## 2 Materials and Methods
### Materials and Datasets
Figure 4: Spectral indices time-series from vegetation areas during 2017 for each study area. Here, both indices are strongly affected by phenology. (**a**) NDMI; (**b**) NDVI. As can be seen in Figure 6, some of the maintenance operations occur in two successive months. This fact leads to the definition of two kinds of operations: the instantaneous operations, that occur in one month only, and the continuous operations. Normally, the latter start at the end of the month and continue into the beginning of the next month. Note that an operation is not an instantaneous procedure; it takes several days between the vegetation cut and the cleaning of the site (and sometimes it can be noticed between observations). So, it may be executed during the same month or in two consecutive months. In Figure 6, the difference between an instantaneous and a continuous operation is shown. The first is characterized by a single event (June of 2017), while the second by two events (May and June of 2017). The change in a continuous operation is, usually, softer than the instantaneous one, being usually harder to detect. The implementation of the methodology relied on three datasets: training, validation and test. The first two resort only to data from Fundao, Seia, Serra dos Candeeiros and Serta. A random stratified split was executed, generating the training and validation dataset (the first with 67% of the data and the second with the remaining). The test dataset is composed of two groups: the real case scenario and the incomplete operations set. The first group is composed by Marisol data, it tested the behaviour of the ANN in an untrained scenario. For the second group, since there is no information about the occurrence of incomplete operations, it was needed to simulate these events. As said before, the maintenance procedures are not instantaneous, which allowed the creation of datasets with partial operations. For this purpose, some observations were removed, being presented to the ANN as an incomplete operation, instead of the real complete operation. In Figure 7, there are several observations of an FB, between (a), (b) and (c), some work is done, but it is only completed in (d). In the real case all observations are used, but for the simulated incomplete operations, each transition is evaluated. The incomplete operations should be divided into different groups, according to their completeness degree. This measure corresponds to the ratio between the area already operated and the FB total area. In Figure 7, an example from Marisol is presented, where in (b), the completeness of the \begin{table}
\begin{tabular}{c c c c c c} \hline \hline \multirow{2}{*}{**Study Area**} & **Area** & \multicolumn{2}{c}{**Clear Observations**} & \multirow{2}{*}{**Number of**} & \multirow{2}{*}{**Operation Dates**} \\  & **[ha]** & **2017** & **2018** & & & \\ \hline Fundão & 71.2 & 28 & 23 & 3 & JUL/AUG/SEP 2017 \\ Marisol & 2.0 & 40 & 49 & 1 & MAR 2018 \\ Seia & 50.2 & 29 & 24 & 2 & JUN 2017 \\ Serra dos Candeeiros & 105.5 & 59 & 49 & 5 & MAY/JUN/JUL/AUG \\  & & & & & 2017 \\ Serta & 53.2 & 30 & 19 & 3 & JAN/FEB/JUN 2017 \\  & & & & & JUL 2018 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Number of clear observations per study area and year. Figure 5: Spectral indices time-series comparison from FB and VEG areas in Serra dos Candeeiros during 2017. Phenology effects are present in both indices, but when an operation occurs, ExG is more robust than NDVI. (**a**) NDVI; (**b**) ExG. operation is 28% and in (c) it is 61%. If the maintenance covers 75% or more of the FB, it is considered a complete operation. The training and validation dataset were composed by 261 observations and for the test dataset there were 89 observations for Marisol and 21 observations for the definition of 9 incomplete operations.