health, energy, environment etc., community-led NGOs supporting citizen groups in urban commons or communal efforts, infrastructure developers and operators of social housing, transit and energy, and citizen representative groups from a specific region that faces the highest forms of inequality in the city. Due to lack of structured datasets available for the other case studies, they will be used only in part of the thesis, brokered through local academic and policy networks, to understand how various actors view the definition of inequalities proposed, and what is the scope for the framework’s adaptive use in different policy contexts. This will be followed by building a bipartite ontological mapping of indicators of the various social and economic impacts onto the different dimensions of inequalities identified in co-creation process. To identify existing indicators and develop new ones necessary to represent the dimensions of inequalities, we will use a well-established approach in environmental change research that uses multiple indicators for aggregating the extent of social vulnerability and assessing the ranking and spatial distribution of such indicators Cutter et al., 2003. Following the co-creating phase, we will use desk research methods and interviews with the stakeholders, and examine the data at the neighbourhood level (together with anopther thesis student) to identify specific or proxy indicators measuring inequalities.

This thesis will lead to a). developing an overarching conceptual framework for studying inequalities by expanding the scope beyond economic or wealth implications, and casting it as a multidimensional problem instead of tackling it across disciplines and sectors individually; b). a comprehensive translation and mapping of socio-economic indicators for which datasets are maintained by municipalities onto the ontologies of multifaceted inequalities; and, c) methodological insights into transdisciplinary co-creation of frameworks and its use and validation in other contexts.

If you are interested in this topic, please contact Dr. Trivik Verma [t.verma@tudelft.nl] with the email subject [MSc – systemic and interconnected nature of inequalities].

Disaster Antalya Earthquake Data Science

Climate change is causing a concerning increase in the frequency and severity of extreme weather events and natural disasters around the world. These events not only lead to human suffering and economic strain but also contribute to the perpetuation of climate change through the carbon emissions associated with disaster recovery efforts. While some disasters, like earthquakes, are not directly linked to climate change, the lessons learned from rebuilding in their aftermath can provide valuable insights for climate-resilient infrastructure development.

This master’s thesis project aims to investigate the intricate interplay between climate change, disaster impact management, economic consequences, and environmental sustainability. The focus will be on the economic and environmental tradeoffs that decision-makers must consider when investing in climate-related infrastructure and rebuilding after large-scale disasters. The recent earthquake in Southwest Turkey, which resulted in the destruction of approximately 70% of the city of Antalya, will serve as a case study.

This project is in collaboration with Colorado School of Mines, ETH-Zurich and TED University, Turkey. Your tasks will include (1) conducting a comprehensive literature review on climate change, disaster management, economic impacts, and environmental consequences of rebuilding efforts. Identify key theories, methodologies, and gaps in the current research. (2) Analyze data that was collected for Antakya, Turkey and enhance the database as needed to quantify the economic and environmental tradeoffs in the context of Antalya’s recovery efforts. (3) Calculate the carbon footprint associated with the rebuilding process in the aftermath of the Antalya earthquake. This assessment should consider emissions from construction, transportation, and other relevant activities. (4) Conduct a cost-benefit analysis to determine the economic implications of rebuilding versus investing in climate-resilient infrastructure before a disaster occurs. (5) Formulate evidence-based recommendations for policymakers and city planners.

Student would be required to have:

  • Good writing and communication skills for documenting your research and presenting your findings in an academic report.
  • Good data analysis and modeling skills, including tools for calculating carbon emissions.

If you are interested in this topic, please contact Nazli Yonca Aydin [N.Y.Aydin@Tudelft.nl] with the email subject [MSc - Disaster Recovery].

Approximating Accessibility of Regions from Incomplete Volunteered Data

Accessibility Bayesian Information Open-Source Datasets Data Science

Master Thesis or 10-EC Internship Project with HIIG (Berlin)

Being informed about the accessibility of neighbourhoods and cities can help persons with disabilities in making travel decisions. Such information can also aid the design of equitable urban policies. Wheelmap.org is a volunteer-backed website and app to mark places that are ‘wheelchair accessible’ on a map. The project has gathered information on the accessibility status of over one million ‘points of interest’ worldwide so far. 

While being tremendously successful, Wheelmap’s coverage is not exhaustive and contains (missing-information or selection-) biases stemming from volunteer practices. For example, in the state of Berlin, 45% of approximately 63,000 places have their wheelchair accessibility marked, among which 71% are accessible. In the Flevoland region of the Netherlands, on the other hand, only 4% of approx. 6,500 places have their accessibility marked, among which 96% are accessible. The different coverage rates makes comparing accessibility statistics between the regions challenging.

We are seeking a highly motivated master student—with a strong mathematics or computer science background—to research methods to resolve this measurement and approximation challenge. Our initial ideas are to make use of the ‘causal inference’ toolkit for handling selection-bias (references to this framework are available below) as well as conducting external validation with other data sources.

The project is a collaboration between the Humboldt Institute for Internet and Society (HIIG) in Berlin and TU Delft. The project is suitable as either a master thesis or an 10-EC internship and has a flexible start time.  A research visit to Berlin (the home of Wheelmaps) can also be arranged, if desired by the student, but it is not necessary.

If you are interested in this topic, please contact Trivik Verma [t.verma@tudelft.nl] with the email subject [MSc - Incomplete Access].


Integrating Nature-Based Solutions in Urban Environments: Evidence-Based Decision-Making for Resilience and Adaptation

Accessibility Bayesian Information Open-Source Datasets Data Science

The rapid urbanization of cities worldwide has presented an urgent need for the integration of Nature-Based Solutions (NBSs) to enhance urban resilience and climate adaptation. However, the constraints of limited urban space and the long lifespan of NBSs, especially green infrastructures, necessitate careful consideration and evidence-based decision-making when investing in these systems. Despite the growing recognition of NBSs’ benefits, there remains a lack of comprehensive guidelines for decision-makers to effectively implement them and leverage evidence-based insights. Furthermore, cities are experiencing ongoing spatial changes, with certain functions phasing out and others rebuilding. Urban regeneration theory offers a potential avenue to address these dynamics while integrating NBSs into the urban fabric.

Overall aim of this project is to provide a comprehensive framework for decision-makers, urban planners, and policymakers to make informed choices regarding the integration of NBSs in urban environments. This project will tackle challenges stemming from limited space and the long-life span of green infrastructure. It will harness urban regeneration theory and spatial data analysis to guide decisions on what and when to implement NBSs within urban landscapes, with the goal of maximizing benefits and minimizing spatial and social trade-offs.

To accomplish this, this research project has four main objectives. First, it aims to assess the existing urban landscape, identifying areas within the city where NBSs can be strategically integrated while taking into account space constraints, social and long-term impacts of green infrastructure. Second, the project will delve into urban regeneration theory, analyzing how its principles can be applied and improved effectively to facilitate the integration of NBSs within evolving urban landscapes, particularly in areas where certain functions are phasing out and others are undergoing redevelopment. Finally, the research intends to develop a framework that synthesizes urban regeneration theory with evidence-based decision-making, offering support for decision-makers, urban planners, and policymakers to promote the integration of NBSs and to enhance urban resilience and climate adaptation.

Ultimately, this project will leverage spatial data analytics methods and contribute to the sustainable development and resilience of cities in the face of evolving challenges.

Student would be required to have:

  • Good writing and communication skills for documenting your research and presenting your findings in an academic report.
  • Good spatial data analysis and modeling skills.

If you are interested in this topic, please contact Nazli Yonca Aydin [N.Y.Aydin@Tudelft.nl] with the email subject [MSc - Disaster Recovery].