Automated detection of urban heat islands based on satellite imagery, digital surface models, and a low-cost sensor network

Schlögl, Sebastian; Bader, Nico; Anet, Julien Gérard; Frey, Martin; Spirig, Curdin; Renold, Manuel; Gutbrod, Karl

doi:10.5194/egusphere-egu21-14143

Publication type:	Conference poster
Type of review:	Not specified
Title:	Automated detection of urban heat islands based on satellite imagery, digital surface models, and a low-cost sensor network
Authors:	Schlögl, Sebastian Bader, Nico Anet, Julien Gérard Frey, Martin Spirig, Curdin Renold, Manuel Gutbrod, Karl
et. al:	No
DOI:	10.5194/egusphere-egu21-14143
Conference details:	EGU General Assembly 2021, Online, 19-30 April 2021
Issue Date:	2021
Publisher / Ed. Institution:	European Geosciences Union
Language:	English
Subject (DDC):	551: Geology and hydrology
Abstract:	Today, more than half of the world’s population lives in urban areas and the proportion is projected to increase further in the near future. The increased number of heatwaves worldwide caused by the anthropogenic climate change may lead to heat stress and significant economic and ecological damages. Therefore, the growth of urban areas in combination with climate change can increase future mortality rates in cities, given that cities are more vulnerable to heatwaves due to the greater heat storage capacity of artificial surfaces towards higher longwave radiation fluxes. To detect urban heat islands and resolve the micro-scale air temperature field in an urban environment, a low-cost air temperature network, including 450 sensors, was installed in the Swiss cities of Zurich and Basel in 2019 and 2020. These air temperature data, complemented with further official measurement stations, force a statistical air temperature downscaling model for urban environments, which is used operationally to calculate hourly micro-scale air temperatures in 10 m horizontal resolution. In addition to air temperature measurements from the low-cost sensor network, the model is further forced by albedo, NDVI, and NDBI values generated from the polar-orbiting satellite Sentinel-2, land surface temperatures estimated from Landsat-8, and high-resolution digital surface and elevation models. Urban heat islands (UHI) are processed averaging hourly air temperatures over an entire year for each grid point, and comparing this average to the overall average in rural areas. UHI effects can then be correlated to high-resolution local climate zone maps and other local factors. Between 60-80 % of the urban area is modeled with an accuracy below 1 K for an hourly time step indicating that the approach may work well in different cities. However, the outcome may depend on the complexity of the cities. The model error decreases rapidly by increasing the number of spatially distributed sensor data used to train the model, from 0 to 70 sensors, and then plateaus with further increases. An accuracy below 1 K can be expected for more than 50 air temperature measurements within the investigated cities and the surrounding rural areas. A strong statistical air temperature model coupled with atmospheric boundary layer models (e.g. PALM-4U, MUKLIMO, FITNAH) will aid to generate highly resolved urban heat island prediction maps that help decision-makers to identify local heat islands easier. This will ensure that financial resources will be invested as efficiently as possible in mitigation actions.
URI:	https://digitalcollection.zhaw.ch/handle/11475/22484
Fulltext version:	Published version
License (according to publishing contract):	Licence according to publishing contract
Departement:	School of Engineering
Organisational Unit:	Institute of Data Analysis and Process Design (IDP) Centre for Aviation (ZAV)
Appears in collections:	Publikationen School of Engineering

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Schlögl, S., Bader, N., Anet, J. G., Frey, M., Spirig, C., Renold, M., & Gutbrod, K. (2021). Automated detection of urban heat islands based on satellite imagery, digital surface models, and a low-cost sensor network. EGU General Assembly 2021, Online, 19-30 April 2021. https://doi.org/10.5194/egusphere-egu21-14143

Schlögl, S. et al. (2021) ‘Automated detection of urban heat islands based on satellite imagery, digital surface models, and a low-cost sensor network’, in EGU General Assembly 2021, Online, 19-30 April 2021. European Geosciences Union. Available at: https://doi.org/10.5194/egusphere-egu21-14143.

S. Schlögl et al., “Automated detection of urban heat islands based on satellite imagery, digital surface models, and a low-cost sensor network,” in EGU General Assembly 2021, Online, 19-30 April 2021, 2021. doi: 10.5194/egusphere-egu21-14143.

SCHLÖGL, Sebastian, Nico BADER, Julien Gérard ANET, Martin FREY, Curdin SPIRIG, Manuel RENOLD und Karl GUTBROD, 2021. Automated detection of urban heat islands based on satellite imagery, digital surface models, and a low-cost sensor network. In: EGU General Assembly 2021, Online, 19-30 April 2021. Conference poster. European Geosciences Union. 2021

Schlögl, Sebastian, Nico Bader, Julien Gérard Anet, Martin Frey, Curdin Spirig, Manuel Renold, and Karl Gutbrod. 2021. “Automated Detection of Urban Heat Islands Based on Satellite Imagery, Digital Surface Models, and a Low-Cost Sensor Network.” Conference poster. In EGU General Assembly 2021, Online, 19-30 April 2021. European Geosciences Union. https://doi.org/10.5194/egusphere-egu21-14143.

Schlögl, Sebastian, et al. “Automated Detection of Urban Heat Islands Based on Satellite Imagery, Digital Surface Models, and a Low-Cost Sensor Network.” EGU General Assembly 2021, Online, 19-30 April 2021, European Geosciences Union, 2021, https://doi.org/10.5194/egusphere-egu21-14143.