## 1 Introduction
### 1.1. Comfort Indicators  
The environmental variables and morphological characteristics of the natural and artificial environments at the urban scale influence the comfort and behaviors of the citizens. Urban parks and gardens play a key role in creating a microclimate that can bring well-being to humans. Wellness resulting from exposure to the natural environment is both physical and psychological. The latter aspect is one of the impacted factors during and after the COVID-19 pandemic, with differences depending on age [2]. Climate and environmental factors influence the human body during visits to gardens. The literature refers to the heat-balance model of the human body [3] to measure this effect. Heat-balance considers the metabolic rate, the physical work output, the net radiation of the body, the storage of heat flow or cooling, and the convective heat flow but also the heat flow to evaporation through the skin, the sweat and humidity of the air, the effective temperature (ET) [4], and the Gage two-node model. These models have been applied in the heat-balance by the Munich energy-balance model for individuals (MEMI) [5], which is the base for the calculation of the physiological equivalent temperature (PET) and the standard effective temperature (SET). PET is defined as the air temperature at which, in a typical indoor setting (without wind and solar radiation), the heat budget of the human body is balanced with the same core and skin temperature as under the complex outdoor conditions to be assessed [6]. SET considers the temperature of a hypothetical isothermal environment at 50% or relative humidity in which a human subject while wearing clothing, standardized for the activity concerned, would have the same skin wetness and heat exchange at the skin surface as he would have in the actual test environment [7]. The difference between the PET and SET is that the reference environment considers the skin and core temperatures rather than the temperature and humidity at skin level. However, the same environmental parameters are used in both formulas. The predicted mean vote (PMV) index is a thermal sensation measure with values that range from \(-3\) to \(+3\) which describe the feeling from too cold to too hot respectively, with zero being a neutral vote and thus maximum comfort [8].  
Comfort indices consider physiological and environmental parameters. Four are environmental parameters: (i) air temperature, (ii) mean radiant temperature, (iii) wind velocity, (iv) humidity. Two are physiological factors: (i) clothing level and (ii) metabolism at 20 \({}^{\circ}\)C. Clothing level can have a value from zero to one, and metabolism can be expressed as energy flux, e.g., 81 W/m\({}^{2}\) for slow walking. Hence, comfort indices are normalized for clothing and metabolic activity, focusing on the four environmental parameters listed above.  
Other studies have highlighted the thermo-physiological effect of short-wave and long-wave radiation fluxes in human beings under both indoor and outdoor conditions [9]. In this sense, the RayMan model estimates the direct and reflected solar radiation in the three-dimensional space that surrounds the human body under the different visible sections of the sky and canopy cover using pyranometers and hemispherical photos. However, RayMan is a stationary model influenced by the complexity of the urban environment, such as the presence of structures [10]. On the other hand, potential issues in the estimation of comfort indices are related to data collection, especially in non-stationary conditions or for long-lasting experiments. Outdoor environments are complex scenarios for comfort calculation, where tall vegetation and a mixture of buildings, vegetation, direct and diffuse solar radiation conditions that depend on atmospheric conditions, and shade from vegetation or buildings have to be accounted for.