In the present work, the main methodologies used to reconstruct wind fields in the U-SPACE have been analyzed. The SESAR U-SPACE program aims to develop an Unmanned Traffic Management system with a progressive introduction of procedures and services designed to support secure access to the air space for a large number of drones. Some of these techniques were originally developed for reconstruction at high altitudes, but successively adapted to treat different heights. A common approach to all techniques is to approximate the probabilistic distribution of wind speed over time with some parametric models, apply spatial interpolation to the parameters and then read the predicted value. The approaches are based on the fact that modern aircraft are equipped with automatic systems. Moreover, the proposed concepts demonstrated the possibility of using drones as a large network to complement the current network of sensors. The methods can serve the micro-scale weather forecasts and the collection of information necessary for the definition of the flight plan of drones in urban contexts. Existing limitations in the applications of wind field reconstruction, related to the fact that estimations can be produced only if a sufficient number of drones are already flying, could be mitigated using data provided by Numerical Weather Prediction models (NWPs). The coupling of methodologies used to reconstruct wind fields with an NWP will ensure that estimations can be produced in any geographical area.