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Multi-Decadal Surface Urban Heat Island Dynamics and Short-Term Land Surface Temperature Forecasting in Morocco: A Multi-Sensor Analysis Across Five Contrasting Climatic Settings

Domaine:

climategeospatialenvironment and energy

Type de record:

paper
Créateur:
AdnSalHasLai
Éditeur:
MDP
Hôte:
Surface urban heat island (SUHI) behavior in dryland cities can reverse sign when hot, bare peripheral surfaces exceed urban-core temperatures, yet long monthly records across contrasting climates remain scarce. This study reconstructs land surface temperature (LST) and standardized urban-core–periphery thermal contrasts for five Moroccan cities from 1995 to 2024 using Landsat, ERA5-Land, NDVI, and the annual MODIS MCD12Q1 land-cover product. The diagnostic analysis of SUHI and Urban Heat Sink (UHS) occurrence is explicitly separated from the forecasting component: SARIMA, Random Forest, XGBoost, and LSTM models predict monthly LST rather than UHI intensity. Tangier exhibits a persistent positive SUHI (mean: 4.6 °C; UHS frequency: 3.0%), whereas Béni Mellal, Ifrane, Laayoune, and Taza have negative mean contrasts of −1.4, −2.4, −1.0, and −0.7 °C, respectively; Ifrane records the highest UHS frequency (90.5%). No city shows a statistically significant monotonic UHI trend, and Sen’s slopes remain close to zero. Forecasting skill is city-dependent: SARIMA performs best in Ifrane and Tangier (R2 = 0.94 and 0.93), while Random Forest performs best in Taza and Laayoune (R2 = 0.90 and 0.79). Approximate 95% empirical uncertainty half-widths derived from held-out RMSE range from ±3.78 to ±15.48 °C, indicating substantial model- and city-specific uncertainty. The results support the hypothesis that local climate and peripheral land-cover context can outweigh urban fraction as controls on SUHI sign and amplitude. Generalization is limited by fixed reference distances, possible urbanization of the outer ring, clear-sky satellite sampling, the distinction between LST and air temperature, and the 36-month recursive forecasting chain used to display the 2026–2027 outlook.

Visit

doi.org

Languages

Arabic, Moroccan Spoken

Licenses

https://creativecommons.org/licenses/by/4.0/

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Forecasting Urban Heat Island Dynamics in Morocco Using Multi-Sensor Remote Sensing and Machine Learning: A Multi-Decadal Analysis Across Five Contrasting Climatic Settings

Forecasting Urban Heat Island Dynamics in Morocco Using Multi-Sensor Remote Sensing and Machine Learning: A Multi-Decadal Analysis Across Five Contrasting Climatic Settings

Urban heat islands (UHI) represent one of the most consequential manifestations of anthropogenic lan