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Cited by 34Urban Heat Island MitigationWind and Air Flow StudiesLand Use and Ecosystem Services

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Urban Heat Island’s Vulnerability Assessment by Integrating Urban Planning Policies: A Case Study of Montpellier Méditerranée Metropolitan Area, France

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Técher, Magalie, Ait Haddou, Hassan, Aguejdad, Rahim·2023·Sustainability
DOI 10.3390/su15031820
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Abstract

The energy balance differences between urban and rural areas give rise to a representative phenomenon of urban climate change called the urban heat island (UHI). The UHI phenomenon, which is exacerbated by global warming effects and urban expansion, exposes urban areas and populations to thermal stress and overheating. Therefore, measuring the intensity of UHI vulnerability is needed to mitigate its effects on health, comfort, energy consumption and infrastructure. Additionally, urban decision makers are looking for methodologies to identify the most vulnerable areas in urban planning. This research aims to investigate areas prone to urban overheating in Montpellier Mediterranean metropolitan area as a representative case study of the French urban planning context. The objective is to develop a methodology for assessing UHI vulnerability based on the interaction of exposure and sensitivity to urban planning policies. Accordingly, a set of fifteen indicators is developed to visualize urban planning policies, exposure and sensitivity to urban overheating. A statistical-based method is applied to determine the individual weights based on the indicators’ variance, which is calculated using principal component analysis (PCA). The spatial and urban planning distribution of vulnerability is then analyzed. The results indicate that the areas with the highest urban planning challenges are most vulnerable to UHI. In fact, the results reveal that these areas have urban planning characteristics likely to aggravate urban overheating. Therefore, this research proposes a methodology for integrating mitigation solutions into urban planning: increase in permeable and green areas; improvement of urban ventilation and heat exchange and decrease in anthropogenic heat generation. It demonstrates that combining urban planning policies with exposure and sensitivity is a new perspective for vulnerability studies. The findings of this study can be utilized by decision makers to better visualize areas susceptible to UHI and plan appropriate mitigation strategies.

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Figures

Figure 1 Conceptual framework of UHI vulnerability assessment scheme. Figure 1. Conceptual framework of UHI vulnerability assessment scheme. Figure 1. Conceptual framework of UHI vulnerability assessment scheme.
Figure 1 Conceptual framework of UHI vulnerability assessment scheme. Figure 1. Conceptual framework of UHI vulnerability assessment scheme. Figure 1. Conceptual framework of UHI vulnerability assessment scheme.CC-BY · From the PDF
Figure 2 ( a ) Location of Montpellier Méditerranée Metropolitan area in France; ( b ) 31 municipalities of Montpellier Méditerranée Metropolitan area. Figure 2. ( a ) Location of Montpellier Méditerranée Metropolitan area in France; ( b ) 31 municipalities of Montpellier Méditerranée Metropolitan area. Figure 2. ( a ) Location of Montpellier M é diterran é e Metropolitan area in France; ( b ) 31 municipalities of Montpellier M é diterran é e Metropolitan area.
Figure 2 ( a ) Location of Montpellier Méditerranée Metropolitan area in France; ( b ) 31 municipalities of Montpellier Méditerranée Metropolitan area. Figure 2. ( a ) Location of Montpellier Méditerranée Metropolitan area in France; ( b ) 31 municipalities of Montpellier Méditerranée Metropolitan area. Figure 2. ( a ) Location of Montpellier M é diterran é e Metropolitan area in France; ( b ) 31 municipalities of Montpellier M é diterran é e Metropolitan area.CC-BY · From the PDF
Figure 3 Annual mean temperature and number of heat wave days (temperature 5 °C higher than normal for at least 5 consecutive days) from 1980 to 2018. Figure 3. Annual mean temperature and number of heat wave days (temperature 5 ◦ C higher than normal for at least 5 consecutive days) from 1980 to 2018.
Figure 3 Annual mean temperature and number of heat wave days (temperature 5 °C higher than normal for at least 5 consecutive days) from 1980 to 2018. Figure 3. Annual mean temperature and number of heat wave days (temperature 5 ◦ C higher than normal for at least 5 consecutive days) from 1980 to 2018.CC-BY · From the PDF
Figure 4 ( a ) Building footprint coefficient; ( b ) proportion of green spaces; ( c ) building height; ( d ) implantation of air-conditioning systems; ( e ) construction's location to plot boundaries. Figure 4. ( a ) Building footprint coefficient; ( b ) proportion of green spaces; ( c ) building height; ( d ) implantation of air-conditioning systems; ( e ) construction's location to plot boundaries.
Figure 4 ( a ) Building footprint coefficient; ( b ) proportion of green spaces; ( c ) building height; ( d ) implantation of air-conditioning systems; ( e ) construction's location to plot boundaries. Figure 4. ( a ) Building footprint coefficient; ( b ) proportion of green spaces; ( c ) building height; ( d ) implantation of air-conditioning systems; ( e ) construction's location to plot boundaries.CC-BY · From the PDF
Figure 5 ( a ) Topographical map; ( b ) proximity to green spaces; ( c ) proximity to water spaces. Figure 5. ( a ) Topographical map; ( b ) proximity to green spaces; ( c ) proximity to water spaces.
Figure 5 ( a ) Topographical map; ( b ) proximity to green spaces; ( c ) proximity to water spaces. Figure 5. ( a ) Topographical map; ( b ) proximity to green spaces; ( c ) proximity to water spaces.CC-BY · From the PDF
Figure 6 ( a ) SUHI intensity (daytime); ( b ) SUHI intensity (nighttime); ( c ) population density; ( d ) land use classification.
Figure 6 ( a ) SUHI intensity (daytime); ( b ) SUHI intensity (nighttime); ( c ) population density; ( d ) land use classification.CC-BY · From the PDF
Figure 7 ( a ) Proportion of sensitive population by age; ( b ) proportion of low-income households; ( c ) presence of health and care facilities; ( d ) building age. Figure 7. ( a ) Proportion of sensitive population by age; ( b ) proportion of low-income households; ( c ) presence of health and care facilities; ( d ) building age.
Figure 7 ( a ) Proportion of sensitive population by age; ( b ) proportion of low-income households; ( c ) presence of health and care facilities; ( d ) building age. Figure 7. ( a ) Proportion of sensitive population by age; ( b ) proportion of low-income households; ( c ) presence of health and care facilities; ( d ) building age.CC-BY · From the PDF
Image 8
CC-BY · From the PDF
Figure 9 ( a ) Distribution of urban vulnerability levels of cells affected by medium-to-high classes of 'urban planning policies' indicators to total study area; ( b ) Distribution of urban vulnerability levels of cells affected by medium-to-high classes of 'urban planning policies' indicators to the total area of affected cells. Figure 9. ( a ) Distribution of urban vulnerability levels of cells affected by medium-to-high classes of 'urban planning policies' indicators to total study area; ( b ) Distribution of urban vulnerability levels of cells affected by medium-to-high classes of 'urban planning policies' indicators to the total area of affected cells.
Figure 9 ( a ) Distribution of urban vulnerability levels of cells affected by medium-to-high classes of 'urban planning policies' indicators to total study area; ( b ) Distribution of urban vulnerability levels of cells affected by medium-to-high classes of 'urban planning policies' indicators to the total area of affected cells. Figure 9. ( a ) Distribution of urban vulnerability levels of cells affected by medium-to-high classes of 'urban planning policies' indicators to total study area; ( b ) Distribution of urban vulnerability levels of cells affected by medium-to-high classes of 'urban planning policies' indicators to the total area of affected cells.CC-BY · From the PDF
Figure 10 ( a ) Distribution of urban vulnerability levels of urban planning zoning to total study area; ( b ) distribution of urban vulnerability levels of urban planning zoning to the total area of affected cells; ( c ) urban planning zoning of Montpellier Metropolitan area representing the 4 regulatory land uses. 3.3.2. Vulnerability Assessment of Authorized Land Use Figure 10. ( a ) Distribution of urban vulnerability levels of urban planning zoning to total study area; ( b ) distribution of urban vulnerability levels of urban planning zoning to the total area of affected cells; ( c ) urban planning zoning of Montpellier Metropolitan area representing the 4 regulatory land uses.
Figure 10 ( a ) Distribution of urban vulnerability levels of urban planning zoning to total study area; ( b ) distribution of urban vulnerability levels of urban planning zoning to the total area of affected cells; ( c ) urban planning zoning of Montpellier Metropolitan area representing the 4 regulatory land uses. 3.3.2. Vulnerability Assessment of Authorized Land Use Figure 10. ( a ) Distribution of urban vulnerability levels of urban planning zoning to total study area; ( b ) distribution of urban vulnerability levels of urban planning zoning to the total area of affected cells; ( c ) urban planning zoning of Montpellier Metropolitan area representing the 4 regulatory land uses.CC-BY · From the PDF
Figure 11 ( a ) Distribution of urban vulnerability levels of authorized land use to total study area; ( b ) distribution of urban vulnerability levels of authorized land use to the total area of affected cells. Figure 11. ( a ) Distribution of urban vulnerability levels of authorized land use to total study area; ( b ) distribution of urban vulnerability levels of authorized land use to the total area of affected cells.
Figure 11 ( a ) Distribution of urban vulnerability levels of authorized land use to total study area; ( b ) distribution of urban vulnerability levels of authorized land use to the total area of affected cells. Figure 11. ( a ) Distribution of urban vulnerability levels of authorized land use to total study area; ( b ) distribution of urban vulnerability levels of authorized land use to the total area of affected cells.CC-BY · From the PDF
Image 12
CC-BY · From the PDF
Figure 12 ( a ) Distribution of urban vulnerability levels of the date of approval of Local Urban Plans to total study area; ( b ) distribution of urban vulnerability levels of the date of approval of Local Urban Plans to total area of affected cells. Figure 12. ( a ) Distribution of urban vulnerability levels of the date of approval of Local Urban Plans to total study area; ( b ) distribution of urban vulnerability levels of the date of approval of Local Urban Plans to total area of affected cells.
Figure 12 ( a ) Distribution of urban vulnerability levels of the date of approval of Local Urban Plans to total study area; ( b ) distribution of urban vulnerability levels of the date of approval of Local Urban Plans to total area of affected cells. Figure 12. ( a ) Distribution of urban vulnerability levels of the date of approval of Local Urban Plans to total study area; ( b ) distribution of urban vulnerability levels of the date of approval of Local Urban Plans to total area of affected cells.CC-BY · From the PDF
Image 14
CC-BY · From the PDF

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Research works printed but not linked: 3

  1. Alonso, L. (2021). Intérêt de la Modélisation de la Température de l’air Associé à la Nécessité de la Caractérisation des Vulnérabilités Territoriales pour une Compréhension Systémique du Risque aux Fortes Chaleurs en Milieu Urbain sur Lyon et Tokyo. [Ph.D. Thesis, Jean Moulin Lyon III University].
  2. Athamena, K., Musy, M., and Bouyer, J. (2009, January 22–24). Proposal of indicators dedicated to the analysis of contribution of urban projects to urban Heat Island. Proceedings of the PLEA26—26th Conference on Passive and Low Energy Architecture, Quebec, QC, Canada.
  3. De Munck, C. (2013). Modélisation de la Végétation Urbaine et des Stratégies D’adaptation au Changement Climatique pour L’amélioration du Confort Climatique et de la Demande Energétique en Ville. [Ph.D. Thesis, Atmosphere and Continental Surface, Toulouse University].

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Metadata

Authors
Técher, M., Ait Haddou, H., & Aguejdad, R.
Affiliations
  • École Nationale Supérieure d'Architecture Montpellier (FR)
  • LIFAM Laboratory, High School of Architecture (ENSAM), 34090 Montpellier, France
  • Centre National de la Recherche Scientifique (FR)
Corresponding author
Técher, Magalie
ORCID
Aguejdad, Rahim
Venue
Sustainability
Publisher
MDPI AG
Published
2023-01-18
Volume
15
Issue
3
Pages
1820
ISSN
2071-1050 (ISSN-L)
DOI
10.3390/su15031820
OpenAlex
W4317423772
Cited by
29
References
67
Citations by year
2026: 7 · 2025: 10 · 2024: 7 · 2023: 5
FWCI
2.42
Type
journal article
Language
en
Open access
Licence
Locations
  • Sustainability (publishedVersion, cc-by)
  • HAL (submittedVersion, cc-by)
  • RePEc: Research Papers in Economics (submittedVersion)
Funders
  • ADEME
  • Ecological Transition Agency
  • French Ministry of Culture
Topics
  • Physical Sciences › Environmental Science › Environmental Engineering › Urban Heat Island Mitigation
  • Physical Sciences › Environmental Science › Environmental Engineering › Wind and Air Flow Studies
  • Physical Sciences › Environmental Science › Global and Planetary Change › Land Use and Ecosystem Services
Keywords
urban heat island, urban planning policy, exposure and sensitivity, vulnerability indicators, urban overheating, heat mitigation strategies, green spaces, urban ventilation, anthropogenic heat, urban climate change

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