{"title":"Assessing the impact of industrial areas on land surface temperature: A comparison with urban and green spaces in the context of global warming","authors":"Asfra Rizwan Toor, Zubair Khalid","doi":"10.1016/j.scs.2026.107185","DOIUrl":null,"url":null,"abstract":"<div><div>This study provides a comprehensive analysis of the urban heat island (UHI) effect and land surface temperature (LST) variations across Lahore, Pakistan, focusing on industrial, residential, and green spaces. Within the broader UHI framework, the study foregrounds the intra-urban heat island (IHI) phenomenon, which captures fine-scale thermal contrasts among industrial, residential, and green spaces. This perspective helps show how industrial growth creates localized hotspots in the urban environment. Using Landsat imagery, the split-window algorithm, and vegetation and built-up indices, the study tracks LST trends over 24 years (2000–2024). A comparative analysis of supervised classification algorithms and Otsu thresholding with K-means clustering was conducted to assess vegetation distribution, demonstrating the value of combining automated and supervised methods for improved land-cover assessment. Results reveal a clear industrial thermal footprint following the establishment of the industrial estate in 2007, with peak summer LST reaching 43.2 <span><math><mrow><mo>°</mo><mi>C</mi></mrow></math></span> at the core and declining to 41.6 <span><math><mrow><mo>°</mo><mi>C</mi></mrow></math></span> within a 5 km radius. A maximum temperature contrast (<span><math><mrow><mi>Δ</mi><msub><mrow><mi>T</mi></mrow><mrow><mo>max</mo></mrow></msub></mrow></math></span>) of 3 <span><math><mrow><mo>°</mo><mi>C</mi></mrow></math></span> confirms localized heat accumulation. Residential areas show persistent warming, whereas green spaces consistently maintain the lowest LST. Vegetation loss is associated with an increase in LST of up to 4.6 <span><math><mrow><mo>°</mo><mi>C</mi></mrow></math></span>, underscoring the cooling role of green infrastructure. Despite peak rainfall of 905 mm in 2021, IA temperatures remained high, indicating that impervious surfaces limit precipitation-driven cooling. The study offers long-term empirical insight but is constrained by Landsat’s spatial resolution and the absence of socioeconomic or atmospheric pollution variables, which future work should integrate for a more holistic assessment. The study advocates for targeted nature-based interventions to reduce heat stress and enhance urban resilience.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"138 ","pages":"Article 107185"},"PeriodicalIF":13.3000,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Sustainable Cities and Society","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2210670726000727","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2026/1/27 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"CONSTRUCTION & BUILDING TECHNOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
This study provides a comprehensive analysis of the urban heat island (UHI) effect and land surface temperature (LST) variations across Lahore, Pakistan, focusing on industrial, residential, and green spaces. Within the broader UHI framework, the study foregrounds the intra-urban heat island (IHI) phenomenon, which captures fine-scale thermal contrasts among industrial, residential, and green spaces. This perspective helps show how industrial growth creates localized hotspots in the urban environment. Using Landsat imagery, the split-window algorithm, and vegetation and built-up indices, the study tracks LST trends over 24 years (2000–2024). A comparative analysis of supervised classification algorithms and Otsu thresholding with K-means clustering was conducted to assess vegetation distribution, demonstrating the value of combining automated and supervised methods for improved land-cover assessment. Results reveal a clear industrial thermal footprint following the establishment of the industrial estate in 2007, with peak summer LST reaching 43.2 at the core and declining to 41.6 within a 5 km radius. A maximum temperature contrast () of 3 confirms localized heat accumulation. Residential areas show persistent warming, whereas green spaces consistently maintain the lowest LST. Vegetation loss is associated with an increase in LST of up to 4.6 , underscoring the cooling role of green infrastructure. Despite peak rainfall of 905 mm in 2021, IA temperatures remained high, indicating that impervious surfaces limit precipitation-driven cooling. The study offers long-term empirical insight but is constrained by Landsat’s spatial resolution and the absence of socioeconomic or atmospheric pollution variables, which future work should integrate for a more holistic assessment. The study advocates for targeted nature-based interventions to reduce heat stress and enhance urban resilience.
期刊介绍:
Sustainable Cities and Society (SCS) is an international journal that focuses on fundamental and applied research to promote environmentally sustainable and socially resilient cities. The journal welcomes cross-cutting, multi-disciplinary research in various areas, including:
1. Smart cities and resilient environments;
2. Alternative/clean energy sources, energy distribution, distributed energy generation, and energy demand reduction/management;
3. Monitoring and improving air quality in built environment and cities (e.g., healthy built environment and air quality management);
4. Energy efficient, low/zero carbon, and green buildings/communities;
5. Climate change mitigation and adaptation in urban environments;
6. Green infrastructure and BMPs;
7. Environmental Footprint accounting and management;
8. Urban agriculture and forestry;
9. ICT, smart grid and intelligent infrastructure;
10. Urban design/planning, regulations, legislation, certification, economics, and policy;
11. Social aspects, impacts and resiliency of cities;
12. Behavior monitoring, analysis and change within urban communities;
13. Health monitoring and improvement;
14. Nexus issues related to sustainable cities and societies;
15. Smart city governance;
16. Decision Support Systems for trade-off and uncertainty analysis for improved management of cities and society;
17. Big data, machine learning, and artificial intelligence applications and case studies;
18. Critical infrastructure protection, including security, privacy, forensics, and reliability issues of cyber-physical systems.
19. Water footprint reduction and urban water distribution, harvesting, treatment, reuse and management;
20. Waste reduction and recycling;
21. Wastewater collection, treatment and recycling;
22. Smart, clean and healthy transportation systems and infrastructure;