The water color simulator WASI: an integrating software tool for analysis and simulation of optical in situ spectra

Gege, Peter

doi:10.1016/j.cageo.2004.03.005

Cited by 72 publications

(51 citation statements)

References 19 publications

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“…The chlorophyll-a fluorescence emission function was approximated by a Gaussian peak centered at 685 nm with a standard deviation of 10.6 nm. 35 To carry out the analysis we set the parameters to typical values found in turbid productive water by using our experimental data set 1 and published data ( Table 1).…”

Section: Discussionmentioning

confidence: 99%

Effect of bio-optical parameter variability and uncertainties in reflectance measurements on the remote estimation of chlorophyll-a concentration in turbid productive waters: modeling results

2006

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Most algorithms for retrieving chlorophyll-a concentration (Chla) from reflectance spectra assume that bio-optical parameters such as the phytoplankton specific absorption coefficient (a *) or the chlorophyll-a fluorescence quantum yield ͑͒ are constant. Yet there exist experimental data showing large ranges of variability for these quantities. The main objective of this study was to analyze the sensitivity of two Chla algorithms to variations in bio-optical parameters and to uncertainties in reflectance measurements. These algorithms are specifically designed for turbid productive waters and are based on red and near-infrared reflectances. By means of simulated data, it is shown that the spectral regions where the algorithms are maximally sensitive to Chla overlap those of maximal sensitivity to variations in the above bio-optical parameters. Thus, to increase the accuracy of Chla retrieval, we suggest using spectral regions where the algorithms are less sensitive to Chla, but also less sensitive to these interferences. a * appeared to be one of the most important sources of error for retrieving Chla. However, when the phytoplankton backscattering coefficient ͑b b, ͒ dominates the total backscattering, as is likely during algal blooms, variations in the specific b b, may introduce large systematic uncertainties in Chla estimation. Also, uncertainties in reflectance measurements, which are due to incomplete atmospheric correction or reflected skylight removal, seem to affect considerably the accuracy of Chla estimation. Instead, variations in other bio-optical parameters, such as or the specific backscattering coefficient of total suspended particles, appear to have minor importance. Suggestions regarding the optimal band locations to be used in the above algorithms are finally provided.

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Section: Discussionmentioning

confidence: 99%

Effect of bio-optical parameter variability and uncertainties in reflectance measurements on the remote estimation of chlorophyll-a concentration in turbid productive waters: modeling results

2006

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“…The water column correction was according to absorption models for phytoplankton [52] and colored dissolved organic matter [42], to backscattering models for phytoplankton [53] and non-algal particles [54], as well as absorption and backscattering coefficients of water and to the radiative transfer model of Albert and Mobley [55]. For calculating the required water constituent concentrations (Chl-a), colored dissolved organic matter (cDOM) and suspended particulate matter (SPM) were derived by an inversion of the diffuse vertical attenuation coefficient for downwelling irradiance as implemented in the water colour simulator WASI [56,57]. The attenuation coefficient was calculated with the method of Maritorena [58] by using measurements in two different depths (b and 0) at the same spot.…”

Section: Data Processingmentioning

confidence: 99%

“…These protracted and detailed spectral pieces of information can strongly improve the knowledge of the seasonal variation of macrophyte species. The output spectra of these models provide a useful and necessary basis for bio-optical models such as BOMBER [54] or WASI [56,57].…”

Section: Reflectance Modelmentioning

confidence: 99%

“…The knowledge of phenologic development related spectral response seems necessary when trying to improve the simulation and analysis of optical properties and light field parameters of deep and shallow waters in satellite datasets. This detailed information for the diverse phenologic stages of macrophytes are expected to improve the inversion success of bio-optical models such as BOMBER [54] and WASI [56,57]. Such models presently are the most sophisticated methods for deriving optical properties and light field parameters of deep and shallow waters from satellite data.…”

Section: Model Inversion For Species Level Classificationmentioning

confidence: 99%

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Seasonal Variation in Spectral Response of Submerged Aquatic Macrophytes: A Case Study at Lake Starnberg (Germany)

Fritz

Schneider

Geist

2017

Water

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Submerged macrophytes are important structural components of freshwater ecosystems that are widely used as long-term bioindicators for the trophic state of freshwater lakes. Climate change and related rising water temperatures are suspected to affect macrophyte growth and species composition as well as the length of the growing season. Alternative to the traditional ground-based monitoring methods, remote sensing is expected to provide fast and effective tools to map submerged macrophytes at short intervals and over large areas. This study analyses interrelations between spectral signature, plant phenology and the length of growing season as influenced by the variable water temperature. During the growing seasons of 2011 and 2015, remote sensing reflectance spectra of macrophytes and sediment were collected systematically in-situ with hyperspectral underwater spectroradiometer at Lake Starnberg, Germany. The established spectral libraries were used to develop reflectance models. The combination of spectral information and phenologic characteristics allows the development of a phenologic fingerprint for each macrophyte species. By inversion, the reflectance models deliver day and daytime specific spectral signatures of the macrophyte populations. The subsequent classification processing chain allowed distinguishing species-specific macrophyte growth at different phenologic stages. The analysis of spectral signatures within the phenologic development indicates that the invasive species Elodea nuttallii is less affected by water temperature oscillations than the native species Chara spp. and Potamogeton perfoliatus.

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“…[23]) could be employed. Instead, we tested an approach using fundamental water end members derived from the HS images to map the relative abundances of the selected surface water parameters and the ground truth data to validate the results of spectral mapping.…”

mentioning

confidence: 99%

Applying Spectral Unmixing to Determine Surface Water Parameters in a Mining Environment

Kopačková

Hladíková

2014

Remote Sensing

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Compared to natural waters, mine waters represent an extreme water type that is frequently heavily polluted. Although they have been traditionally monitored by in situ measurements of point samples taken at regular intervals, the emergence of a new generation of multispectral and hyperspectral (HS) sensors means that image spectroscopy has the potential to become a modern method for monitoring polluted surface waters. This paper describes an approach employing linear Spectral Unmixing (LSU) for analysis of hyperspectral image data to map the relative abundances of mine water components (dissolved Fe-Fediss, dissolved organic carbon-DOC, undissolved particles). The ground truth data (8 monitored ponds) were used to validate the results of spectral mapping. The same approach applied to HS data was tested using the image data resampled to WorldView2 (WV2) spectral resolution. A key aspect of the image data processing was to define the proper pure image end members for the fundamental water types. The highest correlations detected between the studied water parameters and the fractional images using the HyMap and the resampled WV2 data, respectively, were: dissolved Fe (R 2 = 0.74 and R 2 vw2 = 0.6), undissolved particles (R 2 = 0.57 and R 2 vw2 = 0.49) and DOC (R 2 = 0.42 and R 2 vw2 < 0.40). These fractional images were further classified to create semi-quantitative maps. In conclusion, the classification still benefited from the higher spectral resolution of the HyMap data; however the WV2 reflectance data can be suitable for mapping specific inherent optical properties (SIOPs), which significantly differ from one another from an optical point of view OPEN ACCESSRemote Sens. 2014, 6 11205 (e.g., mineral suspension, dissolved Fe and phytoplankton), but it seems difficult to differentiate among diverse suspension particles, especially when the waters have more complex properties (e.g., mineral particles, DOC together with tripton or other particles, etc.).

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The water color simulator WASI: an integrating software tool for analysis and simulation of optical in situ spectra

Cited by 72 publications

References 19 publications

Effect of bio-optical parameter variability and uncertainties in reflectance measurements on the remote estimation of chlorophyll-a concentration in turbid productive waters: modeling results

Effect of bio-optical parameter variability and uncertainties in reflectance measurements on the remote estimation of chlorophyll-a concentration in turbid productive waters: modeling results

Seasonal Variation in Spectral Response of Submerged Aquatic Macrophytes: A Case Study at Lake Starnberg (Germany)

Applying Spectral Unmixing to Determine Surface Water Parameters in a Mining Environment

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