Analytical canopy reflectance (CR) models have reached the level of adequacy that makes it possible to estimate vegetation parameters by inversion of such models. The growing efficiency of algorithms and the increasing power of computers urge the development of procedures for the estimation of vegetation phytometrical parameters on large areas using satellite data and inversion of theoretical CR models. In this article, clusterization of a Landsat Thematic Mapper (TM) quarter scene is performed in the space of spectral signatures, and the CR model is inverted for these clusters. Optical parameters of the atmosphere which are needed for the atmospheric correction are estimated on the same image. The estimated Leaf Area Index (LAI) pattern is in good accordance to the land use map. Estimated LAI and chlorophyll content of forests are systematically biased.