My thesis presents theoretical basics for remote sensing, most common vegetation indices, and their use in estimation of vegetation state as well as in integrated applications. Special focus was put on NDVI, SAVI, PRI, CWSI and LAI indices. Vegetation indices are based upon the ratio of absorbed and reflected wavelengths of light. Absorbed and reflected light at a particular wavelength is measured by remote sensing with spectralradiometric imaging from space, planes, drones or ground. Imaging can be done with multispectral imaging which has its wavebands predefined or with hyperspectral imaging where we define wavebands later, according to the evaluation needs. With vegetation indices one can estimate primary production, photosynthesis, leaf biomass, water deficit and plant stress, evapotranspiration and vegetation structure. The aim of the thesis is to present the difference in obtaining data between multispectral and hyperspectral imaging and the usefulness of vegetation indices in practice.