Resumen
The post-pandemic era has raised awareness on the importance of physical and psychological well-being for decreasing the vulnerability of both individuals and populations. Citizens in urban areas are subject to numerous stress factors which can be mitigated by green spaces such as parks and gardens. Sensor and internet technologies support nature-based solutions in various ways. In this paper, we show the results of ongoing research on the use of spatially distributed IoT sensors that collect climate data in an ~8 ha urban garden. The novelty resides in the method for merging the IoT data with a detailed 3D model created by a laser scan survey from a drone flight. The end products are 1 m resolution thermal comfort maps of user-defined scenarios, e.g., at specific times or aggregated in daily/monthly/yearly statistics that represent a thermal comfort distribution. For full replicability, the code is open source and available as an R package on Github.