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Article

Water Quality Retrieval from PRISMA Hyperspectral Images: First Experience in a Turbid Lake and Comparison with Sentinel-2

1
Center for Information and Communication Technology, Fondazione Bruno Kessler, Via Sommarive, 18 I-38123 Trento, Italy
2
Department of Information Engineering and Computer Science, University of Trento, Via Sommarive, 5 I-38123 Trento, Italy
*
Author to whom correspondence should be addressed.
Remote Sens. 2020, 12(23), 3984; https://doi.org/10.3390/rs12233984
Received: 4 November 2020 / Revised: 1 December 2020 / Accepted: 4 December 2020 / Published: 6 December 2020
(This article belongs to the Special Issue Remote Sensing of Lake Properties and Dynamics)
A new era of spaceborne hyperspectral imaging has just begun with the recent availability of data from PRISMA (PRecursore IperSpettrale della Missione Applicativa) launched by the Italian space agency (ASI). There has been pre-launch optimism that the wealth of spectral information offered by PRISMA can contribute to a variety of aquatic science and management applications. Here, we examine the potential of PRISMA level 2D images in retrieving standard water quality parameters, including total suspended matter (TSM), chlorophyll-a (Chl-a), and colored dissolved organic matter (CDOM) in a turbid lake (Lake Trasimeno, Italy). We perform consistency analyses among the aquatic products (remote sensing reflectance (Rrs) and constituents) derived from PRISMA and those from Sentinel-2. The consistency analyses are expanded to synthesized Sentinel-2 data as well. By spectral downsampling of the PRISMA images, we better isolate the impact of spectral resolution in retrieving the constituents. The retrieval of constituents from both PRISMA and Sentinel-2 images is built upon inverting the radiative transfer model implemented in the Water Color Simulator (WASI) processor. The inversion involves a parameter (gdd) to compensate for atmospheric and sun-glint artifacts. A strong agreement is indicated for the cross-sensor comparison of Rrs products at different wavelengths (average R ≈ 0.87). However, the Rrs of PRISMA at shorter wavelengths (<500 nm) is slightly overestimated with respect to Sentinel-2. This is in line with the estimates of gdd through the inversion that suggests an underestimated atmospheric path radiance of PRISMA level 2D products compared to the atmospherically corrected Sentinel-2 data. The results indicate the high potential of PRISMA level 2D imagery in mapping water quality parameters in Lake Trasimeno. The PRISMA-based retrievals agree well with those of Sentinel-2, particularly for TSM. View Full-Text
Keywords: PRISMA; hyperspectral imagery; water quality; remote sensing reflectance; lake; chlorophyll-a; TSM; CDOM; Sentinel-2; physics-based inversion PRISMA; hyperspectral imagery; water quality; remote sensing reflectance; lake; chlorophyll-a; TSM; CDOM; Sentinel-2; physics-based inversion
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MDPI and ACS Style

Niroumand-Jadidi, M.; Bovolo, F.; Bruzzone, L. Water Quality Retrieval from PRISMA Hyperspectral Images: First Experience in a Turbid Lake and Comparison with Sentinel-2. Remote Sens. 2020, 12, 3984. https://doi.org/10.3390/rs12233984

AMA Style

Niroumand-Jadidi M, Bovolo F, Bruzzone L. Water Quality Retrieval from PRISMA Hyperspectral Images: First Experience in a Turbid Lake and Comparison with Sentinel-2. Remote Sensing. 2020; 12(23):3984. https://doi.org/10.3390/rs12233984

Chicago/Turabian Style

Niroumand-Jadidi, Milad, Francesca Bovolo, and Lorenzo Bruzzone. 2020. "Water Quality Retrieval from PRISMA Hyperspectral Images: First Experience in a Turbid Lake and Comparison with Sentinel-2" Remote Sensing 12, no. 23: 3984. https://doi.org/10.3390/rs12233984

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