2023
Wellmann, Thilo; Andersson, Erik; Knapp, Sonja; Scheuer, Sebastian; Lausch, Angela; Palliwoda, Julia; Haase, Dagmar
Reinforcing nature-based solutions through tools providing social-ecological-technological integration Journal Article
In: Ambio, vol. 52, pp. 489–507, 2023.
Abstract | Links | BibTeX | Tags: Climate Change Adaptation, functional diversity, Nature-based solutions, nbs, Remote Sensing, resilience, sets, social-ecological-technological systems
@article{Wellmann2022b,
title = {Reinforcing nature-based solutions through tools providing social-ecological-technological integration},
author = {Thilo Wellmann and Erik Andersson and Sonja Knapp and Sebastian Scheuer and Angela Lausch and Julia Palliwoda and Dagmar Haase},
doi = {10.1007/s13280-022-01801-4},
year = {2023},
date = {2023-03-01},
urldate = {2022-01-01},
journal = {Ambio},
volume = {52},
pages = {489–507},
abstract = {While held to be a means for climate change adaptation and mitigation, nature-based solutions (NbS) themselves are vulnerable to climate change. To find ways of compensating for this vulnerability we combine a focused literature review on how information technology has been used to strengthen positive social–ecological–technological feedback, with the development of a prototype decision-support tool. Guided by the literature review, the tool integrates recent advances in using globally available remote sensing data to elicit information on functional diversity and ecosystem service provisioning with information on human service demand and population vulnerability. When combined, these variables can inform climate change adaptation strategies grounded in local social–ecological realities. This type of integrated monitoring and packaging information to be actionable have potential to support NbS management and local knowledge building for context-tailored solutions to societal challenges in urban environments.},
keywords = {Climate Change Adaptation, functional diversity, Nature-based solutions, nbs, Remote Sensing, resilience, sets, social-ecological-technological systems},
pubstate = {published},
tppubtype = {article}
}
While held to be a means for climate change adaptation and mitigation, nature-based solutions (NbS) themselves are vulnerable to climate change. To find ways of compensating for this vulnerability we combine a focused literature review on how information technology has been used to strengthen positive social–ecological–technological feedback, with the development of a prototype decision-support tool. Guided by the literature review, the tool integrates recent advances in using globally available remote sensing data to elicit information on functional diversity and ecosystem service provisioning with information on human service demand and population vulnerability. When combined, these variables can inform climate change adaptation strategies grounded in local social–ecological realities. This type of integrated monitoring and packaging information to be actionable have potential to support NbS management and local knowledge building for context-tailored solutions to societal challenges in urban environments.
2022
Wellmann, Thilo; Andersson, Erik; Knapp, Sonja; Scheuer, Sebastian; Lausch, Angela; Palliwoda, Julia; Haase, Dagmar
Reinforcing nature-based solutions through tools providing social-ecological-technological integration Journal Article
In: Ambio, 2022.
Links | BibTeX | Tags: Climate Change Adaptation, functional diversity, Nature-based solutions, nbs, Remote Sensing, resilience, sets, social-ecological-technological systems
@article{Wellmann2022,
title = {Reinforcing nature-based solutions through tools providing social-ecological-technological integration},
author = {Thilo Wellmann and Erik Andersson and Sonja Knapp and Sebastian Scheuer and Angela Lausch and Julia Palliwoda and Dagmar Haase},
doi = {10.1007/s13280-022-01801-4},
year = {2022},
date = {2022-01-01},
journal = {Ambio},
keywords = {Climate Change Adaptation, functional diversity, Nature-based solutions, nbs, Remote Sensing, resilience, sets, social-ecological-technological systems},
pubstate = {published},
tppubtype = {article}
}
2021
Lessel, Tilia; Wellmann, Thilo
Umweltgerechtigkeit aus bürgerschaftlicher Perspektive: Handlungsempfehlung am Beispiel Berlin-Schöneberg Journal Article
In: Stadt+Grün, vol. 01, 2021.
Abstract | Links | BibTeX | Tags: Berlin, Climate Change, Climate Change Adaptation, Environmental justice, Urban development, Urban green infrastructure, Urban planning
@article{Thilo_Wellmann_107218183,
title = {Umweltgerechtigkeit aus bürgerschaftlicher Perspektive: Handlungsempfehlung am Beispiel Berlin-Schöneberg},
author = {Tilia Lessel and Thilo Wellmann},
url = {https://stadtundgruen.de/artikel/umweltgerechtigkeit-aus-buergerschaftlicher-perspektive-15076.html},
year = {2021},
date = {2021-01-01},
urldate = {2021-01-01},
journal = {Stadt+Grün},
volume = {01},
abstract = {Städte sind für die Umsetzung von Umweltgerechtigkeit von zentraler Bedeutung. Rund drei Viertel der EuropäerInnen leben in urbanen Räumen, so dass Fragen von Gerechtigkeit und Zugang zu Umweltqualitäten besonders hier entschieden werden. Zudem schaffen Städte durch ihre Baumasse Wärme- und Trockeninseln und damit ein besonders extremes, umwelt- und gesundheitsbelastendes Lokalklima. Vor diesem Hintergrund ist absehbar, dass die Effekte des Klimawandels die Städte besonders betreffen.},
keywords = {Berlin, Climate Change, Climate Change Adaptation, Environmental justice, Urban development, Urban green infrastructure, Urban planning},
pubstate = {published},
tppubtype = {article}
}
Städte sind für die Umsetzung von Umweltgerechtigkeit von zentraler Bedeutung. Rund drei Viertel der EuropäerInnen leben in urbanen Räumen, so dass Fragen von Gerechtigkeit und Zugang zu Umweltqualitäten besonders hier entschieden werden. Zudem schaffen Städte durch ihre Baumasse Wärme- und Trockeninseln und damit ein besonders extremes, umwelt- und gesundheitsbelastendes Lokalklima. Vor diesem Hintergrund ist absehbar, dass die Effekte des Klimawandels die Städte besonders betreffen.
Scheuer, Sebastian; Haase, Dagmar; Haase, Annegret; Wolff, Manuel; Wellmann, Thilo
In: Natural Hazards and Earth System Sciences, vol. 21, no. 1, pp. 203–217, 2021.
Abstract | Links | BibTeX | Tags: Climate Change, Climate Change Adaptation, Leipzig, Machine learning, Natural hazards, Random forest, Risk assessment
@article{Scheuer_2021,
title = {A glimpse into the future of exposure and vulnerabilities in cities? Modelling of residential location choice of urban population with random forest},
author = {Sebastian Scheuer and Dagmar Haase and Annegret Haase and Manuel Wolff and Thilo Wellmann},
url = {https://doi.org/10.5194%2Fnhess-21-203-2021},
doi = {10.5194/nhess-21-203-2021},
year = {2021},
date = {2021-01-01},
urldate = {2021-01-01},
journal = {Natural Hazards and Earth System Sciences},
volume = {21},
number = {1},
pages = {203--217},
publisher = {Copernicus GmbH},
abstract = {The most common approach to assessing natural hazard risk is investigating the willingness to pay in the presence or absence of such risk. In this work, we propose a new, machine-learning-based, indirect approach to the problem, i.e. through residential-choice modelling. Especially in urban environments, exposure and vulnerability are highly dynamic risk components, both being shaped by a complex and continuous reorganization and redistribution of assets within the urban space, including the (re-)location of urban dwellers. By modelling residential-choice behaviour in the city of Leipzig, Germany, we seek to examine how exposure and vulnerabilities are shaped by the residential-location-choice process. The proposed approach reveals hot spots and cold spots of residential choice for distinct socioeconomic groups exhibiting heterogeneous preferences. We discuss the relationship between observed patterns and disaster risk through the lens of exposure and vulnerability, as well as links to urban planning, and explore how the proposed methodology may contribute to predicting future trends in exposure, vulnerability, and risk through this analytical focus. Avenues for future research include the operational strengthening of these linkages for more effective disaster risk management.},
keywords = {Climate Change, Climate Change Adaptation, Leipzig, Machine learning, Natural hazards, Random forest, Risk assessment},
pubstate = {published},
tppubtype = {article}
}
The most common approach to assessing natural hazard risk is investigating the willingness to pay in the presence or absence of such risk. In this work, we propose a new, machine-learning-based, indirect approach to the problem, i.e. through residential-choice modelling. Especially in urban environments, exposure and vulnerability are highly dynamic risk components, both being shaped by a complex and continuous reorganization and redistribution of assets within the urban space, including the (re-)location of urban dwellers. By modelling residential-choice behaviour in the city of Leipzig, Germany, we seek to examine how exposure and vulnerabilities are shaped by the residential-location-choice process. The proposed approach reveals hot spots and cold spots of residential choice for distinct socioeconomic groups exhibiting heterogeneous preferences. We discuss the relationship between observed patterns and disaster risk through the lens of exposure and vulnerability, as well as links to urban planning, and explore how the proposed methodology may contribute to predicting future trends in exposure, vulnerability, and risk through this analytical focus. Avenues for future research include the operational strengthening of these linkages for more effective disaster risk management.
Lessel, Tilia; Wellmann, Thilo
Umweltgerechtigkeit aus bürgerschaftlicher Perspektive: Handlungsempfehlung am Beispiel Berlin-Schöneberg Journal Article
In: Stadt+Grün, vol. 01, 2021.
Abstract | Links | BibTeX | Tags: Berlin, Climate Change, Climate Change Adaptation, Environmental justice, Urban development, Urban green infrastructure, Urban planning
@article{Thilo_Wellmann_107218183b,
title = {Umweltgerechtigkeit aus bürgerschaftlicher Perspektive: Handlungsempfehlung am Beispiel Berlin-Schöneberg},
author = {Tilia Lessel and Thilo Wellmann},
url = {https://stadtundgruen.de/artikel/umweltgerechtigkeit-aus-buergerschaftlicher-perspektive-15076.html},
year = {2021},
date = {2021-01-01},
urldate = {2021-01-01},
journal = {Stadt+Grün},
volume = {01},
abstract = {Städte sind für die Umsetzung von Umweltgerechtigkeit von zentraler Bedeutung. Rund drei Viertel der EuropäerInnen leben in urbanen Räumen, so dass Fragen von Gerechtigkeit und Zugang zu Umweltqualitäten besonders hier entschieden werden. Zudem schaffen Städte durch ihre Baumasse Wärme- und Trockeninseln und damit ein besonders extremes, umwelt- und gesundheitsbelastendes Lokalklima. Vor diesem Hintergrund ist absehbar, dass die Effekte des Klimawandels die Städte besonders betreffen.},
keywords = {Berlin, Climate Change, Climate Change Adaptation, Environmental justice, Urban development, Urban green infrastructure, Urban planning},
pubstate = {published},
tppubtype = {article}
}
Städte sind für die Umsetzung von Umweltgerechtigkeit von zentraler Bedeutung. Rund drei Viertel der EuropäerInnen leben in urbanen Räumen, so dass Fragen von Gerechtigkeit und Zugang zu Umweltqualitäten besonders hier entschieden werden. Zudem schaffen Städte durch ihre Baumasse Wärme- und Trockeninseln und damit ein besonders extremes, umwelt- und gesundheitsbelastendes Lokalklima. Vor diesem Hintergrund ist absehbar, dass die Effekte des Klimawandels die Städte besonders betreffen.
Scheuer, Sebastian; Haase, Dagmar; Haase, Annegret; Wolff, Manuel; Wellmann, Thilo
In: Natural Hazards and Earth System Sciences, vol. 21, no. 1, pp. 203–217, 2021.
Abstract | Links | BibTeX | Tags: Climate Change, Climate Change Adaptation, Leipzig, Machine learning, Natural hazards, Random forest, Risk assessment
@article{Scheuer_2021d,
title = {A glimpse into the future of exposure and vulnerabilities in cities? Modelling of residential location choice of urban population with random forest},
author = {Sebastian Scheuer and Dagmar Haase and Annegret Haase and Manuel Wolff and Thilo Wellmann},
url = {https://doi.org/10.5194%2Fnhess-21-203-2021},
doi = {10.5194/nhess-21-203-2021},
year = {2021},
date = {2021-01-01},
urldate = {2021-01-01},
journal = {Natural Hazards and Earth System Sciences},
volume = {21},
number = {1},
pages = {203–217},
publisher = {Copernicus GmbH},
abstract = {The most common approach to assessing natural hazard risk is investigating the willingness to pay in the presence or absence of such risk. In this work, we propose a new, machine-learning-based, indirect approach to the problem, i.e. through residential-choice modelling. Especially in urban environments, exposure and vulnerability are highly dynamic risk components, both being shaped by a complex and continuous reorganization and redistribution of assets within the urban space, including the (re-)location of urban dwellers. By modelling residential-choice behaviour in the city of Leipzig, Germany, we seek to examine how exposure and vulnerabilities are shaped by the residential-location-choice process. The proposed approach reveals hot spots and cold spots of residential choice for distinct socioeconomic groups exhibiting heterogeneous preferences. We discuss the relationship between observed patterns and disaster risk through the lens of exposure and vulnerability, as well as links to urban planning, and explore how the proposed methodology may contribute to predicting future trends in exposure, vulnerability, and risk through this analytical focus. Avenues for future research include the operational strengthening of these linkages for more effective disaster risk management.},
keywords = {Climate Change, Climate Change Adaptation, Leipzig, Machine learning, Natural hazards, Random forest, Risk assessment},
pubstate = {published},
tppubtype = {article}
}
The most common approach to assessing natural hazard risk is investigating the willingness to pay in the presence or absence of such risk. In this work, we propose a new, machine-learning-based, indirect approach to the problem, i.e. through residential-choice modelling. Especially in urban environments, exposure and vulnerability are highly dynamic risk components, both being shaped by a complex and continuous reorganization and redistribution of assets within the urban space, including the (re-)location of urban dwellers. By modelling residential-choice behaviour in the city of Leipzig, Germany, we seek to examine how exposure and vulnerabilities are shaped by the residential-location-choice process. The proposed approach reveals hot spots and cold spots of residential choice for distinct socioeconomic groups exhibiting heterogeneous preferences. We discuss the relationship between observed patterns and disaster risk through the lens of exposure and vulnerability, as well as links to urban planning, and explore how the proposed methodology may contribute to predicting future trends in exposure, vulnerability, and risk through this analytical focus. Avenues for future research include the operational strengthening of these linkages for more effective disaster risk management.