Atmospheric correction issues for retrieving total suspended matter concentrations in inland waters using OLI/Landsat-8 image

Bernardo, Nariane; Watanabe, Fernanda; Rodrigues, Thanan; Alcântara, Enner

doi:10.1016/j.asr.2017.02.017

Cited by 73 publications

(40 citation statements)

References 43 publications

(77 reference statements)

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“…Other investigators have also found the surface reflectance product to be a reasonable choice for water pixels [35,75]. In particular, Pahlevan et al (2017) [76] wrote that ρ is expected to have seemingly reasonable radiometric properties over small inland bodies of water, and Bernardo et al (2017) [77] found that using ρ outperforms reflectance products from several other atmospheric correction methods in TSS retrieval in a Brazilian reservoir. Our results for Lake Pukaki support this ( Figure 11).…”

Section: Limitations Of Our Approachmentioning

confidence: 97%

“…Most aquatic remote sensing studies use remote sensing reflectance, which has sun and sky glint contributions removed by atmospheric correction methods that are designed for ocean colour applications [76,78]. Developing better atmospheric correction of inland and coastal targets is an active area of research and there is currently no consensus as to the best method [76,77,79]. To see whether atmospheric correction developed for aquatic targets improves our analysis, we processed five of our Landsat 8 scenes using SeaDAS with default settings, as described in [76,80].…”

Section: Limitations Of Our Approachmentioning

confidence: 99%

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Colour Classification of 1486 Lakes across a Wide Range of Optical Water Types

et al. 2018

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Remote sensing by satellite-borne sensors presents a significant opportunity to enhance the spatio-temporal coverage of environmental monitoring programmes for lakes, but the estimation of classic water quality attributes from inland water bodies has not reached operational status due to the difficulty of discerning the spectral signatures of optically active water constituents. Determination of water colour, as perceived by the human eye, does not require knowledge of inherent optical properties and therefore represents a generally applicable remotely-sensed water quality attribute. In this paper, we implemented a recent algorithm for the retrieval of colour parameters (hue angle, dominant wavelength) and derived a new correction for colour purity to account for the spectral bandpass of the Landsat 8 Operational Land Imager (OLI). We used this algorithm to calculate water colour on almost 45,000 observations over four years from 1486 lakes from a diverse range of optical water types in New Zealand. We show that the most prevalent lake colours are yellow-orange and blue, respectively, while green observations are comparatively rare. About 40% of the study lakes show transitions between colours at a range of time scales, including seasonal. A preliminary exploratory analysis suggests that both geo-physical and anthropogenic factors, such as catchment land use, provide environmental control of lake colour and are promising avenues for future analysis.

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Section: Limitations Of Our Approachmentioning

confidence: 97%

Section: Limitations Of Our Approachmentioning

confidence: 99%

Colour Classification of 1486 Lakes across a Wide Range of Optical Water Types

et al. 2018

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“…The model was applied in L8SR product, which showed a better matching with in situ R rs (Bernardo et al 2017). Comparing the Chl-a range in the map and collected in situ, the underestimation in the model is apparent; however, it better represented the Chl-a range and distribution in BBHR.…”

Section: Water Quality Parametersmentioning

confidence: 99%

Remote sensing of the chlorophyll-a based on OLI/Landsat-8 and MSI/Sentinel-2A (Barra Bonita reservoir, Brazil)

Watanabe

Alcântara

Rodrigues

et al. 2018

An. Acad. Bras. Ciênc.

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In this present research, we assessed the performance of band algorithms in estimating chlorophyll-a (Chl-a) concentration based on bands of two new sensors: Operational Land Imager onboard Landsat-8 satellite (OLI/Landsat-8), and MultiSpectral Instrument onboard Sentinel-2A (MSI/Sentinel-2A). Band combinations designed for Thematic Mapper onboard Landsat-5 satellite (TM/Landsat-5) and MEdium Resolution Imaging Spectrometer onboard Envisat platform (MERIS/Envisat) were adapted for OLI/ Landsat-8 and MSI/Sentinel-2A bands. Algorithms were calibrated using in situ measurements collected in three field campaigns carried out in different seasons. The study area was the Barra Bonita hydroelectric reservoir (BBHR), a highly productive aquatic system. With exception of the three-band algorithm, the algorithms were spectrally few affected by sensors changes. On the other hands, algorithm performance has been hampered by the bio-optical difference in the reservoir sections, drought in 2014 and pigment packaging.

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“…OLI applications for inland water systems were recently investigated and demonstrated great results [43][44][45][46] due to their spatial resolutions that are able to represent significant details in hydrologic process in such environments. Besides, the Landsat dataset has demonstrated high suitability for inland and coastal studies [47,48].…”

Section: Oli Assessmentmentioning

confidence: 99%

“…Then, the convoluted values of R rs were compared to the R rs from OLI images to assess if our glint removal dataset matches the OLI dataset. Considering that LaSRC retrieved the irradiance reflectance, the images were converted into R rs by dividing them to π, and applying the scale factor of 10,000 [46]. The images were also visually assessed in order to identify the presence of glint.…”

Section: Oli Assessmentmentioning

confidence: 99%

Glint Removal Assessment to Estimate the Remote Sensing Reflectance in Inland Waters with Widely Differing Optical Properties

et al. 2018

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The quality control of remote sensing reflectance (R rs ) is a challenging task in remote sensing applications, mainly in the retrieval of accurate in situ measurements carried out in optically complex aquatic systems. One of the main challenges is related to glint effect into the in situ measurements. Our study evaluates four different methods to reduce the glint effect from the R rs spectra collected in cascade reservoirs with widely differing optical properties. The first (i) method adopts a constant coefficient for skylight correction (ρ) for any geometry viewing of in situ measurements and wind speed lower than 5 m·s −1 ; (ii) the second uses a look-up-table with variable ρ values accordingly to viewing geometry acquisition and wind speed; (iii) the third method is based on hyperspectral optimization to produce a spectral glint correction, and (iv) computes ρ as a function of wind speed. The glint effect corrected R rs spectra were assessed using HydroLight simulations. The results showed that using the glint correction with spectral ρ achieved the lowest errors, however, in a Colored Dissolved Organic Matter (CDOM) dominated environment with no remarkable chlorophyll-a concentrations, the best method was the second. Besides, the results with spectral glint correction reduced almost 30% of errors.

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Atmospheric correction issues for retrieving total suspended matter concentrations in inland waters using OLI/Landsat-8 image

Cited by 73 publications

References 43 publications

Colour Classification of 1486 Lakes across a Wide Range of Optical Water Types

Colour Classification of 1486 Lakes across a Wide Range of Optical Water Types

Remote sensing of the chlorophyll-a based on OLI/Landsat-8 and MSI/Sentinel-2A (Barra Bonita reservoir, Brazil)

Glint Removal Assessment to Estimate the Remote Sensing Reflectance in Inland Waters with Widely Differing Optical Properties

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