The accelerated erosion of biodiversity is a critical environmental challenge. Operational methods for the monitoring of biodiversity taking advantage of remotely sensed data are needed in order to provide information to ecologists and decision‐makers. We present an R package designed to compute a selection of α‐ and β‐diversity indicators from optical imagery, based on spectral variation hypothesis. This package builds upon previous work on biodiversity mapping using airborne imaging spectroscopy, and has been adapted in order to process broader range of data sources, including Sentinel‐2 satellite images. biodivMapR is able to produce α‐diversity maps including Shannon and Simpson indices, as well as β‐diversity maps derived from Bray–Curtis dissimilarity. It is able to process large images efficiently with moderate computational requirements on a personal computer. Additional functions allow computing diversity indicators directly from field plots defined as polygon shapefiles for easy comparison with ground data and validation. The package biodivMapR should contribute to improved standards for biodiversity mapping using remotely sensed data. It should also contribute to the identification of relevant Remotely Sensed enabled Essential Biodiversity Variables.