6,025 research outputs found
Monthly Median, SICEv3.0 Greenland snow and ice broadband albedo and surface optical properties from Sentinel-3’s OLCI at 500 m resolution, 2017-2023
No full textMonthly Median of SICEv3.0 Greenland snow and ice broadband albedo and surface optical properties from Sentinel-3’s OLCI at 500 m resolution, 2017-2023
Near-optimal deterministic single-source distance sensitivity oracles
No full textGiven a graph with a distinguished source vertex s, the Single Source Replacement Paths (SSRP) problem is to compute and output, for any target vertex t and edge e, the length d(s, t, e) of a shortest path from s to t that avoids a failing edge e. A Single-Source Distance Sensitivity Oracle (Single-Source DSO) is a compact data structure that answers queries of the form (t, e) by returning the distance d(s, t, e). We show how to deterministically compress the output of the SSRP problem on n-vertex, m-edge graphs with integer edge weights in the range [1, M] into a Single-Source DSO that has size O(M1/2n3/2) and query time Oe(1). We prove that the space requirement is optimal (up to the word size). Our techniques can also handle vertex failures within the same bounds. Chechik and Cohen [SODA 2019] presented a combinatorial, randomized Oe(m√n + n2) time SSRP algorithm for undirected and unweighted graphs. We derandomize their algorithm with the same asymptotic running time and apply our compression to obtain a deterministic Single-Source DSO with Oe(m√n +n2) preprocessing time, O(n3/2) space, and Oe(1) query time. Our combinatorial Single-Source DSO has near-optimal space, preprocessing and query time for unweighted graphs, improving the preprocessing time by a √n -factor compared to previous results with o(n2) space. Grandoni and Vassilevska Williams [FOCS 2012, TALG 2020] gave an algebraic, randomized Oe(Mnω) time SSRP algorithm for (undirected and directed) graphs with integer edge weights in the range [1, M], where ω < 2.373 is the matrix multiplication exponent. We derandomize it for undirected graphs and apply our compression to obtain an algebraic Single-Source DSO with Oe(Mnω) preprocessing time, O(M1/2 n3/2) space, and Oe(1) query time. This improves the preprocessing time of algebraic Single-Source DSOs by polynomial factors compared to previous o(n2)-space oracles. We also present further improvements of our Single-Source DSOs. We show that the query time can be reduced to a constant at the cost of increasing the size of the oracle to O(M1/3 n5/3) and that all our oracles can be made path-reporting. On sparse graphs with m = O(nM5/74/−4ε) edges, for any constant ε > 0, we reduce the preprocessing to randomized Oe(M7/8 m1/2 n11/8) = O(n2−ε/2) time. To the best of our knowledge, this is the first truly subquadratic time algorithm for building Single-Source DSOs on sparse graphs
SICEv2.3.2 Southern Arctic Canada snow and ice broadband albedo and surface optical properties from Sentinel-3’s OLCI at 1000 m resolution, 2017-2023
No full textTimespan
1 April, to 31 September for each year 2017 to 2023 and is being updated starting ~April each year
Description
For multiple Arctic glaciated regions (Table 1), 1km daily data (Table 2) from the SICE v1.6 algorithm, see Wehrlé et al (2021) and Kokhanovsky et al (2019) 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. We suggest using rasterio to read the data files.
Table 1, SICE regions, sorted by decreasing area
region
area, sq km
area, sq km
Greenland
1,744,666
82.7
Arctic Canada North
100,691
4.8
Alaska and Yukon
96,909
4.6
Arctic Canada South
40,970
1.9
Norway
34,018
1.6
Svalbard
32,506
1.5
Novaya Zemlya
21,506
1.0
Severnaya Zemlya
15,842
0.8
Frans Josef Land
12,131
0.6
Iceland
11,489
0.5
Table 2, SICE v1 data
name
description
BBA_combination
broadband albedo based on albedo_bb_planar_sw for albedo_bb_planar_sw above 0.565 and based on empirical algorithm for albedo_bb_planar_sw less than 0.565
SCDA_final
cloud mask
albedo_bb_planar_sw
diagnostic_retrieval
per pixel diagnostic info
num_scenes
number of scenes
r_TOA_01
TOA reflectance, band 1
r_TOA_06
TOA reflectance, band 6
r_TOA_17
TOA reflectance, band 17
r_TOA_21
TOA reflectance, band 21
snow_specific_surface_area
SSA
Reference Publications
Kokhanovsky A., Lamare M., Danne O., Brockmann C., Dumont M., Picard G., Arnaud L., Favier V., Jourdain B., Le Meur E., Di Mauro B., Aoki T., Niwano M., Rozanov V., Korkin S., Kipfstuhl S., Freitag J., Hoerhold M., Zuhr A., Vladimirova D., Faber A-K., Steen-Larsen HC., Wahl S., Andersen JK., Vandecrux B., van As D., Mankoff KD., Kern M., Zege E., Box JE. 2019. Retrieval of Snow Properties from the Sentinel-3 Ocean and Land Colour Instrument. Remote Sensing 11:2280. https://doi.org/10.3390/rs11192280
Wehrlé A., Box JE., Niwano M., Anesio AM., Fausto RS. 2021. Greenland bare-ice albedo from PROMICE automatic weather station measurements and Sentinel-3 satellite observations. GEUS Bulletin 47. https://doi.org/10.34194/geusb.v47.5284
Related Publications
Kokhanovsky A., Lamare M., Di Mauro B., Picard G., Arnaud L., Dumont M., Tuzet F., Brockmann C., Box JE. 2018. On the reflectance spectroscopy of snow. The Cryosphere 12:2371–2382. https://doi.org/10.5194/tc-12-2371-2018
Related Information
https://snow.geus.dk/
Questions?
contact Jason Box, [email protected]
SICEv2.3.2 Svalbard snow and ice broadband albedo and surface optical properties from Sentinel-3’s OLCI at 1000 m resolution, 2017-2023
No full textTimespan
1 April, to 31 September for each year 2017 to 2023 and is being updated starting ~April each year
Description
For multiple Arctic glaciated regions (Table 1), 1km daily data (Table 2) from the SICE v1.6 algorithm, see Wehrlé et al (2021) and Kokhanovsky et al (2019) 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. We suggest using rasterio to read the data files.
Table 1, SICE regions, sorted by decreasing area
region
area, sq km
area, sq km
Greenland
1,744,666
82.7
Arctic Canada North
100,691
4.8
Alaska and Yukon
96,909
4.6
Arctic Canada South
40,970
1.9
Norway
34,018
1.6
Svalbard
32,506
1.5
Novaya Zemlya
21,506
1.0
Severnaya Zemlya
15,842
0.8
Frans Josef Land
12,131
0.6
Iceland
11,489
0.5
Table 2, SICE v1 data
name
description
BBA_combination
broadband albedo based on albedo_bb_planar_sw for albedo_bb_planar_sw above 0.565 and based on empirical algorithm for albedo_bb_planar_sw less than 0.565
SCDA_final
cloud mask
albedo_bb_planar_sw
diagnostic_retrieval
per pixel diagnostic info
num_scenes
number of scenes
r_TOA_01
TOA reflectance, band 1
r_TOA_06
TOA reflectance, band 6
r_TOA_17
TOA reflectance, band 17
r_TOA_21
TOA reflectance, band 21
snow_specific_surface_area
SSA
Reference Publications
Kokhanovsky A., Lamare M., Danne O., Brockmann C., Dumont M., Picard G., Arnaud L., Favier V., Jourdain B., Le Meur E., Di Mauro B., Aoki T., Niwano M., Rozanov V., Korkin S., Kipfstuhl S., Freitag J., Hoerhold M., Zuhr A., Vladimirova D., Faber A-K., Steen-Larsen HC., Wahl S., Andersen JK., Vandecrux B., van As D., Mankoff KD., Kern M., Zege E., Box JE. 2019. Retrieval of Snow Properties from the Sentinel-3 Ocean and Land Colour Instrument. Remote Sensing 11:2280. https://doi.org/10.3390/rs11192280
Wehrlé A., Box JE., Niwano M., Anesio AM., Fausto RS. 2021. Greenland bare-ice albedo from PROMICE automatic weather station measurements and Sentinel-3 satellite observations. GEUS Bulletin 47. https://doi.org/10.34194/geusb.v47.5284
Related Publications
Kokhanovsky A., Lamare M., Di Mauro B., Picard G., Arnaud L., Dumont M., Tuzet F., Brockmann C., Box JE. 2018. On the reflectance spectroscopy of snow. The Cryosphere 12:2371–2382. https://doi.org/10.5194/tc-12-2371-2018
Related Information
https://snow.geus.dk/
Questions?
contact Jason Box, [email protected]
SICEv2.3.2 Frans Josef Land snow and ice broadband albedo and surface optical properties from Sentinel-3’s OLCI at 1000 m resolution, 2017-2023
No full text
SICE v2.3.2. Multi-regional 1 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 multiple Arctic glaciated regions (Table 1), 1km daily data (Table 2) from the SICE v1.6 algorithm, see Wehrlé et al (2021) and Kokhanovsky et al (2019) 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. We suggest using rasterio to read the data files.
Table 1, SICE regions, sorted by decreasing area
region, area, sq km, percent of multi-regional area
Greenland, 1,744,666, 82.7
Arctic Canada North, 100,691, 4.8
Alaska and Yukon, 96,909, 4.6
Arctic Canada South, 40,970, 1.9
Norway, 34,018, 1.6
Svalbard, 32,506, 1.5
Novaya Zemlya, 21,506, 1.0
Severnaya Zemlya, 15,842, 0.8
Frans Josef Land, 12,131, 0.6
Iceland, 11,489, 0.5
Table 2, SICE v1 data
name, description
BBA_combination, broadband albedo based on albedo_bb_planar_sw for albedo_bb_planar_sw above 0.565 and based on empirical algorithm for albedo_bb_planar_sw less than 0.565
SCDA_final, cloud mask
albedo_bb_planar_sw,
diagnostic_retrieval, per pixel diagnostic info
num_scenes, number of scenes
r_TOA_01, TOA reflectance, band 1
r_TOA_06, TOA reflectance, band 6
r_TOA_17, TOA reflectance, band 17
r_TOA_21, TOA reflectance, band 21
snow_specific_surface_area, SSA
Reference Publications
Kokhanovsky A., Lamare M., Danne O., Brockmann C., Dumont M., Picard G., Arnaud L., Favier V., Jourdain B., Le Meur E., Di Mauro B., Aoki T., Niwano M., Rozanov V., Korkin S., Kipfstuhl S., Freitag J., Hoerhold M., Zuhr A., Vladimirova D., Faber A-K., Steen-Larsen HC., Wahl S., Andersen JK., Vandecrux B., van As D., Mankoff KD., Kern M., Zege E., Box JE. 2019. Retrieval of Snow Properties from the Sentinel-3 Ocean and Land Colour Instrument. Remote Sensing 11:2280. https://doi.org/10.3390/rs11192280
Kokhanovsky, A., Box, J., and Vandecrux, B.: Pre-operational Sentinel-3 snow and ice (SICE) products: Algorithm theoretical basis document, https://doi.org/10.20944/preprints202009.0529.v1, 23 September 2020.
Wehrlé A., Box JE., Niwano M., Anesio AM., Fausto RS. 2021. Greenland bare-ice albedo from PROMICE automatic weather station measurements and Sentinel-3 satellite observations. GEUS Bulletin 47. https://doi.org/10.34194/geusb.v47.5284
Code
Wehrlé, A., Mankoff, K., Vandecrux, B., and Box, J. E.: Sentinel-3 snow and ice optical properties retrieval (SICE) version 2.3.2, https://doi.org/10.5281/zenodo.10036416, 2023.
How to gather and read the data
see https://github.com/GEUS-SICE/SICE_gather and raise any issues there.
Related Publications
Kokhanovsky A., Lamare M., Di Mauro B., Picard G., Arnaud L., Dumont M., Tuzet F., Brockmann C., Box JE. 2018. On the reflectance spectroscopy of snow. The Cryosphere 12:2371–2382. https://doi.org/10.5194/tc-12-2371-2018
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
SICEv2.3.2 Beaufort snow and ice broadband albedo and surface optical properties from Sentinel-3’s OLCI at 1000 m resolution, 2017-2023
No full textSICE v2.3.2. Multi-regional 1 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 multiple Arctic glaciated regions (Table 1), 1km daily data (Table 2) from the SICE v1.6 algorithm, see Wehrlé et al (2021) and Kokhanovsky et al (2019) 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. We suggest using rasterio to read the data files.
Table 1, SICE regions, sorted by decreasing area
region, area, sq km, percent of multi-regional area
Greenland, 1,744,666, 82.7
Arctic Canada North, 100,691, 4.8
Alaska and Yukon, 96,909, 4.6
Arctic Canada South, 40,970, 1.9
Norway, 34,018, 1.6
Svalbard, 32,506, 1.5
Novaya Zemlya, 21,506, 1.0
Severnaya Zemlya, 15,842, 0.8
Frans Josef Land, 12,131, 0.6
Iceland, 11,489, 0.5
Table 2, SICE v2.3.2 Beaufort data
name, description
BBA_emp, broadband albedo based on albedo_bb_planar_sw for albedo_bb_planar_sw above 0.565 and based on empirical algorithm for albedo_bb_planar_sw less than 0.565
SCDA_final, cloud mask
albedo_bb_planar_sw,
albedo_spectral_planar_NN, multispectral albedo_spectral_planar, where
NN is a number for bands 01-21
albedo_spectral_spherical_NN, multispectral albedo_spectral_spherical,
where
NN is a number for bands 01-21
grain_diameter, effective optical snow grain diameter
diagnostic_retrieval, per pixel diagnostic info
num_scenes, number of scenes
li>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
OAA, observing azimuth angle
OZA observing zenith angle
O3, OLCI total ozone retrieval corrected for ozone scattering after Kokhanovsky et al 2020
Reference Publications
Kokhanovsky A., Lamare M., Danne O., Brockmann C., Dumont M., Picard G., Arnaud L., Favier V., Jourdain B., Le Meur E., Di Mauro B., Aoki T., Niwano M., Rozanov V., Korkin S., Kipfstuhl S., Freitag J., Hoerhold M., Zuhr A., Vladimirova D., Faber A-K., Steen-Larsen HC., Wahl S., Andersen JK., Vandecrux B., van As D., Mankoff KD., Kern M., Zege E., Box JE. 2019. Retrieval of Snow Properties from the Sentinel-3 Ocean and Land Colour Instrument. Remote Sensing 11:2280. https://doi.org/10.3390/rs11192280
Kokhanovsky, A., Box, J., and Vandecrux, B.: Pre-operational Sentinel-3 snow and ice (SICE) products: Algorithm theoretical basis document, https://doi.org/10.20944/preprints202009.0529.v1, 23 September 2020.
Wehrlé A., Box JE., Niwano M., Anesio AM., Fausto RS. 2021. Greenland bare-ice albedo from PROMICE automatic weather station measurements and Sentinel-3 satellite observations. GEUS Bulletin 47. https://doi.org/10.34194/geusb.v47.5284
Code
Wehrlé, A., Mankoff, K., Vandecrux, B., and Box, J. E.: Sentinel-3 snow and ice optical properties retrieval (SICE) version 2.3.2, https://doi.org/10.5281/zenodo.10036416, 2023.
How to gather and read the data
see https://github.com/GEUS-SICE/SICE_gather and raise any issues there.
Related Publications
Kokhanovsky A., Lamare M., Di Mauro B., Picard G., Arnaud L., Dumont M., Tuzet F., Brockmann C., Box JE. 2018. On the reflectance spectroscopy of snow. The Cryosphere 12:2371–2382. https://doi.org/10.5194/tc-12-2371-2018
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]
SICEv2.3.2 Northern Arctic Canada snow and ice broadband albedo and surface optical properties from Sentinel-3’s OLCI at 1000 m resolution, 2017-2023
No full text
SICE v2.3.2. Multi-regional 1 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 multiple Arctic glaciated regions (Table 1), 1km daily data (Table 2) from the SICE v1.6 algorithm, see Wehrlé et al (2021) and Kokhanovsky et al (2019) 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. We suggest using rasterio to read the data files.
Table 1, SICE regions, sorted by decreasing area
region, area, sq km, percent of multi-regional area
Greenland, 1,744,666, 82.7
Arctic Canada North, 100,691, 4.8
Alaska and Yukon, 96,909, 4.6
Arctic Canada South, 40,970, 1.9
Norway, 34,018, 1.6
Svalbard, 32,506, 1.5
Novaya Zemlya, 21,506, 1.0
Severnaya Zemlya, 15,842, 0.8
Frans Josef Land, 12,131, 0.6
Iceland, 11,489, 0.5
Table 2, SICE v1 data
name, description
BBA_combination, broadband albedo based on albedo_bb_planar_sw for albedo_bb_planar_sw above 0.565 and based on empirical algorithm for albedo_bb_planar_sw less than 0.565
SCDA_final, cloud mask
albedo_bb_planar_sw,
diagnostic_retrieval, per pixel diagnostic info
num_scenes, number of scenes
r_TOA_01, TOA reflectance, band 1
r_TOA_06, TOA reflectance, band 6
r_TOA_17, TOA reflectance, band 17
r_TOA_21, TOA reflectance, band 21
snow_specific_surface_area, SSA
Reference Publications
Kokhanovsky A., Lamare M., Danne O., Brockmann C., Dumont M., Picard G., Arnaud L., Favier V., Jourdain B., Le Meur E., Di Mauro B., Aoki T., Niwano M., Rozanov V., Korkin S., Kipfstuhl S., Freitag J., Hoerhold M., Zuhr A., Vladimirova D., Faber A-K., Steen-Larsen HC., Wahl S., Andersen JK., Vandecrux B., van As D., Mankoff KD., Kern M., Zege E., Box JE. 2019. Retrieval of Snow Properties from the Sentinel-3 Ocean and Land Colour Instrument. Remote Sensing 11:2280. https://doi.org/10.3390/rs11192280
Kokhanovsky, A., Box, J., and Vandecrux, B.: Pre-operational Sentinel-3 snow and ice (SICE) products: Algorithm theoretical basis document, https://doi.org/10.20944/preprints202009.0529.v1, 23 September 2020.
Wehrlé A., Box JE., Niwano M., Anesio AM., Fausto RS. 2021. Greenland bare-ice albedo from PROMICE automatic weather station measurements and Sentinel-3 satellite observations. GEUS Bulletin 47. https://doi.org/10.34194/geusb.v47.5284
Code
Wehrlé, A., Mankoff, K., Vandecrux, B., and Box, J. E.: Sentinel-3 snow and ice optical properties retrieval (SICE) version 2.3.2, https://doi.org/10.5281/zenodo.10036416, 2023.
How to gather and read the data
see https://github.com/GEUS-SICE/SICE_gather and raise any issues there.
Related Publications
Kokhanovsky A., Lamare M., Di Mauro B., Picard G., Arnaud L., Dumont M., Tuzet F., Brockmann C., Box JE. 2018. On the reflectance spectroscopy of snow. The Cryosphere 12:2371–2382. https://doi.org/10.5194/tc-12-2371-2018
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
sj-pdf-1-fao-10.1177_24730114231213369 – Supplemental material for Foot and Ankle Outcome Score (FAOS): Reference Values From a National Representative Sample
No full textSupplemental material, sj-pdf-1-fao-10.1177_24730114231213369 for Foot and Ankle Outcome Score (FAOS): Reference Values From a National Representative Sample by Peter Larsen, Michael S. Rathleff, Ewa M. Roos and Rasmus Elsoe in Foot & Ankle Orthopaedics</p
Utilization of pulp mill side streams as a part of cementitious binders
No full textAbstract
Different industries produce vast amounts of residue that can be used as raw materials in cementitious systems. In the context of this thesis, the most important systems include alkali-activated materials (AAMs) and supplementary cementitious materials (SCMs). This thesis concentrates on two pulp mill residues: recovery boiler fly ash (RBA) and green liquor dregs (GLD). The aim was to find out whether these residues would work as alternative alkali activators, since the challenge faced by AAMs is the high environmental footprint of commercial activators. Two RBAs were used as-received, while three batches of daily GLD samples were first combined to produce three GLDs, which were then thermally treated at moderately low temperatures (105 °C, 300 °C, 525 °C, or 650 °C).
Results proved that both RBAs and thermally treated GLDs activated blast furnace slag-based precursors. RBA, which is rich in sodium sulfate, showed similar or superior activating properties to commercial sodium sulfate, and common hydration products were formed during hydration. According to the results, a suitable dosage of RBA was 1–3 wt.% (Na2O eq.). In the GLD experiments, it was found that thermal pretreatment (Tmax 525 °C) modified the properties of GLD by removing most of the remaining organic carbon and increasing the amount of soluble calcium, which led to an increased pH. It was also found that, in addition to CaCO3, complex magnesium-rich phases including layered double hydroxide group phases (LDHs) occurred in GLDs.
The activating effect of thermally treated GLDs was enhanced by a higher treatment temperature. However, at 28 days, samples activated with GLD treated at 300 °C gained the highest strength. In the SCM experiments, 25% of cement was substituted with thermally treated GLDs and it was found that the addition of GLD decreased the 90-day strength by more than 15%. In both systems, AAM and SCM, the addition of GLD increased the viscosity and reduced the workability; however, both of these impacts were decreased by a higher pretreatment temperature. One interesting finding was that LDHs were also found in hydrated samples including GLDs treated at 525 °C or 650 °C, indicating the possible reconstruction of these phases after thermal treatment. To summarize, GLDs, earlier seen as non-reactive material, exhibited an activating effect on blast furnace slag. Original papers Rasmus, J., Ohenoja, K., Oksanen, J., Adesanya, E., Kinnunen, P., & Illikainen, M. (2023). Alternative alkali activator from pulp mill waste – One-part blast furnace slag mortar activated with recovery boiler fly ash. Journal of Building Engineering, 76, 107113. https://doi.org/10.1016/j.jobe.2023.107113 https://doi.org/10.1016/j.jobe.2023.107113 Self-archived version Rasmus, J., Adesanya, E., Silva Santos, H., Kilpimaa, K., & Illikainen, M. (2024). Effects of thermal treatment on the characteristics of pulp mill residue. Journal of Environmental Management, 351, 119793. https://doi.org/10.1016/j.jenvman.2023.119793 https://doi.org/10.1016/j.jenvman.2023.119793 Self-archived version Rasmus, J., Adesanya, E., & Kilpimaa, K. (2024). Utilization of pretreated green liquor dregs as an activator for blast furnace slag: Effect on hydration, phase assemblage, and rheology. Journal of Environmental Management, 370, 123021. https://doi.org/10.1016/j.jenvman.2024.123021 https://doi.org/10.1016/j.jenvman.2024.123021 Self-archived version Rasmus, J., Gouda, S., Adesanya, E., & Kilpimaa, K. (2024). Pretreated green liquor dregs as supplementary cementitious material – fresh and hardened state properties. Manuscript in preparation. Tiivistelmä
Eri teollisuudenalat tuottavat suuria määriä sellaisia sivuvirtoja, joita voidaan hyödyntää osana sementtimäisiä materiaaleja, joista tämän väitöskirjan kannalta keskeisimmät ovat alkaliaktivoidut materiaalit (AAM) ja sementtiä korvaavat materiaalit (SCM). Tässä työssä keskitytään selluteollisuuden tuottamien soodakattilan lentotuhkan (RBA) sekä viherlipeäsakan (sakka) tutkimiseen. Tavoitteena oli selvittää, toimivatko nämä vaihtoehtoisena alkaliaktivaattorina, sillä yleisesti AAM:ssa käytetyt kemikaalipohjaiset aktivaattorit nostavat AAM:n ympäristökuormaa. RBA:t käytettiin sellaisenaan. Sakkanäytteitä vastaanotettiin kolmessa erässä, ja näistä tehtiin kolme kokoomanäytettä, jotka lämpökäsiteltiin ennen käyttöä (105 °C, 300 °C, 525 °C tai 650 °C).
Tulosten mukaan RBA:t ja sakat aktivoivat masuunikuonapohjaista AAM:ää. Natriumsulfaattirikkaat RBA:t osoittivat vastaavia tai parempia aktivoivia ominaisuuksia kuin verrokkina toiminut kaupallinen natriumsulfaatti. Hydrataation aikana muodostui myös tyypillisiä hydrataatiotuotteita. Tulosten perusteella sopiva RBA:n annostus on 1–3 m-% (Na2O-ekv). Sakan lämpökäsittelyn (Tmax 525 °C) havaittiin muokkaavan materiaalin ominaisuuksia, muun muassa vähentämällä orgaanisen jäännöshiilen määrää sekä nostamalla liukoisen kalsiumin määrää. Liukoisen kalsiumin määrän noustessa myös pH kohosi. Kiteisen CaCO3:n lisäksi näytteistä havaittiin monimutkaisia magnesiumrikkaita faaseja, jotka sisälsivät ainakin hydrotalsiitin kaltaisia kerrostuneita kaksoishydroksideja (LDH).
Käsittelylämpötilan nostaminen 525 °C:seen paransi sakan aktivoivaa vaikutusta, joskin korkeimmat lujuudet 28 päivän iässä mitattiin, kun sakka oli käsitelty 300 °C:ssa. Kun lämpökäsiteltyä sakkaa kokeiltiin SCM:nä 25 % korvausosuudella, havaittiin, että 90 päivän lujuudet putosivat yli 15 %. Molemmissa systeemeissä (AAM ja SCM) sakan lisääminen nosti näytteen viskositeettia ja heikensi työstettävyyttä. Vaikutus kuitenkin pieneni, kun sakan käsittelylämpötilaa nostettiin. Yksi mielenkiintoisimmista tuloksista oli, että LDH-faaseja löydettiin myös niistä hydratoituneista näytteistä, joissa oli käytetty 525 tai 650 °C:ssa käsiteltyä sakkaa. Tämä viittaa siihen, että nämä faasit ovat uudelleenmuodostuneet lämpökäsittelyn jälkeen. Väitöskirjan tulokset osoittavat, että aiemmin inerttinä pidetyllä sakalla on aktivoivia ominaisuuksia. Osajulkaisut Rasmus, J., Ohenoja, K., Oksanen, J., Adesanya, E., Kinnunen, P., & Illikainen, M. (2023). Alternative alkali activator from pulp mill waste – One-part blast furnace slag mortar activated with recovery boiler fly ash. Journal of Building Engineering, 76, 107113. https://doi.org/10.1016/j.jobe.2023.107113 https://doi.org/10.1016/j.jobe.2023.107113 Rinnakkaistallennettu versio Rasmus, J., Adesanya, E., Silva Santos, H., Kilpimaa, K., & Illikainen, M. (2024). Effects of thermal treatment on the characteristics of pulp mill residue. Journal of Environmental Management, 351, 119793. https://doi.org/10.1016/j.jenvman.2023.119793 https://doi.org/10.1016/j.jenvman.2023.119793 Rinnakkaistallennettu versio Rasmus, J., Adesanya, E., & Kilpimaa, K. (2024). Utilization of pretreated green liquor dregs as an activator for blast furnace slag: Effect on hydration, phase assemblage, and rheology. Journal of Environmental Management, 370, 123021. https://doi.org/10.1016/j.jenvman.2024.123021 https://doi.org/10.1016/j.jenvman.2024.123021 Rinnakkaistallennettu versio Rasmus, J., Gouda, S., Adesanya, E., & Kilpimaa, K. (2024). Pretreated green liquor dregs as supplementary cementitious material – fresh and hardened state properties. Manuscript in preparation. Academic dissertation to be presented with the assent of the Doctoral Programme Committee of Technology and Natural Sciences of the University of Oulu for public defence in the Oulun Puhelin auditorium (L5), Linnanmaa, on 28 February 2025, at 12 noonAbstract
Different industries produce vast amounts of residue that can be used as raw materials in cementitious systems. In the context of this thesis, the most important systems include alkali-activated materials (AAMs) and supplementary cementitious materials (SCMs). This thesis concentrates on two pulp mill residues: recovery boiler fly ash (RBA) and green liquor dregs (GLD). The aim was to find out whether these residues would work as alternative alkali activators, since the challenge faced by AAMs is the high environmental footprint of commercial activators. Two RBAs were used as-received, while three batches of daily GLD samples were first combined to produce three GLDs, which were then thermally treated at moderately low temperatures (105 °C, 300 °C, 525 °C, or 650 °C).
Results proved that both RBAs and thermally treated GLDs activated blast furnace slag-based precursors. RBA, which is rich in sodium sulfate, showed similar or superior activating properties to commercial sodium sulfate, and common hydration products were formed during hydration. According to the results, a suitable dosage of RBA was 1–3 wt.% (Na2O eq.). In the GLD experiments, it was found that thermal pretreatment (Tmax 525 °C) modified the properties of GLD by removing most of the remaining organic carbon and increasing the amount of soluble calcium, which led to an increased pH. It was also found that, in addition to CaCO3, complex magnesium-rich phases including layered double hydroxide group phases (LDHs) occurred in GLDs.
The activating effect of thermally treated GLDs was enhanced by a higher treatment temperature. However, at 28 days, samples activated with GLD treated at 300 °C gained the highest strength. In the SCM experiments, 25% of cement was substituted with thermally treated GLDs and it was found that the addition of GLD decreased the 90-day strength by more than 15%. In both systems, AAM and SCM, the addition of GLD increased the viscosity and reduced the workability; however, both of these impacts were decreased by a higher pretreatment temperature. One interesting finding was that LDHs were also found in hydrated samples including GLDs treated at 525 °C or 650 °C, indicating the possible reconstruction of these phases after thermal treatment. To summarize, GLDs, earlier seen as non-reactive material, exhibited an activating effect on blast furnace slag.Tiivistelmä
Eri teollisuudenalat tuottavat suuria määriä sellaisia sivuvirtoja, joita voidaan hyödyntää osana sementtimäisiä materiaaleja, joista tämän väitöskirjan kannalta keskeisimmät ovat alkaliaktivoidut materiaalit (AAM) ja sementtiä korvaavat materiaalit (SCM). Tässä työssä keskitytään selluteollisuuden tuottamien soodakattilan lentotuhkan (RBA) sekä viherlipeäsakan (sakka) tutkimiseen. Tavoitteena oli selvittää, toimivatko nämä vaihtoehtoisena alkaliaktivaattorina, sillä yleisesti AAM:ssa käytetyt kemikaalipohjaiset aktivaattorit nostavat AAM:n ympäristökuormaa. RBA:t käytettiin sellaisenaan. Sakkanäytteitä vastaanotettiin kolmessa erässä, ja näistä tehtiin kolme kokoomanäytettä, jotka lämpökäsiteltiin ennen käyttöä (105 °C, 300 °C, 525 °C tai 650 °C).
Tulosten mukaan RBA:t ja sakat aktivoivat masuunikuonapohjaista AAM:ää. Natriumsulfaattirikkaat RBA:t osoittivat vastaavia tai parempia aktivoivia ominaisuuksia kuin verrokkina toiminut kaupallinen natriumsulfaatti. Hydrataation aikana muodostui myös tyypillisiä hydrataatiotuotteita. Tulosten perusteella sopiva RBA:n annostus on 1–3 m-% (Na2O-ekv). Sakan lämpökäsittelyn (Tmax 525 °C) havaittiin muokkaavan materiaalin ominaisuuksia, muun muassa vähentämällä orgaanisen jäännöshiilen määrää sekä nostamalla liukoisen kalsiumin määrää. Liukoisen kalsiumin määrän noustessa myös pH kohosi. Kiteisen CaCO3:n lisäksi näytteistä havaittiin monimutkaisia magnesiumrikkaita faaseja, jotka sisälsivät ainakin hydrotalsiitin kaltaisia kerrostuneita kaksoishydroksideja (LDH).
Käsittelylämpötilan nostaminen 525 °C:seen paransi sakan aktivoivaa vaikutusta, joskin korkeimmat lujuudet 28 päivän iässä mitattiin, kun sakka oli käsitelty 300 °C:ssa. Kun lämpökäsiteltyä sakkaa kokeiltiin SCM:nä 25 % korvausosuudella, havaittiin, että 90 päivän lujuudet putosivat yli 15 %. Molemmissa systeemeissä (AAM ja SCM) sakan lisääminen nosti näytteen viskositeettia ja heikensi työstettävyyttä. Vaikutus kuitenkin pieneni, kun sakan käsittelylämpötilaa nostettiin. Yksi mielenkiintoisimmista tuloksista oli, että LDH-faaseja löydettiin myös niistä hydratoituneista näytteistä, joissa oli käytetty 525 tai 650 °C:ssa käsiteltyä sakkaa. Tämä viittaa siihen, että nämä faasit ovat uudelleenmuodostuneet lämpökäsittelyn jälkeen. Väitöskirjan tulokset osoittavat, että aiemmin inerttinä pidetyllä sakalla on aktivoivia ominaisuuksia
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