Influence of urban land-use change on cold-air path occurrence and spatial distribution

Abstract: The urban population is predicted to reach a 70 % share of global population by mid-century. Future urbanization might be directed along several development typologies, e.g. sprawling urbanization, more compact cities, greener cities, or a combination of different typologies. These developments induce urban land-use change that will impact urban climate and might reinforce phenomena such as the urban heat island and thermal discomfort of urban residents. A planning-based mitigation approach to ensure thermal comfort of residents are urban cold-air paths, i.e. low-roughness areas enabling drainage and transport of colder air masses from rural surroundings. This dataset shows how urban land-use change scenarios influence cold-air path occurrence probability and spatial distribution in a mid-European city using the machine learning approach boosted regression trees. Four scenarios were calculated: Urban Sprawl Scenario (USS), Green City Scenario (GCS), Compact Green City Scenario (CGCS) and Compact City Scenario (CCS). The used method allows for the identification of priority areas for cold-air path preservation in urban planning.

Data and Resources

This dataset has no data

Cite this as

Grunwald, Laura, Weber, Stephan (2021). Dataset: Influence of urban land-use change on cold-air path occurrence and spatial distribution. https://doi.org/10.24355/dbbs.084-202108090856-0

DOI retrieved: 2021

Additional Info

Field Value
Imported on January 8, 2025
Last update January 8, 2025
License CC-BY-4.0
Source https://doi.org/10.24355/dbbs.084-202108090856-0
Author Grunwald, Laura
Given Name Laura
Family Name Grunwald
More Authors
Weber, Stephan
Source Creation 2021
Publication Year 2021
Resource Type Dataset - research_data
Subject Areas
Name: Cold-air path

Name: Machine learning

Name: Urban climate

Name: Land-use change

Name: Urban development

Name: 711

Name: 55

Related Identifiers
Identifier: https://leopard.tu-braunschweig.de/receive/dbbs_mods_00069685?XSL.Transformer=mods
Type: URL
Relation: HasMetadata