Analysis of Urban Heat Islands and the Effects of Land Use Changes and Its Synoptic Patterns (Case Study of Ramsar City)
This study aimed to evaluate the effects of urban land use changes on land surface temperature (LST) in Ramsar utilizing a comprehensive methodology that employed Landsat imagery. The results indicated that the built-up index (BI) and built-up area (BU) indices experienced significant growth, increa...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2025-01-01
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| Series: | Advances in Meteorology |
| Online Access: | http://dx.doi.org/10.1155/adme/8876372 |
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| Summary: | This study aimed to evaluate the effects of urban land use changes on land surface temperature (LST) in Ramsar utilizing a comprehensive methodology that employed Landsat imagery. The results indicated that the built-up index (BI) and built-up area (BU) indices experienced significant growth, increasing by ~157.5% and 38.91%, respectively. In contrast, the normalized difference water index (NDWI) exhibited a negative trend, decreasing by ~61.2%. In the base year, man-made land use accounted for ~20% of the city’s area. By 2022, this proportion had risen to ~76%, reflecting an impressive growth rate of 230.4%. This increase in man-made land use demonstrated a strong and positive correlation with the BI and BU indices at confidence levels of 0.01 and 0.05. Furthermore, the urban LST rose from ~35.55°C in the base year to ~38.91°C in 2022. This trend exhibited a significant relationship with the urban hot season temperature, yielding a correlation coefficient of 0.760 at an error level of 0.05. The temperature trends were consistent across various urban areas. Geographically weighted regression (GWR) analysis of LST and urban land use yielded an R2 value of 0.7835 and an adjusted R2 value of 0.7712. The multivariate regression results indicated that the four indices—temperature station, NDWI, BI, and urban—were associated with urban LST at a 95% confidence level. Additionally, the findings from logistic regression involving six indices—normalized difference vegetation index (NDVI), BU, BI, temperature station, gardens, and urban human-made areas—showed significant relationships with LST at error levels of 0.05 and 0.01. Synoptic analysis during the study period revealed that three types of high-pressure systems originating from the subtropical high over Iran influence the surface temperature in Ramsar. These systems include the Saudi Arabian high-pressure system, the Iranian high-pressure pattern, and a weak ridge pattern over Iran. While these systems share the common characteristic of being high-altitude patterns, their origins differ. Heat islands tend to form under stable atmospheric conditions with lower airflow speeds, enhancing their likelihood of occurrence. The results indicated that climate changes in the region, combined with the expansion of urban areas and climate subsidence during the warmer season, have contributed to the intensity and spread of surface temperature in Ramsar City. This trend underscores the necessity for innovative and effective multifaceted approaches to predict and understand this phenomenon, which can assist in urban planning efforts in Ramsar City. |
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| ISSN: | 1687-9317 |