source at a given indoor point under overcast sky conditions [12]. DF is defined as a static metric, since the calculation scenario has an invariant luminance distribution regardless of the solar altitude, as location and orientation are irrelevant considering an ideal overcast sky [13]. Accordingly, the indoor illuminance at a given point can be quantified knowing the outdoor illuminance. This concept has served as a useful tool to determine the proper design of architectural features [14; 15] to provide a suitable amount of natural light. Despite its usefulness, DF cannot be applied for determining the energy consumption of electric lighting, since this metric ignores the dynamic variation of the sky, as well as the illuminance requirements to carry out the tasks [16]. Given this context, the dynamic metrics arose, as these tools quantify the energy savings based on location, window orientation and the luminous distribution of the sky vault in accordance with statistical weather data. Daylight autonomy (DA) is the most common dynamic metric. This concept was proposed in 1989 by the Association Suisse des Electriciens [17] and subsequently redefined by [PERSON] et al. [18]. DA is defined as the percentage of the time fraction during the year when an illuminance threshold is met by daylight alone. Therefore, the higher the metric value, the shorter the switching on time of electric lighting. According to this definition, a limitation of its application arises, given that the chosen lighting schedules just can represent users behavior probabilistically [19]. This affects not only to the behavior of the building in use, but also to those periods in which the building is unoccupied, such as during holidays. On the other hand, the validation of dynamic metrics in real conditions is complex due to the difficulties derived from monitoring illuminance in occupied rooms for a prolonged period [20]. In this way, there are several studies that have analyzed the divergences between the simulation and monitoring of dynamic metrics using spaces without occupancy, obtaining divergences below 10% [21; 22]. Two main metrics have evolved from the original conception of DA, with similar limitations. The variation proposed by [PERSON] et al. [18] is the continuous daylight autonomy (DACon), defined as the occupied time throughout the year when a threshold is met by daylight, considering a partial credit linearly to values below the threshold defined, in accordance with the adaptive capacity of human vision. This definition is not commonly used [23], despite its usefulness in quantifying the energy consumption provided by a dimmer control [24]. The second variation, proposed by [PERSON] et al. [8], corresponds to the minimum daylight autonomy (DAm) which determines the percentage of the occupied time when the required illuminance value is met by natural light under the most common worst case scenario, overcast sky conditions. This metric, developed by [PERSON] et al., arose with the aim of bridging the gap between static metrics such as DF and dynamic metrics. One of the most interesting dynamic metrics is useful daylight illuminance (UDI), which quantifies the time fraction when daylight levels are appropriate for occupants [25; 26]. [PERSON] et al. developed this usefulness concept, determining the percentage of the occupied time when the illuminance is suitable, between 100 and 3000 lx, falling short, below 100 lx, or too high, at over 3000 lx. Most recently, there is a trend that has led to the development of dynamic metrics not only linked to a determined time frame, but also to the occupied space. Accordingly, the spatial metrics provide a score to the studied surface--either a room or an entire building--ignoring the quantification of the daylight use in a specific point.