It is of extreme relevance to understand the behavior of vegetation for planning and decision-making regarding areas for planting, adequate use of water resources, irrigation and monitoring of vegetation dynamics, for example. In this sense, Remote Sensing (SR) has been a relevant support for the monitoring of ecosystems, since it is observed several researches involving the application of this technique through different mathematical algorithms titled indexes. The new satellites, unmanned vehicles and highresolution cameras that maintains products in the visible (RGB) range bring new perspectives to RS's performance in vegetation, especially in agriculture. Thus, it was developed over the years indices that allowed the detection of vegetation in visible spectral bands and, thus, facilitating agropastoral processes, precision agriculture and the reduction of SR as a whole. Thus, this work aims to review vegetation indices for processing in the RGB range. From the review, the origin of fifteen RGB indices is verified, being designed by diverse needs and equipment, where all reach competitive satisfactory. It is important to note that the developed indexes have improved the RS analyzes, where these improvements have led to new learning that directly contributed to the study of ecosystems, especially vegetation environments. The RS's dynamism makes it an innovation gimmick, in which, through demands and demands, new indices can be created by contributing to the maintenance and provision of social, economic and ecological activities.
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