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Remotely Sensed Derived Land Surface Temperature (LST) as a Proxy for Air Temperature and Thermal Comfort at a Small Geographical Scale

Author

Listed:
  • Ran Goldblatt

    (New Light Technologies Inc., 1440 G Street Northwest, Washington, DC 20005, USA)

  • Abdullah Addas

    (Landscape Architecture Department, Faculty of Architecture & Planning, King Abdulaziz University, P.O. Box 80210, Jeddah 21589, Saudi Arabia)

  • Daynan Crull

    (New Light Technologies Inc., 1440 G Street Northwest, Washington, DC 20005, USA)

  • Ahmad Maghrabi

    (Landscape Architecture Department, Faculty of Architecture & Planning, King Abdulaziz University, P.O. Box 80210, Jeddah 21589, Saudi Arabia)

  • Gabriel Gene Levin

    (New Light Technologies Inc., 1440 G Street Northwest, Washington, DC 20005, USA)

  • Steven Rubinyi

    (Urban, Disaster Risk Management, Resilience, and Land Global Practice, The World Bank, Washington, DC 20433, USA)

Abstract

Urban Heat Islands (UHIs) and Urban Cool Islands (UCIs) can be measured by means of in situ measurements and interpolation methods, which often require densely distributed networks of sensors and can be time-consuming, expensive and in many cases infeasible. The use of satellite data to estimate Land Surface Temperature (LST) and spectral indices such as the Normalized Difference Vegetation Index (NDVI) has emerged in the last decade as a promising technique to map Surface Urban Heat Islands (SUHIs), primarily at large geographical scales. Furthermore, thermal comfort, the subjective perception and experience of humans of micro-climates, is also an important component of UHIs. It remains unanswered whether LST can be used to predict thermal comfort. The objective of this study is to evaluate the accuracy of remotely sensed data, including a derived LST, at a small geographical scale, in the case study of King Abdulaziz University (KAU) campus (Jeddah, Saudi Arabia) and four surrounding neighborhoods. We evaluate the potential use of LST estimates as proxy for air temperature (T air ) and thermal comfort. We estimate LST based on Landsat-8 measurements, T air and other climatological parameters by means of in situ measurements and subjective thermal comfort by means of a Physiological Equivalent Temperature (PET) model. We find a significant correlation (r = 0.45, p < 0.001) between LST and mean T air and the compatibility of LST and T air as equivalent measures using Bland-Altman analysis. We evaluate several models with LST, NDVI, and Normalized Difference Built-up Index (NDBI) as data inputs to proxy T air and find that they achieve error rates across metrics that are two orders of magnitude below that of a comparison with LST and T air alone. We also find that, using only remotely sensed data, including LST, NDVI, and NDBI, random forest classifiers can detect sites with “very hot” classification of thermal comfort nearly as effectively as estimates using in situ data, with one such model attaining an F1 score of 0.65. This study demonstrates the potential use of remotely sensed measurements to infer the Physiological Equivalent Temperature (PET) and subjective thermal comfort at small geographical scales as well as the impacts of land cover and land use characteristics on UHI and UCI. Such insights are fundamental for sustainable urban planning and would contribute enormously to urban planning that considers people’s well-being and comfort.

Suggested Citation

  • Ran Goldblatt & Abdullah Addas & Daynan Crull & Ahmad Maghrabi & Gabriel Gene Levin & Steven Rubinyi, 2021. "Remotely Sensed Derived Land Surface Temperature (LST) as a Proxy for Air Temperature and Thermal Comfort at a Small Geographical Scale," Land, MDPI, vol. 10(4), pages 1-24, April.
  • Handle: RePEc:gam:jlands:v:10:y:2021:i:4:p:410-:d:535527
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    References listed on IDEAS

    as
    1. Abdullah Addas & Ran Goldblatt & Steven Rubinyi, 2020. "Utilizing Remotely Sensed Observations to Estimate the Urban Heat Island Effect at a Local Scale: Case Study of a University Campus," Land, MDPI, vol. 9(6), pages 1-26, June.
    2. Azad Rasul & Heiko Balzter & Claire Smith & John Remedios & Bashir Adamu & José A. Sobrino & Manat Srivanit & Qihao Weng, 2017. "A Review on Remote Sensing of Urban Heat and Cool Islands," Land, MDPI, vol. 6(2), pages 1-10, June.
    3. Salim Ferwati & Cynthia Skelhorn & Vivek Shandas & Yasuyo Makido, 2019. "A Comparison of Neighborhood-Scale Interventions to Alleviate Urban Heat in Doha, Qatar," Sustainability, MDPI, vol. 11(3), pages 1-20, January.
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    Cited by:

    1. Mohsin Ramzan & Zulfiqar Ahmad Saqib & Ejaz Hussain & Junaid Aziz Khan & Abid Nazir & Muhammad Yousif Sardar Dasti & Saqib Ali & Nabeel Khan Niazi, 2022. "Remote Sensing-Based Prediction of Temporal Changes in Land Surface Temperature and Land Use-Land Cover (LULC) in Urban Environments," Land, MDPI, vol. 11(9), pages 1-19, September.
    2. Taher Safarrad & Mostafa Ghadami & Andreas Dittmann & Mousa Pazhuhan (Panahandeh Khah), 2021. "Tourism Effect on the Spatiotemporal Pattern of Land Surface Temperature (LST): Babolsar and Fereydonkenar Cities (Cases Study in Iran)," Land, MDPI, vol. 10(9), pages 1-25, September.
    3. Dongying Li & Galen D Newman & Bev Wilson & Yue Zhang & Robert D Brown, 2022. "Modeling the relationships between historical redlining, urban heat, and heat-related emergency department visits: An examination of 11 Texas cities," Environment and Planning B, , vol. 49(3), pages 933-952, March.
    4. Abdullah Addas, 2023. "Understanding the Relationship between Urban Biophysical Composition and Land Surface Temperature in a Hot Desert Megacity (Saudi Arabia)," IJERPH, MDPI, vol. 20(6), pages 1-16, March.
    5. Uk-Je Sung & Jeong-Hee Eum & Jeong-Min Son & Jeong-Hak Oh, 2021. "Planning Strategies of Wind Corridor Forests Utilizing the Properties of Cold Air," Land, MDPI, vol. 10(6), pages 1-17, June.
    6. Eduilson Carneiro & Wilza Lopes & Giovana Espindola, 2021. "Linking Urban Sprawl and Surface Urban Heat Island in the Teresina–Timon Conurbation Area in Brazil," Land, MDPI, vol. 10(5), pages 1-16, May.

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