Water Quality Retrieval from PRISMA Hyperspectral Images: First Experience in a Turbid Lake and Comparison with Sentinel-2
A new era of spaceborne hyperspectral imaging has just begun with the recent availability of data from PRISMA (PRecursore IperSpettrale della Missione Applicativa) launched by the Italian space agency (ASI). There has been pre-launch optimism that the wealth of spectral information offered by PRISMA...
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Published in | Remote sensing (Basel, Switzerland) Vol. 12; no. 23; p. 3984 |
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Main Authors | , , |
Format | Journal Article |
Language | English |
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01.12.2020
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Abstract | A new era of spaceborne hyperspectral imaging has just begun with the recent availability of data from PRISMA (PRecursore IperSpettrale della Missione Applicativa) launched by the Italian space agency (ASI). There has been pre-launch optimism that the wealth of spectral information offered by PRISMA can contribute to a variety of aquatic science and management applications. Here, we examine the potential of PRISMA level 2D images in retrieving standard water quality parameters, including total suspended matter (TSM), chlorophyll-a (Chl-a), and colored dissolved organic matter (CDOM) in a turbid lake (Lake Trasimeno, Italy). We perform consistency analyses among the aquatic products (remote sensing reflectance (Rrs) and constituents) derived from PRISMA and those from Sentinel-2. The consistency analyses are expanded to synthesized Sentinel-2 data as well. By spectral downsampling of the PRISMA images, we better isolate the impact of spectral resolution in retrieving the constituents. The retrieval of constituents from both PRISMA and Sentinel-2 images is built upon inverting the radiative transfer model implemented in the Water Color Simulator (WASI) processor. The inversion involves a parameter (gdd) to compensate for atmospheric and sun-glint artifacts. A strong agreement is indicated for the cross-sensor comparison of Rrs products at different wavelengths (average R ≈ 0.87). However, the Rrs of PRISMA at shorter wavelengths (<500 nm) is slightly overestimated with respect to Sentinel-2. This is in line with the estimates of gdd through the inversion that suggests an underestimated atmospheric path radiance of PRISMA level 2D products compared to the atmospherically corrected Sentinel-2 data. The results indicate the high potential of PRISMA level 2D imagery in mapping water quality parameters in Lake Trasimeno. The PRISMA-based retrievals agree well with those of Sentinel-2, particularly for TSM. |
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AbstractList | A new era of spaceborne hyperspectral imaging has just begun with the recent availability of data from PRISMA (PRecursore IperSpettrale della Missione Applicativa) launched by the Italian space agency (ASI). There has been pre-launch optimism that the wealth of spectral information offered by PRISMA can contribute to a variety of aquatic science and management applications. Here, we examine the potential of PRISMA level 2D images in retrieving standard water quality parameters, including total suspended matter (TSM), chlorophyll-a (Chl-a), and colored dissolved organic matter (CDOM) in a turbid lake (Lake Trasimeno, Italy). We perform consistency analyses among the aquatic products (remote sensing reflectance (Rrs) and constituents) derived from PRISMA and those from Sentinel-2. The consistency analyses are expanded to synthesized Sentinel-2 data as well. By spectral downsampling of the PRISMA images, we better isolate the impact of spectral resolution in retrieving the constituents. The retrieval of constituents from both PRISMA and Sentinel-2 images is built upon inverting the radiative transfer model implemented in the Water Color Simulator (WASI) processor. The inversion involves a parameter (gdd) to compensate for atmospheric and sun-glint artifacts. A strong agreement is indicated for the cross-sensor comparison of Rrs products at different wavelengths (average R ≈ 0.87). However, the Rrs of PRISMA at shorter wavelengths (<500 nm) is slightly overestimated with respect to Sentinel-2. This is in line with the estimates of gdd through the inversion that suggests an underestimated atmospheric path radiance of PRISMA level 2D products compared to the atmospherically corrected Sentinel-2 data. The results indicate the high potential of PRISMA level 2D imagery in mapping water quality parameters in Lake Trasimeno. The PRISMA-based retrievals agree well with those of Sentinel-2, particularly for TSM. A new era of spaceborne hyperspectral imaging has just begun with the recent availability of data from PRISMA (PRecursore IperSpettrale della Missione Applicativa) launched by the Italian space agency (ASI). There has been pre-launch optimism that the wealth of spectral information offered by PRISMA can contribute to a variety of aquatic science and management applications. Here, we examine the potential of PRISMA level 2D images in retrieving standard water quality parameters, including total suspended matter (TSM), chlorophyll-a (Chl-a), and colored dissolved organic matter (CDOM) in a turbid lake (Lake Trasimeno, Italy). We perform consistency analyses among the aquatic products (remote sensing reflectance (Rᵣₛ) and constituents) derived from PRISMA and those from Sentinel-2. The consistency analyses are expanded to synthesized Sentinel-2 data as well. By spectral downsampling of the PRISMA images, we better isolate the impact of spectral resolution in retrieving the constituents. The retrieval of constituents from both PRISMA and Sentinel-2 images is built upon inverting the radiative transfer model implemented in the Water Color Simulator (WASI) processor. The inversion involves a parameter (gdd) to compensate for atmospheric and sun-glint artifacts. A strong agreement is indicated for the cross-sensor comparison of Rᵣₛ products at different wavelengths (average R ≍ 0.87). However, the Rᵣₛ of PRISMA at shorter wavelengths (<500 nm) is slightly overestimated with respect to Sentinel-2. This is in line with the estimates of gdd through the inversion that suggests an underestimated atmospheric path radiance of PRISMA level 2D products compared to the atmospherically corrected Sentinel-2 data. The results indicate the high potential of PRISMA level 2D imagery in mapping water quality parameters in Lake Trasimeno. The PRISMA-based retrievals agree well with those of Sentinel-2, particularly for TSM. |
Author | Bruzzone, Lorenzo Niroumand-Jadidi, Milad Bovolo, Francesca |
Author_xml | – sequence: 1 givenname: Milad orcidid: 0000-0002-9432-3032 surname: Niroumand-Jadidi fullname: Niroumand-Jadidi, Milad – sequence: 2 givenname: Francesca surname: Bovolo fullname: Bovolo, Francesca – sequence: 3 givenname: Lorenzo orcidid: 0000-0002-6036-459X surname: Bruzzone fullname: Bruzzone, Lorenzo |
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Cites_doi | 10.3390/rs8080640 10.1016/j.rse.2015.02.007 10.1016/j.isprsjprs.2013.06.008 10.1007/s10712-018-9476-0 10.1016/j.pocean.2013.12.008 10.1016/j.rse.2004.11.009 10.3390/rs9101070 10.1016/j.marpolbul.2016.02.076 10.3390/rs8060497 10.3390/rs12142247 10.1016/j.rse.2015.05.014 10.1016/j.rse.2014.11.017 10.1016/j.rse.2007.12.014 10.1364/AO.32.003531 10.3390/w12010284 10.5194/isprsarchives-XLI-B8-361-2016 10.1016/B978-0-12-804644-9.00001-X 10.1364/OE.26.007404 10.1016/j.rse.2018.09.022 10.3390/rs5126812 10.1016/j.rse.2014.04.034 10.1109/TGRS.2019.2933251 10.1016/j.hal.2016.01.005 10.1364/AO.36.008710 10.3390/rs11010064 10.1016/j.rse.2019.03.018 10.1080/01431168108948342 10.1109/TGRS.2004.827260 10.1364/AO.51.001407 10.1016/j.rse.2020.112091 10.1029/2017WR022437 10.3390/rs70708830 10.3390/s19163609 10.3390/s20030742 10.1016/j.rse.2014.05.020 10.1080/01431160500104111 10.4319/lo.1990.35.8.1657 10.3390/rs11121469 10.3390/ijgi6120383 10.3390/rs8110941 10.3390/rs11232883 10.1016/j.watres.2011.11.068 10.3390/rs12152381 10.3390/w12010169 10.3390/rs10020157 10.1038/s41598-019-54453-y 10.3390/s16081298 10.1175/BAMS-D-18-0056.1 10.1080/01431161.2018.1506951 10.1016/j.rse.2006.12.017 10.1016/j.cageo.2004.03.005 10.3390/rs71114781 10.3390/rs10070982 10.1109/TGRS.2003.815999 10.1016/j.rse.2015.05.003 10.3390/rs11030262 10.1016/j.rse.2020.111900 10.3390/s20164553 10.1109/IGARSS.2018.8518384 10.1016/j.rse.2016.01.007 10.3390/jmse8020143 10.1016/j.rse.2018.07.014 10.1016/j.rse.2015.05.022 10.1016/j.rse.2008.12.003 10.14358/PERS.69.6.695 10.1016/j.cageo.2013.07.022 10.1364/OE.11.002873 10.1016/j.rse.2015.01.025 |
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References | ref_50 Vitti (ref_19) 2018; 218 ref_58 ref_13 ref_57 ref_12 ref_54 Guanter (ref_32) 2015; 7 ref_51 Bruzzone (ref_55) 2018; Volume 10789 Seegers (ref_79) 2018; 26 ref_18 Xi (ref_43) 2015; 7 Mishra (ref_10) 2019; 9 Barnsley (ref_34) 2004; 42 Moses (ref_41) 2012; 46 Ungar (ref_33) 2003; 41 Kutser (ref_15) 2015; 157 ref_61 ref_60 Gege (ref_59) 2014; 62 ref_25 ref_68 ref_23 ref_67 ref_66 ref_64 Werdell (ref_37) 2019; 100 Gege (ref_76) 2012; 51 Slonecker (ref_16) 2016; 107 Bovolo (ref_22) 2020; 251 ref_28 ref_27 Lyzenga (ref_20) 1981; 2 Gower (ref_6) 2014; 123 Vanhellemont (ref_63) 2015; 161 ref_70 Pu (ref_48) 2013; 83 Sheffield (ref_2) 2018; 54 Bovolo (ref_56) 2019; 57 Giardino (ref_62) 2015; 157 Harvey (ref_3) 2015; 158 Lee (ref_47) 2007; 1 ref_35 Palacios (ref_42) 2015; 167 ref_78 Kutser (ref_14) 2005; 94 Hu (ref_45) 2015; 167 ref_31 ref_75 ref_30 ref_74 Warren (ref_65) 2019; 225 Pope (ref_71) 1997; 36 Albert (ref_69) 2003; 11 Goetz (ref_29) 2009; 113 Devred (ref_36) 2013; 5 ref_80 Giardino (ref_46) 2007; 109 Stumpf (ref_11) 2016; 54 Schweizer (ref_17) 2005; 26 Wicaksono (ref_26) 2018; 39 Brando (ref_53) 2009; 113 Kou (ref_72) 1993; 32 Ritchie (ref_1) 2003; 69 Hedley (ref_21) 2018; 216 Morel (ref_73) 1974; 14 Olmanson (ref_24) 2016; 185 Gregg (ref_77) 1990; 35 Gege (ref_52) 2004; 30 ref_49 ref_9 Bell (ref_44) 2015; 167 ref_8 Kudela (ref_40) 2015; 167 ref_5 ref_4 ref_7 Vandermeulen (ref_39) 2020; 247 Giardino (ref_38) 2019; 40 |
References_xml | – ident: ref_78 – ident: ref_74 – ident: ref_7 doi: 10.3390/rs8080640 – volume: 161 start-page: 89 year: 2015 ident: ref_63 article-title: Advantages of high quality SWIR bands for ocean colour processing: Examples from Landsat-8 publication-title: Remote Sens. Environ. doi: 10.1016/j.rse.2015.02.007 – volume: 83 start-page: 116 year: 2013 ident: ref_48 article-title: A protocol for improving mapping and assessing of seagrass abundance along the West Central Coast of Florida using Landsat TM and EO-1 ALI/Hyperion images publication-title: ISPRS J. Photogramm. Remote Sens. doi: 10.1016/j.isprsjprs.2013.06.008 – ident: ref_51 – volume: 40 start-page: 401 year: 2019 ident: ref_38 article-title: Imaging Spectrometry of Inland and Coastal Waters: State of the Art, Achievements and Perspectives publication-title: Surv. Geophys. doi: 10.1007/s10712-018-9476-0 – ident: ref_68 – volume: 123 start-page: 123 year: 2014 ident: ref_6 article-title: A review of ocean color remote sensing methods and statistical techniques for the detection, mapping and analysis of phytoplankton blooms in coastal and open oceans publication-title: Prog. Oceanogr. doi: 10.1016/j.pocean.2013.12.008 – volume: 94 start-page: 535 year: 2005 ident: ref_14 article-title: Mapping lake CDOM by satellite remote sensing publication-title: Remote Sens. Environ. doi: 10.1016/j.rse.2004.11.009 – volume: Volume 10789 start-page: 23 year: 2018 ident: ref_55 article-title: A novel approach for bathymetry of shallow rivers based on spectral magnitude and shape predictors using stepwise regression publication-title: Proceedings of the Image and Signal Processing for Remote Sensing XXIV – ident: ref_23 doi: 10.3390/rs9101070 – volume: 107 start-page: 518 year: 2016 ident: ref_16 article-title: The new Landsat 8 potential for remote sensing of colored dissolved organic matter (CDOM) publication-title: Mar. Pollut. Bull. doi: 10.1016/j.marpolbul.2016.02.076 – ident: ref_8 doi: 10.3390/rs8060497 – volume: 1 start-page: 1 year: 2007 ident: ref_47 article-title: Water and bottom properties of a coastal environment derived from Hyperion data measured from the EO-1 spacecraft platform publication-title: J. Appl. Remote Sens. – ident: ref_31 doi: 10.3390/rs12142247 – volume: 167 start-page: 269 year: 2015 ident: ref_42 article-title: Remote sensing of phytoplankton functional types in the coastal ocean from the HyspIRI Preparatory Flight Campaign publication-title: Remote Sens. Environ. doi: 10.1016/j.rse.2015.05.014 – volume: 158 start-page: 417 year: 2015 ident: ref_3 article-title: Satellite-based water quality monitoring for improved spatial and temporal retrieval of chlorophyll-a in coastal waters publication-title: Remote Sens. Environ. doi: 10.1016/j.rse.2014.11.017 – volume: 113 start-page: S5 year: 2009 ident: ref_29 article-title: Three decades of hyperspectral remote sensing of the Earth: A personal view publication-title: Remote Sens. Environ. doi: 10.1016/j.rse.2007.12.014 – volume: 32 start-page: 3531 year: 1993 ident: ref_72 article-title: Refractive indices of water and ice in the 065- to 25-μm spectral range publication-title: Appl. Opt. doi: 10.1364/AO.32.003531 – ident: ref_9 doi: 10.3390/w12010284 – ident: ref_54 doi: 10.5194/isprsarchives-XLI-B8-361-2016 – ident: ref_60 doi: 10.1016/B978-0-12-804644-9.00001-X – volume: 26 start-page: 7404 year: 2018 ident: ref_79 article-title: Performance metrics for the assessment of satellite data products: An ocean color case study publication-title: Opt. Express doi: 10.1364/OE.26.007404 – volume: 218 start-page: 132 year: 2018 ident: ref_19 article-title: Multiple Optimal Depth Predictors Analysis (MODPA) for river bathymetry: Findings from spectroradiometry, simulations, and satellite imagery publication-title: Remote Sens. Environ. doi: 10.1016/j.rse.2018.09.022 – volume: 14 start-page: 1 year: 1974 ident: ref_73 article-title: Optical Properties of Pure Water and Pure Sea Water publication-title: Opt. Asp. Oceanogr. – volume: 5 start-page: 6812 year: 2013 ident: ref_36 article-title: Future Retrievals of Water Column Bio-Optical Properties using the Hyperspectral Infrared Imager (HyspIRI) publication-title: Remote Sens. doi: 10.3390/rs5126812 – volume: 157 start-page: 48 year: 2015 ident: ref_62 article-title: Airborne hyperspectral data to assess suspended particulate matter and aquatic vegetation in a shallow and turbid lake publication-title: Remote Sens. Environ. doi: 10.1016/j.rse.2014.04.034 – volume: 57 start-page: 10285 year: 2019 ident: ref_56 article-title: Novel Spectra-Derived Features for Empirical Retrieval of Water Quality Parameters: Demonstrations for OLI, MSI, and OLCI Sensors publication-title: IEEE Trans. Geosci. Remote Sens. doi: 10.1109/TGRS.2019.2933251 – volume: 54 start-page: 160 year: 2016 ident: ref_11 article-title: Challenges for mapping cyanotoxin patterns from remote sensing of cyanobacteria publication-title: Harmful Algae doi: 10.1016/j.hal.2016.01.005 – volume: 36 start-page: 8710 year: 1997 ident: ref_71 article-title: Absorption spectrum (380–700 nm) of pure water II Integrating cavity measurements publication-title: Appl. Opt. doi: 10.1364/AO.36.008710 – ident: ref_5 doi: 10.3390/rs11010064 – volume: 225 start-page: 267 year: 2019 ident: ref_65 article-title: Assessment of atmospheric correction algorithms for the Sentinel-2A MultiSpectral Imager over coastal and inland waters publication-title: Remote Sens. Environ. doi: 10.1016/j.rse.2019.03.018 – volume: 2 start-page: 71 year: 1981 ident: ref_20 article-title: Remote sensing of bottom reflectance and water attenuation parameters in shallow water using aircraft and Landsat data publication-title: Int. J. Remote Sens. doi: 10.1080/01431168108948342 – volume: 42 start-page: 1512 year: 2004 ident: ref_34 article-title: The PROBA/CHRIS mission: A low-cost smallsat for hyperspectral multiangle observations of the earth surface and atmosphere publication-title: IEEE Trans. Geosci. Remote Sens. doi: 10.1109/TGRS.2004.827260 – volume: 51 start-page: 1407 year: 2012 ident: ref_76 article-title: Analytic model for the direct and diffuse components of downwelling spectral irradiance in water publication-title: Appl. Opt. doi: 10.1364/AO.51.001407 – volume: 251 start-page: 112091 year: 2020 ident: ref_22 article-title: SMART-SDB: Sample-specific multiple band ratio technique for satellite-derived bathymetry publication-title: Remote Sens. Environ. doi: 10.1016/j.rse.2020.112091 – volume: 54 start-page: 9724 year: 2018 ident: ref_2 article-title: Satellite Remote Sensing for Water Resources Management: Potential for Supporting Sustainable Development in Data-Poor Regions publication-title: Water Resour. Res. doi: 10.1029/2017WR022437 – volume: 7 start-page: 8830 year: 2015 ident: ref_32 article-title: The EnMAP Spaceborne Imaging Spectroscopy Mission for Earth Observation publication-title: Remote Sens. doi: 10.3390/rs70708830 – ident: ref_66 doi: 10.3390/s19163609 – ident: ref_12 doi: 10.3390/s20030742 – volume: 157 start-page: 138 year: 2015 ident: ref_15 article-title: Estimating lake carbon fractions from remote sensing data publication-title: Remote Sens. Environ. doi: 10.1016/j.rse.2014.05.020 – volume: 26 start-page: 2657 year: 2005 ident: ref_17 article-title: Remote sensing characterization of benthic habitats and submerged vegetation biomass in Los Roques Archipelago National Park, Venezuela publication-title: Int. J. Remote Sens. doi: 10.1080/01431160500104111 – volume: 35 start-page: 1657 year: 1990 ident: ref_77 article-title: A simple spectral solar irradiance model for cloudless maritime atmospheres publication-title: Limnol. Oceanogr. doi: 10.4319/lo.1990.35.8.1657 – ident: ref_67 – ident: ref_64 doi: 10.3390/rs11121469 – ident: ref_57 doi: 10.3390/ijgi6120383 – ident: ref_61 doi: 10.3390/rs8110941 – ident: ref_4 doi: 10.3390/rs11232883 – volume: 46 start-page: 993 year: 2012 ident: ref_41 article-title: Estimation of chlorophyll-a concentration in turbid productive waters using airborne hyperspectral data publication-title: Water Res. doi: 10.1016/j.watres.2011.11.068 – ident: ref_28 doi: 10.3390/rs12152381 – ident: ref_49 doi: 10.3390/w12010169 – ident: ref_30 doi: 10.3390/rs10020157 – volume: 9 start-page: 1 year: 2019 ident: ref_10 article-title: Measurement of Cyanobacterial Bloom Magnitude using Satellite Remote Sensing publication-title: Sci. Rep. doi: 10.1038/s41598-019-54453-y – ident: ref_80 doi: 10.3390/s16081298 – volume: 100 start-page: 1775 year: 2019 ident: ref_37 article-title: The plankton, aerosol, cloud, ocean ecosystem mission status, science, advances publication-title: Bull. Am. Meteorol. Soc. doi: 10.1175/BAMS-D-18-0056.1 – volume: 39 start-page: 5739 year: 2018 ident: ref_26 article-title: Assessment of PlanetScope images for benthic habitat and seagrass species mapping in a complex optically shallow water environment publication-title: Int. J. Remote Sens. doi: 10.1080/01431161.2018.1506951 – ident: ref_75 – ident: ref_25 – volume: 109 start-page: 183 year: 2007 ident: ref_46 article-title: Assessment of water quality in Lake Garda (Italy) using Hyperion publication-title: Remote Sens. Environ. doi: 10.1016/j.rse.2006.12.017 – ident: ref_50 – volume: 30 start-page: 523 year: 2004 ident: ref_52 article-title: The water color simulator WASI: An integrating software tool for analysis and simulation of optical in situ spectra publication-title: Comput. Geosci. doi: 10.1016/j.cageo.2004.03.005 – volume: 7 start-page: 14781 year: 2015 ident: ref_43 article-title: Hyperspectral Differentiation of Phytoplankton Taxonomic Groups: A Comparison between Using Remote Sensing Reflectance and Absorption Spectra publication-title: Remote Sens. doi: 10.3390/rs71114781 – ident: ref_13 doi: 10.3390/rs10070982 – volume: 41 start-page: 1149 year: 2003 ident: ref_33 article-title: Overview of the Earth Observing One (EO-1) mission publication-title: IEEE Trans. Geosci. Remote Sens. doi: 10.1109/TGRS.2003.815999 – volume: 167 start-page: 218 year: 2015 ident: ref_44 article-title: Remote monitoring of giant kelp biomass and physiological condition: An evaluation of the potential for the Hyperspectral Infrared Imager (HyspIRI) mission publication-title: Remote Sens. Environ. doi: 10.1016/j.rse.2015.05.003 – ident: ref_18 doi: 10.3390/rs11030262 – volume: 247 start-page: 111900 year: 2020 ident: ref_39 article-title: 150 shades of green: Using the full spectrum of remote sensing reflectance to elucidate color shifts in the ocean publication-title: Remote Sens. Environ. doi: 10.1016/j.rse.2020.111900 – ident: ref_58 doi: 10.3390/s20164553 – ident: ref_35 doi: 10.1109/IGARSS.2018.8518384 – volume: 185 start-page: 119 year: 2016 ident: ref_24 article-title: Comparison of Landsat 8 and Landsat 7 for regional measurements of CDOM and water clarity in lakes publication-title: Remote Sens. Environ. doi: 10.1016/j.rse.2016.01.007 – ident: ref_70 – ident: ref_27 doi: 10.3390/jmse8020143 – volume: 216 start-page: 598 year: 2018 ident: ref_21 article-title: Coral reef applications of Sentinel-2: Coverage, characteristics, bathymetry and benthic mapping with comparison to Landsat 8 publication-title: Remote Sens. Environ. doi: 10.1016/j.rse.2018.07.014 – volume: 167 start-page: 229 year: 2015 ident: ref_45 article-title: Spectral and spatial requirements of remote measurements of pelagic Sargassum macroalgae publication-title: Remote Sens. Environ. doi: 10.1016/j.rse.2015.05.022 – volume: 113 start-page: 755 year: 2009 ident: ref_53 article-title: A physics based retrieval and quality assessment of bathymetry from suboptimal hyperspectral data publication-title: Remote Sens. Environ. doi: 10.1016/j.rse.2008.12.003 – volume: 69 start-page: 695 year: 2003 ident: ref_1 article-title: Remote Sensing Techniques to Assess Water Quality publication-title: Photogramm. Eng. Remote Sens. doi: 10.14358/PERS.69.6.695 – volume: 62 start-page: 208 year: 2014 ident: ref_59 article-title: WASI-2D: A software tool for regionally optimized analysis of imaging spectrometer data from deep and shallow waters publication-title: Comput. Geosci. doi: 10.1016/j.cageo.2013.07.022 – volume: 11 start-page: 2873 year: 2003 ident: ref_69 article-title: An analytical model for subsurface irradiance and remote sensing reflectance in deep and shallow case-2 waters publication-title: Opt. Express doi: 10.1364/OE.11.002873 – volume: 167 start-page: 196 year: 2015 ident: ref_40 article-title: Application of hyperspectral remote sensing to cyanobacterial blooms in inland waters publication-title: Remote Sens. Environ. doi: 10.1016/j.rse.2015.01.025 |
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