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<p>Understanding historical and anticipated changes in land use and land cover (LULC) is essential for assessing the effects of urban thermal dynamics, especially in swiftly urbanizing cities in developing countries. This study aims&#xa0;to examine LULC changes&#xa0;from 1990 to 2020, with future forecasts for 2030, 2040, and 2050 in Kolkata Metropolitan Area (KMA), India&#xa0;using Cellular Automata–Markov Chain (CA–MC) model. This study evaluated seasonal fluctuations in land surface temperature (LST) and fragmentation in landscape&#xa0;metrics such as&#xa0;core area (CA), edge density (ED), patch density (PD), and perforated landscapes. The findings indicated a substantial 70% rise in built-up areas from 1990 to 2020, alongside a 35.92% and 13.17% decrease in agricultural land and water bodies. As per as the LULC projection, agricultural areas anticipated to decrease from 24.02%5 in 2020 to 13.83% by 2050, and vegetation from 7.09% in 2020% to 5.27 in 2050%. The mean LST increased by 7.05%, with winter exhibiting the most significant seasonal increase at 9.03%. The areas with extremely high LST areas increased from 11.57% in 1990 to an anticipated 28.77% by 2050. Landscape fragmentation escalated significantly due to considerable increases in ED, PD, CA, and perforated landscapes from 1990 to 2050. The alterations were accompanied by a significant increase in LST values across all landscape metrics. The results suggested the necessity for sustainable urban planning policies that protect natural ecosystems&#xa0;(such as green and blue spaces), limit uncontrolled urban sprawl, and incorporate green infrastructure to improve thermal regulation and landscape connectedness.</p>

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Unveiling the landscape fragmentation and its impact on land surface temperature using machine learning approach in Kolkata Metropolitan Area (India)

  • 期刊论文

  • 发表日期：

    2025年6月23日

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  • Anik Saha,
  • Sunil Saha,
  • Arijit Das,
  • Sudipta Mandal,
  • Raju Sarkar,
  • Manob Das

摘要

Understanding historical and anticipated changes in land use and land cover (LULC) is essential for assessing the effects of urban thermal dynamics, especially in swiftly urbanizing cities in developing countries. This study aims to examine LULC changes from 1990 to 2020, with future forecasts for 2030, 2040, and 2050 in Kolkata Metropolitan Area (KMA), India using Cellular Automata–Markov Chain (CA–MC) model. This study evaluated seasonal fluctuations in land surface temperature (LST) and fragmentation in landscape metrics such as core area (CA), edge density (ED), patch density (PD), and perforated landscapes. The findings indicated a substantial 70% rise in built-up areas from 1990 to 2020, alongside a 35.92% and 13.17% decrease in agricultural land and water bodies. As per as the LULC projection, agricultural areas anticipated to decrease from 24.02%5 in 2020 to 13.83% by 2050, and vegetation from 7.09% in 2020% to 5.27 in 2050%. The mean LST increased by 7.05%, with winter exhibiting the most significant seasonal increase at 9.03%. The areas with extremely high LST areas increased from 11.57% in 1990 to an anticipated 28.77% by 2050. Landscape fragmentation escalated significantly due to considerable increases in ED, PD, CA, and perforated landscapes from 1990 to 2050. The alterations were accompanied by a significant increase in LST values across all landscape metrics. The results suggested the necessity for sustainable urban planning policies that protect natural ecosystems (such as green and blue spaces), limit uncontrolled urban sprawl, and incorporate green infrastructure to improve thermal regulation and landscape connectedness.