The Impact of Urbanization-Induced Land Use Change on Land Surface Temperature
(2024) In Remote Sensing 16(23).- Abstract
Rapid urbanization can change local climate by increasing land surface temperature (LST), particularly in metropolitan regions. This study uses two decades of remote sensing data to investigate how urbanization-induced changes in land use/land cover (LULC) affect LST in the Beijing Region, China. By focusing on the key issue of LST and its contributing variables through buffer zones, we determined how variables influence LST across buffer zones—core, transit, and suburban areas. This approach is crucial for identifying and prioritizing key variables in each zone, enabling targeted, zone-specific measures that can more effectively mitigate LST rise. The main driving variables for the Beijing Region were determined, and the... (More)
Rapid urbanization can change local climate by increasing land surface temperature (LST), particularly in metropolitan regions. This study uses two decades of remote sensing data to investigate how urbanization-induced changes in land use/land cover (LULC) affect LST in the Beijing Region, China. By focusing on the key issue of LST and its contributing variables through buffer zones, we determined how variables influence LST across buffer zones—core, transit, and suburban areas. This approach is crucial for identifying and prioritizing key variables in each zone, enabling targeted, zone-specific measures that can more effectively mitigate LST rise. The main driving variables for the Beijing Region were determined, and the spatial-temporal relationship between LST and driving variables was investigated using a geographically weighted regression (GWR) model. The results demonstrate that the Beijing Region’s LST climbed from 2002 to 2022, with increases of 0.904, 0.768, and 0.248 °C in core, transit, and suburban areas, respectively. The study found that human-induced variables contributed significantly to the increase in LST across core and transit areas. Meanwhile, natural variables in suburban areas predominated and contributed to stabilizing local climates and cooling. Over two decades and in all buffer zones, GWR models slightly outperformed ordinary least squares (OLS) models, suggesting that the LST is highly influenced by its local geographical location, incorporating natural and human-induced variables. The results of this study have substantial implications for designing methods to mitigate LST across the three buffer zones in the Beijing Region.
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- author
- Halefom, Afera ; He, Yan ; Nemoto, Tatsuya ; Feng, Lei ; Li, Runkui ; Raghavan, Venkatesh ; Jing, Guifei ; Song, Xianfeng and Duan, Zheng LU
- organization
- publishing date
- 2024-12
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- buffer zones, human-induced, land surface temperature, urbanization
- in
- Remote Sensing
- volume
- 16
- issue
- 23
- article number
- 4502
- publisher
- MDPI AG
- external identifiers
-
- scopus:85211811942
- ISSN
- 2072-4292
- DOI
- 10.3390/rs16234502
- language
- English
- LU publication?
- yes
- id
- 2dd71b61-c606-4457-a0be-e72fe6571c4e
- date added to LUP
- 2025-01-22 11:40:29
- date last changed
- 2025-04-04 14:12:53
@article{2dd71b61-c606-4457-a0be-e72fe6571c4e,
abstract = {{<p>Rapid urbanization can change local climate by increasing land surface temperature (LST), particularly in metropolitan regions. This study uses two decades of remote sensing data to investigate how urbanization-induced changes in land use/land cover (LULC) affect LST in the Beijing Region, China. By focusing on the key issue of LST and its contributing variables through buffer zones, we determined how variables influence LST across buffer zones—core, transit, and suburban areas. This approach is crucial for identifying and prioritizing key variables in each zone, enabling targeted, zone-specific measures that can more effectively mitigate LST rise. The main driving variables for the Beijing Region were determined, and the spatial-temporal relationship between LST and driving variables was investigated using a geographically weighted regression (GWR) model. The results demonstrate that the Beijing Region’s LST climbed from 2002 to 2022, with increases of 0.904, 0.768, and 0.248 °C in core, transit, and suburban areas, respectively. The study found that human-induced variables contributed significantly to the increase in LST across core and transit areas. Meanwhile, natural variables in suburban areas predominated and contributed to stabilizing local climates and cooling. Over two decades and in all buffer zones, GWR models slightly outperformed ordinary least squares (OLS) models, suggesting that the LST is highly influenced by its local geographical location, incorporating natural and human-induced variables. The results of this study have substantial implications for designing methods to mitigate LST across the three buffer zones in the Beijing Region.</p>}},
author = {{Halefom, Afera and He, Yan and Nemoto, Tatsuya and Feng, Lei and Li, Runkui and Raghavan, Venkatesh and Jing, Guifei and Song, Xianfeng and Duan, Zheng}},
issn = {{2072-4292}},
keywords = {{buffer zones; human-induced; land surface temperature; urbanization}},
language = {{eng}},
number = {{23}},
publisher = {{MDPI AG}},
series = {{Remote Sensing}},
title = {{The Impact of Urbanization-Induced Land Use Change on Land Surface Temperature}},
url = {{http://dx.doi.org/10.3390/rs16234502}},
doi = {{10.3390/rs16234502}},
volume = {{16}},
year = {{2024}},
}