## 5 Results and Discussion
### Trends to Be Further Explored
#### 5.3.1 Less Frequently Used Spectral Bands and VIs
SWIR VIs improved the detection of burned pastures, burned secondary regrowth, and tilled pastures. [PERSON] et al. [156] extracted metrics from Landsat NDVI time series and developed a Short-Wave Infra-Red Index (SWIR-Index) to separate cropland, pasture, and natural savanna vegetation in the Brazilian Cerrado by a spectral-temporal approach. SWIR bands showed more importance among 30 features to the RF model, and the classification achieved an OA equal to 93% for six classes. SWIR and associated VIs also allowed the accurate separability between foreground-background objects, such as grassland and crops [157], and improved classifications accuracies in heterogeneous landscapes based on S2/MSI [146; 158] and L8/OLI time series [62]. Using Landsat data from 2000 to 2015, [PERSON] et al. [159] considered SWIR bands and the associated VI Land Surface Water Index (LSWI) [160] the most useful information to classify maize and soybean, with an OA equal to 96%. Using S2/MSI data and the RF algorithm to identify optimal temporal windows for crop mapping in southern China, [PERSON] et al. [161] showed that the use of all images during a cycle of crop growth is not necessary, considering the later stages and the SWIR and NIR bands more useful. Assessing 28 VIs, [PERSON] et al. [162] demonstrate the suitability of S2/MSI SWIR bands to separate broad LULC classes and tree species. SWIR-based VIs were used to classify built-up and bare lands [163; 164]. The term Red-edge refers to the abrupt reflectance rise caused by vegetation within the electromagnetic spectrum from 680 nm to 750 nm, which is related to two optical effects of plant tissue: (a) strong chlorophyll absorption, causing low Red reflectance, and (b) high internal leaf scattering, causing large NIR reflectance [165]. This spectral region is correlated with photosynthetic capacity and is an important measurement of chlorophyll content and vegetation health [95]. The presence of Red-edge bands in the S2/MSI mission expanded their use for LULC classification, representing a significant spectral enrichment regarding other sensors used in LULC classification [166]. Especially in circumstances of saturation, Red-edge bands have the potential to improve the accuracy of biomass and crop yield estimates [58]. It has been reported that the Red-edge band close to Red wavelengths (band 5) is related to the difference in chlorophyll content, while the one close to NIR (band 7) is correlated to variations in leaf structure [38]. This suggests that the separability of Red-edge features lies in both leaf structure and chlorophyll content of different vegetation species [85], which is suitable to map heterogeneous landscapes, especially by using Red-edge-associated VIs [166]. Red-edge bands and associated VIs have been applied to estimate biophysical variables in vegetation, as LAI, Fraction of Absorbed Photosynthetically Active Radiation (FAPAR), and Gross Primary Productivity (GPP) [84; 167; 168; 169], suggesting that VIs formulated with Red-edge bands can reduce the saturation when compared with VIs derived from the Red band. VIs like these use the Red-edge region of the electromagnetic spectrum, taking as chlorophyll concentration contained in vegetation, strongly correlates with it [84]. Several papers demonstrate that S2/MSI Red-edge bands and associated VIs have provided more accurate results in LULC classification, thus improving overall and class-specific accuracies. For [PERSON] et al. [102], the inclusion of Red-edge bands in a LULC classification model positively impacted on vegetation classes and improved OA. [PERSON] et al. [146] showed Red-edge as the most important S2/MSI bands for crop discrimination over an Austrian agricultural area. [PERSON] et al. [157] confirmed this assumption in southern Belgium, showing that the second and third Red-edge bands performed better than the first. Integrating L8/OLI and S2/MSI for LULC classification in West Africa, [PERSON] et al.