title: Application of Landsat imagery to regional-scale assessments of lake clarity.
abstract: A procedure that uses Landsat imagery to estimate Secchi disk transparency (SDT) of lakes was developed and applied to approximately 500 lakes with surface areas > 10 ha in the seven-county metropolitan area of Minneapolis and St. Paul, MN, USA, to assess spatial patterns and temporal trends in lake clarity. Thirteen Landsat MSS and TM images over the period 1973-1998 were used for the analysis. Satellite brightness values from lake surfaces were calibrated against available historical data on SDT (n = approximately 20-40) measured nearly contemporaneously with the acquisition date of each image. Calibration regression equations for the late-summer TM images had a range of r2 from 0.72 to 0.93. Regression analysis for three late-summer MSS images yielded r2 values ranging from 0.60 to 0.79. Results indicate that a single late-summer image yields a reliable estimate of regional lake clarity and reasonably accurate estimates of SDT for individual lakes. An analysis of seasonal patterns on a large lake water-quality database was used to develop a model that adjusts synoptic satellite SDT estimates from different dates to a common reference, making them more comparable from year-to-year. Analysis of long-term trends shows that in spite of the large land-use changes within the region over the study period, only 49 (about 10%) of assessed lakes in the region showed significant temporal trends in SDT over the period, and more lakes had increasing SDT (34) than decreasing SDT (15).
authors.affiliation: Metropolitan Council Environmental Services, St. Paul, MN 55101, USA.
authors.forename: Steven M
authors.initials: SM
authors.lastname: Kloiber
authors.forename: Patrick L
authors.initials: PL
authors.lastname: Brezonik
authors.forename: Marvin E
authors.initials: ME
authors.lastname: Bauer
mesh_terms: D003952:Diagnostic Imaging / Q000379:methods*; D005618:Fresh Water / Q000737:chemistry*; D009391:Nephelometry and Turbidimetry; D012044:Regression Analysis; D017215:Satellite Communications; D012621:Seasons