Sven Lautenbach
Biographic Data
| ID | 4348181 |
|---|---|
| NAME | Sven Lautenbach |
| GIVEN NAMES | Sven |
| FAMILY NAME | Lautenbach |
| SIGNATURE | LAUTENBACH S |
| AFFILIATIONS | Heidelberg University |
| ORCID | 0000-0003-1825-9996 |
| VERIFIED | Yes |
| TOTAL WORKS | 19 |
| TOTAL CITATIONS | 33 |
| AUTHOR COUNT | 19 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2011 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 3 |
Unveiling spatiotemporal mechanisms of urban traffic: Multi-scale determinants and explainable street-level dynamics of a graph neural network in Berlin
Predisposing factors of sugarcane abandonment in Rio de Janeiro: Exploring policy implications
Cropland abandonment is an agricultural land use change with notable socioeconomic and environmental implications. Previously managed fields are no longer cultivated and undergo natural succession. Biophysical, socioeconomic, and institutional factors that drive cropland abandonment differ between regions across the globe. In Brazil, Rio de Janeiro State has been showing a strong loss of cropland areas since the end of the 1980s. Especially sugar…
How politics affect pandemic forecasting: Spatio-temporal early warning capabilities of different geo-social media topics in the context of state-level political leaning
Objectives: Due to political polarization, adherence to public health measures varied across US states during the COVID-19 pandemic. Although social media posts have been shown effective in anticipating COVID-19 surges, the impact of political leaning on the effectiveness of different topics for early warning remains mostly unexplored. Our study examines the spatio-temporal early warning potential of different geo-social media topics across repub…
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: A study in Rio de Janeiro, Brazil
Crime-associated inequality in geographical access to education: Insights from the municipality of Rio de Janeiro
How to assess the needs of vulnerable population groups towards heat-sensitive routing: An evidence-based and practical approach to reducing urban heat stress
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 …
Assessing Completeness of OpenStreetMap Building Footprints Using MapSwipe
Natural hazards threaten millions of people all over the world. To address this risk, exposure and vulnerability models with high resolution data are essential. However, in many areas of the world, exposure models are rather coarse and are aggregated over large areas. Although OpenStreetMap (OSM) offers great potential to assess risk at a detailed building-by-building level, the completeness of OSM building footprints is still heterogeneous. We p…
SocialMedia2Traffic: Derivation of Traffic Information from Social Media Data
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…
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…
Farmland abandonment in Rio de Janeiro: Underlying and contributory causes of an announced development
Spatial variations and determinants of infant and under-five mortality in Bangladesh
Collinearity: A review of methods to deal with it and a simulation study evaluating their performance
Collinearity refers to the non independence of predictor variables, usually in a regression‐type analysis. It is a common feature of any descriptive ecological data set and can be a problem for parameter estimation because it inflates the variance of regression parameters and hence potentially leads to the wrong identification of relevant predictors in a statistical model. Collinearity is a severe problem when a model is trained on data from one …
Identifying trade-offs between ecosystem services, land use, and biodiversity: A plea for combining scenario analysis and optimization on different spatial scales
Mapping global land system archetypes
Mental health in the slums of Dhaka - a geoepidemiological study
Factors determining mental well-being were related to the socio-physical environment and individual level characteristics. Given that mental well-being is associated with physiological well-being, our study may provide crucial information for developing better health care and disease prevention programmes in slums of Dhaka and other comparable settings
A quantitative review of ecosystem service studies: approaches, shortcomings and the road ahead: Priorities for ecosystem service studies
1. Ecosystem services are defined as the benefits that humans obtain from ecosystems. Employing the ecosystem service concept is intended to support the development of policies and instruments that integrate social, economic and ecological perspectives. In recent years, this concept has become the paradigm of ecosystem management. 2. The prolific use of the term ‘ecosystem services’ in scientific studies has given rise to concerns about its arbit…
Identifying trade-offs between ecosystem services, land use, and biodiversity: A plea for combining scenario analysis and optimization on different spatial scales
Mapping global land system archetypes
Farmland abandonment in Rio de Janeiro: Underlying and contributory causes of an announced development
Spatial variations and determinants of infant and under-five mortality in Bangladesh
A quantitative review of ecosystem service studies: approaches, shortcomings and the road ahead: Priorities for ecosystem service studies
1. Ecosystem services are defined as the benefits that humans obtain from ecosystems. Employing the ecosystem service concept is intended to support the development of policies and instruments that integrate social, economic and ecological perspectives. In recent years, this concept has become the paradigm of ecosystem management. 2. The prolific use of the term ‘ecosystem services’ in scientific studies has given rise to concerns about its arbit…
Mental health in the slums of Dhaka - a geoepidemiological study
Factors determining mental well-being were related to the socio-physical environment and individual level characteristics. Given that mental well-being is associated with physiological well-being, our study may provide crucial information for developing better health care and disease prevention programmes in slums of Dhaka and other comparable settings
Collinearity: A review of methods to deal with it and a simulation study evaluating their performance
Collinearity refers to the non independence of predictor variables, usually in a regression‐type analysis. It is a common feature of any descriptive ecological data set and can be a problem for parameter estimation because it inflates the variance of regression parameters and hence potentially leads to the wrong identification of relevant predictors in a statistical model. Collinearity is a severe problem when a model is trained on data from one …
Identifying trade-offs between ecosystem services, land use, and biodiversity: A plea for combining scenario analysis and optimization on different spatial scales
Mapping global land system archetypes
Spatial variations and determinants of infant and under-five mortality in Bangladesh
Farmland abandonment in Rio de Janeiro: Underlying and contributory causes of an announced development
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…
SocialMedia2Traffic: Derivation of Traffic Information from Social Media Data
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…
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 …
Assessing Completeness of OpenStreetMap Building Footprints Using MapSwipe
Natural hazards threaten millions of people all over the world. To address this risk, exposure and vulnerability models with high resolution data are essential. However, in many areas of the world, exposure models are rather coarse and are aggregated over large areas. Although OpenStreetMap (OSM) offers great potential to assess risk at a detailed building-by-building level, the completeness of OSM building footprints is still heterogeneous. We p…
How to assess the needs of vulnerable population groups towards heat-sensitive routing: An evidence-based and practical approach to reducing urban heat stress
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…
How politics affect pandemic forecasting: Spatio-temporal early warning capabilities of different geo-social media topics in the context of state-level political leaning
Objectives: Due to political polarization, adherence to public health measures varied across US states during the COVID-19 pandemic. Although social media posts have been shown effective in anticipating COVID-19 surges, the impact of political leaning on the effectiveness of different topics for early warning remains mostly unexplored. Our study examines the spatio-temporal early warning potential of different geo-social media topics across repub…
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: A study in Rio de Janeiro, Brazil
Crime-associated inequality in geographical access to education: Insights from the municipality of Rio de Janeiro
Unveiling spatiotemporal mechanisms of urban traffic: Multi-scale determinants and explainable street-level dynamics of a graph neural network in Berlin
Predisposing factors of sugarcane abandonment in Rio de Janeiro: Exploring policy implications
Cropland abandonment is an agricultural land use change with notable socioeconomic and environmental implications. Previously managed fields are no longer cultivated and undergo natural succession. Biophysical, socioeconomic, and institutional factors that drive cropland abandonment differ between regions across the globe. In Brazil, Rio de Janeiro State has been showing a strong loss of cropland areas since the end of the 1980s. Especially sugar…
Computer Science (11 works) · Geography (10 works) · Environmental Science (5 works) · Land Use and Ecosystem Services (5 works) · Data science (4 works) · Economics (4 works) · Engineering (4 works) · Human Mobility and Location-Based Analysis (4 works) · Political science (4 works) · Traffic Prediction and Management Techniques (4 works)