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    SICEv3.0 Southern Arctic Canada snow and ice broadband albedo and surface optical properties from Sentinel-3’s OLCI at 500 m resolution, Near Real Time (NRT)

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    SICE v3.0. 0.5 km Arctic land ice SSA, broadband albedo and spectral reflectance for 2017 to 2023 Timespan 1 April, to 31 September for each year 2017 to 2023 and is being updated starting ~April each year Description For Greenland, 0.5km daily data (Table 1) from the pySICE v2.1 algorithm, see Bahbah et al (2023) and Kokhanovsky et al (2023) for details. Broadband albedo "albedo_bb_planar_sw" is after Kokhanovsky et al (2019). "BBA_combination" is albedo_bb_planar_sw for albedo_bb_planar_sw values above 0.565 and is combined with an ampirical albedo for albedo_bb_planar_sw below or equal to 0.565, see Wehrlé et al (2021). Data format is GeoTiff in the EPSG:3413 - WGS 84 / NSIDC Sea Ice Polar Stereographic North. We suggest using rasterio to read the data files. The data are also available from https://thredds.geus.dk/ Data Format Data format is GeoTiff in the EPSG:3413 - WGS 84 / NSIDC Sea Ice Polar Stereographic North projection. &nbsp; Table 1, SICE v3.0 data, alphabetical name, description ANG, Angström parameter for atmospheric aerosol correction AOD_550, aerosol optical depth at 550 nm from CAMS, m units al, effective absorption length, mm units albedo_bb_spherical_sw, albedo under isotropic radiation albedo_bb_planar_sw, broadband albedo albedo_spectral_planar_NN, multispectral albedo_spectral_planar, where NN is a number for bands 01-21 diagnostic_retrieval, per pixel diagnostic info cloud_mask,SCDA cloud mask cloud_mask, SCDA cloud mask cv1, quality check 1 (see ATBD) cv2, quality check 2 (see ATBD) factor grain_diameter, effective optical snow grain diameter isnow, See Table 2 lat, decimal latitude lon, decimal longitude O3_SICE, OLCI total ozone retrieval corrected for ozone scattering after Kokhanovsky et al 2020 r0, reflectance of a semi-infinite non-absorbing snow layer r_TOA_NN, multispectral TOA reflectance, where NN is a number for bands 01-21 r_BRR_NN, multispectral botttom of atmosphere reflectance, where NN is a number for bands 01-21 snow_specific_surface_area, SSA saa, solar azimuth angle sza, solar zenith angle vaa, viewing azimuth angle vza, viewing zenith angle Table 2, Diagnostic codes Diagnostic Code, Description 0, clean snow 1, polluted snow 6, polluted snow for which r0 was calculated and not derived from observations 7, polluted snow of calculated spherical albedo in bands 1 and 2 greater than 0.98 reprocessed as clean snow 100, sza exceeding 75, no retrival albedo 102, TOA reflectance at band 21 less than 0.1, no retrieval 104, grain_diameter less than 0.1, no retrieval, potential cloud flag -N, impossible to solve polluted snow albedo equation at band N See also related information below Reference Publications Kokhanovsky, A., Vandecrux, B., Wehrlé, A., Danne, O., Brockmann, C., and Box, J. E.: An improved retrieval of snow and Ice properties using spaceborne OLCI/S-3 spectral reflectance measurements: Updated atmospheric correction and snow impurity load estimation, Remote Sens. (Basel), 15, 77, https://doi.org/10.3390/rs15010077, 2022 Kokhanovsky A.A., Lamare, M. and Rozanov, V. (2020) Retrieval of the total ozone over Antarctica using Sentinel-3 ocean and land colour instrument. Journal of Quantitative Spectroscopy and Radiative Transfer 251, 107045 https://doi.org/10.1016/j.jqsrt.2020.107045 Code Bahbah, R., Wehrlé, A., Mankoff, K., Vandecrux, B., and Box, J. E.: Sentinel-3 snow and ice optical properties retrieval (SICE) version 3.0, https://doi.org/10.5281/zenodo.10058790, 2023. How to gather and read the data see https://github.com/GEUS-SICE/SICE_gather and raise any issues there. Acknowledgements SICE has been supported by the following contracts to the European Space Agency (ESA): Dec. 2016 – Jan. 2019 SEOM S34Sci Land Study 1: Snow, ESRIN Contract 4000118926/16/I-NB Dec. 2018 – Jul. 2020 EO Science For Society, ESA/Contract 4000125043/18/I-NB – ESA/AO/1-9101/17/I-NB EO SCIENCE FOR SOCIETY, Pre-operational Sentinel-3 Snow and Ice Products (SICE) Jan. 2019 – Dec. 2020 ESA PRODEX, An operational service of new Sentinel-3 algorithms for climate monitoring of the Greenland Cryosphere within the CryoClim network May 2021 – June 2023 ESA PRODEX, Seamless Integration of Sentinel-3 Albedos in a Weather-modelling System (SISAWS) Feb 2022 – Oct. 2023 ESA EO Science For Society, Snow and ICE optical and physical properties from Sentinel-3 (SICE), ESA CCN contract 4000125043/18/I-NB and the ESA Network of Resources, Related Information description of variables, inputs and outputs https://github.com/GEUS-SICE/pySICE/tree/pySICEv2.1 https://snow.geus.dk/ Questions? contact Jason Box, [email protected] </html
    GEUS Dataverse

    SICEv3.0 Novaya Zemlya snow and ice broadband albedo and surface optical properties from Sentinel-3’s OLCI at 500 m resolution, Near Real Time (NRT)

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    SICE v3.0. 0.5 km Arctic land ice SSA, broadband albedo and spectral reflectance for 2017 to 2023 Timespan 1 April, to 31 September for each year 2017 to 2023 and is being updated starting ~April each year Description For Greenland, 0.5km daily data (Table 1) from the pySICE v2.1 algorithm, see Bahbah et al (2023) and Kokhanovsky et al (2023) for details. Broadband albedo "albedo_bb_planar_sw" is after Kokhanovsky et al (2019). "BBA_combination" is albedo_bb_planar_sw for albedo_bb_planar_sw values above 0.565 and is combined with an ampirical albedo for albedo_bb_planar_sw below or equal to 0.565, see Wehrlé et al (2021). Data format is GeoTiff in the EPSG:3413 - WGS 84 / NSIDC Sea Ice Polar Stereographic North. We suggest using rasterio to read the data files. The data are also available from https://thredds.geus.dk/ Data Format Data format is GeoTiff in the EPSG:3413 - WGS 84 / NSIDC Sea Ice Polar Stereographic North projection. &nbsp; Table 1, SICE v3.0 data, alphabetical name, description ANG, Angström parameter for atmospheric aerosol correction AOD_550, aerosol optical depth at 550 nm from CAMS, m units al, effective absorption length, mm units albedo_bb_spherical_sw, albedo under isotropic radiation albedo_bb_planar_sw, broadband albedo albedo_spectral_planar_NN, multispectral albedo_spectral_planar, where NN is a number for bands 01-21 diagnostic_retrieval, per pixel diagnostic info cloud_mask,SCDA cloud mask cloud_mask, SCDA cloud mask cv1, quality check 1 (see ATBD) cv2, quality check 2 (see ATBD) factor grain_diameter, effective optical snow grain diameter isnow, See Table 2 lat, decimal latitude lon, decimal longitude O3_SICE, OLCI total ozone retrieval corrected for ozone scattering after Kokhanovsky et al 2020 r0, reflectance of a semi-infinite non-absorbing snow layer r_TOA_NN, multispectral TOA reflectance, where NN is a number for bands 01-21 r_BRR_NN, multispectral botttom of atmosphere reflectance, where NN is a number for bands 01-21 snow_specific_surface_area, SSA saa, solar azimuth angle sza, solar zenith angle vaa, viewing azimuth angle vza, viewing zenith angle Table 2, Diagnostic codes Diagnostic Code, Description 0, clean snow 1, polluted snow 6, polluted snow for which r0 was calculated and not derived from observations 7, polluted snow of calculated spherical albedo in bands 1 and 2 greater than 0.98 reprocessed as clean snow 100, sza exceeding 75, no retrival albedo 102, TOA reflectance at band 21 less than 0.1, no retrieval 104, grain_diameter less than 0.1, no retrieval, potential cloud flag -N, impossible to solve polluted snow albedo equation at band N See also related information below Reference Publications Kokhanovsky, A., Vandecrux, B., Wehrlé, A., Danne, O., Brockmann, C., and Box, J. E.: An improved retrieval of snow and Ice properties using spaceborne OLCI/S-3 spectral reflectance measurements: Updated atmospheric correction and snow impurity load estimation, Remote Sens. (Basel), 15, 77, https://doi.org/10.3390/rs15010077, 2022 Kokhanovsky A.A., Lamare, M. and Rozanov, V. (2020) Retrieval of the total ozone over Antarctica using Sentinel-3 ocean and land colour instrument. Journal of Quantitative Spectroscopy and Radiative Transfer 251, 107045 https://doi.org/10.1016/j.jqsrt.2020.107045 Code Bahbah, R., Wehrlé, A., Mankoff, K., Vandecrux, B., and Box, J. E.: Sentinel-3 snow and ice optical properties retrieval (SICE) version 3.0, https://doi.org/10.5281/zenodo.10058790, 2023. How to gather and read the data see https://github.com/GEUS-SICE/SICE_gather and raise any issues there. Acknowledgements SICE has been supported by the following contracts to the European Space Agency (ESA): Dec. 2016 – Jan. 2019 SEOM S34Sci Land Study 1: Snow, ESRIN Contract 4000118926/16/I-NB Dec. 2018 – Jul. 2020 EO Science For Society, ESA/Contract 4000125043/18/I-NB – ESA/AO/1-9101/17/I-NB EO SCIENCE FOR SOCIETY, Pre-operational Sentinel-3 Snow and Ice Products (SICE) Jan. 2019 – Dec. 2020 ESA PRODEX, An operational service of new Sentinel-3 algorithms for climate monitoring of the Greenland Cryosphere within the CryoClim network May 2021 – June 2023 ESA PRODEX, Seamless Integration of Sentinel-3 Albedos in a Weather-modelling System (SISAWS) Feb 2022 – Oct. 2023 ESA EO Science For Society, Snow and ICE optical and physical properties from Sentinel-3 (SICE), ESA CCN contract 4000125043/18/I-NB and the ESA Network of Resources, Related Information description of variables, inputs and outputs https://github.com/GEUS-SICE/pySICE/tree/pySICEv2.1 https://snow.geus.dk/ Questions? contact Jason Box, [email protected] </html
    GEUS Dataverse

    SICEv3.0 Severnaya Zemlya snow and ice broadband albedo and surface optical properties from Sentinel-3’s OLCI at 500 m resolution, Near Real Time (NRT)

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    SICE v3.0. 0.5 km Arctic land ice SSA, broadband albedo and spectral reflectance for 2017 to 2023 Timespan 1 April, to 31 September for each year 2017 to 2023 and is being updated starting ~April each year Description For Greenland, 0.5km daily data (Table 1) from the pySICE v2.1 algorithm, see Bahbah et al (2023) and Kokhanovsky et al (2023) for details. Broadband albedo "albedo_bb_planar_sw" is after Kokhanovsky et al (2019). "BBA_combination" is albedo_bb_planar_sw for albedo_bb_planar_sw values above 0.565 and is combined with an ampirical albedo for albedo_bb_planar_sw below or equal to 0.565, see Wehrlé et al (2021). Data format is GeoTiff in the EPSG:3413 - WGS 84 / NSIDC Sea Ice Polar Stereographic North. We suggest using rasterio to read the data files. The data are also available from https://thredds.geus.dk/ Data Format Data format is GeoTiff in the EPSG:3413 - WGS 84 / NSIDC Sea Ice Polar Stereographic North projection. &nbsp; Table 1, SICE v3.0 data, alphabetical name, description ANG, Angström parameter for atmospheric aerosol correction AOD_550, aerosol optical depth at 550 nm from CAMS, m units al, effective absorption length, mm units albedo_bb_spherical_sw, albedo under isotropic radiation albedo_bb_planar_sw, broadband albedo albedo_spectral_planar_NN, multispectral albedo_spectral_planar, where NN is a number for bands 01-21 diagnostic_retrieval, per pixel diagnostic info cloud_mask,SCDA cloud mask cloud_mask, SCDA cloud mask cv1, quality check 1 (see ATBD) cv2, quality check 2 (see ATBD) factor grain_diameter, effective optical snow grain diameter isnow, See Table 2 lat, decimal latitude lon, decimal longitude O3_SICE, OLCI total ozone retrieval corrected for ozone scattering after Kokhanovsky et al 2020 r0, reflectance of a semi-infinite non-absorbing snow layer r_TOA_NN, multispectral TOA reflectance, where NN is a number for bands 01-21 r_BRR_NN, multispectral botttom of atmosphere reflectance, where NN is a number for bands 01-21 snow_specific_surface_area, SSA saa, solar azimuth angle sza, solar zenith angle vaa, viewing azimuth angle vza, viewing zenith angle Table 2, Diagnostic codes Diagnostic Code, Description 0, clean snow 1, polluted snow 6, polluted snow for which r0 was calculated and not derived from observations 7, polluted snow of calculated spherical albedo in bands 1 and 2 greater than 0.98 reprocessed as clean snow 100, sza exceeding 75, no retrival albedo 102, TOA reflectance at band 21 less than 0.1, no retrieval 104, grain_diameter less than 0.1, no retrieval, potential cloud flag -N, impossible to solve polluted snow albedo equation at band N See also related information below Reference Publications Kokhanovsky, A., Vandecrux, B., Wehrlé, A., Danne, O., Brockmann, C., and Box, J. E.: An improved retrieval of snow and Ice properties using spaceborne OLCI/S-3 spectral reflectance measurements: Updated atmospheric correction and snow impurity load estimation, Remote Sens. (Basel), 15, 77, https://doi.org/10.3390/rs15010077, 2022 Kokhanovsky A.A., Lamare, M. and Rozanov, V. (2020) Retrieval of the total ozone over Antarctica using Sentinel-3 ocean and land colour instrument. Journal of Quantitative Spectroscopy and Radiative Transfer 251, 107045 https://doi.org/10.1016/j.jqsrt.2020.107045 Code Bahbah, R., Wehrlé, A., Mankoff, K., Vandecrux, B., and Box, J. E.: Sentinel-3 snow and ice optical properties retrieval (SICE) version 3.0, https://doi.org/10.5281/zenodo.10058790, 2023. How to gather and read the data see https://github.com/GEUS-SICE/SICE_gather and raise any issues there. Acknowledgements SICE has been supported by the following contracts to the European Space Agency (ESA): Dec. 2016 – Jan. 2019 SEOM S34Sci Land Study 1: Snow, ESRIN Contract 4000118926/16/I-NB Dec. 2018 – Jul. 2020 EO Science For Society, ESA/Contract 4000125043/18/I-NB – ESA/AO/1-9101/17/I-NB EO SCIENCE FOR SOCIETY, Pre-operational Sentinel-3 Snow and Ice Products (SICE) Jan. 2019 – Dec. 2020 ESA PRODEX, An operational service of new Sentinel-3 algorithms for climate monitoring of the Greenland Cryosphere within the CryoClim network May 2021 – June 2023 ESA PRODEX, Seamless Integration of Sentinel-3 Albedos in a Weather-modelling System (SISAWS) Feb 2022 – Oct. 2023 ESA EO Science For Society, Snow and ICE optical and physical properties from Sentinel-3 (SICE), ESA CCN contract 4000125043/18/I-NB and the ESA Network of Resources, Related Information description of variables, inputs and outputs https://github.com/GEUS-SICE/pySICE/tree/pySICEv2.1 https://snow.geus.dk/ Questions? contact Jason Box, [email protected] </html
    GEUS Dataverse

    SICEv3.0 Iceland snow and ice broadband albedo and surface optical properties from Sentinel-3’s OLCI at 500 m resolution, Near Real Time (NRT)

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    SICE v3.0. 0.5 km Arctic land ice SSA, broadband albedo and spectral reflectance for 2017 to 2023 Timespan 1 April, to 31 September for each year 2017 to 2023 and is being updated starting ~April each year Description For Greenland, 0.5km daily data (Table 1) from the pySICE v2.1 algorithm, see Bahbah et al (2023) and Kokhanovsky et al (2023) for details. Broadband albedo "albedo_bb_planar_sw" is after Kokhanovsky et al (2019). "BBA_combination" is albedo_bb_planar_sw for albedo_bb_planar_sw values above 0.565 and is combined with an ampirical albedo for albedo_bb_planar_sw below or equal to 0.565, see Wehrlé et al (2021). Data format is GeoTiff in the EPSG:3413 - WGS 84 / NSIDC Sea Ice Polar Stereographic North. We suggest using rasterio to read the data files. The data are also available from https://thredds.geus.dk/ Data Format Data format is GeoTiff in the EPSG:3413 - WGS 84 / NSIDC Sea Ice Polar Stereographic North projection. &nbsp; Table 1, SICE v3.0 data, alphabetical name, description ANG, Angström parameter for atmospheric aerosol correction AOD_550, aerosol optical depth at 550 nm from CAMS, m units al, effective absorption length, mm units albedo_bb_spherical_sw, albedo under isotropic radiation albedo_bb_planar_sw, broadband albedo albedo_spectral_planar_NN, multispectral albedo_spectral_planar, where NN is a number for bands 01-21 diagnostic_retrieval, per pixel diagnostic info cloud_mask,SCDA cloud mask cloud_mask, SCDA cloud mask cv1, quality check 1 (see ATBD) cv2, quality check 2 (see ATBD) factor grain_diameter, effective optical snow grain diameter isnow, See Table 2 lat, decimal latitude lon, decimal longitude O3_SICE, OLCI total ozone retrieval corrected for ozone scattering after Kokhanovsky et al 2020 r0, reflectance of a semi-infinite non-absorbing snow layer r_TOA_NN, multispectral TOA reflectance, where NN is a number for bands 01-21 r_BRR_NN, multispectral botttom of atmosphere reflectance, where NN is a number for bands 01-21 snow_specific_surface_area, SSA saa, solar azimuth angle sza, solar zenith angle vaa, viewing azimuth angle vza, viewing zenith angle Table 2, Diagnostic codes Diagnostic Code, Description 0, clean snow 1, polluted snow 6, polluted snow for which r0 was calculated and not derived from observations 7, polluted snow of calculated spherical albedo in bands 1 and 2 greater than 0.98 reprocessed as clean snow 100, sza exceeding 75, no retrival albedo 102, TOA reflectance at band 21 less than 0.1, no retrieval 104, grain_diameter less than 0.1, no retrieval, potential cloud flag -N, impossible to solve polluted snow albedo equation at band N See also related information below Reference Publications Kokhanovsky, A., Vandecrux, B., Wehrlé, A., Danne, O., Brockmann, C., and Box, J. E.: An improved retrieval of snow and Ice properties using spaceborne OLCI/S-3 spectral reflectance measurements: Updated atmospheric correction and snow impurity load estimation, Remote Sens. (Basel), 15, 77, https://doi.org/10.3390/rs15010077, 2022 Kokhanovsky A.A., Lamare, M. and Rozanov, V. (2020) Retrieval of the total ozone over Antarctica using Sentinel-3 ocean and land colour instrument. Journal of Quantitative Spectroscopy and Radiative Transfer 251, 107045 https://doi.org/10.1016/j.jqsrt.2020.107045 Code Bahbah, R., Wehrlé, A., Mankoff, K., Vandecrux, B., and Box, J. E.: Sentinel-3 snow and ice optical properties retrieval (SICE) version 3.0, https://doi.org/10.5281/zenodo.10058790, 2023. How to gather and read the data see https://github.com/GEUS-SICE/SICE_gather and raise any issues there. Acknowledgements SICE has been supported by the following contracts to the European Space Agency (ESA): Dec. 2016 – Jan. 2019 SEOM S34Sci Land Study 1: Snow, ESRIN Contract 4000118926/16/I-NB Dec. 2018 – Jul. 2020 EO Science For Society, ESA/Contract 4000125043/18/I-NB – ESA/AO/1-9101/17/I-NB EO SCIENCE FOR SOCIETY, Pre-operational Sentinel-3 Snow and Ice Products (SICE) Jan. 2019 – Dec. 2020 ESA PRODEX, An operational service of new Sentinel-3 algorithms for climate monitoring of the Greenland Cryosphere within the CryoClim network May 2021 – June 2023 ESA PRODEX, Seamless Integration of Sentinel-3 Albedos in a Weather-modelling System (SISAWS) Feb 2022 – Oct. 2023 ESA EO Science For Society, Snow and ICE optical and physical properties from Sentinel-3 (SICE), ESA CCN contract 4000125043/18/I-NB and the ESA Network of Resources, Related Information description of variables, inputs and outputs https://github.com/GEUS-SICE/pySICE/tree/pySICEv2.1 https://snow.geus.dk/ Questions? contact Jason Box, [email protected] </html
    GEUS Dataverse

    Author Instructions

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    Cartographic Perspectives (E-Journal - North American Cartographic Information Society, NACIS)

    Going Beyond Counting First Authors in Author Co-citation Analysis

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    The present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
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    Variations on the Author

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    “Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
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    Kent Academic Repository

    Appropriate Similarity Measures for Author Cocitation Analysis

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    We provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
    Research Papers in Economics

    Dispelling the Myths Behind First-author Citation Counts

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    We conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more sophisticated methods
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    Author Index

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