title: Assessment of nutrient distributions in Lake Champlain using satellite remote sensing.
abstract: The introduction of nutrients to lakes causing eutrophic conditions is a major problem around the world. Proper monitoring and modeling are important to effectively manage eutrophication in lake waters. The goal is to develop remote sensing models for nutrients, total phosphorus and total nitrogen, in Lake Champlain. The remote sensing models were created using multivariate linear regression with the unique band combinations of Landsat Enhanced Thematic Mapper Plus (ETM+) imagery based on the empirical relationship with the field observations. The resulting models successfully showed nutrient distributions in the most eutrophic part of Lake Champlain, Missisquoi Bay, with reasonable adjusted coefficient of determination values (R(2)=0.81 and 0.75 for total phosphorus and total nitrogen, respectively). The results show the feasibility and the utility of satellite imagery to detect spatial distributions of lake water quality constituents, which can be used to better understand nutrient distributions in Lake Champlain. This approach can be applicable to other lakes experiencing eutrophication assisting decision making when implementing Best Management Practices and other mitigation techniques to lakes.
authors.affiliation: Department of Civil and Environmental Engineering, University of Massachusetts Amherst, MA 01003, USA. Electronic address: isenstein@engin.umass.edu.
authors.forename: Elizabeth M
authors.initials: EM
authors.lastname: Isenstein
authors.affiliation: Department of Civil and Environmental Engineering, University of Massachusetts Amherst, MA 01003, USA. Electronic address: mpark@ecs.umass.edu.
authors.forename: Mi-Hyun
authors.initials: MH
authors.lastname: Park
mesh_terms: D060106:Lakes / Q000032:analysis*; D009518:New York; D009584:Nitrogen / Q000032:analysis*; D010758:Phosphorus / Q000032:analysis*; D058998:Remote Sensing Technology; D014707:Vermont
chemical_list: D010758:Phosphorus; D009584:Nitrogen
keywords: Monitoring; Nutrients; Phosphorus; Remote sensing