The Spatiotemporal Implications of Urbanization for Urban Heat Islands in Beijing: A Predictive Approach Based on CA–Markov Modeling (2004–2050)
The rapid increase in infrastructural development in populated areas has had numerous adverse impacts. The rise in land surface temperature (LST) and its associated damage to urban ecological systems result from urban development. Understanding the current and future LST phenomenon and its relations...
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MDPI AG
2021
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oai:doaj.org-article:cc87ae53e31f41e0b16ae8cb19eb9ec32021-11-25T18:55:29ZThe Spatiotemporal Implications of Urbanization for Urban Heat Islands in Beijing: A Predictive Approach Based on CA–Markov Modeling (2004–2050)10.3390/rs132246972072-4292https://doaj.org/article/cc87ae53e31f41e0b16ae8cb19eb9ec32021-11-01T00:00:00Zhttps://www.mdpi.com/2072-4292/13/22/4697https://doaj.org/toc/2072-4292The rapid increase in infrastructural development in populated areas has had numerous adverse impacts. The rise in land surface temperature (LST) and its associated damage to urban ecological systems result from urban development. Understanding the current and future LST phenomenon and its relationship to landscape composition and land use/cover (LUC) changes is critical to developing policies to mitigate the disastrous impacts of urban heat islands (UHIs) on urban ecosystems. Using remote sensing and GIS data, this study assessed the multi-scale relationship of LUCC and LST of the cosmopolitan exponentially growing area of Beijing, China. We investigated the impacts of LUC on LST in urban agglomeration for a time series (2004–2019) of Landsat data using Classification and Regression Trees (CART) and a single channel algorithm (SCA), respectively. We built a CA–Markov model to forecast future (2025 and 2050) LUCC and LST spatial patterns. Our results indicate that the cumulative changes in an urban area (UA) increased by about 908.15 km<sup>2</sup> (5%), and 11% of vegetation area (VA) decreased from 2004 to 2019. The correlation coefficient of LUCC including vegetation, water bodies, and built-up areas with LST had values of r = −0.155 (<i>p</i> > 0.419), −0.809 (<i>p</i> = 0.000), and 0.526 (<i>p</i> = 0.003), respectively. The results surrounding future forecasts revealed an estimated 2309.55 km<sup>2</sup> (14%) decrease in vegetation (urban and forest), while an expansion of 1194.78 km<sup>2</sup> (8%) was predicted for a built-up area from 2019 to 2050. This decrease in vegetation cover and expansion of settlements would likely cause a rise of about ~5.74 °C to ~9.66 °C in temperature. These findings strongly support the hypothesis that LST is directly related to the vegetation index. In conclusion, the estimated overall increase of 7.5 °C in LST was predicted from 2019–2050, which is alarming for the urban community’s environmental health. The present results provide insight into sustainable environmental development through effective urban planning of Beijing and other urban hotspots.Muhammad Amir SiddiqueYu WangNinghan XuNadeem UllahPeng ZengMDPI AGarticleurban heat island (UHI)sustainable spatial planningCA–Markovurban geographyurban planning and developmenturban change modelingScienceQENRemote Sensing, Vol 13, Iss 4697, p 4697 (2021) |
| institution |
DOAJ |
| collection |
DOAJ |
| language |
EN |
| topic |
urban heat island (UHI) sustainable spatial planning CA–Markov urban geography urban planning and development urban change modeling Science Q |
| spellingShingle |
urban heat island (UHI) sustainable spatial planning CA–Markov urban geography urban planning and development urban change modeling Science Q Muhammad Amir Siddique Yu Wang Ninghan Xu Nadeem Ullah Peng Zeng The Spatiotemporal Implications of Urbanization for Urban Heat Islands in Beijing: A Predictive Approach Based on CA–Markov Modeling (2004–2050) |
| description |
The rapid increase in infrastructural development in populated areas has had numerous adverse impacts. The rise in land surface temperature (LST) and its associated damage to urban ecological systems result from urban development. Understanding the current and future LST phenomenon and its relationship to landscape composition and land use/cover (LUC) changes is critical to developing policies to mitigate the disastrous impacts of urban heat islands (UHIs) on urban ecosystems. Using remote sensing and GIS data, this study assessed the multi-scale relationship of LUCC and LST of the cosmopolitan exponentially growing area of Beijing, China. We investigated the impacts of LUC on LST in urban agglomeration for a time series (2004–2019) of Landsat data using Classification and Regression Trees (CART) and a single channel algorithm (SCA), respectively. We built a CA–Markov model to forecast future (2025 and 2050) LUCC and LST spatial patterns. Our results indicate that the cumulative changes in an urban area (UA) increased by about 908.15 km<sup>2</sup> (5%), and 11% of vegetation area (VA) decreased from 2004 to 2019. The correlation coefficient of LUCC including vegetation, water bodies, and built-up areas with LST had values of r = −0.155 (<i>p</i> > 0.419), −0.809 (<i>p</i> = 0.000), and 0.526 (<i>p</i> = 0.003), respectively. The results surrounding future forecasts revealed an estimated 2309.55 km<sup>2</sup> (14%) decrease in vegetation (urban and forest), while an expansion of 1194.78 km<sup>2</sup> (8%) was predicted for a built-up area from 2019 to 2050. This decrease in vegetation cover and expansion of settlements would likely cause a rise of about ~5.74 °C to ~9.66 °C in temperature. These findings strongly support the hypothesis that LST is directly related to the vegetation index. In conclusion, the estimated overall increase of 7.5 °C in LST was predicted from 2019–2050, which is alarming for the urban community’s environmental health. The present results provide insight into sustainable environmental development through effective urban planning of Beijing and other urban hotspots. |
| format |
article |
| author |
Muhammad Amir Siddique Yu Wang Ninghan Xu Nadeem Ullah Peng Zeng |
| author_facet |
Muhammad Amir Siddique Yu Wang Ninghan Xu Nadeem Ullah Peng Zeng |
| author_sort |
Muhammad Amir Siddique |
| title |
The Spatiotemporal Implications of Urbanization for Urban Heat Islands in Beijing: A Predictive Approach Based on CA–Markov Modeling (2004–2050) |
| title_short |
The Spatiotemporal Implications of Urbanization for Urban Heat Islands in Beijing: A Predictive Approach Based on CA–Markov Modeling (2004–2050) |
| title_full |
The Spatiotemporal Implications of Urbanization for Urban Heat Islands in Beijing: A Predictive Approach Based on CA–Markov Modeling (2004–2050) |
| title_fullStr |
The Spatiotemporal Implications of Urbanization for Urban Heat Islands in Beijing: A Predictive Approach Based on CA–Markov Modeling (2004–2050) |
| title_full_unstemmed |
The Spatiotemporal Implications of Urbanization for Urban Heat Islands in Beijing: A Predictive Approach Based on CA–Markov Modeling (2004–2050) |
| title_sort |
spatiotemporal implications of urbanization for urban heat islands in beijing: a predictive approach based on ca–markov modeling (2004–2050) |
| publisher |
MDPI AG |
| publishDate |
2021 |
| url |
https://doaj.org/article/cc87ae53e31f41e0b16ae8cb19eb9ec3 |
| work_keys_str_mv |
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| _version_ |
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