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Remote Sensing of Phytoplankton

A special issue of Remote Sensing (ISSN 2072-4292).

Deadline for manuscript submissions: closed (30 July 2013) | Viewed by 112381

Special Issue Editor

Ocean Sciences Department, University of California, A-461 Earth & Marine Sciences Bldg., Santa Cruz, CA 95064, USA
Interests: ecological modeling and remote sensing; satellite oceanography; phytoplankton ecology and harmful algal blooms

Special Issue Information

Dear Colleagues,

The advent of ocean color sensors introduced a new understanding of the dynamics inherent to phytoplankton biomass and productivity in both marine and freshwater systems. Remote sensing provides the only reasonable way to synoptically map aquatic systems, and through the development of Climate Data Records provides a long-term perspective on changes driven by basin-scale and global trends. The next generation of sensors provide improved spatial and spectral resolution, enabling the scientific community to move beyond simple indices of biomass to produce novel algorithms for phytoplankton functional types, colored dissolved material, particle composition, and other relevant optical properties. This special issue will draw from ongoing studies focused on remote observation of phytoplankton and related parameters in aquatic systems, from local to global scales.

Dr. Raphael M. Kudela
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • ocean remote sensing
  • remote sensing of lakes and reservoirs
  • phytoplankton Functional Types (PFT)
  • phytoplankton biomass and productivity
  • water color
  • optical properties of aquatic environments
  • phytoplankton biogeochemistry
  • climate change
  • biogeography

Published Papers (11 papers)

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Research

3536 KiB  
Article
An EOF-Based Algorithm to Estimate Chlorophyll a Concentrations in Taihu Lake from MODIS Land-Band Measurements: Implications for Near Real-Time Applications and Forecasting Models
by Lin Qi, Chuanmin Hu, Hongtao Duan, Brian B. Barnes and Ronghua Ma
Remote Sens. 2014, 6(11), 10694-10715; https://doi.org/10.3390/rs61110694 - 05 Nov 2014
Cited by 61 | Viewed by 9591
Abstract
For near real-time water applications, the Moderate Resolution Imaging Spectroradiometers (MODIS) on Terra and Aqua are currently the only satellite instruments that can provide well-calibrated top-of-atmosphere (TOA) radiance data over the global aquatic environments. However, TOA radiance data in the MODIS ocean bands [...] Read more.
For near real-time water applications, the Moderate Resolution Imaging Spectroradiometers (MODIS) on Terra and Aqua are currently the only satellite instruments that can provide well-calibrated top-of-atmosphere (TOA) radiance data over the global aquatic environments. However, TOA radiance data in the MODIS ocean bands over turbid atmosphere in east China often saturate, leaving only four land bands to use. In this study, an approach based on Empirical Orthogonal Function (EOF) analysis has been developed and validated to estimate chlorophyll a concentrations (Chla, μg/L) in surface waters of Taihu Lake, the third largest freshwater lake in China. The EOF approach analyzed the spectral variance of normalized Rayleigh-corrected reflectance (Rrc) data at 469, 555, 645, and 859 nm, and subsequently related that variance to Chla using 28 concurrent MODIS and field measurements. This empirical algorithm was then validated using another 30 independent concurrent MODIS and field measurements. Image analysis and radiative transfer simulations indicated that the algorithm appeared to be tolerant to aerosol perturbations, with unbiased RMS uncertainties of <80% for Chla ranging between 3 and 100 μg/L. Application of the algorithm to a total of 853 MODIS images between 2000 and 2013 under cloud-free conditions revealed spatial distribution patterns and seasonal changes that are consistent to previous findings based on floating algae mats. The current study can provide additional quantitative estimates of Chla that can be assimilated in an existing forecast model, which showed improved performance over the use of a previous Chla algorithm. However, the empirical nature, relatively large uncertainties, and limited number of spectral bands all point to the need of further improvement in data availability and accuracy with future satellite sensors. Full article
(This article belongs to the Special Issue Remote Sensing of Phytoplankton)
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2860 KiB  
Article
Evaluation of Satellite Retrievals of Ocean Chlorophyll-a in the California Current
by Mati Kahru, Raphael M. Kudela, Clarissa R. Anderson, Marlenne Manzano-Sarabia and B. Greg Mitchell
Remote Sens. 2014, 6(9), 8524-8540; https://doi.org/10.3390/rs6098524 - 11 Sep 2014
Cited by 37 | Viewed by 8045
Abstract
Retrievals of ocean surface chlorophyll-a concentration (Chla) by multiple ocean color satellite sensors (SeaWiFS, MODIS-Terra, MODIS-Aqua, MERIS, VIIRS) using standard algorithms were evaluated in the California Current using a large archive of in situ measurements. Over the full range of in situ Chla, [...] Read more.
Retrievals of ocean surface chlorophyll-a concentration (Chla) by multiple ocean color satellite sensors (SeaWiFS, MODIS-Terra, MODIS-Aqua, MERIS, VIIRS) using standard algorithms were evaluated in the California Current using a large archive of in situ measurements. Over the full range of in situ Chla, all sensors produced a coefficient of determination (R2) between 0.79 and 0.88 and a median absolute percent error (MdAPE) between 21% and 27%. However, at in situ Chla > 1 mg m3, only products from MERIS (both the ESA produced algal_1 and NASA produced chlor_a) maintained reasonable accuracy (R2 from 0.74 to 0.52 and MdAPE from 23% to 31%, respectively), while the other sensors had R2 below 0.5 and MdAPE higher than 36%. We show that the low accuracy at medium and high Chla is caused by the poor retrieval of remote sensing reflectance. Full article
(This article belongs to the Special Issue Remote Sensing of Phytoplankton)
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4844 KiB  
Article
ESA-MERIS 10-Year Mission Reveals Contrasting Phytoplankton Bloom Dynamics in Two Tropical Regions of Northern Australia
by David Blondeau-Patissier, Thomas Schroeder, Vittorio E. Brando, Stefan W. Maier, Arnold G. Dekker and Stuart Phinn
Remote Sens. 2014, 6(4), 2963-2988; https://doi.org/10.3390/rs6042963 - 01 Apr 2014
Cited by 29 | Viewed by 9922
Abstract
The spatial and temporal variability of phytoplankton blooms was investigated in two tropical coastal regions of northern Australia using the MEdium Resolution Imaging Spectrometer (MERIS) full mission (2002–2012) reduced resolution dataset. Satellite-derived proxies for phytoplankton (Chlorophyll-a (Chl), Fluorescence Line Height (FLH), Maximum Chlorophyll [...] Read more.
The spatial and temporal variability of phytoplankton blooms was investigated in two tropical coastal regions of northern Australia using the MEdium Resolution Imaging Spectrometer (MERIS) full mission (2002–2012) reduced resolution dataset. Satellite-derived proxies for phytoplankton (Chlorophyll-a (Chl), Fluorescence Line Height (FLH), Maximum Chlorophyll Index (MCI)) and suspended sediment (Total Suspended Matter (TSM)) were jointly analyzed for two clusters of the Great Barrier Reef Wet tropics (GBRW; 15°–19.5°S; Queensland) and the Van Diemen Gulf (VDG; 9°–13°S; Northern Territory). The analysis of time-series and Hovmöller diagrams of the four MERIS products provided a unique perspective on the processes linking phytoplankton blooms and river runoff, or resuspension, across spatio-temporal scales. Both regions are characterized by a complex oceanography and seasonal inflows of sediment, freshwater and nutrients during the tropical wet season months (November to April). The GBRW is characterized by a great variability in water clarity (Secchi depth 0–25 m). A long history of agricultural land use has led to a large increase in the seasonal discharge of sediments and nutrients, triggering seasonal phytoplankton blooms (>0.4 mg∙m−3) between January and April. In contrast, the VDG is a poorly flushed, turbid (Secchi depth <5 m) environment with strong tidal-energy (4–8 m) and very limited land use. Phytoplankton blooms here were found to have higher Chl concentrations (>1.0 mg∙m−3) than in the GBRW, occurring up to twice a year between January and April. Over the 10-year MERIS mission, a weak decline in Chl and TSM was observed for the VDG (Sen slope: −2.85%/decade, τ = −0.32 and −3.57%/decade, τ = −0.24; p 0.05), while no significant trend in those two satellite products was observed in the GBRW. Cyanobacteria surface algal blooms occur in both regions between August and October. The MCI and FLH products were found to adequately complement Chl, while TSM provided relevant insight for the assessment of sediment resuspension and river runoff. Full article
(This article belongs to the Special Issue Remote Sensing of Phytoplankton)
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10429 KiB  
Article
Application of the Hyperspectral Imager for the Coastal Ocean to Phytoplankton Ecology Studies in Monterey Bay, CA, USA
by John P. Ryan, Curtiss O. Davis, Nicholas B. Tufillaro, Raphael M. Kudela and Bo-Cai Gao
Remote Sens. 2014, 6(2), 1007-1025; https://doi.org/10.3390/rs6021007 - 27 Jan 2014
Cited by 83 | Viewed by 14234 | Correction
Abstract
As a demonstrator for technologies for the next generation of ocean color sensors, the Hyperspectral Imager for the Coastal Ocean (HICO) provides enhanced spatial and spectral resolution that is required to understand optically complex aquatic environments. In this study we apply HICO, along [...] Read more.
As a demonstrator for technologies for the next generation of ocean color sensors, the Hyperspectral Imager for the Coastal Ocean (HICO) provides enhanced spatial and spectral resolution that is required to understand optically complex aquatic environments. In this study we apply HICO, along with satellite remote sensing and in situ observations, to studies of phytoplankton ecology in a dynamic coastal upwelling environment—Monterey Bay, CA, USA. From a spring 2011 study, we examine HICO-detected spatial patterns in phytoplankton optical properties along an environmental gradient defined by upwelling flow patterns and along a temporal gradient of upwelling intensification. From a fall 2011 study, we use HICO’s enhanced spatial and spectral resolution to distinguish a small-scale “red tide” bloom, and we examine bloom expansion and its supporting processes using other remote sensing and in situ data. From a spectacular HICO image of the Monterey Bay region acquired during fall of 2012, we present a suite of algorithm results for characterization of phytoplankton, and we examine the strengths, limitations, and distinctions of each algorithm in the context of the enhanced spatial and spectral resolution. Full article
(This article belongs to the Special Issue Remote Sensing of Phytoplankton)
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9636 KiB  
Article
Interannual Variation in Phytoplankton Primary Production at A Global Scale
by Cecile S. Rousseaux and Watson W. Gregg
Remote Sens. 2014, 6(1), 1-19; https://doi.org/10.3390/rs6010001 - 19 Dec 2013
Cited by 125 | Viewed by 15682
Abstract
We used the NASA Ocean Biogeochemical Model (NOBM) combined with remote sensing data via assimilation to evaluate the contribution of four phytoplankton groups to the total primary production. First, we assessed the contribution of each phytoplankton groups to the total primary production at [...] Read more.
We used the NASA Ocean Biogeochemical Model (NOBM) combined with remote sensing data via assimilation to evaluate the contribution of four phytoplankton groups to the total primary production. First, we assessed the contribution of each phytoplankton groups to the total primary production at a global scale for the period 1998–2011. Globally, diatoms contributed the most to the total phytoplankton production (~50%, the equivalent of ~20 PgC∙y−1). Coccolithophores and chlorophytes each contributed ~20% (~7 PgC∙y−1) of the total primary production and cyanobacteria represented about 10% (~4 PgC∙y−1) of the total primary production. Primary production by diatoms was highest in the high latitudes (>40°) and in major upwelling systems (Equatorial Pacific and Benguela system). We then assessed interannual variability of this group-specific primary production over the period 1998–2011. Globally the annual relative contribution of each phytoplankton groups to the total primary production varied by maximum 4% (1–2 PgC∙y−1). We assessed the effects of climate variability on group-specific primary production using global (i.e., Multivariate El Niño Index, MEI) and “regional” climate indices (e.g., Southern Annular Mode (SAM), Pacific Decadal Oscillation (PDO) and North Atlantic Oscillation (NAO)). Most interannual variability occurred in the Equatorial Pacific and was associated with climate variability as indicated by significant correlation (p < 0.05) between the MEI and the group-specific primary production from all groups except coccolithophores. In the Atlantic, climate variability as indicated by NAO was significantly correlated to the primary production of 2 out of the 4 groups in the North Central Atlantic (diatoms/cyanobacteria) and in the North Atlantic (chlorophytes and coccolithophores). We found that climate variability as indicated by SAM had only a limited effect on group-specific primary production in the Southern Ocean. These results provide a modeling and data assimilation perspective to phytoplankton partitioning of primary production and contribute to our understanding of the dynamics of the carbon cycle in the oceans at a global scale. Full article
(This article belongs to the Special Issue Remote Sensing of Phytoplankton)
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1917 KiB  
Article
Future Retrievals of Water Column Bio-Optical Properties using the Hyperspectral Infrared Imager (HyspIRI)
by Emmanuel Devred, Kevin R. Turpie, Wesley Moses, Victor V. Klemas, Tiffany Moisan, Marcel Babin, Gerardo Toro-Farmer, Marie-Hélène Forget and Young-Heon Jo
Remote Sens. 2013, 5(12), 6812-6837; https://doi.org/10.3390/rs5126812 - 06 Dec 2013
Cited by 58 | Viewed by 10574
Abstract
Interpretation of remote sensing reflectance from coastal waters at different wavelengths of light yields valuable information about water column constituents, which in turn, gives information on a variety of processes occurring in coastal waters, such as primary production, biogeochemical cycles, sediment transport, coastal [...] Read more.
Interpretation of remote sensing reflectance from coastal waters at different wavelengths of light yields valuable information about water column constituents, which in turn, gives information on a variety of processes occurring in coastal waters, such as primary production, biogeochemical cycles, sediment transport, coastal erosion, and harmful algal blooms. The Hyperspectral Infrared Imager (HyspIRI) is well suited to produce global, seasonal maps and specialized observations of coastal ecosystems and to improve our understanding of how phytoplankton communities are spatially distributed and structured, and how they function in coastal and inland waters. This paper draws from previously published studies on high-resolution, hyperspectral remote sensing of coastal and inland waters and provides an overview of how the HyspIRI mission could enable the retrieval of new aquatic biophysical products or improve the retrieval accuracy of existing satellite-derived products (e.g., inherent optical properties, phytoplankton functional types, pigment composition, chlorophyll-a concentration, etc.). The intent of this paper is to introduce the development of the HyspIRI mission to the coastal and inland remote sensing community and to provide information regarding several potential data products that were not originally part of the HyspIRI mission objectives but could be applicable to research related to coastal and inland waters. Further work toward quantitatively determining the extent and quality of these products, given the instrument and mission characteristics, is recommended. Full article
(This article belongs to the Special Issue Remote Sensing of Phytoplankton)
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2611 KiB  
Article
Time-Space Variability of Chlorophyll-a and Associated Physical Variables within the Region off Central-Southern Chile
by Carmen E. Morales, Samuel Hormazabal, Isabel Andrade and Marco A. Correa-Ramirez
Remote Sens. 2013, 5(11), 5550-5571; https://doi.org/10.3390/rs5115550 - 28 Oct 2013
Cited by 17 | Viewed by 7554
Abstract
Time-space fluctuations of chlorophyll-a (Chl-a) within the region off central-southern Chile (33–42°S), and their association with meteorological-oceanographic conditions, were analyzed using satellite time series data (2002–2012). The mean distribution of moderate values of Chl-a (~0.5 mg∙m−3) in the northern section (33–38°S) [...] Read more.
Time-space fluctuations of chlorophyll-a (Chl-a) within the region off central-southern Chile (33–42°S), and their association with meteorological-oceanographic conditions, were analyzed using satellite time series data (2002–2012). The mean distribution of moderate values of Chl-a (~0.5 mg∙m−3) in the northern section (33–38°S) extended out to ~200 km of the coast whereas they were restricted to a narrower band in the southern section (38–42°S). Mean wind stress and wind stress curl were upwelling favorable for most part of the year in the northern section whereas upwelling-downwelling periods were distinct in the southern section. The dominant frequency of Chl-a variability in the coastal zone and the coastal transition zone was annual, as it was for the rest of the variables, except in a transitional band between these zones and where a semi-permanent jet is located. At the annual frequency, the alongshore distribution of coastal Chl-a presented strong discontinuities, with minimum values around upwelling centers (~37 and 40°S) and higher values (> 2 mg∙m−3) in between. Also at the annual frequency, correlation analyses suggest that Ekman transport and Ekman pumping might act synchronously to extend the offshore distribution of the highest Chl-a values during the spring-summer period whereas mesoscale activity appears to contribute to Chl-a increases in the coastal transition zone. Sea surface temperature does not appear to be associated with the annual cycle of Chl-a in the coastal zone and in the coastal transition zone it might be linked to Chl-a variability through the effects of internal waves. Full article
(This article belongs to the Special Issue Remote Sensing of Phytoplankton)
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1663 KiB  
Article
A Performance Review of Reflectance Based Algorithms for Predicting Phycocyanin Concentrations in Inland Waters
by Igor Ogashawara, Deepak R. Mishra, Sachidananda Mishra, Marcelo P. Curtarelli and José L. Stech
Remote Sens. 2013, 5(10), 4774-4798; https://doi.org/10.3390/rs5104774 - 26 Sep 2013
Cited by 74 | Viewed by 9165
Abstract
We evaluated the accuracy and sensitivity of six previously published reflectance based algorithms to retrieve Phycocyanin (PC) concentration in inland waters. We used field radiometric and pigment data obtained from two study sites located in the United States and Brazil. All the algorithms [...] Read more.
We evaluated the accuracy and sensitivity of six previously published reflectance based algorithms to retrieve Phycocyanin (PC) concentration in inland waters. We used field radiometric and pigment data obtained from two study sites located in the United States and Brazil. All the algorithms targeted the PC absorption feature observed in the water reflectance spectra between 600 and 625 nm. We evaluated the influence of chlorophyll-a (chl-a) absorption on the performance of these algorithms in two contrasting environments with very low and very high cyanobacteria content. All algorithms performed well in low to moderate PC concentrations and showed signs of saturation or decreased sensitivity for high PC concentration with a nonlinear trend. MM09 was found to be the most accurate algorithm overall with a RMSE of 15.675%. We also evaluated the use of these algorithms with the simulated spectral bands of two hyperspectral space borne sensors including Hyperion and Compact High-Resolution Imaging Spectrometer (CHRIS) and a hyperspectral air borne sensor, Hyperspectral Infrared Imager (HyspIRI). Results showed that the sensitivity for chl-a of PC retrieval algorithms for Hyperion simulated data were less noticable than using the spectral bands of CHRIS; HyspIRI results show that SC00 could be used for this sensor with low chl-a influence. This review of reflectance based algorithms can be used to select the optimal approach in studies involving cyanobacteria monitoring through optical remote sensing techniques. Full article
(This article belongs to the Special Issue Remote Sensing of Phytoplankton)
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1380 KiB  
Article
Ultraviolet Fluorescence LiDAR (UFL) as a Measurement Tool for Water Quality Parameters in Turbid Lake Conditions
by Stephanie C.J. Palmer, Vadim V. Pelevin, Igor Goncharenko, Attila W. Kovács, András Zlinszky, Mátyás Présing, Hajnalka Horváth, Virginia Nicolás-Perea, Heiko Balzter and Viktor R. Tóth
Remote Sens. 2013, 5(9), 4405-4422; https://doi.org/10.3390/rs5094405 - 11 Sep 2013
Cited by 44 | Viewed by 9685
Abstract
Despite longstanding contributions to oceanography, similar use of fluorescence light detection and ranging (LiDAR) in lake settings is not routine. The potential for ship-mounted, multispectral Ultraviolet Fluorescence LiDAR (UFL) to provide rapid, high-resolution data in variably turbid and productive lake conditions are investigated [...] Read more.
Despite longstanding contributions to oceanography, similar use of fluorescence light detection and ranging (LiDAR) in lake settings is not routine. The potential for ship-mounted, multispectral Ultraviolet Fluorescence LiDAR (UFL) to provide rapid, high-resolution data in variably turbid and productive lake conditions are investigated here through a series of laboratory tank and field measurements carried out on Lake Balaton, Hungary. UFL data, calibrated empirically to a set of coinciding conventionally-analyzed samples, provide simultaneous estimates of three important parameters-chlorophyll a(chla), total suspended matter (TSM) and colored dissolved organic matter (CDOM). Successful UFL retrievals from both laboratory and field measurements were achieved for chla (0.01–378 mg∙m−3; R = 0.83–0.92), TSM (0.1–130 g∙m−3; R = 0.90–0.96) and CDOM (0.003–0.125 aCDOM(440); R = 0.80–0.97). Fluorescence emission at 685 nm is shown through tank measurements to display robust but distinct relationships with chla concentration for the two cultured algae species investigated (cyanobacteria, Cylindrospermopsis raciborskii, and chlorophyta, Scenedesmus armatus). The ratio between fluorescence emissions measured at 650 nm, related to the phycocyanin fluorescence maximum, to that at 685 nm is demonstrated to effectively distinguish these two species. Validation through both laboratory measurements and field measurements confirmed that site specific calibration is necessary. This study presents the first known assessment and application of ship-mounted fluorescence LiDAR in freshwater lake conditions and demonstrates the use of UFL in measuring important water quality parameters despite the more complicated hydro-optic conditions of inland waters. Full article
(This article belongs to the Special Issue Remote Sensing of Phytoplankton)
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5513 KiB  
Article
Characterizing the Absorption Properties for Remote Sensing of Three Small Optically-Diverse South African Reservoirs
by Mark William Matthews and Stewart Bernard
Remote Sens. 2013, 5(9), 4370-4404; https://doi.org/10.3390/rs5094370 - 09 Sep 2013
Cited by 46 | Viewed by 8090
Abstract
Characterizing the specific inherent optical properties (SIOPs) of water constituents is fundamental to remote sensing applications. Therefore, this paper presents the absorption properties of phytoplankton, gelbstoff and tripton for three small, optically-diverse South African inland waters. The three reservoirs, Hartbeespoort, Loskop and Theewaterskloof, [...] Read more.
Characterizing the specific inherent optical properties (SIOPs) of water constituents is fundamental to remote sensing applications. Therefore, this paper presents the absorption properties of phytoplankton, gelbstoff and tripton for three small, optically-diverse South African inland waters. The three reservoirs, Hartbeespoort, Loskop and Theewaterskloof, are challenging for remote sensing, due to differences in phytoplankton assemblage and the considerable range of constituent concentrations. Relationships between the absorption properties and biogeophysical parameters, chlorophyll-a (chl-a), TChl (chl-a plus phaeopigments), seston, minerals and tripton, are established. The value determined for the mass-specific tripton absorption coefficient at 442 nm, a(442), ranges from 0.024 to 0.263 m2·g1. The value of the TChl-specific phytoplankton absorption coefficient (a ) was strongly influenced by phytoplankton species, size, accessory pigmentation and biomass. a(440) ranged from 0.056 to 0.018 m2·mg1 in oligotrophic to hypertrophic waters. The positive relationship between cell size and trophic state observed in open ocean waters was violated by significant small cyanobacterial populations. The phycocyanin-specific phytoplankton absorption at 620 nm, a(620), was determined as 0.007 m2·g1 in a M. aeruginosa bloom. Chl-a was a better indicator of phytoplankton biomass than phycocyanin (PC) in surface scums, due to reduced accessory pigment production. Absorption budgets demonstrate that monospecific blooms of M. aeruginosa and C. hirundinella may be treated as “cultures”, removing some complexities for remote sensing applications. These results contribute toward a better understanding of IOPs and remote sensing applications in hypertrophic inland waters. However, the majority of the water is optically complex, requiring the usage of all the SIOPs derived here for remote sensing applications. The SIOPs may be used for developing remote sensing algorithms for the detection of biogeophysical parameters, including chl-a, suspended matter, tripton and gelbstoff, and in advanced remote sensing studies for phytoplankton type detection. Full article
(This article belongs to the Special Issue Remote Sensing of Phytoplankton)
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596 KiB  
Article
Subsurface Ocean Signals from an Orbiting Polarization Lidar
by James H. Churnside, Brandi J. McCarty and Xiaomei Lu
Remote Sens. 2013, 5(7), 3457-3475; https://doi.org/10.3390/rs5073457 - 19 Jul 2013
Cited by 40 | Viewed by 7786
Abstract
Detection of subsurface returns from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) on the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite were demonstrated. Despite the coarse range resolution of this aerosol lidar, evidence of subsurface scattering was observed as a delay [...] Read more.
Detection of subsurface returns from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) on the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite were demonstrated. Despite the coarse range resolution of this aerosol lidar, evidence of subsurface scattering was observed as a delay and broadening of the cross-polarized signal relative to the co-polarized signal in the three near-surface range bins. These two effects contributed to an increased depolarization at the nominal depth of 25 m. These features were all correlated with near-surface chlorophyll concentrations. An increase in the depolarization was also seen at a depth of 50 m under certain conditions, suggesting that chlorophyll concentration at that depth could be estimated if an appropriate retrieval technique can be developed. At greater depths, the signal is dominated by the temporal response of the detectors, which was approximated by an analytical expression. The depolarization caused by aerosols in the atmosphere was calculated and eliminated as a possible artifact. Full article
(This article belongs to the Special Issue Remote Sensing of Phytoplankton)
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