Exploring Urban Land Cover Changes and the Effect on Nocturnal Air Temperature Dynamics in Helsingborg - A temperature modeling made with TAPM
Abstract
In light of increasing global temperatures, urban areas face growing challenges related to heat
stress. Alterations in land cover (LC) within cities contribute to changes in the intra-urban
climate, predominantly driven by the replacement of vegetated surfaces with impermeable
materials. These changes affect the thermal properties of urban environments, exacerbating
the Urban Heat Island effect. Understanding the impact of land cover changes (LCC) on
urban climate necessitates the use of remote sensing, pre-trained deep learning models, and
temperature modeling techniques.
This study focuses on assessing land cover changes in the Helsingborg urban area from 2004
to 2020 through image classification utilizing a pre-trained deep learning model.
Furthermore, it investigates the influence of LCC on nocturnal air temperature using the
three-dimensional prognostic air pollution and meteorological model, The Air Pollution
Model (TAPM). Specifically, the analysis centers around the 2018 heatwave in Sweden,
aiming to evaluate TAPM's ability to differentiate between various land cover types and
identify temperature patterns within the Intra-Urban Heat Islands. The deep learning model
achieved an overall accuracy exceeding 90%, revealing a decline in grass surfaces and an
increase in areas covered by buildings and trees. TAPM's temperature modeling, based on the
land cover classifications, demonstrated distinct temperature variations at a 100 x 100-meter
local scale. Additionally, it indicated a higher proportion of areas with elevated nighttime
temperatures (>18°C), posing potential health risks during heatwave events akin to the
summer of 2018
Degree
Student essay
Collections
View/ Open
Date
2023-10-09Author
Bäck, Amanda
Keywords
Nocturnal Air Temperature
Intra-Urban Heat Island
Land Cover Classification
Deep learning
The Air Pollution Model (TAPM)
Land Cover Change
Series/Report no.
B1272
Language
eng