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  • 1
    facet.materialart.
    Unknown
    Database (DSM) of in situ POC and SPM and satellite Rrs (matchup) collected between 2002 and 2018 (2023)
    PANGAEA
    Details
    Publication Date: 2023-11-01
    Description: This data release includes in situ measurements collected between 2002 and 2012 during different study sites (Full description of the methods adopted for each measurements in the references). DSM measurements include 101 coincident in situ concentrations of Particulate Organic Carbon (POC) (μgL-1) and Suspended Particulate Matter (SPM) (mg/l) and remote-sensing reflectances (Rrs, sr-1) matchups for the sensor Meris. It addressed the objective: 1) Validate the POC/SPM ratio using satellite Rrs (matchup)
    Keywords: According to source references; bbp; Carbon, organic, particulate; cp; Cruise/expedition; DATE/TIME; Event label; Grande_campagne_Belgica2010; LATITUDE; LONGITUDE; Phabop_1; Phabop_2; Phabop_3; Phabop_4; Phabop_5; Phabop_6; Phabop_7; POC; Remote sensing reflectance at 412 nm; Remote sensing reflectance at 443 nm; Remote sensing reflectance at 490 nm; Remote sensing reflectance at 510 nm; Remote sensing reflectance at 560 nm; Remote sensing reflectance at 665 nm; Rrs; Somlit_Id:1_1; Somlit_Id:1_10; Somlit_Id:1_11; Somlit_Id:1_12; Somlit_Id:1_13; Somlit_Id:1_14; Somlit_Id:1_15; Somlit_Id:1_16; Somlit_Id:1_17; Somlit_Id:1_18; Somlit_Id:1_19; Somlit_Id:1_2; Somlit_Id:1_20; Somlit_Id:1_21; Somlit_Id:1_22; Somlit_Id:1_3; Somlit_Id:1_4; Somlit_Id:1_5; Somlit_Id:1_6; Somlit_Id:1_7; Somlit_Id:1_8; Somlit_Id:1_9; Somlit_Id:12_1; Somlit_Id:17_1; Somlit_Id:17_2; Somlit_Id:17_3; Somlit_Id:17_4; Somlit_Id:17_5; Somlit_Id:17_6; Somlit_Id:17_7; Somlit_Id:2_1; Somlit_Id:2_10; Somlit_Id:2_11; Somlit_Id:2_12; Somlit_Id:2_13; Somlit_Id:2_14; Somlit_Id:2_15; Somlit_Id:2_16; Somlit_Id:2_17; Somlit_Id:2_18; Somlit_Id:2_19; Somlit_Id:2_2; Somlit_Id:2_20; Somlit_Id:2_21; Somlit_Id:2_22; Somlit_Id:2_23; Somlit_Id:2_24; Somlit_Id:2_25; Somlit_Id:2_26; Somlit_Id:2_27; Somlit_Id:2_28; Somlit_Id:2_29; Somlit_Id:2_3; Somlit_Id:2_30; Somlit_Id:2_31; Somlit_Id:2_32; Somlit_Id:2_4; Somlit_Id:2_5; Somlit_Id:2_6; Somlit_Id:2_7; Somlit_Id:2_8; Somlit_Id:2_9; Somlit_Id:3_1; Somlit_Id:3_10; Somlit_Id:3_11; Somlit_Id:3_12; Somlit_Id:3_13; Somlit_Id:3_14; Somlit_Id:3_15; Somlit_Id:3_16; Somlit_Id:3_17; Somlit_Id:3_18; Somlit_Id:3_19; Somlit_Id:3_2; Somlit_Id:3_20; Somlit_Id:3_21; Somlit_Id:3_22; Somlit_Id:3_23; Somlit_Id:3_24; Somlit_Id:3_25; Somlit_Id:3_26; Somlit_Id:3_27; Somlit_Id:3_28; Somlit_Id:3_29; Somlit_Id:3_3; Somlit_Id:3_4; Somlit_Id:3_5; Somlit_Id:3_6; Somlit_Id:3_7; Somlit_Id:3_8; Somlit_Id:3_9; SPM; Suspended particulate matter; VITEL2011_1; VITEL2011_2
    Type: Dataset
    Format: text/tab-separated-values, 908 data points
    Location Call Number Expected Availability
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    DATA PANGAEA
  • 2
    facet.materialart.
    Unknown
    Database (DSM) of in situPOC, SPM and Rrs collected between 1997 and 2018 (2023)
    PANGAEA
    Details
    Publication Date: 2023-11-01
    Description: This data release includes in situ measurements collected between 2010 and 2014 during different cruise missions and study sites (Full description of the methods adopted for each measurements in the references). Measurements include concentrations of Particulate Organic Carbon (POC) (μgL-1) and Suspended Particulate Matter (SPM) (mg/l), remote-sensing reflectances (Rrs, sr-1), the particulate backscattering coefficient (bbp), and the particulate attenuation coefficient (cp) (m-1) at 650 nm. The first in situ database, named DS0, includes 300 coincident in situ POC, SPM, bbp, and cp measurements. DS1 includes 325 coincident in situ POC, SPM and Rrs. It addressed two main objectives: 1) Check the relationship between POC/SPM and bbp/cp 2) Develop a POC/SPM algorithm based on Rrs
    Keywords: Attenuation coefficient of particles, 650 nm; Backscattering coefficient/attenuation coefficient of particle ratio; Backscattering coefficient of particles, 650 nm; bbp; Belcolor_250; Belcolor_702N; Belcolor_MH3; Belcolor_MH4; Belcolor_MH5; Belcolor_MH5-B_profil; Belcolor_MH5-C_profil; Belcolor_MH5-F_profil; Belcolor_MH5-G_profil; Belcolor_MH5-H_profil; Belcolor_MH5-I_profil; Belcolor_MH5-J_profil; Belcolor_MH6; Belcolor_MOD-A_profil; Belcolor_MOD-B_profil; Belcolor_MOW-G; Belcolor_MOW-J; Belcolor_MOW-M; Belcolor_S01; Belcolor_W02; Belcolor_W03; Belcolor_W04; Belcolor_W04_profil; Belcolor_W05; Belcolor_W06_profil; Belcolor_W07; Belcolor_W08_profil; Belcolor_W10; Black_Carbon2012_BC2012_HL01; Black_Carbon2012_BC2012_HL02; Black_Carbon2012_BC2012_HL02-01; Black_Carbon2012_BC2012_HL02-02; Black_Carbon2012_BC2012_HL02-03; Black_Carbon2012_BC2012_HL02-04; Black_Carbon2012_BC2012_HL02-05; Black_Carbon2012_BC2012_HL02-06; Black_Carbon2012_BC2012_HL03; Black_Carbon2012_BC2012_HL04; Black_Carbon2012_BC2012_HL05; Black_Carbon2012_BC2012_HL06; Black_Carbon2012_BC2012_HL07; Black_Carbon2012_BC2012_HL08; Black_Carbon2012_BC2012_HL09; Black_Carbon2012_BC2012_HL10; Black_Carbon2012_BC2012_HL11; Black_Carbon2012_BC2012_HL12; Black_Carbon2012_BC2012_HL13; Black_Carbon2012_BC2012_HL13-01; Black_Carbon2012_BC2012_HL13-03; Black_Carbon2012_BC2012_HL13-04; Black_Carbon2012_BC2012_HL13-05; Black_Carbon2012_BC2012_HL13-06; Black_Carbon2012_BC2012_HL14; Black_Carbon2012_BC2012_HL14-01; Black_Carbon2012_BC2012_HL14-02; Black_Carbon2012_BC2012_HL14-03; Black_Carbon2012_BC2012_HL14-04; Black_Carbon2012_BC2012_HL14-05; Black_Carbon2012_BC2012_HL14-06; Black_Carbon2012_BC2012_HL15; Black_Carbon2012_BC2012_HL16; Black_Carbon2013_BC2013_HL02-01; Black_Carbon2013_BC2013_HL02-02; Black_Carbon2013_BC2013_HL02-03; Black_Carbon2013_BC2013_HL02-04; Black_Carbon2013_BC2013_HL02-05; Black_Carbon2013_BC2013_HL02-06; Black_Carbon2013_BC2013_HL13-01; Black_Carbon2013_BC2013_HL13-02; Black_Carbon2013_BC2013_HL13-03; Black_Carbon2013_BC2013_HL13-04; Black_Carbon2013_BC2013_HL13-05; Black_Carbon2013_BC2013_HL13-06; Black_Carbon2013_BC2013_HL14-01; Black_Carbon2013_BC2013_HL14-02; Black_Carbon2013_BC2013_HL14-04; Black_Carbon2013_BC2013_HL14-05; Black_Carbon2013_BC2013_HL14-06; Calculated; Carbon, organic, particulate; Carbon, organic, particulate/suspended particulate matter ratio; cp; Cruise/expedition; DATE/TIME; Dyphyma_DPM01; Dyphyma_DPM06; Dyphyma_DPM07; Dyphyma_DPM09; Dyphyma_DPM10; Dyphyma_DPM11; Dyphyma_DPM12; Dyphyma_DPM13; Dyphyma_DPM15; Dyphyma_DPM38; Dyphyma_DPM40; Dyphyma_DPM41; Dyphyma_DPM42; Dyphyma_DPM43; Dyphyma_DPM44; Dyphyma_DPM45; Dyphyma_DPM48; Dyphyma_DPM49; Dyphyma_DPM51; Dyphyma_DPM52; Dyphyma_DPM53; Event label; Grande_campagne_Belgica2010_ZBLR04; Grande_campagne_Belgica2010_ZBLR05; Grande_campagne_Belgica2010_ZBLR06; Grande_campagne_Belgica2010_ZBLR07; Grande_campagne_Belgica2010_ZBLR10; Grande_campagne_Belgica2010_ZBLR11; Grande_campagne_Belgica2010_ZBLR17; Grande_campagne_Belgica2010_ZBLR18; Grande_campagne_Belgica2010_ZBLR19; Grande_campagne_Belgica2010_ZBLR20; Grande_campagne_Belgica2010_ZBLR22; Grande_campagne_Belgica2010_ZBLR23; Grande_campagne_Belgica2010_ZBLR24; Grande_campagne_Belgica2010_ZBLR26; Grande_campagne_Belgica2010_ZBLR28; Grande_campagne_Belgica2010_ZBLR29; Grande_campagne_Belgica2010_ZBLR31; Grande_campagne_Belgica2010_ZBLR32; Grande_campagne_Belgica2010_ZBLR33; Grande_campagne_Belgica2010_ZBLR34; Grande_campagne_Belgica2010_ZBLR35; Guyane2012_G2012_A1; Guyane2012_G2012_B4; Guyane2012_G2012_S113; Guyane2012_G2012_S13; Guyane2012_G2012_S161b; Guyane2012_G2012_S166; Guyane2012_G2012_S167; Guyane2012_G2012_S173; Guyane2012_G2012_S174; Guyane2012_G2012_S29b; Guyane2012_G2012_S31b; Guyane2012_G2012_S8; In situ Instrument; ISI; LATITUDE; LONGITUDE; POC; Rrs; SPM; Station label; Suspended particulate matter; VITEL2011_A01; VITEL2011_A02; VITEL2011_A03; VITEL2011_A04; VITEL2011_A05; VITEL2011_A06; VITEL2011_A07; VITEL2011_A08; VITEL2011_A09; VITEL2011_A10; VITEL2011_A12; VITEL2011_A13; VITEL2011_A14; VITEL2011_A15; VITEL2011_A16; VITEL2011_A17; VITEL2011_A18; VITEL2011_A19; VITEL2011_A20; VITEL2011_A21; VITEL2011_A22; VITEL2011_A23; VITEL2011_D01; VITEL2011_D02; VITEL2011_D03; VITEL2011_D04; VITEL2011_D05; VITEL2011_D06; VITEL2011_D07; VITEL2011_DV01; VITEL2011_DV02; VITEL2011_DV03; VITEL2011_DV04; VITEL2011_DV09; VITEL2011_DV11; VITEL2011_DV12; VITEL2011_DV13; VITEL2011_DV14; VITEL2011_H06; VITEL2011_H10; VITEL2011_H11; VITEL2011_H13; VITEL2011_H15; VITEL2011_H23; VITEL2011_H28; VITEL2011_H32; VITEL2011_H33; VITEL2014_N01; VITEL2014_N02; VITEL2014_N03; VITEL2014_N04; VITEL2014_N05; VITEL2014_N11; VITEL2014_N12; VITEL2014_N13; VITEL2014_N14; VITEL2014_N15; VITEL2014_N21; VITEL2014_N22; VITEL2014_N23; VITEL2014_N24; VITEL2014_N25; VITEL2014_N31; VITEL2014_N32; VITEL2014_N33; VITEL2014_N42; VITEL2014_N51; VITEL2014_N52; VITEL2014_N53; VITEL2014_N54; VITEL2014_N62; VITEL2014_N63; VITEL2014_N71; VITEL2014_N72
    Type: Dataset
    Format: text/tab-separated-values, 2400 data points
    Location Call Number Expected Availability
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  • 3
    facet.materialart.
    Unknown
    Particle Size Distribution and Size-partitioned Phytoplankton Carbon Using a Two-Component Coated-Spheres Bio-optical Model: Monthly Global 4 km Imagery Based on the OC-CCI v5.0 Merged Ocean Color Satellite Data Set (2022)
    PANGAEA
    Details
    Publication Date: 2024-04-20
    Description: Monthly global 4km satellite products spanning September 1997 to December 2020. The data contains Particle Size Distribution (PSD) parameters of an assumed power-law PSD, absolute and fractional size-partitioned phytoplankton carbon and associated variables such as particulate organic carbon (POC) and Chlorophyll-a as derived from the PSD algorithm. The retrieval is based on a backscattering bio-optical model using two particle populations and coated spheres for phytoplankton inherent optical properties (IOP) modeling, and a retrieval using spectral angle mapping (SAM - where satellite spectra are classified using a comparison to a collection of modeled end-member spectra, by treating spectra as vectors and using their dot product). Partial uncertainties are given as standard deviation and are estimated using a combination of Monte Carlo simulations and analytical error propagation. An empirical tuning factor is given for attaining more realistic estimated model concentrations of POC and Chlorophyll-a. The tuning factor is multiplicative, to be applied in linear space. This tuning factor has not been applied to the monthly data, users can choose whether or not to apply it to absolute carbon and Chlorophyll-a concentrations. The factor does not affect retrievals of fractional contributions of phytoplankton size classes to total phytoplankton carbon. Monthly climatologies files and an overall climatology file are also provided, and in those files, both untuned (tuning factor not applied) and tuned (tuning factor applied) variables are provided, for user convenience. Input remote-sensing reflectance data are v5.0 of the Ocean Colour -Climate Change Initiative (OC-CCI) of the European Space Agency. The OC-CCI general reference is Sathyendranath et al. (2019; doi:10.3390/s19194285), and for v5.0 of the dataset, the reference is Sathyendranath et al. (2021; doi:10.5285/1dbe7a109c0244aaad713e078fd3059a). More detailed metadata, including geospatial metadata, are given in the netCDF files. Variable names should be self-explanatory. Quick browse images are provided as well. Coastlines in these quick browse images are from v2.3.7 of the GSHHS data set - see Wessel and Smith (1996) (doi:10.1029/96JB00104). Modeling and data processing was done in MATLAB ®.
    Keywords: Binary Object; Binary Object (File Size); Binary Object (MD5 Hash); Binary Object (Media Type); coated spheres; Comment; equivalent algal populations; Image; MATLAB ® - modeling and processing; Mie theory; OC-CCI; ocean color; ocean colour; Particle size distribution; Phytoplankton; phytoplankton carbon; phytoplankton functional types; phytoplankton size classes
    Type: Dataset
    Format: text/tab-separated-values, 880 data points
    Location Call Number Expected Availability
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  • 4
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    Unknown
    The LSST DESC data challenge 1: generation and analysis of synthetic images for next-generation surveys (2020)
    Oxford University Press
    Details
    Publication Date: 2020-07-13
    Description: Data Challenge 1 (DC1) is the first synthetic data set produced by the Rubin Observatory Legacy Survey of Space and Time (LSST) Dark Energy Science Collaboration (DESC). DC1 is designed to develop and validate data reduction and analysis and to study the impact of systematic effects that will affect the LSST data set. DC1 is comprised of r-band observations of 40 deg2 to 10 yr LSST depth. We present each stage of the simulation and analysis process: (a) generation, by synthesizing sources from cosmological N-body simulations in individual sensor-visit images with different observing conditions; (b) reduction using a development version of the LSST Science Pipelines; and (c) matching to the input cosmological catalogue for validation and testing. We verify that testable LSST requirements pass within the fidelity of DC1. We establish a selection procedure that produces a sufficiently clean extragalactic sample for clustering analyses and we discuss residual sample contamination, including contributions from inefficiency in star–galaxy separation and imperfect deblending. We compute the galaxy power spectrum on the simulated field and conclude that: (i) survey properties have an impact of 50 per cent of the statistical uncertainty for the scales and models used in DC1; (ii) a selection to eliminate artefacts in the catalogues is necessary to avoid biases in the measured clustering; and (iii) the presence of bright objects has a significant impact (2σ–6σ) in the estimated power spectra at small scales (ℓ 〉 1200), highlighting the impact of blending in studies at small angular scales in LSST.
    Print ISSN: 0035-8711
    Electronic ISSN: 1365-2966
    Topics: Physics
    Published by Oxford University Press on behalf of The Royal Astronomical Society.
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  • 5
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    Unknown
    Use of optical absorption indices to assess seasonal variability of dissolved organic matter in Amazon floodplain lakes (2020)
    Copernicus
    Details
    Publication Date: 2020-11-09
    Description: Given the importance of dissolved organic matter (DOM) in the carbon cycling of aquatic ecosystems, information on its seasonal variability is crucial. In this study we assess the use of optical absorption indices available in the literature based on in situ data to both characterize the seasonal variability of DOM in a highly complex environment and for application in large-scale studies using remote sensing data. The study area comprises four lakes located in the Mamirauá Sustainable Development Reserve (MSDR). Samples for the determination of colored dissolved organic matter (CDOM) and measurements of remote sensing reflectance (Rrs) were acquired in situ. The Rrs was used to simulate the response of the visible bands of the Sentinel-2 MultiSpectral Instrument (MSI), which was used in the proposed models. Differences between lakes were tested using the CDOM indices. The results highlight the role of the flood pulse in the DOM dynamics at the floodplain lakes. The validation results show that the use of the absorption coefficient of CDOM (aCDOM) as a proxy of the spectral slope between 275 and 295 nm (S275–295) during rising water is worthwhile, demonstrating its potential application to Sentinel-2 MSI imagery data for studying DOM dynamics on the large scale.
    Print ISSN: 1726-4170
    Electronic ISSN: 1726-4189
    Topics: Biology , Geosciences
    Published by Copernicus on behalf of European Geosciences Union.
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