Anais do XX Simpósio Brasileiro de Sensoriamento Remoto

Currently, spectral vegetation indices (VIs) derived from satellite data have an essential role as spectral and temporal features for improving the accuracy of land use and land cover mappings and the landscape characterization. The wide range of VIs led to the creation of repositories that catalog, summarize, describe, and link their formulations to a code editor and collections of spectral bands, in order to facilitate their calculation and diffuse their potential. In this scope, we developed the “Surface Reflectance to Vegetation Indices” (sr2vgi) package. In python language, it is a ready-to-use repository that allows accessing and computing VIs from spectral bands. All VIs can be formulated as expressions by selecting the spectral bands that compose their formulations in a math field specific for band ratio calculation. The package demonstrates how much VIs can be effortlessly computed inside a code editor, speeding up remote sensing-based analyses by avoiding hard coding.