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Proceedings Paper

Possibilities of water quality monitoring with the use of different remote sensed data sources (Conference Presentation)
Author(s): Malgorzata Slapinska

Paper Abstract

The aim of this study was to retrieve empirical formulas for water quality of three coastal lakes using remote sensing data - HySpex airborne imaging spectrometer and Sentinel-2A data. The Lebsko Lake, the Gardno Lake and the Great Dolgie Lake are salt-water lakes located in Slowinski National Park in Poland on the Baltic Sea coast. They all are shallow and turbid reservoirs prone to cyanobacteria blooms and eutrophication. Hyperspectral remote sensing data were acquired by the HySpex airborne sensor (in the range of 400-2500 nm) on 03.08.2015, multispectral data was acquired on the same date by MSI imager from Sentinel-2A satellite (in the range of 443-2190 nm). The ground measurements campaign was conducted 2-4.08.2015. The ground measurements consisted of two parts. First part included spectral reflectance sampling with spectroradiometer ASD FieldSpec 3, which covered the wavelength range of 350-2500 nm at ̴5 nm intervals. In situ data were collected both for water and for specific objects within the area. Second part of the campaign included water parameters in 48 points such as Secchi disc depth (SDD), electric conductivity (EC), pH, temperature, water chemistry (F, Br, Cl, NO2 NO3, PO4, SO4, Li, Na, NH4, Mn, Ca, N, DOC) and, phytoplankton groups. The empirical formulas for our water parameters were retrieved based on the reflecatance data from different remote sensed data sources from the time of field campaign. This study compared utility of HySpex and Sentinel-2A data sources - their means and limitations in terms of water quality modelling.

Paper Details

Date Published: 18 October 2017
PDF
Proc. SPIE 10421, Remote Sensing for Agriculture, Ecosystems, and Hydrology XIX, 1042108 (18 October 2017); doi: 10.1117/12.2278643
Show Author Affiliations
Malgorzata Slapinska, Warsaw Univ. of Life Sciences SGGW (Poland)


Published in SPIE Proceedings Vol. 10421:
Remote Sensing for Agriculture, Ecosystems, and Hydrology XIX
Christopher M. U. Neale; Antonino Maltese, Editor(s)

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