Quantifying urban heat exposure at fine scale - modeling outdoor and indoor temperatures using citizen science and VHR remote sensing

  • Global warming and advancing urbanization lead to an increased heat exposure for city dwellers. Especially during summertime heatwaves, extreme daytime as well as high nighttime temperatures expose vulnerable people to potentially deadly heat risk. This applies specifically to indoor air temperatures, since people spend a lot of their time indoors. Against this background, this study relates outdoor and indoor air temperature measurements to area-wide geospatial data regarding summertime urban heat in the city of Augsburg, Germany. Air temperature data is collected from formalized as well as citizen science measurements, while remote sensing data with very-high spatial resolution (VHR) is utilized for assessment of their drivers and influencing factors. A land use regression approach is developed for city-wide modeling of outdoor and indoor air temperatures at the level of individual residential buildings. Daytime outdoor temperatures could be largely explained by vegetation parametersGlobal warming and advancing urbanization lead to an increased heat exposure for city dwellers. Especially during summertime heatwaves, extreme daytime as well as high nighttime temperatures expose vulnerable people to potentially deadly heat risk. This applies specifically to indoor air temperatures, since people spend a lot of their time indoors. Against this background, this study relates outdoor and indoor air temperature measurements to area-wide geospatial data regarding summertime urban heat in the city of Augsburg, Germany. Air temperature data is collected from formalized as well as citizen science measurements, while remote sensing data with very-high spatial resolution (VHR) is utilized for assessment of their drivers and influencing factors. A land use regression approach is developed for city-wide modeling of outdoor and indoor air temperatures at the level of individual residential buildings. Daytime outdoor temperatures could be largely explained by vegetation parameters and imperviousness, whereas nighttime temperatures were more related to the building stock and radiation properties. For indoor temperatures, building density as well as building height and volume are additionally relevant. Outdoor air temperatures could be modeled with higher accuracies (mean absolute error (MAE) < 0.5 °C) compared to indoor temperatures (MAE < 1.5 °C), whereas outdoor and indoor modeling results are consistent with well-known patterns across different local climate zones (LCZ).show moreshow less

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Metadaten
Author:Tobias Leichtle, Marlene Kühnl, Ariane Droin, Christoph BeckORCiDGND, Michael Hiete, Hannes Taubenböck
URN:urn:nbn:de:bvb:384-opus4-1041846
Frontdoor URLhttps://opus.bibliothek.uni-augsburg.de/opus4/104184
ISSN:2212-0955OPAC
Parent Title (English):Urban Climate
Publisher:Elsevier BV
Place of publication:Amsterdam
Type:Article
Language:English
Year of first Publication:2023
Publishing Institution:Universität Augsburg
Release Date:2023/05/09
Tag:Atmospheric Science; Urban Studies; Environmental Science (miscellaneous); Geography, Planning and Development
Volume:49
First Page:101522
DOI:https://doi.org/10.1016/j.uclim.2023.101522
Institutes:Fakultät für Angewandte Informatik
Fakultät für Angewandte Informatik / Institut für Geographie
Fakultät für Angewandte Informatik / Institut für Geographie / Lehrstuhl für Physische Geographie mit Schwerpunkt Klimaforschung
Nachhaltigkeitsziele
Nachhaltigkeitsziele / Ziel 11 - Nachhaltige Städte und Gemeinden
Dewey Decimal Classification:9 Geschichte und Geografie / 91 Geografie, Reisen / 910 Geografie, Reisen
Licence (German):CC-BY-NC-ND 4.0: Creative Commons: Namensnennung - Nicht kommerziell - Keine Bearbeitung (mit Print on Demand)