The rapid seasonal growth and accumulation of opportunistic green algae (OGA) in intertidal areas subject to eutrophication is a major global phenomenon. Many parts of the coast of Britain, especially those areas subject to weak tidal flow or restricted water exchange, are seriously influenced by OGA blooms which can achieve densities of 40 kg wet weight m-2 and form dense mats up to 1 m thick. Typically, the area covered by a bloom is between 10 and 102 km2 giving a total bloom biomass in a particular locality in the range 105 to 106 tonnes wet weight. Extensive evidence has demonstrated a close relationship between nutrient enrichment, which chiefly derives from land run-off and anthropological sources, and the occurrence of OGA blooms. A key element underpinning any statutory programme designed to mitigate the development of OGA blooms is knowledge of the areal extent and biomass associated with the various stages of development of a bloom together with information on the main taxonomic components. Remote Sensing offers major advantages in terms of economics and spatial coverage for assessing the areal extent of OGA blooms. Techniques for obtaining large spatial scale information on the contribution of contrasting green algal taxa to OGA blooms and the distribution of higher plants in bloom areas are lacking. The main OGA contributing to blooms appear to be members of the Ulvales, particularly Enteromorpha, Chaetomorpha and Ulva together with Cladophora. As with other plants, the spectral reflectance of algae depends on their chlorophyll and accessory pigment content, particularly the carotenoid and phycobiliprotein content. There are well-documented differences in the relative content of these light-absorbing materials in thalli of different algal taxonomic groups and there is now the potential to exploit these differences to estimate the contribution of the various OGA taxa to bloom biomass. A number of studies using airborne remote sensing data have been carried out but the results have been limited by a number of factors including the use of uncalibrated airborne spectral data, the lack of detailed, comprehensive ground measurements acquired contemporaneously with the acquisition of the remote sensing data and the restricted spatial and temporal resolution of the remote sensing data . (e.g. Fuller et al., 1995a-b). Additional problems limiting the applicability of remote sensing data in estuarine environmental analysis such as the mixed pixel problem, the effects of differing thickness of algae, the effect of light transmission through algae, the effects of different sediment substrates and the effect of the degree of saturation of the substrate have also not been fully addressed.