MORICHI
a Dataset to Study Urban Overheating during Extreme Heat in a Hot-Summer Humid Continental Climate
Miguel Martin (TU Delft - Urban Data Science)
Clara Garcia-Sanchez (TU Delft - Urban Data Science)
Jantien Stoter (TU Delft - Urbanism)
Mario Berges
More Info
expand_more
Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.
Abstract
This paper describes a firsthand and open dataset comprising weather data collected from four street-level stations and microscale thermal images captured by a single infrared thermal camera during an extreme heat event in late August 2024 in Pittsburgh, United States. The weather data includes air temperature, relative humidity, wind speed and direction, and rainfall, measured at a height of 2 meters above the ground. From microscale thermal images, it is possible to assess the temperatures of built-up surfaces within a street canyon on a university campus, including a road, sidewalks, and building façades. Other factors that contribute to or mitigate urban overheating, such as waste heat emissions, traffic, and vegetation, can also be analyzed using the microscale thermal images. The weather data and microscale thermal images are publicly accessible in the 4TU.ResearchData repository under the CC BY 4.0 license. A Python library was developed to extract and process the data, particularly microscale thermal images, and is publicly available via the PIP package installer.
help_outline