## 5 Results and Discussion
### Trends to Be Further Explored
#### 5.3.1 Less Frequently Used Spectral Bands and VIs
[144] showed that the use of S2/MSI Red-edge bands improved the map accuracy in 4% compared to that of L8/OLI and other S2/MSI bands. Inaddition, the authors reformulated the Red-edge-based VI named Normalized Difference Vegetation Index Red-edge (NDVIre) [170] formula with the Red-edge bands 5 and 6 of the S2/MSI, creating two relevant Red-edge associated VIs. Assessing the potential of the S2/MSI to classify grass species, [PERSON] and [PERSON] [171] attested the importance of Red-edge bands to equalize the OA with a Worldview-2 classification (high spatial resolution) considering three species. [PERSON] et al. [39] indicated that the Red-edge VIs Chlorophyll Index Red-edge (CIre) [172], Red-edge Inflection Point (REIP) [173], and NDVIre, and the proposed SWIR ratio index can monitor grass tissue concentrations of soil nutrients as Nitrogen, Potassium, Calcium, and Magnesium, which can be valuable features to increase the separability between natural vegetation and crop type classes. [PERSON] et al. [174] showed the potential of NDVIre to separate bare land from built-up areas in Turkey using the SVM algorithm. The OA was equal to 93% mapping seven classes. Extracting spatio-temporal information in VIs time series to classify crop types in Manitoba, Canada, [PERSON] et al. [63] indicate that NDVIre performed better than NDVI and SAVI (OA 88.31%, 87.27%, and 84.36%, respectively) for six crop types using RapidEye images to formulate the VIs, and indicating that the integration among multi-sources can be more exploited to further improve field-scale crop analysis and mapping. In the work of [PERSON] et al. [107], the integration between L8/OLI and S2/MSI data to generate a national-scale LULC map of Germany detecting the crop type distribution at a 30 m spatial resolution, provided an OA equal to 81% for 12 LULC classes. The inclusion of Red-edge bands improved all class-specific accuracies. [PERSON] et al. [175] attested the importance of the S2/MSI Red-edge bands and derived VIs (NDVIre, SAVIre, MSRre, and CIre) to map sunflower and wheat crops in India, using a c-means classification approach. [PERSON] et al. [85] mapped six LULC classes at one level and five crop types at another level using an RF classifier and showed that including Red-edge, the OA of crop type mapping improved when compared with only conventional optical features. The OA was equal to 94.05% and 83.22%, respectively. [PERSON] et al. [158] attested the importance of Red-edge bands and associated VIs to map agricultural fields in Mali's cotton belt by using an RF algorithm. All of these results emphasize the robustness of these bands and associated VIs to provide accurate mapping of different LULC classes in heterogeneous landscapes. Although there are various studies exploring VIs for LULC mapping and monitoring, this is still very restricted to the traditional ones. There is a lack of literature focusing on summarizing combinations of several VIs for this. With L8/OLI and, especially, S2/MSI data, less frequently applied VIs have been useful for improving classification results in dynamic and heterogeneous regions. The suitability of less frequently applied VIs for mapping different LULC classes, considering the papers cited in this systematic review, is summarized in Table 3, in order to provide guidance for future applications. The formulas are presented in the Supplementary Material (Tables S1-S3). In the future, harmonized Landsat and Sentinel data can drive the classifications, and the potential inclusion of Red-edge [29; 43; 105; 140], as well as additional narrower bands with 10 m spatial resolution in the visible, NIR, SWIR, and Thermal Infrared regions in future Landsat missions [58], can boost the use of these and other VIs in a dense time series perspective, which will be promising to improve accuracies. However, despite the differences between the L8/OLI and S2/MSI band wavelengths, we observed that some of the cited VIs have different terminologies, but the same formula, or different formulas for the same VI.