Radiative Transfer Theory for Inland Waters

Gege, Peter

doi:10.1016/b978-0-12-804644-9.00002-1

Cited by 13 publications

(10 citation statements)

References 94 publications

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“…Several studies analyzed the satellite sensor requirements for a monitoring system resulting in 5–10 nm spectral resolution and a spatial resolution 17 m to 60 m pixel size, covering wavelength ranges up to 1000 nm [29,33,34,35]. Given these requirements, DESIS can play an essential role in developing a next-generation coastal and inland water monitoring system [36,37,38,39], allowing the retrieval of water reflectance, physical parameters such as turbidity and water clarity [40], suspended and dissolved water quality components (e.g., Chl-a concentration as a proxy of phytoplankton biomass), colored dissolved organic matter (CDOM) and total suspended matter (TSM) [9,41]. Compared to traditional EO systems based on MODIS, MERIS, Sentinel and Landsat [42,43], imaging spectroscopy has clear advantages in discriminating phytoplankton types [43], characterizing submerged habitat compositions [44], assessing water quality [32], observing environmental threats such as coral bleaching and estimating bathymetry [45].…”

Section: Application Fields Of Desismentioning

confidence: 99%

Data Products, Quality and Validation of the DLR Earth Sensing Imaging Spectrometer (DESIS)

Alonso¹,

Bachmann

Burch

et al. 2019

Sensors

129

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Imaging spectrometry from aerial or spaceborne platforms, also known as hyperspectral remote sensing, provides dense sampled and fine structured spectral information for each image pixel, allowing the user to identify and characterize Earth surface materials such as minerals in rocks and soils, vegetation types and stress indicators, and water constituents. The recently launched DLR Earth Sensing Imaging Spectrometer (DESIS) installed on the International Space Station (ISS) closes the long-term gap of sparsely available spaceborne imaging spectrometry data and will be part of the upcoming fleet of such new instruments in orbit. DESIS measures in the spectral range from 400 and 1000 nm with a spectral sampling distance of 2.55 nm and a Full Width Half Maximum (FWHM) of about 3.5 nm. The ground sample distance is 30 m with 1024 pixels across track. In this article, a detailed review is given on the applicability of DESIS data based on the specifics of the instrument, the characteristics of the ISS orbit, and the methods applied to generate products. The various DESIS data products available for users are described with the focus on specific processing steps. The results of the data quality and product validation studies show that top-of-atmosphere radiance, geometrically corrected, and bottom-of-atmosphere reflectance products meet the mission requirements. The limitations of the DESIS data products are also subject to a critical examination.

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Section: Application Fields Of Desismentioning

confidence: 99%

Data Products, Quality and Validation of the DLR Earth Sensing Imaging Spectrometer (DESIS)

Alonso¹,

Bachmann

Burch

et al. 2019

Sensors

129

View full text Add to dashboard Cite

show abstract

“…Its coefficients have been derived using Hydrolight [21] simulations, covering wide ranges of environmental parameters, including all concentrations of the standard scenarios and most of the high concentrations of the extreme scenarios. A similar model has been developed by Lee et al [22,25] for narrower ranges; see [26] for a comparison of the equations and parameter ranges. The following is Albert's equation for optically deep water: (5) and the following is the equation for optically shallow water:…”

Section: Determination Of the Optimal Spectral Resolutionmentioning

confidence: 99%

Spectral and Radiometric Measurement Requirements for Inland, Coastal and Reef Waters

Gege

Dekker

2020

Remote Sensing

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This paper studies the measurement requirements of spectral resolution and radiometric sensitivity to enable the quantitative determination of water constituents and benthic parameters for the majority of optically deep and optically shallow waters on Earth. The spectral and radiometric variability is investigated by simulating remote sensing reflectance (Rrs) spectra of optically deep water for twelve inland water scenarios representing typical and extreme concentration ranges of phytoplankton, colored dissolved organic matter and non-algal particles. For optically shallow waters, Rrs changes induced by variable water depth are simulated for fourteen bottom substrate types, from lakes to coastal waters and coral reefs. The required radiometric sensitivity is derived for the conditions that the spectral shape of Rrs should be resolvable with a quantization of 100 levels and that measurable reflection differences at at least one wavelength must occur at concentration changes in water constituents of 10% and depth differences of 20 cm. These simulations are also used to derive the optimal spectral resolution and the most sensitive wavelengths. Finally, the Rrs spectra and their changes are converted to radiances and radiance differences in order to derive sensor (noise-equivalent radiance) and measurement requirements (signal-to-noise ratio) at the water surface and at the top of the atmosphere for a range of solar zenith angles.

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“…A similar r − rs (λ) model has been developed by Lee et al [53,55], but Albert's model additionally accounts for the sun zenith angle and the viewing angle, and it covers a wider range of environmental parameters, including most of the high concentrations of water constituents as observed in inland waters. More details on the applied models and a comparison with the models and parameter ranges of Lee et al [53,55] can be found in Gege [56].…”

Section: Remote Sensing Reflectancementioning

confidence: 99%

Retrieval of Water Constituents from Hyperspectral In-Situ Measurements under Variable Cloud Cover—A Case Study at Lake Stechlin (Germany)

et al. 2018

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Abstract:Remote sensing and field spectroscopy of natural waters is typically performed under clear skies, low wind speeds and low solar zenith angles. Such measurements can also be made, in principle, under clouds and mixed skies using airborne or in-situ measurements; however, variable illumination conditions pose a challenge to data analysis. In the present case study, we evaluated the inversion of hyperspectral in-situ measurements for water constituent retrieval acquired under variable cloud cover. First, we studied the retrieval of Chlorophyll-a (Chl-a) concentration and colored dissolved organic matter (CDOM) absorption from in-water irradiance measurements. Then, we evaluated the errors in the retrievals of the concentration of total suspended matter (TSM), Chl-a and the absorption coefficient of CDOM from above-water reflectance measurements due to highly variable reflections at the water surface. In order to approximate cloud reflections, we extended a recent three-component surface reflectance model for cloudless atmospheres by a constant offset and compared different surface reflectance correction procedures. Our findings suggest that in-water irradiance measurements may be used for the analysis of absorbing compounds even under highly variable weather conditions. The extended surface reflectance model proved to contribute to the analysis of above-water reflectance measurements with respect to Chl-a and TSM. Results indicate the potential of this approach for all-weather monitoring.

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Radiative Transfer Theory for Inland Waters

Cited by 13 publications

References 94 publications

Data Products, Quality and Validation of the DLR Earth Sensing Imaging Spectrometer (DESIS)

Data Products, Quality and Validation of the DLR Earth Sensing Imaging Spectrometer (DESIS)

Spectral and Radiometric Measurement Requirements for Inland, Coastal and Reef Waters

Retrieval of Water Constituents from Hyperspectral In-Situ Measurements under Variable Cloud Cover—A Case Study at Lake Stechlin (Germany)

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