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May 6, 2026Urban Science0 citationsOpen Access

Long-Term Assessment of Surface Urban Heat Islands Using Open Access Remote Sensing Data (1984–2024) in the Moroccan Atlantic Coast

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SASana AjjoulAZAdil ZabadiASAyyoub Sbihi

Key Points

  • The aim is to assess long-term urban heat island effects using remote sensing data from 1984 to 2024.
  • Utilized a 40-year time series of Landsat thermal data to analyze surface temperature variations.
  • Mapped urban environments between Kenitra and Rabat to identify heat-excess zones.
  • Evaluated Random Forest model for classification effectiveness using Receiver Operating Characteristic and Kappa index.
  • Surface Urban Heat Island effect escalated with temperatures rising from 27 °C in 1984 to 44 °C in 2024.
  • Urbanization growth in the region increased from 1.8% to 3% between 1984 and 2024.
  • Significant decrease in agricultural land and bare soils observed, highlighting the rapid urban expansion.

Abstract

Rapid urbanization combined with global climate change is intensifying the Surface Urban Heat Island (SUHI) effect worldwide, posing significant risks to human health, thermal comfort, and quality of life in cities. Characterized by notably higher temperatures in urban areas compared to their rural surroundings, the SUHI phenomenon is driven by factors such as increased built-up density and reduced vegetation cover. In this context, open-source remote sensing data, particularly from the Landsat satellite series, play a crucial role in studying surface urban heat islands. Available freely, Landsat’s multispectral and thermal imagery provides extensive spatial coverage and consistent temporal frequency, enabling long-term diachronic analyses. This study leverages a 40-year time series (1984–2024) of Landsat thermal data to map surface temperature variations in urban environments between Kenitra and Rabat cities, facilitating the identification of heat-excess zones linked to anthropogenic factors. Based on the results obtained, the LU/LC maps show that the study area is characterized by the notable growth of urbanization over the period 1984–2024, particularly in the dynamic poles of the region such as the city centers of Kénitra, Rabat, and Sale. This dynamic is highlighted by an increase from 1.8% to 3% in the total area of the region, accompanied by a remarkable decrease in agricultural land and bare soils. The evaluation of the Random Forest (RF) model’s performance also indicates that it successfully classified the data and predicted the LU/LC classes effectively, as confirmed by metric indices such as the Receiver Operating Characteristic curve and the Kappa index, which present very high average values exceeding 90%. Furthermore, the exploitation of the thermal bands of Landsat images provided relevant information on surface temperature variation. The SUHI maps show that the Rabat-Sale-Kenitra (RSK) region experienced a progressive increase in temperature over the study period, rising from 27 °C in 1984 to 44 °C in 2024. This value could increase further due to the continuous dynamics of urbanization. Together, these tools provide a robust framework for understanding the spatiotemporal dynamics of surface urban heat islands and support sustainable urban planning.

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Cite This Study

Ajjoul et al. (2026) studied this question.

synapsesocial.com/papers/69fa98bd04f884e66b53267dhttps://doi.org/10.3390/urbansci10050237
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