M. van Ham
info
Please Note
<p>This page displays the records of the person named above and is not linked to a unique person identifier. This record may need to be merged to a profile.</p>
166 records found
1
...
The Problem of Uncertain Contextual Characteristic (PUCC)
Does it matter how contextual poverty is measured for the neighbourhood effect estimation?
This paper investigates the sensitivity of neighbourhood effect estimates to the operationalization of contextual poverty. It introduces the Problem of Uncertain Contextual Characteristic (PUCC), which refers to uncertainty surrounding what is measured and represented when constructing contextual variables, potentially resulting in estimation bias. Using longitudinal micro-data from Dutch population registers (2011–2020), we assess four key parameters when operationalizing poverty: poverty dimensions, reference groups, poverty-line thresholds, and aggregation statistics. We undertake a systematic analysis modelling the effect of each poverty indicator while keeping all other factors constant. We also generate models including different residential context scales and geographies to compare the effects of PUCC with other sources of estimation variation. Results show that the operationalization of contextual poverty substantially influences the estimated neighbourhood effects on individual income. In our analyses, the operationalization of contextual poverty introduced greater variation than the residential context’s scale or the geographical extent of the study. Findings further suggest that PUCC and the Modifiable Areal Unit Problem (MAUP) are closely related, as the impact of contextual poverty measures varies significantly across spatial scales.
...
This paper investigates the sensitivity of neighbourhood effect estimates to the operationalization of contextual poverty. It introduces the Problem of Uncertain Contextual Characteristic (PUCC), which refers to uncertainty surrounding what is measured and represented when constructing contextual variables, potentially resulting in estimation bias. Using longitudinal micro-data from Dutch population registers (2011–2020), we assess four key parameters when operationalizing poverty: poverty dimensions, reference groups, poverty-line thresholds, and aggregation statistics. We undertake a systematic analysis modelling the effect of each poverty indicator while keeping all other factors constant. We also generate models including different residential context scales and geographies to compare the effects of PUCC with other sources of estimation variation. Results show that the operationalization of contextual poverty substantially influences the estimated neighbourhood effects on individual income. In our analyses, the operationalization of contextual poverty introduced greater variation than the residential context’s scale or the geographical extent of the study. Findings further suggest that PUCC and the Modifiable Areal Unit Problem (MAUP) are closely related, as the impact of contextual poverty measures varies significantly across spatial scales.
Journal article
(2026)
-
H. Veloso e Zárate, M. Triggianese, Arend van Waart, Alexander Forsch, J.E. Stoter, M. van Ham
In the urgent context of climate change, embodied carbon data has become critical to the decarbonization of the built environment. This research examines the integration of embodied carbon assessment into urban design practice, with a focus on early-stage design. Based on a 3-month practice-based case study in a Dutch architecture office, the study identifies persistent challenges in applying Life-Cycle Assessment (LCA) at the urban scale, including the definition of system boundaries, reconciliation of heterogeneous levels of detail, and communication of data omissions. The findings reveal abductive reasoning, visualization, and tacit knowledge enable designers to transform fluid design artefacts into workable protocols—what is here defined as designerly ways of decarbonizing. The study redefines early-stage design as an operational category for carbon assessment and demonstrates the codification of tacit knowledge in data-enabled tools, advancing understanding of design processes in the low-carbon transition.
...
In the urgent context of climate change, embodied carbon data has become critical to the decarbonization of the built environment. This research examines the integration of embodied carbon assessment into urban design practice, with a focus on early-stage design. Based on a 3-month practice-based case study in a Dutch architecture office, the study identifies persistent challenges in applying Life-Cycle Assessment (LCA) at the urban scale, including the definition of system boundaries, reconciliation of heterogeneous levels of detail, and communication of data omissions. The findings reveal abductive reasoning, visualization, and tacit knowledge enable designers to transform fluid design artefacts into workable protocols—what is here defined as designerly ways of decarbonizing. The study redefines early-stage design as an operational category for carbon assessment and demonstrates the codification of tacit knowledge in data-enabled tools, advancing understanding of design processes in the low-carbon transition.
Journal article
(2026)
-
Maha Habib, Doruntina Zendeli, Marjolein van Esch, Wim J. Timmermans, Maarten van Ham
Residential environments are central to addressing urban heat stress for vulnerable populations and are prime target areas for implementing climate adaptation strategies. The reliance on urban heat island (UHI) intensity mapping alone has been argued to provide limited guidance for adaptation efforts, whereas linking heat patterns to the built environment characteristics through frameworks such as Local Climate Zones (LCZ) provides actionable insights for developing neighborhood cooling strategies. However, the widely used LCZ maps have a few limitations, such as misrepresenting variation within types because they cannot account for sub-classes beyond the standardized framework. This paper presents an unsupervised clustering approach to identify residential typo-morphologies across 99 Dutch cities, enhancing their relevance for urban heat vulnerability assessments. The analysis reveals that five morphological and canopy parameters (FSI, GSI, OSR, Havg, and FVC) selected from 17 parameters are sufficient to identify nine distinct residential typo-morphologies relatable to LCZs within 100 m × 100 m grid cells. The evaluations demonstrate that our approach detects underrepresented LCZ types and reveals new sub-classes absent from standard LCZ classifications. Key findings include detection of high-density areas (LCZ 42) reflecting recent urban densification with one of the highest UHImax next to LCZ 2 (4.2–4.9 K), and vegetation-differentiated variants within sparse and low-rise categories LCZ 9D and LCZ 6D, distinguished by distinctive UHImax (0.5–0.7 K) higher compared to their reference base types. Notably, tree coverage remains low across low-rise and compact typo-morphologies, revealing substantial opportunities for greening interventions. This data-driven refinement preserves LCZ's global comparability while considering local specificity, providing improved frameworks to inform targeted climate adaptation strategies in residential environments.
...
Residential environments are central to addressing urban heat stress for vulnerable populations and are prime target areas for implementing climate adaptation strategies. The reliance on urban heat island (UHI) intensity mapping alone has been argued to provide limited guidance for adaptation efforts, whereas linking heat patterns to the built environment characteristics through frameworks such as Local Climate Zones (LCZ) provides actionable insights for developing neighborhood cooling strategies. However, the widely used LCZ maps have a few limitations, such as misrepresenting variation within types because they cannot account for sub-classes beyond the standardized framework. This paper presents an unsupervised clustering approach to identify residential typo-morphologies across 99 Dutch cities, enhancing their relevance for urban heat vulnerability assessments. The analysis reveals that five morphological and canopy parameters (FSI, GSI, OSR, Havg, and FVC) selected from 17 parameters are sufficient to identify nine distinct residential typo-morphologies relatable to LCZs within 100 m × 100 m grid cells. The evaluations demonstrate that our approach detects underrepresented LCZ types and reveals new sub-classes absent from standard LCZ classifications. Key findings include detection of high-density areas (LCZ 42) reflecting recent urban densification with one of the highest UHImax next to LCZ 2 (4.2–4.9 K), and vegetation-differentiated variants within sparse and low-rise categories LCZ 9D and LCZ 6D, distinguished by distinctive UHImax (0.5–0.7 K) higher compared to their reference base types. Notably, tree coverage remains low across low-rise and compact typo-morphologies, revealing substantial opportunities for greening interventions. This data-driven refinement preserves LCZ's global comparability while considering local specificity, providing improved frameworks to inform targeted climate adaptation strategies in residential environments.
Co-creation with carbon data
Reframing the designer’s role in the decarbonization of the built environment
Cross-scale, multidisciplinary design projects such as station area redevelopment are inherently complex, with many stakeholders and vast amounts of data relevant to decision-making. In the Netherlands, these projects face a dual challenge: meeting housing demands while reducing the embodied carbon emissions associated with construction. Early integration of carbon data is essential, yet the abundance and heterogeneity of supporting datasets required for Life-Cycle Assessment beyond the building scale can hinder progress. This paper presents a collaborative workshop method that enables a data-supported design process for informed decision-making. Sessions with station architects, urban designers, railway operators, and carbon specialists co-create a curated data inventory for low-carbon station design. Using analogue data-cards in a constrained deck turns digital data opulence into a structured, tangible, face-to-face procedure based on a shared language, making tacit choices explicit and traceable. Findings underscore the architect’s new digital-era role as a knowledge integrator.
...
Cross-scale, multidisciplinary design projects such as station area redevelopment are inherently complex, with many stakeholders and vast amounts of data relevant to decision-making. In the Netherlands, these projects face a dual challenge: meeting housing demands while reducing the embodied carbon emissions associated with construction. Early integration of carbon data is essential, yet the abundance and heterogeneity of supporting datasets required for Life-Cycle Assessment beyond the building scale can hinder progress. This paper presents a collaborative workshop method that enables a data-supported design process for informed decision-making. Sessions with station architects, urban designers, railway operators, and carbon specialists co-create a curated data inventory for low-carbon station design. Using analogue data-cards in a constrained deck turns digital data opulence into a structured, tangible, face-to-face procedure based on a shared language, making tacit choices explicit and traceable. Findings underscore the architect’s new digital-era role as a knowledge integrator.
Uneven Digital Visibility of Urban Places
Evidence From TikTok Hotspots
Social media platforms increasingly shape how urban places gain visibility and attention in the digital age. In this article, we examine patterns of “place visibility” on TikTok in Amsterdam. We propose and operationalise a TikTok Place Visibility Score, defined as a composite indicator based on user engagement metrics, to measure the relative visibility of places on the platform. We then explore how TikTok mediates and redistributes visibility within existing urban hierarchies. Drawing on 3,767 TikTok posts associated with #amsterdam and hotspot‐related keywords, we apply geo‐parsing, spatial mapping, visualisation, and network analysis to analyse how visibility is distributed across the city. Our results show that several neighbourhoods just outside the historic urban core—rather than only central locations—exhibit high digital visibility on TikTok. These areas function as digitally prominent activity spaces despite their non‐central position in the urban hierarchy, while central neighbourhoods maintain a strong online presence. The findings suggest that social media algorithms and user interactions affect digital visibility and may reconfigure how attention is redistributed across urban space. We argue that digital visibility patterns shape how places are circulated and prioritised in the digital public sphere, with implications for how people use and engage with urban space. More broadly, the article highlights the importance of attending to platform mechanisms and visibility dynamics when studying urban space in the digital transition era.
...
Social media platforms increasingly shape how urban places gain visibility and attention in the digital age. In this article, we examine patterns of “place visibility” on TikTok in Amsterdam. We propose and operationalise a TikTok Place Visibility Score, defined as a composite indicator based on user engagement metrics, to measure the relative visibility of places on the platform. We then explore how TikTok mediates and redistributes visibility within existing urban hierarchies. Drawing on 3,767 TikTok posts associated with #amsterdam and hotspot‐related keywords, we apply geo‐parsing, spatial mapping, visualisation, and network analysis to analyse how visibility is distributed across the city. Our results show that several neighbourhoods just outside the historic urban core—rather than only central locations—exhibit high digital visibility on TikTok. These areas function as digitally prominent activity spaces despite their non‐central position in the urban hierarchy, while central neighbourhoods maintain a strong online presence. The findings suggest that social media algorithms and user interactions affect digital visibility and may reconfigure how attention is redistributed across urban space. We argue that digital visibility patterns shape how places are circulated and prioritised in the digital public sphere, with implications for how people use and engage with urban space. More broadly, the article highlights the importance of attending to platform mechanisms and visibility dynamics when studying urban space in the digital transition era.
Addressing high-temperature exposure in cities requires understanding multiple environmental dimensions, with urban morphology playing a central role. Urban morphology—which include building density, height, and arrangement—significantly influences microclimatic conditions and opportunities for adaptation. A widely used framework for studying these relationships is the Local Climate Zones (LCZ), which provides a solid theoretical foundation for understanding urban climate variations. However, LCZ categories are often idealized and may not accurately reflect the complexity of real-world environments, particularly when attempting to describe both morphological and thermal properties simultaneously.
Although urban form and thermal behavior are inherently interrelated, similar urban forms can exhibit different thermal responses depending on factors like vegetation cover, impervious surfaces, and building materials. To better represent real-world variability, separating morphological classifications from thermal characteristics allows for an analysis that accounts for these differences.
To address these challenges, we develope an approach that generates empirically derived urban morhophological types while maintaining connections to LCZ categories. Our tool systematically classifies urban morphological types for fine-grained, nationwide assessments, enabling consistent comparisons across diverse Dutch urban residential areas. This approach uses readily available geospatial data and applies unsupervised machine learning techniques to identify urban morphological typologies. By standardizing the classification process into 100 x 100 m grid cells from Statistics Netherlands, our method provides a consistent spatial and temporal framework that transcends changing administrative boundaries.
Our approach helps streamline vulnerability analysis by facilitating the intersection of multiple environmental and social dimensions. We demonstrate the tool's utility through an explorative analysis that identifies which socio-economic groups reside in neighborhoods with high heat exposure, considering both morphological types and additional factors influencing heat exposure. This tool provides urban planners and researchers with an empirically-grounded framework for identifying priority areas in existing settlements for scalable adaptation interventions across different urban contexts. ...
Although urban form and thermal behavior are inherently interrelated, similar urban forms can exhibit different thermal responses depending on factors like vegetation cover, impervious surfaces, and building materials. To better represent real-world variability, separating morphological classifications from thermal characteristics allows for an analysis that accounts for these differences.
To address these challenges, we develope an approach that generates empirically derived urban morhophological types while maintaining connections to LCZ categories. Our tool systematically classifies urban morphological types for fine-grained, nationwide assessments, enabling consistent comparisons across diverse Dutch urban residential areas. This approach uses readily available geospatial data and applies unsupervised machine learning techniques to identify urban morphological typologies. By standardizing the classification process into 100 x 100 m grid cells from Statistics Netherlands, our method provides a consistent spatial and temporal framework that transcends changing administrative boundaries.
Our approach helps streamline vulnerability analysis by facilitating the intersection of multiple environmental and social dimensions. We demonstrate the tool's utility through an explorative analysis that identifies which socio-economic groups reside in neighborhoods with high heat exposure, considering both morphological types and additional factors influencing heat exposure. This tool provides urban planners and researchers with an empirically-grounded framework for identifying priority areas in existing settlements for scalable adaptation interventions across different urban contexts. ...
Addressing high-temperature exposure in cities requires understanding multiple environmental dimensions, with urban morphology playing a central role. Urban morphology—which include building density, height, and arrangement—significantly influences microclimatic conditions and opportunities for adaptation. A widely used framework for studying these relationships is the Local Climate Zones (LCZ), which provides a solid theoretical foundation for understanding urban climate variations. However, LCZ categories are often idealized and may not accurately reflect the complexity of real-world environments, particularly when attempting to describe both morphological and thermal properties simultaneously.
Although urban form and thermal behavior are inherently interrelated, similar urban forms can exhibit different thermal responses depending on factors like vegetation cover, impervious surfaces, and building materials. To better represent real-world variability, separating morphological classifications from thermal characteristics allows for an analysis that accounts for these differences.
To address these challenges, we develope an approach that generates empirically derived urban morhophological types while maintaining connections to LCZ categories. Our tool systematically classifies urban morphological types for fine-grained, nationwide assessments, enabling consistent comparisons across diverse Dutch urban residential areas. This approach uses readily available geospatial data and applies unsupervised machine learning techniques to identify urban morphological typologies. By standardizing the classification process into 100 x 100 m grid cells from Statistics Netherlands, our method provides a consistent spatial and temporal framework that transcends changing administrative boundaries.
Our approach helps streamline vulnerability analysis by facilitating the intersection of multiple environmental and social dimensions. We demonstrate the tool's utility through an explorative analysis that identifies which socio-economic groups reside in neighborhoods with high heat exposure, considering both morphological types and additional factors influencing heat exposure. This tool provides urban planners and researchers with an empirically-grounded framework for identifying priority areas in existing settlements for scalable adaptation interventions across different urban contexts.
Although urban form and thermal behavior are inherently interrelated, similar urban forms can exhibit different thermal responses depending on factors like vegetation cover, impervious surfaces, and building materials. To better represent real-world variability, separating morphological classifications from thermal characteristics allows for an analysis that accounts for these differences.
To address these challenges, we develope an approach that generates empirically derived urban morhophological types while maintaining connections to LCZ categories. Our tool systematically classifies urban morphological types for fine-grained, nationwide assessments, enabling consistent comparisons across diverse Dutch urban residential areas. This approach uses readily available geospatial data and applies unsupervised machine learning techniques to identify urban morphological typologies. By standardizing the classification process into 100 x 100 m grid cells from Statistics Netherlands, our method provides a consistent spatial and temporal framework that transcends changing administrative boundaries.
Our approach helps streamline vulnerability analysis by facilitating the intersection of multiple environmental and social dimensions. We demonstrate the tool's utility through an explorative analysis that identifies which socio-economic groups reside in neighborhoods with high heat exposure, considering both morphological types and additional factors influencing heat exposure. This tool provides urban planners and researchers with an empirically-grounded framework for identifying priority areas in existing settlements for scalable adaptation interventions across different urban contexts.
The spatio-temporal evolution of social inequalities in cities
A multidimensional, multiscalar and longitudinal approach for neighbourhood classification
Understanding the spatial patterns of social inequalities has been a longstanding concern in urban studies. Geodemographic classifications, which group neighbourhoods based on multiple social and physical dimensions, offer a useful tool for this purpose. However, most classifications rely on fixed single-scale administrative boundaries, while studies that adopt multiscale approaches often focus on a single dimension and cover only limited time periods. This limits our understanding of how urban social inequalities evolve over time and across spatial scales. In this study, we extend the geodemographic approach to incorporate multiple dimensions, time periods, and geographical scales, enabling a more comprehensive analysis of the spatio-temporal configuration of urban change. We develop multidimensional, multiscale, and longitudinal spatial profiles of residential contexts in the Metropolitan Agglomeration of Amsterdam (MAA) using bespoke neighbourhoods constructed from detailed population register data (1999–2022). Our results show that the interaction of socioeconomic status, migration background, life-course stages, and housing tenure provides a richer understanding of urban stratification than traditional models based solely on income or ethnicity. The longitudinal perspective reveals distinct timing differences in urban reconfigurations, such as gentrification and displacement, which emerge locally and consolidate more broadly over time. The multiscale approach highlights how patterns of urban change are scale-dependent, with large-scale dynamics, such as poverty suburbanisation and inner-city gentrification, coexisting with the formation of smaller enclaves in areas undergoing or at risk of change. These findings highlight the need for integrated multidimensional, temporal, and multiscale frameworks to better capture the evolving nature of sociospatial inequalities in cities.
...
Understanding the spatial patterns of social inequalities has been a longstanding concern in urban studies. Geodemographic classifications, which group neighbourhoods based on multiple social and physical dimensions, offer a useful tool for this purpose. However, most classifications rely on fixed single-scale administrative boundaries, while studies that adopt multiscale approaches often focus on a single dimension and cover only limited time periods. This limits our understanding of how urban social inequalities evolve over time and across spatial scales. In this study, we extend the geodemographic approach to incorporate multiple dimensions, time periods, and geographical scales, enabling a more comprehensive analysis of the spatio-temporal configuration of urban change. We develop multidimensional, multiscale, and longitudinal spatial profiles of residential contexts in the Metropolitan Agglomeration of Amsterdam (MAA) using bespoke neighbourhoods constructed from detailed population register data (1999–2022). Our results show that the interaction of socioeconomic status, migration background, life-course stages, and housing tenure provides a richer understanding of urban stratification than traditional models based solely on income or ethnicity. The longitudinal perspective reveals distinct timing differences in urban reconfigurations, such as gentrification and displacement, which emerge locally and consolidate more broadly over time. The multiscale approach highlights how patterns of urban change are scale-dependent, with large-scale dynamics, such as poverty suburbanisation and inner-city gentrification, coexisting with the formation of smaller enclaves in areas undergoing or at risk of change. These findings highlight the need for integrated multidimensional, temporal, and multiscale frameworks to better capture the evolving nature of sociospatial inequalities in cities.
Journal article
(2025)
-
Rūta Ubarevičienė, Tiit Tammaru, Maarten van Ham, Leandro Basílio Junior, Māris Bērziņš, Kevin Credit, Diogo Gaspar Silva, Richard Harris, David Manley, More authors...
Previous research based on 2001 and 2011 census data indicated rising levels of residential segregation between socio-economic groups in many large city-regions in Europe as well as globally. Rising segregation is an important societal concern, as place of residence plays a crucial role in shaping access to urban opportunities. Residential isolation can be especially harmful for the most vulnerable groups. Income inequality was identified as the primary driver of this segregation. The current paper extends comparative research on residential segregation in Europe by incorporating the latest 2021 census and register-based data to determine whether segregation levels have continued to rise or have peaked, or whether there are signs of desegregation. It also examines how changes in segregation align with shifts in income inequality and occupational structures. A comparative analysis of 16 European capital city-regions shows a slowdown in the rise of segregation, with some city-regions transitioning from segregation to desegregation. These changes coincide with both a slowdown in the growth of income inequality and increased professionalisation of the workforce. The study suggests that future research should focus on the mechanisms driving residential desegregation in different urban contexts, with particular attention to the diversification of residential patterns among the expanding professional class.
...
Previous research based on 2001 and 2011 census data indicated rising levels of residential segregation between socio-economic groups in many large city-regions in Europe as well as globally. Rising segregation is an important societal concern, as place of residence plays a crucial role in shaping access to urban opportunities. Residential isolation can be especially harmful for the most vulnerable groups. Income inequality was identified as the primary driver of this segregation. The current paper extends comparative research on residential segregation in Europe by incorporating the latest 2021 census and register-based data to determine whether segregation levels have continued to rise or have peaked, or whether there are signs of desegregation. It also examines how changes in segregation align with shifts in income inequality and occupational structures. A comparative analysis of 16 European capital city-regions shows a slowdown in the rise of segregation, with some city-regions transitioning from segregation to desegregation. These changes coincide with both a slowdown in the growth of income inequality and increased professionalisation of the workforce. The study suggests that future research should focus on the mechanisms driving residential desegregation in different urban contexts, with particular attention to the diversification of residential patterns among the expanding professional class.
The Economic Urban Divide
A Detailed Study of Income Inequality and Segregation in Dutch Urban Areas (2011–2022)
Research on segregation and economic inequality is often limited to major capitals and conurbations, neglecting smaller cities. This oversight can lead to public policies based on insights that may not be universally applicable. Leveraging geo-coded register data, this study addresses this problem in the case of the Netherlands by computing income inequality and residential segregation annually in all urban areas from 2011 to 2022. Contrary to most literature, this paper shows that inequality and segregation have remained stable or decreased in most cases. In addition, when looking at how income is distributed among social segments, how segregated they are, and at which geographical scale segregation occurs, we find significant variation between urban areas. More unequal urban areas also tend to be more segregated, but patterns vary, and the same segregation levels can coexist with diverse inequality metrics. Four groups of urban areas are identified through a cluster analysis.
...
Research on segregation and economic inequality is often limited to major capitals and conurbations, neglecting smaller cities. This oversight can lead to public policies based on insights that may not be universally applicable. Leveraging geo-coded register data, this study addresses this problem in the case of the Netherlands by computing income inequality and residential segregation annually in all urban areas from 2011 to 2022. Contrary to most literature, this paper shows that inequality and segregation have remained stable or decreased in most cases. In addition, when looking at how income is distributed among social segments, how segregated they are, and at which geographical scale segregation occurs, we find significant variation between urban areas. More unequal urban areas also tend to be more segregated, but patterns vary, and the same segregation levels can coexist with diverse inequality metrics. Four groups of urban areas are identified through a cluster analysis.
Do you see it how I see it?
Differences in neighborhood perceptions explained by individuals’ socioeconomic characteristics and trust attitudes
Researchers often use register data-based measures of neighborhood characteristics to estimate neighborhood effects. However, the underlying causal mechanisms might be based on the perception of such characteristics. The mismatch between the measures and perceptions is likely influenced by individuals’ characteristics and attitudes. This paper investigates the relationship between the measured percentages of low-income and foreign background neighbors and their perceptions. Using Dutch register data merged with survey data, we found that higher education is associated with the underestimation of both characteristics, but after controlling for individual institutional trust it becomes less significant to the perceived percentage of foreign background neighbors, and insignificant to that of low-income neighbors. Individuals with lower institutional trust are likely to overestimate both percentages. Older age, greater wealth and greater social embeddedness are associated with underestimation of both characteristics, and higher household income with the underestimation of the share of low-income neighbors. We find that trust in democratic and public institutions is associated with biased perceptions of social reality, which can be an important finding for the spatial inequality studies. Our results also suggest that urban research would benefit from augmenting administrative datasets with surveys and interviews.
...
Researchers often use register data-based measures of neighborhood characteristics to estimate neighborhood effects. However, the underlying causal mechanisms might be based on the perception of such characteristics. The mismatch between the measures and perceptions is likely influenced by individuals’ characteristics and attitudes. This paper investigates the relationship between the measured percentages of low-income and foreign background neighbors and their perceptions. Using Dutch register data merged with survey data, we found that higher education is associated with the underestimation of both characteristics, but after controlling for individual institutional trust it becomes less significant to the perceived percentage of foreign background neighbors, and insignificant to that of low-income neighbors. Individuals with lower institutional trust are likely to overestimate both percentages. Older age, greater wealth and greater social embeddedness are associated with underestimation of both characteristics, and higher household income with the underestimation of the share of low-income neighbors. We find that trust in democratic and public institutions is associated with biased perceptions of social reality, which can be an important finding for the spatial inequality studies. Our results also suggest that urban research would benefit from augmenting administrative datasets with surveys and interviews.
Regression Toward the Mean in Neighborhood Effects Research
A Geographic Perspective
Neighborhood effects research focuses on the residential neighborhood, assuming it as the main spatial context relevant to individual outcomes. Individuals, however, are mobile and visit various spatial contexts other than the residential neighborhoods. This article conceptualizes contextual exposures to socioenvironmental factors in daily activity spaces and their relationship with residential exposures. By introducing regression toward the mean, we argue that mobility-based contextual exposures are, on average, less extreme than residential exposures. Previous neighborhood effects studies therefore tend to underestimate actual spatial contextual effects when they misrepresent residential neighborhood effects as the total contextual effects. Despite improved measurement accuracy with the transition from residence- to mobility-based exposures, we suggest the complexities remaining in the estimation of spatial contextual effects from a geographic perspective. These complexities include a possibly limited extent of neighborhood effects regression across neighborhoods and asymmetrical dispersion of between-individual contextual exposures within each neighborhood.
...
Neighborhood effects research focuses on the residential neighborhood, assuming it as the main spatial context relevant to individual outcomes. Individuals, however, are mobile and visit various spatial contexts other than the residential neighborhoods. This article conceptualizes contextual exposures to socioenvironmental factors in daily activity spaces and their relationship with residential exposures. By introducing regression toward the mean, we argue that mobility-based contextual exposures are, on average, less extreme than residential exposures. Previous neighborhood effects studies therefore tend to underestimate actual spatial contextual effects when they misrepresent residential neighborhood effects as the total contextual effects. Despite improved measurement accuracy with the transition from residence- to mobility-based exposures, we suggest the complexities remaining in the estimation of spatial contextual effects from a geographic perspective. These complexities include a possibly limited extent of neighborhood effects regression across neighborhoods and asymmetrical dispersion of between-individual contextual exposures within each neighborhood.
When Ageing Meets Neighbourhood Demolition
Negotiating Time, Space, and Kinship in State-Led Urban Redevelopment in China
This study examines how senior residents navigate the overlapping logics of dispossession and re-possession within urban redevelopment, situating this dialectic within the broader framework of spatial commodification and lived spatiotemporal experiences. While urban redevelopment offers compensation and improved housing, it also generates deep emotional, functional, and temporal disruptions – particularly for older adults. Spatially, redevelopment projects prioritise abstract commodified space, often disregarding seniors’ affective and symbolic attachments to their neighbourhoods. Importantly, seniors’ attachments to place are not uniformly positive. Many express frustrations with deteriorating environments and social fragmentation, viewing redevelopment as an opportunity to improve living conditions or family wealth accumulation. The tension between loss and gain – between being dispossessed and being re-possessed – shapes their complex responses to displacement. These dynamics are further complicated by the temporal mismatch between institutional redevelopment timelines and seniors’ embodied rhythms, such as ageing-related limitations, care responsibilities, and uncertainty about future arrangements. Meanwhile, shifting intergenerational dynamics within the family domain reveal that even with financial compensation and increased family wealth, conflicts often emerge around caregiving and benefits distribution. By centring these tensions, this study moves beyond binary accounts of victimhood or compliance and highlights the ambivalence and contingency in seniors’ engagement with redevelopment. It calls for more nuanced policy responses that align material compensation with emotional and temporal needs, particularly in contexts where family-based ageing care remains central.
...
This study examines how senior residents navigate the overlapping logics of dispossession and re-possession within urban redevelopment, situating this dialectic within the broader framework of spatial commodification and lived spatiotemporal experiences. While urban redevelopment offers compensation and improved housing, it also generates deep emotional, functional, and temporal disruptions – particularly for older adults. Spatially, redevelopment projects prioritise abstract commodified space, often disregarding seniors’ affective and symbolic attachments to their neighbourhoods. Importantly, seniors’ attachments to place are not uniformly positive. Many express frustrations with deteriorating environments and social fragmentation, viewing redevelopment as an opportunity to improve living conditions or family wealth accumulation. The tension between loss and gain – between being dispossessed and being re-possessed – shapes their complex responses to displacement. These dynamics are further complicated by the temporal mismatch between institutional redevelopment timelines and seniors’ embodied rhythms, such as ageing-related limitations, care responsibilities, and uncertainty about future arrangements. Meanwhile, shifting intergenerational dynamics within the family domain reveal that even with financial compensation and increased family wealth, conflicts often emerge around caregiving and benefits distribution. By centring these tensions, this study moves beyond binary accounts of victimhood or compliance and highlights the ambivalence and contingency in seniors’ engagement with redevelopment. It calls for more nuanced policy responses that align material compensation with emotional and temporal needs, particularly in contexts where family-based ageing care remains central.
The urban heat island effect is increasingly affecting the quality of life in cities, and detailed data is crucial in designing mitigation policies. However, weather stations are predominantly situated outside urban environments, limiting their ability to represent the varying air temperatures within street canyons. This data paper addresses this limitation by presenting a dataset of the modeled daily maximum urban heat island (UHImax) effect across 99 Dutch municipalities during the summer of 2023. This is achieved by implementing a semi-empirical equation that incorporates readily available meteorological variables and two key urban morphological indicators, namely the sky view factor and fractional vegetation cover. Two primary datasets are presented: (1) a high-resolution dataset of modeled UHImax, and (2) a sky view factor dataset. Both datasets are provided in GeoTIFF format at a 5-meter spatial resolution. Additionally, this paper presents a straightforward methodology for obtaining UHImax values for other periods. The datasets and accompanying methodology provide valuable resources for advancing urban climate research, urban planning and heat mitigation strategies in the Netherlands.
...
The urban heat island effect is increasingly affecting the quality of life in cities, and detailed data is crucial in designing mitigation policies. However, weather stations are predominantly situated outside urban environments, limiting their ability to represent the varying air temperatures within street canyons. This data paper addresses this limitation by presenting a dataset of the modeled daily maximum urban heat island (UHImax) effect across 99 Dutch municipalities during the summer of 2023. This is achieved by implementing a semi-empirical equation that incorporates readily available meteorological variables and two key urban morphological indicators, namely the sky view factor and fractional vegetation cover. Two primary datasets are presented: (1) a high-resolution dataset of modeled UHImax, and (2) a sky view factor dataset. Both datasets are provided in GeoTIFF format at a 5-meter spatial resolution. Additionally, this paper presents a straightforward methodology for obtaining UHImax values for other periods. The datasets and accompanying methodology provide valuable resources for advancing urban climate research, urban planning and heat mitigation strategies in the Netherlands.
¿Segregados quiénes, cuándo y dónde?
La heterogeneidad de la segregación en Países Bajos
Este artículo ofrece una evaluación detallada y longitudinal de la desigualdad económica y la segregación residencial en todas las zonas urbanas de los Países Bajos, cubriendo el periodo de 2003 a 2010. Al utilizar microdatos que abarcan la totalidad de la población del país, estimamos el nivel de segregación por ingresos mediante el Rank-Order Information Theory Index (ROITI), un indicador avanzado que se adapta a la naturaleza continua de la variable y no necesita establecer categorías de renta arbitrarias. Además, el ROITI permite una desagregación de la estimación al nivel de cada percentil, de forma que nos capacita para estimar la segregación de la pobreza y la segregación de la riqueza como dos elementos diferenciados. Las estimaciones muestran una asociación positiva entre desigualdad y segregación, aunque existe una variación considerable entre zonas urbanas y su evolución en el tiempo. Además, nuestros hallazgos confirman que los hogares más acomodados tienden a estar más separados en el espacio que la población más pobre. Sin embargo, los niveles de segregación de los diferentes segmentos de la distribución de los ingresos han variado de manera muy dispar entre las zonas urbanas de Países Bajos. Estos resultados indican que la segregación constituye un fenómeno distinto entre diferentes áreas geográficas, a lo largo del tiempo y entre distintos grupos sociales.
...
Este artículo ofrece una evaluación detallada y longitudinal de la desigualdad económica y la segregación residencial en todas las zonas urbanas de los Países Bajos, cubriendo el periodo de 2003 a 2010. Al utilizar microdatos que abarcan la totalidad de la población del país, estimamos el nivel de segregación por ingresos mediante el Rank-Order Information Theory Index (ROITI), un indicador avanzado que se adapta a la naturaleza continua de la variable y no necesita establecer categorías de renta arbitrarias. Además, el ROITI permite una desagregación de la estimación al nivel de cada percentil, de forma que nos capacita para estimar la segregación de la pobreza y la segregación de la riqueza como dos elementos diferenciados. Las estimaciones muestran una asociación positiva entre desigualdad y segregación, aunque existe una variación considerable entre zonas urbanas y su evolución en el tiempo. Además, nuestros hallazgos confirman que los hogares más acomodados tienden a estar más separados en el espacio que la población más pobre. Sin embargo, los niveles de segregación de los diferentes segmentos de la distribución de los ingresos han variado de manera muy dispar entre las zonas urbanas de Países Bajos. Estos resultados indican que la segregación constituye un fenómeno distinto entre diferentes áreas geográficas, a lo largo del tiempo y entre distintos grupos sociales.
Changes in commuting mode and the relationship with psychological stress
A quasi-longitudinal analysis in urbanizing China
Emerging longitudinal research on the relationship between commuting mode and psychological wellbeing draws exclusively from cities in developed countries and the findings are not consistent. Our study contributes to the evidence base from urban China, where rapid urban growth has raised great concerns for urbanites’ commuting problems and psychological stress risks. Drawing upon the China Health and Nutrition Survey (2006–2015), we followed a quasi-longitudinal design to examine changes in commuting mode and the associations with long-term psychological stress. Crucially, the neighbourhood-level urbanicity scale was incorporated to analyse geographic variations in the commuting-stress relationship over time. The results show that maintaining car commuting and long-duration active commuting were associated with lower levels of psychological stress, while long-duration motorised commuting trips by car or public transport were predictive of higher stress levels. Moreover, high-urbanicity areas involved more active commuting trips and short motorised commuting trips, which were beneficial to long-term psychological wellbeing. In contrast, the commuting-related stress risks were noticeable in medium urbanicity areas, where the commuting duration by public transport was extremely high. Based on the socio-institutional context of urban growth in China, we recommend that urban governments should change the focus from expanding urban development land to improving urban amenities and urbanites’ wellbeing.
...
Emerging longitudinal research on the relationship between commuting mode and psychological wellbeing draws exclusively from cities in developed countries and the findings are not consistent. Our study contributes to the evidence base from urban China, where rapid urban growth has raised great concerns for urbanites’ commuting problems and psychological stress risks. Drawing upon the China Health and Nutrition Survey (2006–2015), we followed a quasi-longitudinal design to examine changes in commuting mode and the associations with long-term psychological stress. Crucially, the neighbourhood-level urbanicity scale was incorporated to analyse geographic variations in the commuting-stress relationship over time. The results show that maintaining car commuting and long-duration active commuting were associated with lower levels of psychological stress, while long-duration motorised commuting trips by car or public transport were predictive of higher stress levels. Moreover, high-urbanicity areas involved more active commuting trips and short motorised commuting trips, which were beneficial to long-term psychological wellbeing. In contrast, the commuting-related stress risks were noticeable in medium urbanicity areas, where the commuting duration by public transport was extremely high. Based on the socio-institutional context of urban growth in China, we recommend that urban governments should change the focus from expanding urban development land to improving urban amenities and urbanites’ wellbeing.
The evolution of compounding residential inequalities
A multiscale analysis of neighbourhood change trajectories in Amsterdam
Traditionally, studies of spatial inequalities only consider one single dimension, such as income, and one spatial scale - usually a neighbourhood determined by administrative boundaries. Although the existing literature increasingly recognises the multifaceted nature of inequalities in cities, this paper introduces a novel approach by integrating the multidimensional and multiscale perspectives to understand the evolution of social and spatial inequalities over time. Drawing on clustering techniques based on factor analysis and using individual-level geocoded register data from the metropolitan agglomeration of Amsterdam, our methodology classifies neighbourhoods by grouping detailed residential locations with similar socioeconomic, demographic and housing characteristics across multiple geographical scales. Through sequence analysis, we identify trajectories of neighbourhood change from 1999 to 2022, revealing patterns in the timing, duration, and sequencing of shifts across various dimensions. Our results bridge gaps in the multidimensional and multiscale neighbourhood classification literatures, providing a better understanding of how social inequalities interact and overlap in space. By examining the path dependence between different dimensions of spatial and social inequalities, this study provides insights into the processes that produce and reproduce social stratification in cities that may act at different geographical scales for different groups of people. Moreover, the rich and granular data paint a detailed picture of how residential contexts are segregated and how the trajectories of neighbourhood change are distributed spatially. This research offers an innovative framework for visualise and study the dynamic evolution of urban structures over time.
...
Traditionally, studies of spatial inequalities only consider one single dimension, such as income, and one spatial scale - usually a neighbourhood determined by administrative boundaries. Although the existing literature increasingly recognises the multifaceted nature of inequalities in cities, this paper introduces a novel approach by integrating the multidimensional and multiscale perspectives to understand the evolution of social and spatial inequalities over time. Drawing on clustering techniques based on factor analysis and using individual-level geocoded register data from the metropolitan agglomeration of Amsterdam, our methodology classifies neighbourhoods by grouping detailed residential locations with similar socioeconomic, demographic and housing characteristics across multiple geographical scales. Through sequence analysis, we identify trajectories of neighbourhood change from 1999 to 2022, revealing patterns in the timing, duration, and sequencing of shifts across various dimensions. Our results bridge gaps in the multidimensional and multiscale neighbourhood classification literatures, providing a better understanding of how social inequalities interact and overlap in space. By examining the path dependence between different dimensions of spatial and social inequalities, this study provides insights into the processes that produce and reproduce social stratification in cities that may act at different geographical scales for different groups of people. Moreover, the rich and granular data paint a detailed picture of how residential contexts are segregated and how the trajectories of neighbourhood change are distributed spatially. This research offers an innovative framework for visualise and study the dynamic evolution of urban structures over time.
Defining indicators for evaluating the residential environment in historic districts based on human needs
Focusing on two cases in Northern China
Compared to traditional communities, the residential environment in historic districts (HDs) is generally poor. Tourism development within HDs has affected these environments. As tailored assessment indicators are absent in HDs, this study introduces the historic district residential environment assessment indicator (HD-REAI) – a framework designed for the urban setting of HDs. The HD-REAI integrates Maslow’s theory and addresses the challenges and attributes of HDs. HD-REAI focuses on factors like housing property rights and district culture, which are pivotal for HDs. This enables a more nuanced and relevant evaluation of the residential environment in these areas. This study details the development of the HD-REAI and validates its efficacy through its application in two Northern Chinese HDs. The results demonstrate that the HD-REAI effectively assesses the environment, offering a specialized and context-sensitive tool. Moreover, different socioeconomic attributes have different effects on the assessment results. This study could provide a basis for constructing more refined and context-specific assessment tools to enhance residential environments in HDs.
...
Compared to traditional communities, the residential environment in historic districts (HDs) is generally poor. Tourism development within HDs has affected these environments. As tailored assessment indicators are absent in HDs, this study introduces the historic district residential environment assessment indicator (HD-REAI) – a framework designed for the urban setting of HDs. The HD-REAI integrates Maslow’s theory and addresses the challenges and attributes of HDs. HD-REAI focuses on factors like housing property rights and district culture, which are pivotal for HDs. This enables a more nuanced and relevant evaluation of the residential environment in these areas. This study details the development of the HD-REAI and validates its efficacy through its application in two Northern Chinese HDs. The results demonstrate that the HD-REAI effectively assesses the environment, offering a specialized and context-sensitive tool. Moreover, different socioeconomic attributes have different effects on the assessment results. This study could provide a basis for constructing more refined and context-specific assessment tools to enhance residential environments in HDs.
Unravelling the Roles of Active Residents in a Politically Challenging Context
An Exploration in Cairo
Capital cities struggle with population growth that challenges existing infrastructure and affects the quality of urban life. The failure of local governments to manage urban deterioration motivates active resident groups to improve their neighborhoods, but they struggle to play a role in neighborhood governance in contexts where citizens’ engagement in public affairs is restricted. In this article we aim to understand active residents’ roles in the neighborhood governance process and how these roles unfold in a context that challenges citizen engagement in public life. We adopted a case study methodology and interviewed active residents and local officials from selected districts in Cairo, which revealed that active residents’ influence is limited mostly to neighborhood management and implementation activities. In this limited space, the role of active residents is confined to either that of the ‘fixer’ who restores existing services, or that of the struggling and intermittent ‘self-provider’, neither of whom can influence policy formulation. This study provides a structured and zoomed-out view of local activism in Cairo, offering a starting point for scholars and decision makers seeking to enhance active residents’ roles in Cairo.
...
Capital cities struggle with population growth that challenges existing infrastructure and affects the quality of urban life. The failure of local governments to manage urban deterioration motivates active resident groups to improve their neighborhoods, but they struggle to play a role in neighborhood governance in contexts where citizens’ engagement in public affairs is restricted. In this article we aim to understand active residents’ roles in the neighborhood governance process and how these roles unfold in a context that challenges citizen engagement in public life. We adopted a case study methodology and interviewed active residents and local officials from selected districts in Cairo, which revealed that active residents’ influence is limited mostly to neighborhood management and implementation activities. In this limited space, the role of active residents is confined to either that of the ‘fixer’ who restores existing services, or that of the struggling and intermittent ‘self-provider’, neither of whom can influence policy formulation. This study provides a structured and zoomed-out view of local activism in Cairo, offering a starting point for scholars and decision makers seeking to enhance active residents’ roles in Cairo.
The neighbourhood
Where Wilson, Schelling and Hägerstrand meet
There is a longstanding interest in the causes and consequences of socio-spatial inequalities in cities. A large literature has emerged on so-called neighbourhood effects, which seeks to understand how living in neighbourhoods of concentrated poverty affects a range of individual outcomes, such as health, income, education and general wellbeing (Galster, 2012). The literature on neighbourhood effects has developed rapidly in the last three decades. It is now common practice that studies of neighbourhood effects use geocoded longitudinal individual-level data and employ a variety of (often econometric) approaches in an attempt to reduce bias from non-random sorting into neighbourhoods (Knies et al. 2021). Studies of neighbourhood effects have also increasingly looked to incorporate more personal geographic contexts replacing ‘off the shelf’ administrative units with bespoke neighbourhoods (Johnston et al., 2005; Andersson & Malmberg, 2014; Petrović et al. 2022). The most common example of bespoke neighbourhoods are egohoods – neighbourhoods placing everyone at the centre of their own personal residential space (Hipp & Boessen, 2013). More recently, multiscale approaches have been used, whereby neighbourhood characteristics are measured at multiple scales of bespoke neighbourhoods (Petrović et al., 2022). It has been argued that for both theoretical and empirical reasons, the term ‘neighbourhood effects’ should be replaced by the more encompassing term ‘spatial context effects’, as many of the assumed spatial effects are not confined to residential neighbourhoods and the contestable meaning of neighbourhood distracts (Petrović et al. 2019).
...
There is a longstanding interest in the causes and consequences of socio-spatial inequalities in cities. A large literature has emerged on so-called neighbourhood effects, which seeks to understand how living in neighbourhoods of concentrated poverty affects a range of individual outcomes, such as health, income, education and general wellbeing (Galster, 2012). The literature on neighbourhood effects has developed rapidly in the last three decades. It is now common practice that studies of neighbourhood effects use geocoded longitudinal individual-level data and employ a variety of (often econometric) approaches in an attempt to reduce bias from non-random sorting into neighbourhoods (Knies et al. 2021). Studies of neighbourhood effects have also increasingly looked to incorporate more personal geographic contexts replacing ‘off the shelf’ administrative units with bespoke neighbourhoods (Johnston et al., 2005; Andersson & Malmberg, 2014; Petrović et al. 2022). The most common example of bespoke neighbourhoods are egohoods – neighbourhoods placing everyone at the centre of their own personal residential space (Hipp & Boessen, 2013). More recently, multiscale approaches have been used, whereby neighbourhood characteristics are measured at multiple scales of bespoke neighbourhoods (Petrović et al., 2022). It has been argued that for both theoretical and empirical reasons, the term ‘neighbourhood effects’ should be replaced by the more encompassing term ‘spatial context effects’, as many of the assumed spatial effects are not confined to residential neighbourhoods and the contestable meaning of neighbourhood distracts (Petrović et al. 2019).
The conflicting geographies of social frontiers
Exploring the asymmetric impacts of social frontiers on household mobility in Rotterdam
Social frontiers arise when there are sharp differences in the demographic composition of adjacent communities. This paper provides the first quantitative study of their impact on household mobility. We hypothesise that conflicting forces of white flight and territorial allegiance lead to asymmetrical effects, impacting residents on one side of the frontier more than the other due to differences in the range of housing options available to different groups, and different symbolic interpretations of the frontier. Using Dutch registry data for the city of Rotterdam we identify ethnic social frontier locations using a Bayesian spatial model (Dean et al., 2019), exploiting the data’s one hundred metre resolution to estimate frontiers at a very small spatial scale. Regression analysis of moving decisions finds that the ethnic asymmetry of the frontier matters more than ethnicity of individual households. On the ethnic minority side of the frontier, households of all ethnicities in the 28–37 age range have reduced probability of moving compared to non-frontier parts of the city. The opposite is true on the Dutch native side of the frontier. We supplement this analysis with flow models which again find strong frontier effects. Our findings illustrate how the study of social frontiers can shed light on local population dynamics and neighbourhood change.
...
Social frontiers arise when there are sharp differences in the demographic composition of adjacent communities. This paper provides the first quantitative study of their impact on household mobility. We hypothesise that conflicting forces of white flight and territorial allegiance lead to asymmetrical effects, impacting residents on one side of the frontier more than the other due to differences in the range of housing options available to different groups, and different symbolic interpretations of the frontier. Using Dutch registry data for the city of Rotterdam we identify ethnic social frontier locations using a Bayesian spatial model (Dean et al., 2019), exploiting the data’s one hundred metre resolution to estimate frontiers at a very small spatial scale. Regression analysis of moving decisions finds that the ethnic asymmetry of the frontier matters more than ethnicity of individual households. On the ethnic minority side of the frontier, households of all ethnicities in the 28–37 age range have reduced probability of moving compared to non-frontier parts of the city. The opposite is true on the Dutch native side of the frontier. We supplement this analysis with flow models which again find strong frontier effects. Our findings illustrate how the study of social frontiers can shed light on local population dynamics and neighbourhood change.