An algorithm to retrieve chlorophyll, dissolved organic carbon, and suspended minerals from Great Lakes satellite data

Shuchman, Robert A.; Leshkevich, George; Sayers, Michael J.; Johengen, Thomas H.; Brooks, Colin; Pozdnyakov, Dmitry

doi:10.1016/j.jglr.2013.06.017

Cited by 81 publications

(45 citation statements)

References 47 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Removal of atmospheric effects enables further analysis of the reflectance spectra to determine which constituents are present at any given time. While several approaches have been proposed to do this, spectral shape-based algorithms show promise at partitioning the variance associated with these complex optical mixtures (Simis et al, 2005;Moisan et al, 2011;Chase et al, 2013;Shuchman et al, 2013). Application of these methods in these complex environments suggests that they will be effective at less complex marine applications.…”

Section: Implications For Reflectance Estimation and Atmospheric Corrmentioning

confidence: 99%

Intercomparison of Approaches to the Empirical Line Method for Vicarious Hyperspectral Reflectance Calibration

et al. 2017

View full text Add to dashboard Cite

Analysis of visible remote sensing data research requires removing atmospheric effects by conversion from radiance to at-surface reflectance. This conversion can be achieved through theoretical radiative transfer models, which yield good results when well-constrained by field observations, although these measurements are often lacking. Additionally, radiative transfer models often perform poorly in marine or lacustrine settings or when complex air masses with variable aerosols are present. The empirical line method (ELM) measures reference targets of known reflectance in the scene. ELM methods require minimal environmental observations and are conceptually simple. However, calibration coefficients are unique to the image containing the reflectance reference. Here we compare the conversion of hyperspectral radiance observations obtained with the NASA Glenn Research Center Hyperspectral Imager to at-surface reflectance factor using two reflectance reference targets. The first target employs spherical convex mirrors, deployed on the water surface to reflect ambient direct solar and hemispherical sky irradiance to the sensor. We calculate the mirror gain using near concurrent at-sensor reflectance, integrated mirror radiance, and in situ water reflectance. The second target is the Lambertian-like blacktop surface at Maumee Bay State Park, Oregon, OH, where reflectance was measured concurrently by a downward looking, spectroradiometer on the ground, the aerial hyperspectral imager and an upward looking spectroradiometer on the aircraft. These methods allows us to produce an independently calibrated at-surface water reflectance spectrum, when atmospheric conditions are consistent. We compare the mirror and blacktop-corrected spectra to the in situ water reflectance, and find good agreement between methods. The blacktop method can be applied to all scenes, while the mirror calibration method, based on direct observation of the light illuminating the scene validates the results. The two methods are complementary and a powerful evaluation of the quality of atmospheric correction over extended areas. We decompose the resulting spectra using varimax-rotated, principal component analysis, yielding information about the underlying color producing agents that contribute to the Ortiz et al.Vicarious Hyperspectral Reflectance Calibration Methods observed reflectance factor scene, identifying several spectrally and spatially distinct mixtures of algae, cyanobacteria, illite, haematite, and goethite. These results have implications for future hyperspectral remote sensing missions, such as PACE, HyspIRI, and GeoCAPE.

show abstract

Section: Implications For Reflectance Estimation and Atmospheric Corrmentioning

confidence: 99%

Intercomparison of Approaches to the Empirical Line Method for Vicarious Hyperspectral Reflectance Calibration

et al. 2017

View full text Add to dashboard Cite

show abstract

“…Many of these lake changes can be directly or indirectly characterized by changes in colour-producing agents (CPAs) (i.e. the bio-geochemical constituents of the water column that affect the water's spectra, the primary CPAs being chlorophyll, suspended minerals, and coloured dissolved organic matter (Shuchman et al 2013)). Chlorophyll is of particular potential value as a proxy for trophic state, primary production, and total ecosystem productivity (Lyche-Solheim et al 2013).…”

Section: Introductionmentioning

confidence: 99%

“…In brief, these inland techniques can be roughly categorized into two groups. The first group, semi-analytical bio-optical inversion models, were developed for the coastal ocean (Lee, Carder, and Arnone 2002;Maritorena, Siegel, and Peterson 2002) and inland waters (Shuchman et al 2013;Korosov et al 2009) and frequently rely on hyperspectral imagery and require tuning to local/regional inherent optical properties (IOPs) for accuracy, making them difficult to scale up to the global level (Sathyendranath 2000;Lee 2006). The second group is comprised of empirical approaches, including band ratio algorithms (O'Reilly et al 1998(O'Reilly et al , 2000Gons, Rijkeboer, and Ruddick 2002;Binding, Greenberg, and Bukata 2012), which statistically relate the remotely sensed signal directly to chl (see review by Matthews 2011).…”

Section: Introductionmentioning

confidence: 99%

A new method to generate a high-resolution global distribution map of lake chlorophyll

Sayers

Grimm

Shuchman

et al. 2015

International Journal of Remote Sensing

Self Cite

View full text Add to dashboard Cite

A new method was developed, evaluated, and applied to generate a global dataset of growing-season chlorophyll-a (chl) concentrations in 2011 for freshwater lakes. Chl observations from freshwater lakes are valuable for estimating lake productivity as well as assessing the role that these lakes play in carbon budgets. The standard 4 km NASA OceanColor L3 chlorophyll concentration products generated from MODIS and MERIS sensor data are not sufficiently representative of global chl values because these can only resolve larger lakes, which generally have lower chl concentrations than lakes of smaller surface area. Our new methodology utilizes the 300 m-resolution MERIS full-resolution full-swath (FRS) global dataset as input and does not rely on the land mask used to generate standard NASA products, which masks many lakes that are otherwise resolvable in MERIS imagery. The new method produced chl concentration values for 78,938 and 1,074 lakes in the northern and southern hemispheres, respectively. The mean chl for lakes visible in the MERIS composite was 19.2 ± 19.2, the median was 13.3, and the interquartile range was 3.90-28.6 mg m −3 . The accuracy of the MERIS-derived values was assessed by comparison with temporally nearcoincident and globally distributed in situ measurements from the literature (n = 185, RMSE = 9.39, R 2 = 0.72). This represents the first global-scale dataset of satellitederived chl estimates for medium to large lakes.

show abstract

“…Chlorophyll (chla), the photosynthetically active pigment of phytoplankton, and is soluble in water and produced yellow-green color. In addition to the light-absorbing, chla involved in back light with complex interactions [ 2 ] . Chlorophyll concentration as one of the main phytoplankton as representative for the conditions used chemical water quality and ecological status.…”

Section: Introductionmentioning

confidence: 99%

Ocean Color Retrieval Using Landsat-8 Imagery in Coastal Case 2 Waters (Case Study Persian and Oman Gulf)

Moradi

Hasanlou

Saadatseresht

2016

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

View full text Add to dashboard Cite

Commission VIII, WG VIII/9 KEY WORDS: Ocean color, Landsat-8, MODIS, Visible and near infrared bands, Non-Linear Model ABSTRACT:Ocean color (OC) monitoring using satellite imageries provides an appropriate tool for a better understanding of marine processes and changes in the coastal environment. Radiance measurements in the range of visible light of the electromagnetic spectrum provides information of ocean color that is associated with the water constituents. This measurements are used to monitor the level of biological activity and the presence of particles in the water. Ocean features such as the concentration of chlorophyll, suspended sediment concentration and sea surface temperature have a significant impact on the dynamics of the ocean. The concentration of chlorophyll (chla), active pigments of phytoplankton photosynthesis, as a key indicator applied for assessment of water quality and biochemistry. Experimental algorithms chla related to internal communication various optical components in the water that may be change in space and time in the water with different optical characteristics. Therefore, the algorithms have been developed for one area may not work for other places and each region according to its specific characteristics needs that determined by an algorithm may be appropriate to local. We have tried treatment several algorithms for determination of chlorophyll, including experimental algorithms with a simple band ratio of blue-green band (i.e. OCx) and algorithms includes two bands ratio with variable that desired wavelength (i.e. λ1, λ2, λ3 and λ4) in the range of red and near-infrared wavelengths of the electromagnetic spectrum are in the region of the Persian Gulf and Oman Sea look. Despite the high importance of the Persian Gulf and Oman Sea which can have up basin countries, to now few studies have been done in this area. The focus of this article on the northern part of Oman Sea and Persian Gulf, the shores of neighboring Iran (case 2 water). In this paper, by using Landsat 8 satellite imageries, we have discussed chla concentrations and customizing different OC algorithms for this new dataset (Landsat-8 imagery). This satellite was launched in 2013 and its data using two sensors continuously are provided operating one sensor imager land (OLI: Operational Land Imager) and the Thermal Infrared Sensor (TIRS: Thermal InfraRed Sensor) and are available. This sensors collect image data, respectively, for the nine-band short wavelength in the range of 433-2300 nm and dual-band long wavelength thermal. Seven band of the nine band picked up by the sensor information of OLI to deal with sensors TM (Thematic Mapper) and ETM+ (Enhanced Thematic Mapper Plus) in previous satellite Landsat compatible and two other band, the band of coastal water (433 to 453 nm) and Cirrus band (1360 to 1390 nm), short wave infrared provides to measure water quality and high thin clouds. Since OLI sensor in Landsat satellite 8 compared with other sensors to study OC have been allocated a much better spatial resoluti...

show abstract

An algorithm to retrieve chlorophyll, dissolved organic carbon, and suspended minerals from Great Lakes satellite data

Cited by 81 publications

References 47 publications

Intercomparison of Approaches to the Empirical Line Method for Vicarious Hyperspectral Reflectance Calibration

Intercomparison of Approaches to the Empirical Line Method for Vicarious Hyperspectral Reflectance Calibration

A new method to generate a high-resolution global distribution map of lake chlorophyll

Ocean Color Retrieval Using Landsat-8 Imagery in Coastal Case 2 Waters (Case Study Persian and Oman Gulf)

Contact Info

Product

Resources

About