Version 1
: Received: 16 July 2022 / Approved: 18 July 2022 / Online: 18 July 2022 (04:49:07 CEST)
Version 2
: Received: 5 September 2023 / Approved: 6 September 2023 / Online: 7 September 2023 (04:05:46 CEST)
How to cite:
Rasul, A. Artificial Intelligence-Enabled Assessment of Urban Growth Impacts on Land Surface Temperature in a Hot Desert Climate: A Case Study of Baghdad City. Preprints2022, 2022070248. https://doi.org/10.20944/preprints202207.0248.v2
Rasul, A. Artificial Intelligence-Enabled Assessment of Urban Growth Impacts on Land Surface Temperature in a Hot Desert Climate: A Case Study of Baghdad City. Preprints 2022, 2022070248. https://doi.org/10.20944/preprints202207.0248.v2
Rasul, A. Artificial Intelligence-Enabled Assessment of Urban Growth Impacts on Land Surface Temperature in a Hot Desert Climate: A Case Study of Baghdad City. Preprints2022, 2022070248. https://doi.org/10.20944/preprints202207.0248.v2
APA Style
Rasul, A. (2023). Artificial Intelligence-Enabled Assessment of Urban Growth Impacts on Land Surface Temperature in a Hot Desert Climate: A Case Study of Baghdad City. Preprints. https://doi.org/10.20944/preprints202207.0248.v2
Chicago/Turabian Style
Rasul, A. 2023 "Artificial Intelligence-Enabled Assessment of Urban Growth Impacts on Land Surface Temperature in a Hot Desert Climate: A Case Study of Baghdad City" Preprints. https://doi.org/10.20944/preprints202207.0248.v2
Abstract
The rapid growth of urban areas is a major challenge facing cities around the world. This growth can have a significant impact on the local climate, leading to higher temperatures and other changes. In desert climates, the effects of urban expansion can be particularly pronounced. This study investigated the impact of urban expansion on land surface temperature (LST) in Baghdad, Iraq. Notably, this study employs a sophisticated artificial intelligence method known as Random Forest for Land Use Land Cover (LULC) classification, utilizing three Landsat images spanning the temporal spectrum from 1985 to 2021 to meticulously monitor land use transformations and associated LST variations. The results showed that vegetated areas declined by 46.8% during the study period, while built-up areas increased by 124.7%. This decline in vegetation was accompanied by an increase in LST, with bare soil recording the highest temperatures. The study also found that LST has a strong inverse relationship with vegetation and moisture. This means that areas with more vegetation and moisture tend to have lower LSTs. These findings suggest that urban expansion can lead to higher LSTs in desert climates, which can have implications for the health and wellbeing of residents. The study has important implications for urban planners and policymakers in Baghdad and other cities in desert climates. By identifying the main factors that control LST, the study provides insights into strategies for mitigating the effects of urban expansion on temperature.
Keywords
Landsat; urban growth; Land Use Land Cover (LULC); remote sensing; urbanisation; NDVI
Subject
Environmental and Earth Sciences, Environmental Science
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Commenter: Azad Rasul
Commenter's Conflict of Interests: Author