## 3 Materials
### Multispectral Optical Datasets  
The _Sentinel-_2 (hereinafter called S2) mission is part of the European Copernicus programme. The satellite acquires multispectral optical data with a spatial resolution between 10-20 m as a function of the considered band. The temporal resolution is 5 days due to two twin satellites, S2A and S2B. The multispectral optical data were obtained and processed in the Google Earth Engine (GEE) referring to the COPERNICUS/S2_SR collection. Sentinel-2 is a high-resolution, broad-spectrum, multispectral optical mission that supports the Copernicus Land Monitoring Service, including monitoring vegetation, soil and water cover and observing inland waterways and coastal areas. Sentinel-2 L2 data were downloaded from the Copernicus SciHub (the official distribution portal of the Earth Observation data in question). The images were pre-processed in Sen2 cor (the official tool released by the European Space Agency--ESA). The EO data S2 that was pre-processed in Sen2 cor contained 12 spectral bands of UINT16 (see Table 1). The images were ortho-projected in WGS84 and were in ground reflectance rescaled in dimensionless values from 0 to 10,000 starting from the existing DN to calculate the ground reflectance by removing the atmospheric contribution. There are also three QA bands for each scene, one of which (QA60) is a bitmask band with cloud mask information. In GEE, clouds can be removed as an alternative to using pixels in QA quality using COPERNICUS/S2_CLOUD_PROBABILITY. In this case, the QA bands were used.  
A yearly median composite imagery ranging from 1 May 2020 to 30 September 2020 without clouds and shadows was realized. The S2 data were used to create yearly harmonized and filtered NDVI and NDRE stacks with a 10 days step to map woody crops.  
_PlanetScope_, as part of the private space program Planet acquired by Google with its ultra-high spatial resolution microsatellites, is increasingly becoming a reference reality in remote sensing activities due to the possibility of accessing the data free of charge for education and research purposes ([[https://www.planet.com/markets/education-and-research](https://www.planet.com/markets/education-and-research)]([https://www.planet.com/markets/education-and-research](https://www.planet.com/markets/education-and-research)), last access on 6 November 2022). Starting with the daily data acquired by PlanetScope, a stack was created, including all the acquisitions in the reference period of study. With a self-developed GEE algorithm, a composite imagery was generated covering the same period as S2. This image was adopted as an extra product in the validation phase and in the definition of the training sets during a photo-interpretation phase. It is worth noting that the PlanetScope micro-satellites acquire multispectral optical data on a daily basis in four bands with a ground sample distance (GSD) of around 3 m with various levels of processing. In this case, geo-referenced and atmospheric calibrated products in surface reflectance were adopted. Considering that these data are not open-access and have a fee  
\begin{table}
\begin{tabular}{c c c} \hline
**Bands** & **Description** & **Spatial Resolution (m)** \\ \hline B1 & Aerosols & 60 \\ B2 & Blue & 10 \\ B3 & Green & 10 \\ B4 & Red & 10 \\ B5 & Red Edge 1 & 20 \\ B6 & Red Edge 2 & 20 \\ B7 & Red Edge 3 & 20 \\ B8 & NIR & 10 \\ B8A & Red Edge 4 & 20 \\ B9 & Water vapor & 60 \\ B11 & SWIR 1 & 20 \\ B12 & SWIR 2 & 20 \\ SCL & Mask & 10 \\ MSK, CLD\_PRB & Cloud probability mask & 20 \\ QA10-60 & Cloud mask & 10–60 \\ \hline \end{tabular}
\end{table}
Table 1: A simple overview of the Sentinel-2 surface reflectance product collection composition in the Google Earth Engine.  
for use except in scientific purposes, they can be considered optional in the development of a fully free EO geospatial local service. However, they represent a useful tool during the suggested workflow.