Reflectance spectra and related water quality and color data from 325 Minnesota and Wisconsin lakes and rivers

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2013-05-01
2018-09-30

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2023-01-12

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Olmanson, Leif G
olman002@umn.edu

Abstract

This data set contains in situ reflectance spectra measured on 325 lakes and a few rivers broadly across the states of Minnesota and Wisconsin. The spectra were measured at the water surface at 1-nm intervals over the wavelength range 400-900 nm and are called "hyperspectra." Associated data include site identifications, key optical water quality variables measured on samples collected at the time of the reflectance measurements, two quantitative metrics of water color, dominant wavelength and hue angle, calculated from the hyperspectra, and values of the same two water-color metrics computed from simulated data for three satellite sensors (Sentinel-2 MSI, Sentinel-3 OLCI, and Landsat 8 OLI) derived from the hyperspectra using two published algorithms. The computed results are used to compare the reliability of the two published algorithms relative to the results obtained directly from the hyperspectra, which are considered to be the "true" values of dominant wavelength and hue angle metrics. In addition, the data set includes MATLAB code used in the computations.

Description

One data file includes the detailed in situ reflectance hyperspectra from 325 lakes and rivers in Minnesota and Wisconsin, along with information on site locations. A second file includes the water quality data (chlorophyll, CDOM, Secchi depth, and suspended solids) collected at the 325 sites simultaneously with the hyperspectra, along with values of dominant wavelength and hue angle calculated from the hyperspectra and computed by two algorithms from simulated reflectance data for three common satellite sensors. A subfolder contains 10 files of MATLAB codes used in the computations of satellite-derived hue angle and dominant wavelength, along with a readme text file that describes the MATLAB codes.

Referenced by

Burket, M.O.; Olmanson, L.G.; Brezonik, P.L. Comparison of Two Water Color Algorithms: Implications for the Remote Sensing of Water Bodies with Moderate to High CDOM or Chlorophyll Levels. Sensors 2023, 23, 1071.
https://doi.org/10.3390/s23031071

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Olmanson, Leif G; Burket, Martha; Brezonik, Patrick L. (2023). Reflectance spectra and related water quality and color data from 325 Minnesota and Wisconsin lakes and rivers. Retrieved from the Data Repository for the University of Minnesota (DRUM), https://doi.org/10.13020/1c2h-te39.

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