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Geoscientific Model Development An interactive open-access journal of the European Geosciences Union
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© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: model evaluation paper 13 Jul 2020

Submitted as: model evaluation paper | 13 Jul 2020

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This preprint is currently under review for the journal GMD.

A spatially-explicit approach to simulate urban heat islands in complex urban landscapes

Martí Bosch1, Maxence Locatelli1, Perrine Hamel2, Roy P. Remme3, Jérôme Chenal1, and Stéphane Joost4,1 Martí Bosch et al.
  • 1Urban and Regional Planning Community, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
  • 2Asian School of the Environment, Nanyang Technological University, Singapore
  • 3Natural Capital Project, Stanford University, Stanford, USA
  • 4Laboratory of Geographic Information Systems, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland

Abstract. Mitigating urban heat islands has become an important objective for many cities experiencing heat waves. Despite notable progress, the spatial relationship between land use/land cover patterns and the distribution of air temperature remains poorly understood. This article presents a reusable computational workflow to simulate the spatial distribution of air temperature in urban areas from their land use/land cover data. The approach employs the InVEST urban cooling model, which estimates the cooling capacity of the urban fabric based on three biophysical mechanisms, i.e., tree shade, evapotranspiration and albedo. An automated procedure is proposed to calibrate the parameters of the model to best fit air temperature observations from monitoring stations. In a case study in Lausanne, Switzerland, spatial estimates of air temperature obtained with the calibrated model show that the urban cooling model outperforms spatial regressions based on satellite data. This represents two major advances in urban heat island modeling. First, unlike in black-box approaches, the calibrated parameters of the urban cooling model can be interpreted in terms of the physical mechanisms that they represent and can therefore help understanding how urban heat islands emerge in a particular context. Second, the urban cooling model requires only land use/land cover and reference temperature data and can therefore be used to evaluate synthetic scenarios such as master plans, urbanization prospects, and climate scenarios. The proposed approach provides valuable insights into the emergence of urban heat islands which can serve to inform urban planning and assist the design of heat mitigation policies.

Martí Bosch et al.

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Martí Bosch et al.

Martí Bosch et al.


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