## 2 Materials and Methods  
Parameters should be accurately estimated in order to provide a reliable evaluation of renewable energy power plant installation. In Table 2, a typical set of data of the most significant parameters needed to evaluate Earth's conditions in order to better manage renewable resource plants is shown. Figure 1: Copernicus EO satellite constellation [23]. These data are not easy to exploit. First, you will need to receive telemetry collected by sensors on-board the satellite. Then, you need to implement statistical and numerical models and choose the best in describing a specifying phenomenon, In the end, you will give as an input to the model, satellite data in a proper format (data normalization is always required). Only when you reach the final point, can the output data be collected in a larger database and help you in designing and optimizing energy plants and sustainable buildings. In recent times, a spread of tools and software has been noticed, providing the evidence to how sustainability and, specifically, renewable energies are becoming relevant in our modern circular economy. For example, Google, with its \"Project sunroot\" tool, allows you in a user-friendly interface to evaluate if it is convenient to build photovoltaic panels in a certain area, by using satellite data. It is not relevant to this point to list the high number of clean energy software that have been developed across the years, but it's important to speak about the most relevant ones and the way in which they provide useful results for an accurate analysis of renewable energies plants, thanks to the availability of large amount of satellite data (all of the Earth's surface is mapped with more than one sensor). HOMER (Hybrid Optimization Modeling Software) is able to design and analyze the power systems combining traditional and renewable technologies. This tool is very accurate, but it requires too much input data to build a proper scenario, so it is mainly used not for the feasibility study phase, but for the manufacturing phase [26]. Further tools have been developed, as databases or atlases, depicting only a small set of parameters; among these tools, we found the NASA Prediction of Worldwide Energy Resource (POWER) project aimed to improve the current renewable energy data set and to create a new database from new satellite systems. The POWER project is mainly addressed to renewable and sustainable energy [27]. \begin{table}
\begin{tabular}{c l} \hline
**Parameter Category** & **Specific Parameters** \\ \hline SOLAR GEOMETRY & \(\bullet\) Solar noon \\  & \(\bullet\) Daylight hour \\  & \(\bullet\) Hourly solar angles from horizon \\ \hline RADIATION & \(\bullet\) All-sky insolation (Average, Min, Max) \\  & \(\bullet\) Diffuse horizontal radiation (Average, Min, Max) \\  & \(\bullet\) Direct normal radiation (Average, Min, Max) \\  & \(\bullet\) Clear-sky insolation \\  & \(\bullet\) Clear-sky days \\ \hline ILLUMINANCE & \(\bullet\) Illuminance on tilted surfaces at available GMT times \\  & \(\bullet\) Illuminance on tilted surfaces over 24 hour period \\ \hline SURFACE ALBEDO & \(\bullet\) Surface albedo \\ \hline CLOUDS & \(\bullet\) Daylight cloud amount \\  & \(\bullet\) Cloud amount at available GMT times \\  & \(\bullet\) Frequency of cloud amount at available GMT times \\ \hline METEOROLOGY (WIND) & \(\bullet\) Wind speed at 50 m (Average, Min, Max) \\  & \(\bullet\) Percent of time for ranges of wind speed at 50 m \\  & \(\bullet\) Wind speed at 10 m for terrain similar to airports \\ \hline METEOROLOGY (TEMPERATURE) & \(\bullet\) Air temperature at 10 m \\  & \(\bullet\) Daily temperature Range at 10 m \\  & \(\bullet\) Dew point temperature at 10 m \\  & \(\bullet\) Cooling degree days above 18 \({}^{\circ}\)C \\  & \(\bullet\) Heating degree days below 18 \({}^{\circ}\)C \\  & \(\bullet\) Earth skin temperature \\  & \(\bullet\) Frost days \\ \hline PRECIPITATION & \(\bullet\) Precipitation \\ \hline \end{tabular}
\end{table} 
Table 2: Typical set of data for Earth monitoring [25].