It is important to understand the patterns of species distributions as they determine the functioning of ecosystems across a wide range of time and space scales from biogeochemical cycles and partitioning of the energy budget, to changes in biodiversity, habitat characteristics, and trophic structures. However, even high spatial resolution imagery has not been sufficient to identify and map individual species. Mapping large monotypic stands is challenging, unless the spectral properties of the species stand out from their neighbors due to differences in growth form or timing of phenological activity. Where it is possible, mapping of individual species is often restricted to limited areas of ecologically similar conditions, or restricted to analysis of single datasets and do not consider how species identification changes with season, location, and environmental conditions. In the past decade, with the development of environmental spectroscopy, both from field spectrometers and airborne imaging spectrometers, has allowed progress in identifying individual species from remote sensing data. There is now a growing literature on identifying species in many case studies. However, use of environmental spectroscopy for species identification needs understanding at a more fundamental level, especially the development of generalized methodologies and rules for detection and mapping, which is an area of active research today. Conceptually, we have yet to resolve how to identify unique spectral signatures for the estimated 400,000 extant plant species or groups of species (i.e., functional types). In contrast to geologic minerals which are often spectrally distinct, all land plants share a common basic metabolism and biochemistry, making identification uncertain because of the interactions with environmental conditions and phenological stages, in addition to the characteristic properties of individual species. These issues will be explored using examples from a wide range of habitats and site conditions, to develop a robust methodology.