The urgent need for a just transition in housing in Germany, to reduce the global environmental impacts and mitigate the risks of green colonialism, requires the development of policies that enable sufficiency. In the housing sector, this primarily involves reducing floor area per person to significantly decrease energy demand. Research in this field has focused on core principles needed for a sufficiency transition, taking a universalistic and global approach. Sufficiency modelling has been limited by a restricted understanding of sufficiency implementation and feasibility. Furthermore, scholars have neglected the need for differentiation between households living in very unequally distributed living spaces. Research investigating country-specific political and policy environments that allowed for the emergence of high floor area per person households is lacking for almost all regions. Thus, academic policy proposals are often too general, not tailored to households with the largest floor areas, and do not consider regional historical policy contexts. In this thesis, I aim to address this gap, using a mixed-method approach to comprehensively understand
the German housing context for meaningful policy recommendations. With an agglomerative hierarchical clustering algorithm, I identify households with the highest floor area per capita, characterized as single, without children, older, living outside large cities, residing in (detached) single-family houses, owning their homes, having low incomes, and located in West Germany. The historical driver analysis reveals the influence of capitalist, market-oriented policies, which promoted home ownership as retirement security to decrease provisioning by the state. These policies included subsidies favouring ownership and single-family houses, as well as large-scale privatization and financialization, shifting the housing sector’s focus to (international) investor profits rather than providing affordable and sufficient living space for all. Current policies miss the opportunity to redistribute floor area and hinder the flexible matching of housing supply and demand. Taking into account the identified target households and the historical context, a final critical reflection on existing policy proposals enriches the future design of sufficiency-enabling policies for the German housing sector and allows for a more accurate quantification of the impact reduction potential. This social science perspective allows sufficiency and industrial ecology scholars to situate their research in the German context and gain a deeper understanding of the historical drivers and enablers for sufficiency application.

This thesis explores the relationship between urban fragmentation and the spatial segregation of non-EU immigrant communities in Europe. While previous research has linked infrastructural barriers to ethnic group boundaries in American cities, this study argues that such findings cannot be universally applied due to unique historical contexts in different regions. The study aims to not only identify connections between urban fragmentation and segregation but also to contextualize these connections within the local dynamics of various European cities. We employ a mixed-method approach. The quantitative component involves constructing spatial patterns of urban fragmentation using OpenStreetMap data and segregation patterns using data from the European Commission's Data for Integration (D4I) initiative. These patterns are compared using mutual information to assess their similarity. Synthetic urban fragmentation patterns are also generated to ensure observed similarities are not the result of random chance. The qualitative component involves examining the local contexts of selected cities to understand the specific factors influencing segregation. From the 106 cities analyzed, only 33 showed statistically significant relationships between urban fragmentation and segregation patterns, with 26 showing positive and 7 showing negative correlations. These findings indicate that the relationship between urban fragmentation and immigrant segregation is not a generalizable phenomenon in Europe. The city-level analysis of nine cities across seven countries reveals that factors such as urban decay and housing quality, rather than infrastructure, are more closely associated with immigrant concentration. Future research should investigate segregation patterns among other social groups and explore broader impacts of infrastructure on vulnerable populations beyond urban fragmentation.

The urgency of the climate crisis emphasizes the importance of reducing greenhouse gas emissions, a goal that cities intend to achieve by developing their cycling infrastructure. However, sustainability includes social equity, and transport has been shown to play a role in reinforcing urban inequalities. This study seeks to understand how cycling infrastructure can be developed to reduce greenhouse gas emissions and urban inequalities by assessing emerging equity-induced trade-offs in prioritizing cycling projects within the Grand Paris Metropolis, France. By combining automated identification of cycling infrastructure gaps with equity frameworks, this research identifies shifts in the prioritization of infrastructure projects based on degrees of equity emphasis. The focus lies on vulnerable populations, specifically children commuting to school coming from neighborhoods with lower educational attainment and adults commuting to work from neighborhoods with lower median income. The outcomes reveal that introducing equity considerations impacts the order of importance of infrastructure projects, though the overall trajectory remains intact, suggesting that integrating equity into transport planning is an achievable goal.

Flooding, one of the costlier climate change disasters, has emerged as a pressing global challenge, growing in frequency and severity. The traditional reliance on government intervention alone to protect households from flooding is not enough. An essential shift in perspective underscores the need for households themselves to become proactive participants in multi-level protection strategies. To achieve this, drivers of vulnerability shaping household adaptation to flooding are explored, focusing on social, physical and perceived vulnerabilities. Furthermore, examining these vulnerabilities on a local scale is crucial and a knowledge gap, as it is at this level that household adaptation predominantly occurs.

Recognising the varying manifestations of these vulnerabilities depending on the flood-prone location, this study prioritises the examination of disparities in vulnerability profiles between two representative cities: Jakarta, representing the Global South, and Houston, representing the Global North. By doing so, this research contributes significantly to the ongoing scientific discourse on climate change adaptation, as well as assist in extrapolating gained insights to data-scarce regions. This research aims to assists in aligning flood management efforts more closely with the needs and concerns of the residents in each city, acknowledging the distinct perceptions of flood hazards and socio-economic disparities. This, in turn, lays the groundwork for the development of targeted support and interventions, fostering more inclusive and resilient communities capable of mitigating the impacts of flooding and adapting to future challenges. The primary research question driving this study is as follows: 'How are social, physical and perceived vulnerabilities that influence flood adaptation different among households in an urban space?' To answer this question comprehensively, the research employs a multi-faceted approach, examining each vulnerability dimension separately before exploring their interactions in the urban context.

Comparing the social, physical and perceived vulnerability maps for Jakarta in the context of flooding uncovered many discrepancies and complexities that contribute to the scientific debate surrounding flood adaptation. The disparities between these dimensions highlight the need for a comprehensive approach to vulnerability assessment and flood mitigation. By recognising that vulnerability is not solely determined by physical factors, but also influenced by social dynamics and individual perceptions, authorities can develop strategies that foster community resilience and enhance disaster preparedness. Therefore, this research recommends addressing mismatches in risk perception, understanding the nuanced distribution of vulnerabilities and implementing context-specific interventions in order to build a safer and more resilient world in the face of flooding and other environmental challenges.

Accessibility is a fundamental concept concerning urban and transport planning as it is the elementary basis for socio-economic development in cities. It can be described as the potential to reach spatially distributed opportunities. Recent research has identified that excluding person-based features from this analysis might cause inaccurate measurement of accessibility. Age, gender, and income, for instance, are responsible for varying accessibility levels drastically. In addition, studies worldwide have shown that women face different challenges in reaching locations and spatially distributed opportunities. Despite the findings, this research identifies a gap in understanding how a person-based perspective, mainly gender, and other personal characteristics, affect accessibility levels, considering various travel purposes and transport modes. Thus, this research aims to answer the question, ”How do person-based characteristics, mainly gender, can impact accessibility levels?”. The primary objective is to explore how these characteristics influence accessibility metrics, identify the urban groups most affected by the absence of this perspective, and determine the key personal characteristics that significantly impact accessibility levels. To address these objectives, this study considers a combination of quantitative and case-study research approaches. It investigates the Metropolitan Region Rotterdam- The Hague in The Netherlands by applying surveys to obtain perceived accessibility data. In the same region, spatial analysis is conducted by mapping transport networks and points of interest. Then, this study compares spatially calculated accessibility with self-reported accessibility and the presence of mismatches. In addition, cluster analysis identifies the urban profiles most vulnerable to mismatches and their main characteristics. A Binary logistic regression is conducted to determine the variables’ importance in the mismatch occurrence. From the survey answers, it is identified that women have less access to cars than men. In addition, the comparison between perceived accessibility and spatial accessibility uncovers that women present the most critical mismatches to reach activities by car. In other words, several women perceive the car as an impractical option to access points of interest that are spatially considered reachable by car. It raises the hypothesis that the lack of car access highly impacts their accessibility perception. Furthermore, the clustering analysis reveals that foreign women exhibit a higher prevalence of car-related mismatches when compared to other urban groups. Moreover, this research identifies that fathers of young children also encounter greater disparities across all transportation modes. Additionally, the binary logistic regression underscores the importance of safety as a critical factor influencing women’s perception of walking as a viable mode of transportation. This safety importance is also identified from the survey answers. The findings raise new hypotheses that warrant investigation in transport engineering, urban planning, and social sciences. Consequently, this research can contribute to developing more inclusive transport policies and establishing a more equitable transport system.

In today’s world, the transport system is essential in helping people reach the activities they want or need to attend. However, like in many other fields, inequality can exist in access to various opportunities based on personal characteristics. Little is known about how gender and intersectional factors impact people's perceived accessibility. This thesis aims to fill this knowledge gap using a mixed methods approach. First, desk research shows that perceived accessibility can be influenced by a large variety of factors, including, but not limited to, the primary mode used, perceived safety in transport and socio-demographic factors. Second, Structural Equation Modelling is used to investigate the strength of relationships between the various found factors and gender intersectional factors. This analysis shows that being a woman has a negative effect on perceived accessibility, which can for a part be explained by women feeling less safe in transport at night. Additionally, the analysis shows that for women having young children negatively impacts perceived accessibility, but not for men, while for men income positively relates to access to a car and in turn to perceived accessibility, an effect which is not found for women. Finally, the subsequent qualitative analysis, using workshops, shows that little attention has been paid in the past to (social) safety issues in transport and to differences in needs between different kinds of travellers. In the future, more cooperation between transport institutions and integrated intersectional policymaking in transport would be of significant value.

Transport decision-making determines people’s level of accessibility and deeply influences an individual’s access to social and economic opportunities and the quality of life. Socially vulnerable populations are highly dependent on yet often more likely to have less access to transport services and experience lower accessibility. This creates and reinforces social and spatial inequalities by trapping people in disconnected neighborhoods and segregated areas that continue to be deprived of access to opportunities. This research aims to develop a Spatial Decision Support System (SDSS) to explore how re-purposing existing streets for walking and biking could influence the accessibility of vulnerable neighborhoods to support decision-making in enhancing equity of accessibility.

In the SDSS, equity of accessibility is formulated as a generative design (GD) problem, named the Street Allocation Decision Problem (SADP), a single-objective optimization problem that searches for generated designs with the maximum weighted improvement in accessibility per unit of its cost. A GD model is built to solve SADP. Lastly, an operational framework is developed to guide prospective users in tuning and operating the SDSS for their specific context, problem, and objective.

The SDSS is tested on a toy problem, a 0.09km2 area in The Hague, The Netherlands. The toy problem is small in scale, easy and fast to implement and useful for initial testing of the model. Preliminary results have demonstrated the feasibility of the model. This is the first and humble attempt at developing an SDSS for enhancing equity of accessibility with a GD model. However, there are shortcomings in methodology and result quality, which compromise the practicality of the model and the interpretability of results. Although, only a proof of concept at the moment, the SDSS is a valuable starting point due to its advantages, such as transparency, modularity, humane-ness, and flexibility. This SDSS is built to involve decision-makers in the design process, which could serve as a useful learning experience for questioning and understanding what is the problem, what is considered equitable, and what are possible solutions. The SDSS has the potential to facilitate learning during transport decision-making in experimental settings or as explorative aids in early design stages.

This research uses high resolution satellite images in combination with an unsupervised Convolutional Neural Network Autoencoder to identify features that can be used to cluster different built environment typologies. Previous remote sensing research uses ground truth data which for some areas is not available or needs manually labeled training data. This research attempts to circumvent the issue of information scarcity in order to create a methodology that can be applied on any city as long as satellite images are available. From the resulting clusters, clusters can be selected which represent areas with high levels of deprivation which in turn can help identifying the deprived areas.

Densification, the increase of built environment elements in urban areas, has been identified as a tool to mitigate social and environmental consequences of urban sprawl, i.e. the continuous extension of urban boundaries and dispersed construction of built-up areas.
At the same time, unique environmental and social challenges are requiring urban developers to adapt their approaches to changed long-term or short-term physical conditions while considering the social consequences.
Many cities around the globe, and amongst them Amsterdam, The Netherlands, are striving to align urban interventions in the field of densification and climate action. This led to the research question: Which social impacts arise from simultaneous urban densification and climate action in the form of climate change adaptation and the energy transition?
This study provides insight into the current knowledge in scientific literature and the perceptions of urban policymakers. A qualitative mixed methods approach was applied. The approach was constituted of a systematic literature review and semi-structured interviews. A social impact framework was combined with an understanding of the natural sciences, engineering and urban planning to assess the social impacts of urban densification in times of climate action.

I first collected the current literature at the interface of urban densification, the energy transition and climate change adaptation to compile the perspective of academic literature in a knowledge base.
Secondly, I conducted semi-structured interviews with urban policymakers of the Dutch capital of Amsterdam to gain insight into the perspective of policymakers. In the analysis of both my data sets, I discerned explicitly mentioned social impacts as well as social impacts which were not explicitly stated, but could be reasoned from the collected literature and the conducted interviews.
Finally, the comparison of both perspectives shows a strong prevalence of social impacts in the spheres of livability in the built environment, health and economic relations. How densification, the energy transition and climate change adaptation exert consequences on communities and institutional relations is much less observed at the current state. Lastly, impacts on cultural or gender relations are close to absent from the discussion - in academic literature and the perceptions of urban policy-makers in the case study alike.
While the results are largely connected to the conceptualisation and methods applied, implications can be drawn for future research and policy-making. It is essential to explore the origins of the low occurrence of cultural and gender impacts in the data set to evaluate whether these are due to knowledge constraints or actual low impact rates. But, given the understandings gained, I urge to observe these spheres more strongly, in particular in relation to indirect social impacts. Moreover, the case study shows that social impacts of densification and climate action transitions are highly context-driven. They are subject to questions of ownership, human behaviour, urban inequalities and social differentiation within the constraints of physical space and monetary as well as environmental budgets. Additionally, it is indispensable to further strengthen the interaction and communication between researchers, policy-makers and other stakeholders.

In India the COVID-19 pandemic resulted in a nationwide lockdown from March 25, 2020 till the end of May 2020. During this time public and private transportation activities were limited, economic activities came to a standstill and healthcare resources were redistributed. India’s healthcare system faced problems prior to the COVID-19 pandemic such as insufficient availability, suboptimal healthcare services and high out-of-pocket expenditures. The exponential rise in patient care during the COVID-19 pandemic exacerbated existing problems in the Indian healthcare system while introducing new ones. Realizing optimal care during the health crisis became more challenging as the focus was on mitigating the spread of the virus. The absent of public transportation and the pressure on healthcare resources impacted the healthcare accessibility of different demographic groups. During this study we assessed how access to healthcare was influenced due to the policy interventions that were meant to mitigate the spread of COVID-19. The hypothesis is that healthcare access for different demographic groups was negatively impacted by the policies meant to curb the spread. In order to analyse the impact, we performed a case study in the state of Goa using the Network-based Health Accessibility Index Method (NHAIM). This gravitational model allows us to study the spatial distribution of healthcare resources in the state of Goa. Based on our findings we can conclude that healthcare access is unevenly distributed in the state of Goa. Furthermore, we concluded that there is no significant correlation between healthcare availability and the urban and rural mortality rate for the state of Goa. However, there is a significantly strong positive correlation between geographical healthcare access and the urban and rural mortality for the state of Goa.

We find ourselves at a crossroads; without immediate and deep emissions reductions, limiting global warming to 1.5 degrees Celsius will be impossible. For the Netherlands to achieve its climate targets, Dutch municipalities have been delegated the crucial task of the heat transition. Prior research reveals that the Dutch energy transition and policy documents are often techno-economic centred and hardly stress citizens’ central role. However, it remains a thoroughly social affair as changes in energy technologies are accompanied by societal ramifications, and the exclusion of social aspects (public support and energy justice) has detrimental societal effects. This research aims to evaluate the impact of including social information in the information provided for the decision-making process on decisions made by local Dutch policymakers for the heat transition.

Central to this thesis was the following main question: “What is the impact of including social information in the information provided for decision-making processes on the social responsibility of policymakers’ decisions for the heat transition?”. To assess this impact, interviews were conducted, and a 1x2 between-subjects experiment was set up where participants were randomly allocated to one of two conditions: group A: exposure to only technical and economic information, and group B: exposure to technical, economic and social information. With a Mann-Whitney U test, it was determined whether there were differences between the two groups.

The results of this study indicated that the inclusion of social aspects leads to more socially responsible decisions in the heat transition for nine out of 20 neighbourhoods, meaning that neighbourhoods with specific social characteristics are prioritised more than after including this information. These neighbourhoods often had extreme values for the social indicators. For example, neighbourhoods with high public participation or support were prioritised more. Future research should study which social factors increase residents’ participation or public support so policymakers can meaningfully include such social indicators for heat transition decision-making. Another interesting finding is that many policymakers (and therefore municipalities) seemed to have diverging approaches to the heat transition. Future studies should research what causes these differences between municipalities by focusing on personal (of the policymaker) or organisational (of the municipality) characteristics.

In the wake of tackling energy poverty by its roots and protecting vulnerable groups, the European Commission introduced the so-called Renovation Wave, aiming to renovate 35 million inefficient buildings by 2050. However, even though the Renovation Wave was aimed to tackle energy poverty, recent studies have shown that renovation policies have failed to address energy poverty as renovation and social policies lack intersectoral integration resulting in the exclusion of vulnerable groups and an increased risk of social inequity. Moreover, various scholars have tried to identify vulnerability indicators that give rise to energy poverty; however, these have only focused on identifying socio-
economic and energy indicators. Consequently, scholars have called to include justice in renovation policies and explore how vulnerable groups can be identified. To address this knowledge gap, the following main research question was formulated:

Using a Case-Study Mixed Methods (CS-MM) approach, how can justice be included in renovation policies considering the socio-spatial vulnerability to energy poverty?

The results showed that by identifying vulnerable groups based on a locally developed index of the socio-spatial vulnerability to energy poverty and acknowledging their vulnerability, recognitional justice can be included in renovation policies. Besides, identifying tailored policy strategies in a multi-stakeholder environment that, on the one hand, focus on the distribution of renovation resources based on the needs and characteristics of the identified vulnerable groups and, on the other hand, on how the vulnerable groups can be included in the decision-making, distributional and procedural justice can be included in renovation policies. Thus, it can be concluded that by deploying the current CS-MM approach, justice can be included. 
The outcomes of the present study are twofold. Firstly, from a scientific perspective, the present study contributes to the current body of scientific knowledge on: (1) how vulnerable groups in need of renovation can be identified, (2) how justice can be included in renovation policies to address energy poverty and (3) how a CS-MM approach can be deployed to research how justice can be included in renovation policies considering the socio-spatial vulnerability to energy poverty. Secondly, from a societal perspective, this study provides insights to improve policy strategies that enable local decision-makers to identify vulnerable groups and include justice in renovation, considering the socio-spatial vulnerability to energy poverty.

As the effects of climate change are more and more materializing around the globe it is ever more important to reduce our reliance on a fossil fuel based energy system. When coupling this to an ongoing trend of urbanization in many places across the world, the energy systems of our cities become of particular interest. However, the transition away from a fossil fuel based system towards a renewable energy based system is a complex sociotechnical process that in part relies on the extent to which households are able to adopt energy efficient technologies. Not all households are equally capable of investing in these technologies, causing some households to have better access to participate in the renewable energy transition. This unequal access to the renewable energy transition causes an unequitable distribution of energy efficient technologies and could potentially lock-in or perpetuate current injustices. To prevent this from happening there is a need for energy policy that supports socioeconomic groups across society, that have inadequate access to the renewable energy transition. In order to design such policy it is essential to first of all identify who these groups are, and secondly where they are located. As the renewable energy transition is still in its early stages, these insights are currently lacking in literature.

Considering the fact that solar PV is a major driver of the renewable energy transition, this thesis in part addresses this knowledge gap by spatially analyzing which socioeconomic groups in the urban environment lack access to solar PV and where these groups are located. Access to solar PV in this context is defined as: the freedom of individuals or households to decide whether or not to adopt residential solar PV energy resources, dependent on the existence of one or more barriers. Secondly, does the research assess how access to solar PV resources spatially intersects with the ability to generate solar energy through these resources. The location that is selected as the area of study for this research is the city of The Hague, Netherlands. A framework is constructed to assess access to solar PV using the Theory of Planned Behavior originating from social sciences, which is frequently used to model adoption behavior of novel energy technologies. To evaluate the technical PV potential of the case-area the ArcGIS Solar Analyst Tool is applied. A K-means clustering analysis is performed to find any meaningful patterns in the distribution of access to solar PV across the area of study.

The key findings of this study are:
•Access to solar PV resources is unequally distributed across the Hague. Large parts of The Hague have unfavorable characteristics for solar PV adoption.
•The highest levels of technical PV potential are found in areas that are considered to have poor access to solar PV. As a consequence, currently the majority of technical PV potential within the case area is likely to remain unexploited due to poor access to solar PV within these areas.
•There is a need for energy policy that focuses on the groups that have poor access to solar PV and are unserved by current energy policy focused on stimulating adoption of solar PV. These groups are non-home owners in the private rental sector, home-owners that share ownership of the roof of a shared building and households that are provided housing by social housing corporations.

Further research could focus on exploring and evaluating policy design that is aimed at supporting socioeconomic groups that currently lack access to the renewable energy transition. This is important in order to ensure that the renewable energy transition makes its way throughout all layers of society.

More and more research shows the substantial health repercussions
of air pollution. Therefore, improving air quality is high on political agendas in modern societies. In the Netherlands, particularly around major roads, NO2 standards set by the government are often exceeded. Air quality models are used to monitor air quality values and design policies to reduce air pollution. Currently, authorities in the Netherlands use a Gaussian Plume Model for decision-making, but this model paints a rather skewed view of reality due to
its underlying assumptions. This research contributes to academic
knowledge about air quality modelling by evaluating two innovative model types, a physics-based LES model and a data-driven regression model, for their usage in decision-making to improve air quality. This is done by comparing the performance of both models with the performance of a Gaussian Plume Model for predicting NO2 levels around a large highway in the Netherlands. Also, two
combinations of the LES model and the regression model are examined. It is concluded that both the LES model and the regression model show potential for accurately predicting air quality around highways in the Netherlands. The LES model is particularly suitable for predicting high NO2 levels, and the regression model is considered suitable for predicting the average NO2 levels over a longer timeframe. A model in which the LES results were combined with a
regression model outperformed the original models and is therefore considered to hold the most potential for usage within air quality
policy.

Cities around the world constitute complex systems, as sets of sub-components that are connected and interact with each other. Due to this inherent complexity, there are numerous emerging challenges that need to be tackled. In those complex environments, various-interest groups collaborate and compete to achieve their goals and interests, constituting a vital part of urban planning. The advancement of technology and ICT, and the abiding need to keep citizens engaged, marked a critical shift in the way that urban planning confronts the increasingly contemporary complex issues. This advancement has offered citizens a way to digitally participate in urban planning procedures, overcoming certain limitations, while posing, also, challenges related to the level of its effectiveness.
While many methods and tools have been developed over the years, for enhancing citizen engagement and the effectiveness of public participation, there seems to be an evident gap in substantial and two-way collaboration among the (relevant) urban stakeholders. This thesis project aims to hark the perspectives and needs of the urban stakeholders, translating them into a conceptual design of a digital public participation platform. Next to that, except for the importance of the platform itself, as a tool, the focus was also given to participation, as a process, considering that such a platform could and should act as a promoter of effective public participation rather than a stand-alone solution. Consequently, the main research question of this study is: Which characteristics need to be included in designing a public participation platform so that it can enhance citizen engagement and facilitate more effective public participation in urban planning?
For this research, a design science research approach was chosen. A theoretical background was developed on existing theories, methods and frameworks related to public participation and digital platforms. Data collection was conducted using multiple methods, including workshops, semi-structured interviews, and questionnaires, while data analysis was conducted inductively, to identify all the emerging patterns and their interrelations.
From the data analysis, five core themes emerged: General findings; (De)Motivational factors for public participation; Characteristics; Technical requirements; Technological features. Retaining these themes, the analyzed results were then critically synthesized, both in qualitative and quantitative terms, to provide a holistic overview.
Combing the obtained results, the main research outputs were developed, providing an overall answer to the main research question. First, a trifold validation of the results, related to the past, present, and future, was conducted, fulfilling the rigor and design cycle of the design science research, and attaining a continuous assessment. Building upon the evaluation results, for the platform as a tool, a conceptual design was developed, based on the different views of the urban stakeholders. For the process of public participation in general, a set of guidelines was developed, providing recommendations on how to enhance citizen engagement and the effectiveness of public participation, based on the different views of the urban stakeholders.
This thesis concludes with some important final remarks, including limitations, recommendations for future research, research relevance, and the author’s final reflections on the research.

As the urban population grows worldwide and cities are becoming increasingly unequal and segregated, Urban Commons emerge as a potential driver of inclusion and resilience for city dwellers. According to Feinberg et al. (2021), Urban Commons can promote social, environmental, and economic resilience, and Park et al. (2020) suggest they can act as a haven for the excluded. Commons could, therefore, become a policy alternative to address the grand urban challenges of the 21st Century.
However, it is still unclear whether the benefits of Urban Commons are ultimately accessible to the culturally and socioeconomically vulnerable. For instance, in a literature review study, Huron (2017) found significant uncertainties in how Urban Commons relate to feminism, race, gender, and ethnicity – factors that could constitute immaterial barriers of access, following Vrasti & Dayal’s (2017) terminology. In fact, while several studies have investigated the commons’ role in promoting urban justice, explorations of whether access to the commons itself is just have been neglected.

This master’s thesis explores what constitutes material and immaterial barriers to accessing Urban Commons to understand whether these initiatives can work, policy-wise, as a driver of social inclusion. 29 Urban Commons in Amsterdam were selected as a case study. A quantitative geo-spatial analysis was conducted to evaluate the material accessibility to each initiative. In parallel, commoners were surveyed about their perception of immaterial barriers and benefits of commoning. Finally, a representative of the municipality of Amsterdam was interviewed to assess the potential challenges and benefits of policies involving Urban Commons.

Concurring with Park et al. (2020), the case study findings suggest commons could indeed promote social inclusion. Moreover, it was also found that the excluded could face, in addition to the initially proposed material and immaterial walls, an ecosystem barrier to access commons. Yet this could be addressed from a policy standpoint with the development of a commons ecosystem that is capable of scaling the benefits of commoning across an entire city.

The results have academic and societal relevance. This study provides a new theoretical framework to research the factors influencing access to commons and also contributes to literature with a unique city-wide case study. It can also function as a reference for policy-makers who wish to learn about the commons landscape in Amsterdam and who interested in understanding the factors that contribute to participation in a commons.

More and more people are living in cities. As these cities grow, the benefits of living in them are increasingly unequally distributed. One factor that can turn the tide of glooming urban inequality is equitable access to opportunities. Designing policies for equitable access requires taking into account several components that impact accessibility: (i) land-use, (ii) transportation, (iii) individual needs and opportunities, and (iv) temporal constraints. In this research, the interaction between a novel mode of public transport, microtransit, and the first three components of accessibility is investigated. The accessibility implications of microtransit in the case study area: the Southern suburbs of the Minneapolis-St. Paul metropolitan, are assessed. It is concluded that microtransit manages to reach vulnerable rider groups and interacts with the land-use environment by pairing residential areas with commercial centers. Microtransit also interacts with other modes of transit by adding both extra demand and lowering the demand for ride-hailing and personal car use predominantly. Microtransit rarely seems to replace public transit or walking alternatives. Overall, it is found that microtransit does significantly increase accessibility levels in the case study area and especially impacts groups with low car ownership. Lastly, the benefits of microtransit are more fairly distributed than those of traditional transit in the studied area. This research demonstrates the positive access equity impact of microtransit and suggests further research into choice-riders, the application of microtransit in urban (core) and rural environments, and the interplay between public transit and microtransit, as well as policy interventions for policy-makers and transit providers.

in this research, I study the Nitrogen Crisis by comparing Twitter content to real-life events, answering the following research question: How does the intensity of emotions and discussed topics on social media relate to the characteristics of real-life demonstrations during a sustainability policy crisis? To characterise online events, sentiment analysis and topic modelling are applied to analyse tweets about the nitrogen crisis to paint a picture of what subjects were discussed online, and how people are feeling about them. To characterise offline events, a codebook is developed with categories that reveal information on the scale, intensity and extremism during real-life demonstrations. The most promising finding is that topic models with higher numbers of topics but lower coherence scores prove to be more interesting sources of information on underlying topics and trends on Twitter.