## 2 Materials and Methods
### Methodology
#### 2.3.2 Dataset Composition  
Creating the base dataset is critical in the LULC classification processes [52]. In this research, the composition of the S2 dataset started by building a filtered and cloud-masked image collection of S2 L2A, including 547 images. This initial filtering was performed for the study area and the period of interest (from 1 August 2018 to 30 September 2019). The latter was defined considering the reference time of the initial ground control points dataset. Then, the Normalized Difference Vegetation Index (NDVI), the Normalized Difference Moisture Index (NDMI), the Green Normalized Difference Vegetation Index (GNDVI), and the Bare Soil Index (BSI) were calculated for each image (Table 3). The NDVI is often used to map changes in land cover [53; 54] and significantly improves classification accuracy when used for the LULC classification [55]. The GNDVI and the NDMI are normalized ratios similar to the NDVI, but instead of the red band, the former uses the green band and the latter uses the short-infrared band. The GNDVI is more sensitive to the chlorophyll content of the leaves [56], whereas the NDMI is more sensitive to the water content in the spongy mesophyll of vegetation [57]. The BSI is generally used to distinguish bare soil from other land cover categories [58] and categorize and monitor seasonal bare soil locations [59]. A mean-based reduction step was applied to S2 bands and the derived spectral indices to obtain the final S2 composite dataset.  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Index** & **Formula** & **Author** \\ \hline NDVI & \(\frac{\text{NIR }-\text{RED}}{\text{NIR }+\text{RED}}\) & [PERSON] et al., 1973 [60] \\ GNDVI & \(\frac{\text{NIR }-\text{GREEN}}{\text{NIR }+\text{GREEN}}\) & [PERSON] et al., 1996 [61] \\ NDMI & \(\frac{\text{NIR }-\text{SWIRI}}{\text{NIR }+\text{SWIRI}}\) & [PERSON] et al., 1983 [62] \\ BSI & \(\frac{\text{(SWIR }+\text{RED) }+\text{(NIR }+\text{BLUE)}}{\text{(SWIR1 }+\text{RED) }+\text{(NIR }+\text{BLUE)}}\) & [PERSON] et al., 2002 [63] \\ \hline \hline \end{tabular}
\end{table}
Table 3: Spectral indices and related formulas used in the research.  
The composition of the S1 dataset was performed by initial filtering based on the same period and area of interest, instrument mode (IW), and transmitter-receiver polarizations (VV and VH). The filtered dataset includes 212 S1 images. A simple reduction was applied to obtain a final composite image containing the mean VV and VH bands. These bands were added to the S2 dataset to construct the base S2-S1 dataset.  
Similarly, the PL dataset was derived by performing initial filtering based on the same period and area of interest. Considering the type of available PL images from the Planet NCFI program in the selected period, only one four-band 6-month composite image was available with a spatial resolution of 4.77 m. The NDVI and GNDVI (Table 3) were calculated from this image and added to the initial bands to obtain the base Planet composite dataset.  
Before proceeding to the final band composition, to harmonize the different datasets, S2- and S1-derived layers were resampled to a resolution of 4.77 m using a bicubic interpolation [64]. The PL dataset was re-projected to the WGS84 CRS.