Scholarlink

<p>The Urban Heat Island effect is an increasingly critical environmental issue that adversely impacts human thermal comfort in urban areas. This scenario modelling study assesses thermal vulnerability dynamics in Lucknow City, India, by examining how land cover (LC) change influences land surface temperature (LST) and human thermal comfort. Using 2024 as the baseline year, three counterfactual land-cover test configurations were developed to evaluate temperature responses to alternative scenarios. The results show that replacing vegetation with dense built-up areas increases LST by up to 4&#xa0;°C, whereas expanding green cover reduces surface temperature by up to 5&#xa0;°C. A heat risk exposure map, developed using LST, absorbed albedo, and exposure areas was integrated with a 3 × 3 sensitivity-exposure matrix to identify heat-vulnerable zones. Sensitivity mapping incorporated social data, indicating slums as the most exposed and vulnerable areas. The study provides a replicable framework for integrating thermal risk mapping with spatial planning and offers policy-aligned, location-specific mitigation strategies to enhance urban resilience to extreme heat events.</p> Graphical Abstract <p></p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Assessment of Thermal Vulnerability Dynamics: A case of Lucknow City, India

  • 期刊论文

  • 发表日期：

    2026年4月7日

查看全文
  • Chitra Srivastava,
  • Alka Bharat

摘要

The Urban Heat Island effect is an increasingly critical environmental issue that adversely impacts human thermal comfort in urban areas. This scenario modelling study assesses thermal vulnerability dynamics in Lucknow City, India, by examining how land cover (LC) change influences land surface temperature (LST) and human thermal comfort. Using 2024 as the baseline year, three counterfactual land-cover test configurations were developed to evaluate temperature responses to alternative scenarios. The results show that replacing vegetation with dense built-up areas increases LST by up to 4 °C, whereas expanding green cover reduces surface temperature by up to 5 °C. A heat risk exposure map, developed using LST, absorbed albedo, and exposure areas was integrated with a 3 × 3 sensitivity-exposure matrix to identify heat-vulnerable zones. Sensitivity mapping incorporated social data, indicating slums as the most exposed and vulnerable areas. The study provides a replicable framework for integrating thermal risk mapping with spatial planning and offers policy-aligned, location-specific mitigation strategies to enhance urban resilience to extreme heat events.

Graphical Abstract