Alexander Zipf
Dados Biográficos
| ID | 3450067 |
|---|---|
| NOME | Alexander Zipf |
| PRENOMES | Alexander |
| SOBRENOME | Zipf |
| ASSINATURA | ZIPF A |
| AFILIAÇÕES | Heidelberg University |
| ORCID | 0000-0003-4916-9838 |
| VERIFICADO | Sim |
| TOTAL DE OBRAS | 25 |
| TOTAL DE CITAÇÕES | 8 |
| TOTAL COMO AUTOR | 25 |
| TOTAL COMO EDITOR | 0 |
| PRIMEIRO ANO DE PUBLICAÇÃO | 2010 |
| ANO MAIS RECENTE DE PUBLICAÇÃO | 2026 |
| ÍNDICE H | 2 |
Behaviorally calibrated metrics for comparing alcohol outlet configurations along after-work walking commutes in Mannheim, Germany
Unveiling spatiotemporal mechanisms of urban traffic
Urban AI for a sustainable built environment
Transparency and Trust in Collaborative Mapping
Estimating road speed classes
Long-term validation of inner-urban mobility metrics derived from Twitter/X
Urban mobility analysis using Twitter as a proxy has gained significant attention in various application fields; however, long-term validation studies are scarce. This paper addresses this gap by assessing the reliability of Twitter data for modeling inner-urban mobility dynamics over a 27-month period in the metropolitan area of Rio de Janeiro, Brazil. The evaluation involves the validation of Twitter-derived mobility estimates at both temporal …
Urban Aedes aegypti suitability indicators
Mapping energy poverty indices in urban scale
Crime-associated inequality in geographical access to education
Distortions in Judged Spatial Relations in Large Language Models
We present a benchmark for assessing the capability of large language models (LLMs) to discern intercardinal directions between geographic locations and apply it to three prominent LLMs: GPT-3.5, GPT-4, and Llama-2. This benchmark specifically evaluates whether LLMs exhibit a hierarchical spatial bias similar to humans, where judgments about individual locations’ spatial relationships are influenced by the perceived relationships of the larger gr…
How to assess the needs of vulnerable population groups towards heat-sensitive routing
Heat poses a significant risk to human health, particularly for vulnerable populations, such as pregnant women, older individuals, young children and people with pre-existing medical conditions. In view of this, we formulated a heat stress-avoidant routing approach in Heidelberg, Germany, to ensure mobility and support day-to-day activities in urban areas during heat events. Although the primary focus is on pedestrians, it is also applicable to c…
Private Vehicles Greenhouse Gas Emission Estimation at Street Level for Berlin Based on Open Data
As one of the major greenhouse gas (GHG) emitters that has not seen significant emission reductions in the previous decades, the transportation sector requires special attention from policymakers. Policy decisions, thereby need to be supported by traffic emission assessments. Estimations of traffic emissions often rely on huge amounts of actual traffic data whose availability is limited, hampering the transferability of the estimation approaches …
SocialMedia2Traffic
Traffic prediction is a topic of increasing importance for research and applications in the domain of routing and navigation. Unfortunately, open data are rarely available for this purpose. To overcome this, the authors explored the possibility of using geo-tagged social media data (Twitter), land-use and land-cover point of interest data (from OpenStreetMap) and an adapted betweenness centrality measure as feature spaces to predict the traffic c…
Understanding spatiotemporal trip purposes of urban micro-mobility from the lens of dockless e-scooter sharing
The Impact of Community Happenings in OpenStreetMap—Establishing a Framework for Online Community Member Activity Analyses
The collaborative nature of activities in Web 2.0 projects leads to the formation of online communities. To reinforce this community, these projects often rely on happenings centred around data creation and curation activities. We suggest an integrated framework to directly assess online community member performance in a quantitative manner and applied it to the case study of OpenStreetMap. A set of mappers who participated in both field and remo…
Mapping Public Urban Green Spaces Based on OpenStreetMap and Sentinel-2 Imagery Using Belief Functions
Public urban green spaces are important for the urban quality of life. Still, comprehensive open data sets on urban green spaces are not available for most cities. As open and globally available data sets, the potential of Sentinel-2 satellite imagery and OpenStreetMap (OSM) data for urban green space mapping is high but limited due to their respective uncertainties. Sentinel-2 imagery cannot distinguish public from private green spaces and its s…
The Sketch Map Tool Facilitates the Assessment of OpenStreetMap Data for Participatory Mapping
A worldwide increase in the number of people and areas affected by disasters has led to more and more approaches that focus on the integration of local knowledge into disaster risk reduction processes. The research at hand shows a method for formalizing this local knowledge via sketch maps in the context of flooding. The Sketch Map Tool enables not only the visualization of this local knowledge and analyses of OpenStreetMap data quality but also …
Analysing the Impact of Large Data Imports in OpenStreetMap
OpenStreetMap (OSM) is a global mapping project which generates free geographical information through a community of volunteers. OSM is used in a variety of applications and for research purposes. However, it is also possible to import external data sets to OpenStreetMap. The opinions about these data imports are divergent among researchers and contributors, and the subject is constantly discussed. The question of whether importing data, especial…
The role of data in transformations to sustainability
This article investigates the role of digital technologies and data innovations, such as big data and citizen-generated data, to enable transformations to sustainability. We reviewed recent literature in this area and identified that the most prevailing assumption of work is related to the capacity of data to inform decision-making and support transformations. However, there is a lack of critical investigation on the concrete pathways for this to…
Towards Detecting Building Facades with Graffiti Artwork Based on Street View Images
As a recognized type of art, graffiti is a cultural asset and an important aspect of a city’s aesthetics. As such, graffiti is associated with social and commercial vibrancy and is known to attract tourists. However, positional uncertainty and incompleteness are current issues of open geo-datasets containing graffiti data. In this paper, we present an approach towards detecting building facades with graffiti artwork based on the automatic interpr…
An exploration of the interaction between urban human activities and daily traffic conditions
Location‐Based Services
The past decade has seen major advances in location‐based technologies and geospatial information. Gradually, the public's awareness and consideration of the spatial aspects of life are increasing, due to the ubiquity of so‐called location‐based services (LBS). While popular navigation or mapping services like Google Maps have contributed to this “revolution,” today's LBS include an amazing variety of services and are imposing themselves in a muc…
Deriving incline values for street networks from voluntarily collected GPS traces
When producing optimal routes through an environment, considering the incline of surfaces can be of great benefit in a number of use cases. For instance, steep segments need to be avoided for energy-efficient routes and for routes that are suitable for mobility-restricted people. Such incline information may be derived from digital elevation models (DEMs). However, the corresponding data capturing methods (e.g. airborne LiDAR, photogrammetry, and…
A geographic approach for combining social media and authoritative data towards identifying useful information for disaster management
In recent years, social media emerged as a potential resource to improve the management of crisis situations such as disasters triggered by natural hazards. Although there is a growing research body concerned with the analysis of the usage of social media during disasters, most previous work has concentrated on using social media as a stand-alone information source, whereas its combination with other information sources holds a still underexplore…
Generating web-based 3D City Models from OpenStreetMap
The role of data in transformations to sustainability
This article investigates the role of digital technologies and data innovations, such as big data and citizen-generated data, to enable transformations to sustainability. We reviewed recent literature in this area and identified that the most prevailing assumption of work is related to the capacity of data to inform decision-making and support transformations. However, there is a lack of critical investigation on the concrete pathways for this to…
An exploration of the interaction between urban human activities and daily traffic conditions
Generating web-based 3D City Models from OpenStreetMap
Generating web-based 3D City Models from OpenStreetMap
A geographic approach for combining social media and authoritative data towards identifying useful information for disaster management
In recent years, social media emerged as a potential resource to improve the management of crisis situations such as disasters triggered by natural hazards. Although there is a growing research body concerned with the analysis of the usage of social media during disasters, most previous work has concentrated on using social media as a stand-alone information source, whereas its combination with other information sources holds a still underexplore…
Deriving incline values for street networks from voluntarily collected GPS traces
When producing optimal routes through an environment, considering the incline of surfaces can be of great benefit in a number of use cases. For instance, steep segments need to be avoided for energy-efficient routes and for routes that are suitable for mobility-restricted people. Such incline information may be derived from digital elevation models (DEMs). However, the corresponding data capturing methods (e.g. airborne LiDAR, photogrammetry, and…
Location‐Based Services
The past decade has seen major advances in location‐based technologies and geospatial information. Gradually, the public's awareness and consideration of the spatial aspects of life are increasing, due to the ubiquity of so‐called location‐based services (LBS). While popular navigation or mapping services like Google Maps have contributed to this “revolution,” today's LBS include an amazing variety of services and are imposing themselves in a muc…
An exploration of the interaction between urban human activities and daily traffic conditions
Towards Detecting Building Facades with Graffiti Artwork Based on Street View Images
As a recognized type of art, graffiti is a cultural asset and an important aspect of a city’s aesthetics. As such, graffiti is associated with social and commercial vibrancy and is known to attract tourists. However, positional uncertainty and incompleteness are current issues of open geo-datasets containing graffiti data. In this paper, we present an approach towards detecting building facades with graffiti artwork based on the automatic interpr…
The Impact of Community Happenings in OpenStreetMap—Establishing a Framework for Online Community Member Activity Analyses
The collaborative nature of activities in Web 2.0 projects leads to the formation of online communities. To reinforce this community, these projects often rely on happenings centred around data creation and curation activities. We suggest an integrated framework to directly assess online community member performance in a quantitative manner and applied it to the case study of OpenStreetMap. A set of mappers who participated in both field and remo…
Mapping Public Urban Green Spaces Based on OpenStreetMap and Sentinel-2 Imagery Using Belief Functions
Public urban green spaces are important for the urban quality of life. Still, comprehensive open data sets on urban green spaces are not available for most cities. As open and globally available data sets, the potential of Sentinel-2 satellite imagery and OpenStreetMap (OSM) data for urban green space mapping is high but limited due to their respective uncertainties. Sentinel-2 imagery cannot distinguish public from private green spaces and its s…
The Sketch Map Tool Facilitates the Assessment of OpenStreetMap Data for Participatory Mapping
A worldwide increase in the number of people and areas affected by disasters has led to more and more approaches that focus on the integration of local knowledge into disaster risk reduction processes. The research at hand shows a method for formalizing this local knowledge via sketch maps in the context of flooding. The Sketch Map Tool enables not only the visualization of this local knowledge and analyses of OpenStreetMap data quality but also …
Analysing the Impact of Large Data Imports in OpenStreetMap
OpenStreetMap (OSM) is a global mapping project which generates free geographical information through a community of volunteers. OSM is used in a variety of applications and for research purposes. However, it is also possible to import external data sets to OpenStreetMap. The opinions about these data imports are divergent among researchers and contributors, and the subject is constantly discussed. The question of whether importing data, especial…
The role of data in transformations to sustainability
This article investigates the role of digital technologies and data innovations, such as big data and citizen-generated data, to enable transformations to sustainability. We reviewed recent literature in this area and identified that the most prevailing assumption of work is related to the capacity of data to inform decision-making and support transformations. However, there is a lack of critical investigation on the concrete pathways for this to…
SocialMedia2Traffic
Traffic prediction is a topic of increasing importance for research and applications in the domain of routing and navigation. Unfortunately, open data are rarely available for this purpose. To overcome this, the authors explored the possibility of using geo-tagged social media data (Twitter), land-use and land-cover point of interest data (from OpenStreetMap) and an adapted betweenness centrality measure as feature spaces to predict the traffic c…
Understanding spatiotemporal trip purposes of urban micro-mobility from the lens of dockless e-scooter sharing
Private Vehicles Greenhouse Gas Emission Estimation at Street Level for Berlin Based on Open Data
As one of the major greenhouse gas (GHG) emitters that has not seen significant emission reductions in the previous decades, the transportation sector requires special attention from policymakers. Policy decisions, thereby need to be supported by traffic emission assessments. Estimations of traffic emissions often rely on huge amounts of actual traffic data whose availability is limited, hampering the transferability of the estimation approaches …
Distortions in Judged Spatial Relations in Large Language Models
We present a benchmark for assessing the capability of large language models (LLMs) to discern intercardinal directions between geographic locations and apply it to three prominent LLMs: GPT-3.5, GPT-4, and Llama-2. This benchmark specifically evaluates whether LLMs exhibit a hierarchical spatial bias similar to humans, where judgments about individual locations’ spatial relationships are influenced by the perceived relationships of the larger gr…
How to assess the needs of vulnerable population groups towards heat-sensitive routing
Heat poses a significant risk to human health, particularly for vulnerable populations, such as pregnant women, older individuals, young children and people with pre-existing medical conditions. In view of this, we formulated a heat stress-avoidant routing approach in Heidelberg, Germany, to ensure mobility and support day-to-day activities in urban areas during heat events. Although the primary focus is on pedestrians, it is also applicable to c…
Long-term validation of inner-urban mobility metrics derived from Twitter/X
Urban mobility analysis using Twitter as a proxy has gained significant attention in various application fields; however, long-term validation studies are scarce. This paper addresses this gap by assessing the reliability of Twitter data for modeling inner-urban mobility dynamics over a 27-month period in the metropolitan area of Rio de Janeiro, Brazil. The evaluation involves the validation of Twitter-derived mobility estimates at both temporal …
Urban Aedes aegypti suitability indicators
Mapping energy poverty indices in urban scale
Crime-associated inequality in geographical access to education
Behaviorally calibrated metrics for comparing alcohol outlet configurations along after-work walking commutes in Mannheim, Germany
Unveiling spatiotemporal mechanisms of urban traffic
Urban AI for a sustainable built environment
Transparency and Trust in Collaborative Mapping
Estimating road speed classes
Computer Science (14 obras) · Geography (13 obras) · Data science (8 obras) · Human Mobility and Location-Based Analysis (8 obras) · Cartography (6 obras) · World Wide Web (6 obras) · Artificial Intelligence (5 obras) · Data mining (5 obras) · Engineering (5 obras) · Geographic Information Systems Studies (5 obras)