In situ measurements and satellite remote sensing of case 2 waters: first results from the Curonian Lagoon

Giardino, Claudia; Bresciani, Mariano; Pilkaitytė, Renata; Bartoli, Marco; Razinkovas, Artūras

doi:10.5697/oc.52-2.197

Cited by 38 publications

(29 citation statements)

References 27 publications

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“…Indeed, the highest possible accuracy of the hyperspectral water-leaving reflectance improves the detection capability of the dedicated algorithms for the retrieval of water quality parameters (Chlorophyll, Total Suspended Matter and Colored Dissolved Organic Matter) (Gitelson et al, 2011;Lee et al, 2007;Zibordi et al, 2011;Giardino et al, 2010;Guanter et al, 2010;Brando and Dekker, 2003). For example, if the chl a concentration is estimated according to band-ratio, which makes use of a red (680 nm) to very near-infrared (700 nm) wavelengths, the advantage of having a signal on a contiguous spectrum relies on the possibility of defining the algorithm according to the shift of the near-infrared reflectance band to be used (Schalles, 2006).…”

Section: Discussionmentioning

confidence: 99%

“…The methodology applied in this work is based on an analysis of the contribution of aerosol microphysical properties on the accuracy of water-leaving reflectance, whose assessment is closely related to the retrieval of water quality parameters (Chlorophyll, Total Suspended Matter and Colored Dissolved Organic Matter), Giardino et al, 2010;Guanter et al, 2010;Brando and Dekker, 2003).…”

Section: Methodsmentioning

confidence: 99%

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The impact of the microphysical properties of aerosol on the atmospheric correction of hyperspectral data in coastal waters

et al. 2015

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Abstract.Hyperspectral imaging provides quantitative remote sensing of ocean colour by the high spectral resolution of the water features. The HICO ™ (Hyperspectral Imager for the Coastal Ocean) is suitable for coastal studies and monitoring. The accurate retrieval of hyperspectral waterleaving reflectance from HICO ™ data is still a challenge. The aim of this work is to retrieve the water-leaving reflectance from HICO ™ data with a physically based algorithm, using the local microphysical properties of the aerosol in order to overcome the limitations of the standard aerosol types commonly used in atmospheric correction processing. The water-leaving reflectance was obtained using the HICO@CRI (HICO ATmospherically Corrected Reflectance Imagery) atmospheric correction algorithm by adapting the vector version of the Second Simulation of a Satellite Signal in the Solar Spectrum (6SV) radiative transfer code. The HICO@CRI algorithm was applied on to six HICO ™ images acquired in the northern Mediterranean basin, using the microphysical properties measured by the Acqua Alta Oceanographic Tower (AAOT) AERONET site. The HICO@CRI results obtained with AERONET products were validated with in situ measurements showing an accuracy expressed by r 2 = 0.98. Additional runs of HICO@CRI on the six images were performed using maritime, continental and urban standard aerosol types to perform the accuracy assessment when standard aerosol types implemented in 6SV are used. The results highlight that the microphysical properties of the aerosol improve the accuracy of the atmospheric correction compared to standard aerosol types. The normalized root mean square (NRMSE) and the similar spectral value (SSV) of the water-leaving reflectance show reduced accuracy in atmospheric correction results when there is an increase in aerosol loading. This is mainly when the standard aerosol type used is characterized with different optical properties compared to the local aerosol. The results suggest that if a water quality analysis is needed the microphysical properties of the aerosol need to be taken into consideration in the atmospheric correction of hyperspectral data over coastal environments, because aerosols influence the accuracy of the retrieved water-leaving reflectance.

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Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

The impact of the microphysical properties of aerosol on the atmospheric correction of hyperspectral data in coastal waters

et al. 2015

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“…Many Case-2 water models designed to estimate Chl-a using remote sensing data are already in use [11,38,39], but most rely on the typical signal of Chl-a near 700 nm, which is not covered by the first seven bands of the MODIS sensor ( Table 1). The MODIS bands originally designed for ocean color studies, which do cover 700 nm, are at 1-km spatial resolution, which is not suitable for small and medium-sized water bodies.…”

Section: Algorithms Used To Estimated Chl-a Concentrationmentioning

confidence: 99%

Comparative Analysis of Four Models to Estimate Chlorophyll-a Concentration in Case-2 Waters Using MODerate Resolution Imaging Spectroradiometer (MODIS) Imagery

et al. 2012

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Abstract:The occurrence and extent of intense harmful algal blooms (HABs) have increased in inland waters during recent decades. Standard monitor networks, based on infrequent sampling from a few fixed observation stations, are not providing enough information on the extent and intensity of the blooms. Remote sensing has great potential to provide the spatial and temporal coverage needed. Several sensors have been designed to study water properties (AVHRR, SeaBAM, and SeaWIFS), but most lack adequate spatial resolution for monitoring algal blooms in small and medium-sized lakes. Over the last decade, satellite data with 250-m spatial resolution have become available with MODIS. In the present study, three models inspired by published approaches (Kahru, Gitelson, and Floating Algae Index (FAI)) and a new approach named APPEL (APProach by ELimination) were adapted to the specific conditions of southern Quebec and used to estimate chlorophyll-a concentration (Chl-a) using MODIS data. Calibration and validation were provided from in situ Chl-a measured in four lakes over 9 years (2000)(2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008) and concurrent MODIS imagery. MODIS bands 3 to 7, originally at 500-m spatial resolution, were downscaled to 250 m. The APPEL, FAI, and Kahru models yielded satisfactory results and enabled estimation of Chl-a for heavy blooming conditions (Chl-a > 50 mg•m −3 ), with coefficients of determination reaching 0.95, 0.94, and 0.93, respectively. The model inspired from Gitelson did not provide good estimations compared to the others (R 2 = 0.77).However, the performance of all models decreased when Chl-a was below 50 mg•m −3 . OPEN ACCESSRemote Sens. 2012, 4 2374

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“…In order to eliminate the coastal effect on CDOM concentration, three pixels from the shoreline (i.e., 900 m) were discarded from the analysis. The retrieval of chl-a concentration was based on Giardino et al (2010) and Bresciani et al (2012). In their study MERIS data was corrected for the atmospheric effects with the 6S code (Vermote et al 1997;Kotchenova et al 2006).…”

Section: Satellite Datamentioning

confidence: 99%

Spatial and temporal distribution of coloured dissolved organic matter in a hypertrophic freshwater lagoon

Vaičiūtė¹,

Bresciani²,

Bartoli³

et al. 2015

J Limnol

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In situ measurements and satellite remote sensing of case 2 waters: first results from the Curonian Lagoon

Cited by 38 publications

References 27 publications

The impact of the microphysical properties of aerosol on the atmospheric correction of hyperspectral data in coastal waters

The impact of the microphysical properties of aerosol on the atmospheric correction of hyperspectral data in coastal waters

Comparative Analysis of Four Models to Estimate Chlorophyll-a Concentration in Case-2 Waters Using MODerate Resolution Imaging Spectroradiometer (MODIS) Imagery

Spatial and temporal distribution of coloured dissolved organic matter in a hypertrophic freshwater lagoon

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