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.

The present study investigates the effect of fixed external shading devices’ geometry on thermal comfort, daylighting and energy demand for cooling and heating in the hot and dry climate of the city of Ghardaïa (Algeria). A parametric analysis was performed by using three software: RADIANCE 2.0 and DAYSIM 3.1 for daylighting simulation and TRNSYS.17 for thermal dynamic simulation. Three shading device parameters were assessed: the spacing between slats, the tilted angle and the slats installation. The vertical shading angle “VSA” is fixed; it is equal to the optimum shading angle measured for Ghardaïa. The simulation results indicate that fixed external shading devices have a significant impact on decreasing the energy demand for cooling; however, they are unable to reduce the total energy demand since they significantly increase heating loads. It was found that fixed external shading devices remove all risks associated with glare in summer by decreasing illuminance close to the window; however, they do not improve daylighting performance in winter because of glare. We note that even if the vertical shading angle “VSA” was the same for all cases, these did not present the same thermal and luminous behavior. This is mainly due to the amount and the way that the solar radiation penetrates space.

Walking at home can provide valuable information about locomotor efficiency, anticipation of daily hazards and general well-being. Here, we present a multidisciplinary method to reconstruct locomotor trajectories while walking at home with a capacitive proximity sensing device — the SensFloor — which was installed in a real occupied apartment in the city center of Montpellier in France. Our recognition method is based on the spatio-temporal statistical probability of body location corresponding to sensors’ activation. The results led to the localization of the inhabitant in the two-dimensional floor space, and their tracking over a 24-hour period. More precisely, our technique enabled us to distinguish human-related behavior from the location of static objects. It also allowed us to successfully identify locomotor trajectories in a highly confined space, including those from two simultaneously walking individuals in different rooms. It allowed us to obtain valuable information on spatial behavior (trajectory, stationarity) but also on temporal behavior (occupancy time, walking duration). As this technique compensates for the already established low accuracy of capacitive sensors, our method offers innovative possibilities to study locomotor metrics at home using relatively inexpensive sensing technology.