Abstract
The cities in semi-arid and arid regions generally exhibit distinctive land use land cover (LULC) pattern and seasonal variation in urban thermal comfort (UTC) and land surface temperature (LST). This study examines the seasonal variation in LST and UTC and quantify the importance of LULC pattern in influencing LST in eight Indian semi-arid cities using Landsat 8 datasets. Random forest regression (RFR) model has been applied to quantify the influence of LULC in determining LST. The study shows that bare soil and open spaces in outskirts of selected cities have comparatively high LST than the core of cities. The mean LST varies seasonally from 12.84 °C in Udaipur to 26.18 °C in Jaipur in winter and summer. Analysis of UTC shows that autumn and winter seasons have better UTC than spring and summer seasons. RFR analysis shows a robust correlation (R2 > 0.85) between LULC and LST across all cities. Notably, built-up areas, open land, and vegetation cover exert the greatest influence on LST. Study suggests that targeted LULC planning may effectively address UTC problem in semi-arid cities and enhance sustainability. Study may help in understanding the seasonality thermal environment and assist in mitigating UHI and maintain UTC in these cities.
| Original language | English |
|---|---|
| Article number | 102105 |
| Journal | Urban Climate |
| Volume | 57 |
| DOIs | |
| Publication status | Published - Sept 2024 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 15 Life on Land
Keywords
- Land surface temperature
- Land use land cover
- Random Forest regression
- Seasonal urban thermal comfort
- Semi-arid cities
ASJC Scopus subject areas
- Geography, Planning and Development
- Environmental Science (miscellaneous)
- Urban Studies
- Atmospheric Science
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