# Assessment of Interventions in Fuel Management Zones Using Remote Sensing
## 2 Materials and Methods
### Data Sets  
Multiple characteristics were used to describe the FMZ interior and the outside buffer for each section. In addition to the satellite data, new features were extracted using the Sentinel-2 bands and Sentinel-1 polarizations. The extracted features are present in Table 1. For Sentinel-1 the difference and ratio between the VV and VH polarizations in both ascending and descending orbits are calculated since they have already been shown to improve classification accuracy [34]. For Sentinel-2 some vegetation indices were derived. Figure 8: Examples of the intersection of Fuel Management Zones (FMZs) and buffers with the created sections. (**a**) Section of an FMZ along a road. (**b**) Section of an FMZ along an electric line. (**c**) Section of an FMZ around a cluster of dwellings. Figure 7: Stages of segment creation. (**a**) Points of the interior (orange) and the exterior buffer of the FMZ (gray). (**b**) Clusters generated using K-Means. K = 5200. With these characteristics, 5 data sets were created to compare the impact of each group of characteristics in the results (Table 2). The data set _DS_ALL_ has all Sentinel-2 bands, vegetation indices and Sentinel-1 polarizations, data set _DS_INDICES_ has only vegetation indices and _DS_BAND_ has only satellite bands. The _DS_FUSION_ was created using the red, green, red-edge and near-infrared bands, which are the bands that are used in the vegetation indices calculations, and two indices that assess different vegetation characteristics: NDVI and NDWI. Finally, the _DS_SAR_ exclusively using Sentinel-1 data. For each one of these characteristics, the information from the interior of the FMZ and the outer buffer was extracted. Complementing that, the difference (Equation (2)) and ratio (Equation (3)) between the outer buffer and interior FMZ was calculated for every characteristic. With this, every segment ends up with data about the buffer, FMZ, difference, and ratios. \[ \begin{split} dif_{x}=x_{b}-x_{i}\end{split}  \tag{2}\]  
\[ \begin{split} ratio_{x}=\frac{x_{b}}{x_{i}}\end{split}  \tag{3}\]  
where \(x_{b}\) represents buffer data and \(x_{i}\) the FMZ data, for the characteristic \(x\). Multi-temporal analysis can take advantage of the multiple images extracted, as for each characteristic the difference between two consecutive dates is calculated for the whole time series (Equation (4)). \[ \begin{split}\Delta dif_{k}=(\frac{daysToPreviousDate-maxDays}{ maxDays-minDays})*({ dif_{x,k}-{dif_{x,k-1}}})\end{split}  \tag{4}\]  
where \({dif_{x,k}}\) represents the difference between the outer buffer and the interior of the FMZ for attribute \(x\), on date \(k\). \begin{table}
\begin{tabular}{c c} \hline \hline
**Satellite** & **Calculated Characteristics** \\ \hline Sentinel-1 & VV/VH, VV-VH \\ Sentinel-2 & NDVI, NDWI, SAVI, IRECI, SR \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Calculated characteristics for each one of the satellites. \begin{table}
\begin{tabular}{c c} \hline \hline
**Data Sets** & **Base Attributes** \\ \hline \multirow{3}{*}{_DS\_ALL_} & NDVI, NDWI, SAVI, IRECI, SR, B02, B03, B04, B05, B06, B07, \\  & B08, B11, (VV\_DESC, VH\_DESC, VV-VH\_DESC, VV/VH\_DESC, \\  & VV\_ASC, VH\_ASC, VV-VH\_ASC, VV/VH\_ASC) * \\ \hline \multirow{3}{*}{_DS\_INDICES_} & NDVI, NDWI, SAVI, IRECI, SR, \\  & (VV\_DESC, VH\_DESC, VV-VH\_DESC, VV/VH\_DESC, \\  & VV\_ASC, VH\_ASC, VV-VH\_ASC, VV/VH\_ASC) * \\ \hline \multirow{3}{*}{_DS\_BAND_} & B02, B03, B04, B05, B06, B07, B08, B11, \\  & (VV\_DESC, VH\_DESC, VV-VH\_DESC, VV/VH\_DESC, \\  & VV\_ASC, VH\_ASC, VV-VH\_ASC, VV/VH\_ASC) * \\ \hline \multirow{3}{*}{_DS\_FUSION_} & NDVI, NDWI, B03, B04, B05, B06, B07, B08, \\  & (VV\_DESC, VH\_DESC, VV-VH\_DESC, VV/VH\_DESC, \\  & VV\_ASC, VH\_ASC, VV-VH\_ASC, VV/VH\_ASC) * \\ \hline \multirow{3}{*}{_DS\_SAR_} & VV\_DESC, VH\_DESC, VV-VH\_DESC, VV/VH\_DESC, \\  & VV\_ASC, VH\_ASC, VV-VH\_ASC, VV/VH\_ASC \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Tested data sets and its characteristics.