Temporal Analysis of Land Surface Temperature Variability and Urban Climate Dynamics: A Remote Sensing Use Case in Benguerir City, Morocco

Urbanization markedly influences the microclimatic conditions in semi-arid regions by elevating land surface temperatures (LST) and contributing to ecological degradation. This study examined the spatial and temporal evolution of LST and urban heat island (UHI) effects in Benguerir, Morocco, over a 30-year period (1994–2024), employing high-resolution satellite imagery and in situ sensor data. Urban expansion was quantified using thermal bands from Landsat imagery, the Normalized Difference Built-up Index (NDBI), and the Built-up Index (BU), whereas thermal comfort was evaluated through the Universal Thermal Climate Index (UTCI) and Predicted Mean Vote (PMV) using air temperature and humidity data collected via spatial sensor and the Sniffer Bike mobile sensor network. These urban transformations have intensified the UHI effect, resulting in a 29.34 °C increase in mean LST to 41.82 °C in 2024 across built-up areas. Statistical modeling revealed strong linear relationships between LST and urban indices, with R2 values ranging from 0.93 to 0.96, and correlation coefficients around 0.98 (all p-values < 0.001), indicating a reliable model fit. Furthermore, the analysis of thermal comfort trends underscores urbanization’s impact on human well-being. In 1994, 34.2% of the population experienced slight warmth and 65.8% experienced hot conditions. By 2024, conditions had shifted dramatically, with 76.7% experiencing hot conditions and 16.2% exposed to very hot conditions, leaving only 7.1% in the slight warmth category. These findings highlight the urgent need for adaptive urban planning strategies. The implementation of urban greening initiatives, the use of reflective materials, and the integration of data-driven planning approaches are essential to mitigate thermal stress and enhance urban resilience. Leveraging climate modeling and spatial analytics can support the identification of high-risk zones and inform targeted interventions to effectively address the escalating UHI phenomenon.