Martin Fleischmann
Biographic Data
| ID | 4602327 |
|---|---|
| NAME | Martin Fleischmann |
| GIVEN NAMES | Martin |
| FAMILY NAME | Fleischmann |
| SIGNATURE | FLEISCHMANN M |
| AFFILIATIONS | University of Liverpool |
| ORCID | 0000-0003-3319-3366 |
| VERIFIED | Yes |
| TOTAL WORKS | 14 |
| TOTAL CITATIONS | 27 |
| WORKS AS AUTHOR | 14 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2020 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 2 |
The hierarchical morphotope classification
Built environment, formed of a plethora of patterns of building, streets, and plots, has a profound impact on how cities are perceived and function. While various methods exist to classify urban patterns, they often lack a strong theoretical foundation, are not scalable beyond a local level, or sacrifice detail for broader application. This paper introduces the Hierarchical Morphotope Classification (HiMoC), a novel, theory-driven, and computatio…
Adaptive continuity-preserving simplification of street networks
Decoding (urban) form and function using spatially explicit deep learning
This paper explores how can geographical dimension be incorporated into deep learning designed to understand the composition of urban landscapes based on Sentinel 2 satellite imagery. Compared to standard computer vision, satellite imagery is unique as images sampled from the data form a continuous array, rather than being fully independent. We argue that the spatial configuration of the images is as important as the content of each image when at…
In praise of (spatial) bundles
Inequalities in experiencing urban functions. An exploration of human digital (geo-)footprints
Studies on mobility inequalities have so far mostly relied on Survey data or Censuses. While such studies have demonstrated that inequalities strongly influence everyday mobility choices, these data sources lack granular information on people’s movements on a daily basis. By capitalising on high spatio-temporal resolution data provided by Spectus.ai, this study aims at investigating how the deprivation level of the area where people live influenc…
EO + Morphometrics
Earth Observation (EO)-based mapping of cities has great potential to detect patterns beyond the physical ones. However, EO combined with the surge of machine learning techniques to map non-physical, such as socioeconomic, aspects directly, goes to the expense of reproducibility and interpretability, hence scientific validity. In this paper, we suggest shifting the focus from the direct detection of socioeconomic status from raw images through im…
Urban form character and Airbnb in Amsterdam (NL)
Proliferation of Short Term Rental (STR) in cities has generated considerable debate as it was found associated with negative externalities, such as gentrification. Nonetheless, it signals urban qualities working as attractors at different geographical scales. STRs’ relation with urban form remains largely understudied. In this paper, we explore how urban form relates to STRs registered by the Airbnb platform in Amsterdam (NL). First, we identify…
Estimating generalized measures of local neighbourhood context from multispectral satellite images using a convolutional neural network
The increased availability of high-resolution multispectral imagery captured by remote sensing platforms provides new opportunities for the characterisation and differentiation of urban context. The discovery of generalized latent representations from such data are however under researched within the social sciences. As such, this paper exploits advances in machine learning to implement a new method of capturing measures of urban context from mul…
Evolution of Urban Patterns
The recent growth of geographic data science (GDS) fuelled by increasingly available open data and open source tools has influenced urban sciences across a multitude of fields. Yet there is limited application in urban morphology—a science of urban form. Although quantitative approaches to morphological research are finding momentum, existing tools for such analyses have limited scope and are predominantly implemented as plug‐ins for standalone g…
Methodological foundation of a numerical taxonomy of urban form
Cities are complex products of human culture, characterised by a startling diversity of visible traits. Their form is constantly evolving, reflecting changing human needs and local contingencies, manifested in space by many urban patterns. Urban morphology laid the foundation for understanding many such patterns, largely relying on qualitative research methods to extract distinct spatial identities of urban areas. However, the manual, labour-inte…
Urban exodus? Understanding human mobility in Britain during the Covid‐19 pandemic using Meta‐Facebook data
Existing empirical work has focused on assessing the effectiveness of nonpharmaceutical interventions on human mobility to contain the spread of COVID-19. Less is known about the ways in which the COVID-19 pandemic has reshaped the spatial patterns of population movement within countries. Anecdotal evidence of an urban exodus from large cities to rural areas emerged during early phases of the pandemic across western societies. Yet, these claims h…
Spatial Signatures - Understanding (urban) spaces through form and function
This paper presents the notion of spatial signatures as a characterisation of space based on form and function designed to understand urban environments. The spatial configuration of the dif-ferent components of cities is relevant for at least two main reasons. On the one hand, it encodes many aspects of the phenomena that created such an arrangement in the first place. On the other, once in place, this arrangement of urban form and function unde…
Measuring urban form
Unprecedented urbanisation processes characterise the Great Acceleration, urging urban researchers to make sense of data analysis in support of evidence-based and large-scale decision-making. Urban morphologists are no exception since the impact of urban form on fundamental natural and social patterns (equity, prosperity and resource consumption’s efficiency) is now fully acknowledged. However, urban morphology is still far from offering a compre…
Morphological tessellation as a way of partitioning space
Urban exodus? Understanding human mobility in Britain during the Covid‐19 pandemic using Meta‐Facebook data
Existing empirical work has focused on assessing the effectiveness of nonpharmaceutical interventions on human mobility to contain the spread of COVID-19. Less is known about the ways in which the COVID-19 pandemic has reshaped the spatial patterns of population movement within countries. Anecdotal evidence of an urban exodus from large cities to rural areas emerged during early phases of the pandemic across western societies. Yet, these claims h…
Spatial Signatures - Understanding (urban) spaces through form and function
This paper presents the notion of spatial signatures as a characterisation of space based on form and function designed to understand urban environments. The spatial configuration of the dif-ferent components of cities is relevant for at least two main reasons. On the one hand, it encodes many aspects of the phenomena that created such an arrangement in the first place. On the other, once in place, this arrangement of urban form and function unde…
Morphological tessellation as a way of partitioning space
Measuring urban form
Unprecedented urbanisation processes characterise the Great Acceleration, urging urban researchers to make sense of data analysis in support of evidence-based and large-scale decision-making. Urban morphologists are no exception since the impact of urban form on fundamental natural and social patterns (equity, prosperity and resource consumption’s efficiency) is now fully acknowledged. However, urban morphology is still far from offering a compre…
Estimating generalized measures of local neighbourhood context from multispectral satellite images using a convolutional neural network
The increased availability of high-resolution multispectral imagery captured by remote sensing platforms provides new opportunities for the characterisation and differentiation of urban context. The discovery of generalized latent representations from such data are however under researched within the social sciences. As such, this paper exploits advances in machine learning to implement a new method of capturing measures of urban context from mul…
Evolution of Urban Patterns
The recent growth of geographic data science (GDS) fuelled by increasingly available open data and open source tools has influenced urban sciences across a multitude of fields. Yet there is limited application in urban morphology—a science of urban form. Although quantitative approaches to morphological research are finding momentum, existing tools for such analyses have limited scope and are predominantly implemented as plug‐ins for standalone g…
Methodological foundation of a numerical taxonomy of urban form
Cities are complex products of human culture, characterised by a startling diversity of visible traits. Their form is constantly evolving, reflecting changing human needs and local contingencies, manifested in space by many urban patterns. Urban morphology laid the foundation for understanding many such patterns, largely relying on qualitative research methods to extract distinct spatial identities of urban areas. However, the manual, labour-inte…
Urban exodus? Understanding human mobility in Britain during the Covid‐19 pandemic using Meta‐Facebook data
Existing empirical work has focused on assessing the effectiveness of nonpharmaceutical interventions on human mobility to contain the spread of COVID-19. Less is known about the ways in which the COVID-19 pandemic has reshaped the spatial patterns of population movement within countries. Anecdotal evidence of an urban exodus from large cities to rural areas emerged during early phases of the pandemic across western societies. Yet, these claims h…
Spatial Signatures - Understanding (urban) spaces through form and function
This paper presents the notion of spatial signatures as a characterisation of space based on form and function designed to understand urban environments. The spatial configuration of the dif-ferent components of cities is relevant for at least two main reasons. On the one hand, it encodes many aspects of the phenomena that created such an arrangement in the first place. On the other, once in place, this arrangement of urban form and function unde…
EO + Morphometrics
Earth Observation (EO)-based mapping of cities has great potential to detect patterns beyond the physical ones. However, EO combined with the surge of machine learning techniques to map non-physical, such as socioeconomic, aspects directly, goes to the expense of reproducibility and interpretability, hence scientific validity. In this paper, we suggest shifting the focus from the direct detection of socioeconomic status from raw images through im…
Urban form character and Airbnb in Amsterdam (NL)
Proliferation of Short Term Rental (STR) in cities has generated considerable debate as it was found associated with negative externalities, such as gentrification. Nonetheless, it signals urban qualities working as attractors at different geographical scales. STRs’ relation with urban form remains largely understudied. In this paper, we explore how urban form relates to STRs registered by the Airbnb platform in Amsterdam (NL). First, we identify…
Decoding (urban) form and function using spatially explicit deep learning
This paper explores how can geographical dimension be incorporated into deep learning designed to understand the composition of urban landscapes based on Sentinel 2 satellite imagery. Compared to standard computer vision, satellite imagery is unique as images sampled from the data form a continuous array, rather than being fully independent. We argue that the spatial configuration of the images is as important as the content of each image when at…
In praise of (spatial) bundles
Inequalities in experiencing urban functions. An exploration of human digital (geo-)footprints
Studies on mobility inequalities have so far mostly relied on Survey data or Censuses. While such studies have demonstrated that inequalities strongly influence everyday mobility choices, these data sources lack granular information on people’s movements on a daily basis. By capitalising on high spatio-temporal resolution data provided by Spectus.ai, this study aims at investigating how the deprivation level of the area where people live influenc…
The hierarchical morphotope classification
Built environment, formed of a plethora of patterns of building, streets, and plots, has a profound impact on how cities are perceived and function. While various methods exist to classify urban patterns, they often lack a strong theoretical foundation, are not scalable beyond a local level, or sacrifice detail for broader application. This paper introduces the Hierarchical Morphotope Classification (HiMoC), a novel, theory-driven, and computatio…
Adaptive continuity-preserving simplification of street networks
Geography (11 works) · Land Use and Ecosystem Services (10 works) · Computer Science (9 works) · Mathematics (8 works) · Urban Design and Spatial Analysis (7 works) · Cartography (6 works) · Urban planning (6 works) · Civil engineering (5 works) · Engineering (5 works) · Remote Sensing and Land Use (5 works)