# Estimating Double Cropping Plantations in the Brazilian Cerrado through PlanetScope Monthly Mosaics
## 3 Results
### Textural Features  
We found that some GLCM textural features were highly correlated regardless of spectral band or month of the year. This is the case, for example, between asymmetry and maximum probability (r = 0.969) or between mean and variance (r = 0.973) derived from the mosaic obtained in October 2021 and band 4 (Table 3). In this figure, there are 13 combinations with coefficients of correlation higher than 0.80, which agrees with the statement made by ESA [51] that some textural features produced by the GLCM can present some redundancy. Therefore, further analysis of reduction of data dimensionality for optimizing processing was addressed (see Table 3 below). Figure 6: Multitemporal enhanced vegetation index (EVI) of forestlands, cultivated pasturelands, single croplands, and double croplands from the municipality of Goiatuba, Goiás State, Brazil (2020/2021 crop growing season). Table 4 shows the statistical results of RF classification involving all spectral bands and vegetation indices and 20 out of 240 most important combinations involving textural features (10 textural features \(\times\) 6 months \(\times\) 4 bands). As the option with the 10 combinations presented the highest accuracies (overall accuracy = 90.91%; Kappa index = 0.8784), we selected this option for producing the final RF classification map of the municipality of Goiatuba. We chose to generate the final map using the Orteo Toolbox (OTB) plug-in in the QGIS 3.10 software because of the confidence map, an output that represents the level of confidence in the classification of each pixel considering the proportion of votes for the majority class [51]. Figure 7 shows the 10 most relevant input parameters for the RF classification based on the mean decrease accuracy criterion. This figure also shows the importance of PS mosaics from February, a month in which the seven top-ranked input parameters are involved. In terms of GLCM attributes, the variance, mean, and correlation were the most relevant parameters. \begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline  & **ASM** & **CON** & **COR** & **DIS** & **ENE** & **ENT** & **HOM** & **MAX** & **MEAN** & **VAR** \\ \hline ASM & 1 & & & & & & & & \\ CON & \(-\)0.343 & 1 & & & & & & & \\ COR & 0.067 & \(-\)0.381 & 1 & & & & & & \\ DIS & \(-\)0.561 & 0.924 & \(-\)0.358 & 1 & & & & & \\ ENE & 0.957 & \(-\)0.477 & 0.178 & \(-\)0.719 & 1 & & & & \\ ENT & \(-\)0.772 & 0.641 & \(-\)0.234 & 0.862 & \(-\)0.912 & 1 & & & \\ HOM & 0.822 & \(-\)0.636 & 0.180 & \(-\)0.869 & 0.937 & \(-\)0.966 & 1 & & \\ MAX & 0.969 & \(-\)0.400 & 0.084 & \(-\)0.628 & 0.975 & \(-\)0.834 & 0.880 & 1 & \\ MEAN & 0.025 & 0.049 & 0.423 & 0.059 & 0.149 & \(-\)0.086 & \(-\)0.038 & 0.006 & 1 & \\ VAR & 0.149 & 0.006 & 0.359 & \(-\)0.012 & 0.266 & \(-\)0.189 & 0.061 & 0.123 & 0.973 & 1 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Coefficients of correlation of 10 GLCM textural features derived from band 4 of PlanetScope mosaic obtained in October 2021. All positive and negative correlations higher than 0.80 are highlighted in red color. ASM = angular second moment; CON = contrast; COR = correlation; DIS = dissimilarity; ENE = energy; ENT = entropy; HOM = homogeneity; MAX = maximum value; MEAN = mean value; VAR = variance.