Cladophora is a filamentous, green alga that grows attached to solid substrate in all of the Laurentian Great Lakes. Nuisance growth of Cladophora occurs lakewide in comparatively phosphorus-rich shallow waters (0-15m depth) possessing solid substrate, and has recently become a prominent Great Lakes ecological and human health issue again in recent years. The resurgence of nuisance conditions is a result of habitat expansion, i.e. growth enhancement associated with the improved Great Lakes light climate of the post-dreissenid (zebra and quagga mussel) era. We are proposing to use remote sensing to demonstrate the feasibility of accurately and repeatedly detecting Cladophora extent tied to in situ water-truth data. A major focus of this study will be to determine if a distinct spectral signature of Cladophora in relatively shallow (<15m) waters can be accurately and consistently determined using remote sensing. Different types and scales of remote sensing platforms will be evaluated, including aerial photography, AVIRIS, Landsat, and commercial high-resolution satellite systems. Part of the proposed work will include the application of a bottom mapping algorithm for shallow coastal waters. Given a body of water that is shallow and/or transparent enough for light to pass through, reflect off the bottom, and return to the atmosphere from the water surface, a bottom classification algorithm can be used to infer water-bottom type using multi-spectral and hyper-spectral satellite data. These bottom types can be directly linked to the presence of Cladophora growth. We propose to tune this algorithm using in-situ radiometric data along with available bottom-type observations and focused collection of spectral reflectance data. With demonstrated feasibility, natural resource managers in the Great Lakes concerned with the resurgence of Cladophora will have access to a monitoring tool that can be used in assessing the effectiveness of new phosphorous reduction efforts, and to study past Cladophora trends.