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6 Research products, page 1 of 1

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  • Restricted
    Authors: 
    Bartsch, Annett; Nitze, Ingmar;
    Publisher: Zenodo
    Project: EC | Nunataryuk (773421)

    {"references": ["Nitze, I., Grosse, G., Jones, B., Arp, C., Ulrich, M., Fedorov, A., et al. (2017). Landsat-based trend analysis of lake dynamics across northern permafrost regions. Remote Sens. 9:640. doi: 10.3390/rs9070640", "Nitze, I., Grosse, G., Jones, B. M., Romanovsky, V. E., and Boike, J. (2018). Remote sensing quantifies widespread abundance of permafrost region disturbances across the Arctic and Subarctic. Nat. Commun. 9:5423. doi: 10.1038/s41467-018-07663-3", "Bartsch A, Ley S, Nitze I, Pointner G and Vieira G (2020) Feasibility Study for the Application of Synthetic Aperture Radar for Coastal Erosion Rate Quantification Across the Arctic. Front. Environ. Sci. 8:143. doi: 10.3389/fenvs.2020.00143"]} The dataset covers the Laptev Sea coast from 120 to 168 E and Alaska and Canadian Beaufort Sea Coast from 130 to 168 W. Probabilities of erosion and accretion (change of land to water and visa versa) have been derived from Landsat for the time period 1999–2014. A probability threshold of 50% was applied to separate erosion and accretion areas which are provided as polygons (shape files). Further information regarding the algorithm is available in Bartsch et al. (2020). The authors acknowledge financial support by the HORIZON2020 (BG-2017-1) project Nunataryuk, ESA's DUE GlobPermafrost project (Contract Number 4000116196/15/INB) and ESA's CCI+ Permafrost (4000123681/18/I-NB) project.

  • Restricted English
    Authors: 
    Bartsch, Annett; Pointner, Georg; Nitze, Ingmar;
    Publisher: Zenodo
    Project: EC | Nunataryuk (773421), EC | INFRANORTH (885646)

    {"references": ["Bartsch, A., Pointner, G., Ingeman-Nielsen, T. & Lu, W. (2020), 'Towards circumpolar mapping of Arctic settlements and infrastructure based on Sentinel-1 and Sentinel-2', Remote Sensing 12(15), 2368.", "Elvidge, C. D., Zhizhin, M., Ghosh, T., Hsu, F.-C. & Taneja, J. (2021), 'Annual time series of global VIIRS nighttime lights derived from monthly averages: 2012 to 2019',Remote Sensing13(5), 922", "Obu, J., Westermann, S., Barboux, C., Bartsch, A., Delaloye, R., Grosse, G., Heim, B., Hugelius,G., Irrgang, A., K\u00e4\u00e4b, A. M., Kroisleitner, C., Matthes, H., Nitze, I., Pellet, C., Seifert, F. M., Strozzi, T., Wegm\u00fcller, U., Wieczorek, M. & Wiesmann, A. (2021a), 'ESA Permafrost Climate Change Initiative (permafrost_cci): Permafrost active layer thickness for the Northern Hemisphere, v3.0'.", "Obu, J., Westermann, S., Barboux, C., Bartsch, A., Delaloye, R., Grosse, G., Heim, B., Hugelius, G.,Irrgang, A., K\u00e4\u00e4b, A. M., Kroisleitner, C., Matthes, H., Nitze, I., Pellet, C., Seifert, F. M.,Strozzi, T., Wegm \u00fcller, U., Wieczorek, M. & Wiesmann, A. (2021b), 'ESA Permafrost Climate Change Initiative (permafrost_cci): Permafrost extent for the Northern Hemisphere, v3.0'.", "Obu, J., Westermann, S., Barboux, C., Bartsch, A., Delaloye, R., Grosse, G., Heim, B., Hugelius,G., Irrgang, A., K\u00e4\u00e4b, A. M., Kroisleitner, C., Matthes, H., Nitze, I., Pellet, C., Seifert,F. M., Strozzi, T., Wegm\u00fcller, U., Wieczorek, M. & Wiesmann, A. (2021c), 'ESA Permafrost Climate Change Initiative (permafrost_cci): Permafrost ground temperature for the Northern Hemisphere, v3.0", "Wang, S., Ramage, J., Bartsch, A. & Efimova, A. (2021), 'Population in the arctic circumpolar permafrost region at settlement level', Zenodo. 10.5281/ZENODO.45296", "Martha K. Raynolds, Donald A. Walker, Andrew Balser, Christian Bay, Mitch Campbell, Mikhail M. Cherosov, Fred J.A. Dani\u00ebls, Pernille Bronken Eidesen, Ksenia A. Ermokhina, Gerald V. Frost, Birgit Jedrzejek, M. Torre Jorgenson, Blair E. Kennedy, Sergei S. Kholod, Igor A. Lavrinenko, Olga V. Lavrinenko, Borg\u00fe\u00f3r Magn\u00fasson, Nadezhda V. Matveyeva, Sigmar Met\u00fasalemsson, Lennart Nilsen, Ian Olthof, Igor N. Pospelov, Elena B. Pospelova, Darren Pouliot, Vladimir Razzhivin, Gabriela Schaepman-Strub, Jozef \u0160ib\u00edk, Mikhail Yu. Telyatnikov, Elena Troeva (2019): 'A raster version of the Circumpolar Arctic Vegetation Map (CAVM)', Remote Sensing of Environment, Volume 232, 111297.", "Nitze, I., Grosse, G., Jones, B. M., Romanovsky, V. E. & Boike, J. (2018), 'Remote sensing quantifies widespread abundance of permafrost region disturbances across the Arctic and Subarctic', Nature Communications 9(1).", "Bartsch et al. (2021), Expanding infrastructure and growing anthropogenic impacts along Arctic coasts, ERL\u00a0https://iopscience.iop.org/article/10.1088/1748-9326/ac3176/meta"]} The SACHI (Sentinel-1/2 derived Arctic Coastal Human Impact) dataset has been primarily developed as part of the HORIZON2020 project Nunataryuk by b.geos (www.bgeos.com). It covers a 100km buffer from the Arctic Coast (land area), for areas with permafrost near the coast. It is based on Sentinel-1 and Sentinel-2 data from 2016-2020 using the algorithms described in Bartsch et al. (2020). It is a supplement to Bartsch et al. (2021 - https://iopscience.iop.org/article/10.1088/1748-9326/ac3176/meta). It consists of three shape files: 1) SACHI.shp - all identified objects with infrastructure/impact classes and auxiliary information (permafrost status and trends, nightlight radiance, vegetation zone, Normalized Difference Vegetation Index trends from Landsat, settlements names) 2) SACHI_100km_buffer - Buffer polygon (analyses extent) 3) SACHI_granules_acquisition_dates - processed Sentinel-2 granule extent polygons with dates of all used input data SACHI class values: 1=linear transport infrastructure, 2=buildings (and other constructions such as bridges), 3=other impacted area (includes gravel pads, mining sites) See README.TXT for description of data fields. Further support was received by ESA CCI+ Permafrost, HGF AI-CORE, and NSF Permafrost DiscoveryGateway. The processing scheme was developed on a highly performant virtual machine (VM) provided by the Copernicus Research and User Support (RUS). Results are based on modified Copernicus data from 2016 to 2020.

  • Restricted
    Authors: 
    Kristine Korzow Richter; Angela Maccarinelli; Jen Harland; Zoe Bottomley; Kenneth Ritchie; Matthew J Collins;
    Publisher: Zenodo
    Project: EC | MAFRI (660337)

    Images from all 46 archaeological test bones associated with the archaeological test set MALDI-TOF data. MALDI-TOF data from both reference and test sets. Reference sets are labeled with their species identification. Each set consists of .tex files. Files in the same folder are technical replicates of the same extract.

  • Restricted
    Authors: 
    Capet Arthur; Vandenbulcke Luc; Grégoire Marilaure;
    Publisher: Zenodo
    Project: EC | PERSEUS (287600)

    Data files provided in support of 'Global warming triggered a reduced and intermittent ventilation regime in the Black Sea', by Capet et al, 2018. Black_Sea_CIL_Cold_Content_Annual.nc contains the spatial and annual averages of the Black Sea cold intermediate layer cold content, as defined in the above reference, and derived from multiple in-situ and modelling sources, for the period (1955-2017). Black_Sea_CIL_Cold_Content_Weekly.nc contains the spatial and weekly averages of the Black Sea cold intermediate layer cold content, as defined in the above reference, and derived from the GHER3D model, for the period (1981-2017).

  • Restricted English
    Authors: 
    Pafilis, Evangelos; Pavlopoulos, Georgios; Satagopam, Venkata; Papanikolaou, Nikolas; Horn, Heiko; Arvanitidis, Christos; Jensen, Lars Juhl; Schneider, Reinhard; Iliopoulos, Ioannis;
    Country: Luxembourg
    Project: EC | MARBIGEN (264089)

    Retrieving all of the necessary information from databases about bioentities mentioned in an article is not a trivial or an easy task. Following the daily literature about a specific biological topic and collecting all the necessary information about the bioentities mentioned in the literature manually is tedious and time consuming. OnTheFly 2.0 is a web application mainly designed for non-computer experts which aims to automate data collection and knowledge extraction from biological literature in a user friendly and efficient way. OnTheFly 2.0 is able to extract bioentities from individual articles such as text, Microsoft Word, Excel and PDF files. With a simple drag-and-drop motion, the text of a document is extensively parsed for bioentities such as protein/gene names and chemical compound names. Utilizing high quality data integration platforms, OnTheFly allows the generation of informative summaries, interaction networks and at-a-glance popup windows containing knowledge related to the bioentities found in documents. OnTheFly 2.0 provides a concise application to automate the extraction of bioentities hidden in various documents and is offered as a web based application.

  • Other research product . Other ORP type . 2012
    Restricted English
    Authors: 
    Martinelli M.; Moroni D.; Salvetti O.;
    Country: Italy
    Project: EC | ARGOMARINE (234096)

    Based on the idea that contribution of volunteers might play a fundamental role in monitoring and protecting the environment, CNR-ISTI designed and developed a mobile application in order to allow people to timely report oil spills. By downloading the FREE app "ARGO Sentinel" volunteers are helping to monitor the health of our seas and the scientific research by demonstrating that the use of this new technology could be really important to combat pollution. Moreover this experiment suggests that this kind of technology can be applied in many other fields. Whoever at sea sights pollution by oil or hydrocarbons is now able to immediately report the event to the Laboratory of Signals and Images SI-LAB (si.isti.cnr.it) of the Institute of Science and Information Technologies of the Italian National Research Council (CNR-ISTI) in Pisa, allowing the realization of a detailed map of the health of our seas. This information is recorded in the Marine Information System (MIS) produced by CNR, able to collect geotagged data relating to critical and health issues of the sea from various sources (satellites, optical sensors, electronic noses, autonomous underwater vehicles systems) and integrate and generate predictive models to assist the authorities in the management of emergencies at sea. The application, distributed in Italian, English and Greek languages, for smartphones equipped of GPS is an easy to use tool designed for anyone, that for any reason, sail the seas. It allows you to send reports of suspected spills to the CNR specifying the precise point, severity and a description of the spill.

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Advanced search in Research products
Research products
arrow_drop_down
Searching FieldsTerms
Any field
arrow_drop_down
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arrow_drop_down
Include:
The following results are related to European Marine Science. Are you interested to view more results? Visit OpenAIRE - Explore.
6 Research products, page 1 of 1
  • Restricted
    Authors: 
    Bartsch, Annett; Nitze, Ingmar;
    Publisher: Zenodo
    Project: EC | Nunataryuk (773421)

    {"references": ["Nitze, I., Grosse, G., Jones, B., Arp, C., Ulrich, M., Fedorov, A., et al. (2017). Landsat-based trend analysis of lake dynamics across northern permafrost regions. Remote Sens. 9:640. doi: 10.3390/rs9070640", "Nitze, I., Grosse, G., Jones, B. M., Romanovsky, V. E., and Boike, J. (2018). Remote sensing quantifies widespread abundance of permafrost region disturbances across the Arctic and Subarctic. Nat. Commun. 9:5423. doi: 10.1038/s41467-018-07663-3", "Bartsch A, Ley S, Nitze I, Pointner G and Vieira G (2020) Feasibility Study for the Application of Synthetic Aperture Radar for Coastal Erosion Rate Quantification Across the Arctic. Front. Environ. Sci. 8:143. doi: 10.3389/fenvs.2020.00143"]} The dataset covers the Laptev Sea coast from 120 to 168 E and Alaska and Canadian Beaufort Sea Coast from 130 to 168 W. Probabilities of erosion and accretion (change of land to water and visa versa) have been derived from Landsat for the time period 1999–2014. A probability threshold of 50% was applied to separate erosion and accretion areas which are provided as polygons (shape files). Further information regarding the algorithm is available in Bartsch et al. (2020). The authors acknowledge financial support by the HORIZON2020 (BG-2017-1) project Nunataryuk, ESA's DUE GlobPermafrost project (Contract Number 4000116196/15/INB) and ESA's CCI+ Permafrost (4000123681/18/I-NB) project.

  • Restricted English
    Authors: 
    Bartsch, Annett; Pointner, Georg; Nitze, Ingmar;
    Publisher: Zenodo
    Project: EC | Nunataryuk (773421), EC | INFRANORTH (885646)

    {"references": ["Bartsch, A., Pointner, G., Ingeman-Nielsen, T. & Lu, W. (2020), 'Towards circumpolar mapping of Arctic settlements and infrastructure based on Sentinel-1 and Sentinel-2', Remote Sensing 12(15), 2368.", "Elvidge, C. D., Zhizhin, M., Ghosh, T., Hsu, F.-C. & Taneja, J. (2021), 'Annual time series of global VIIRS nighttime lights derived from monthly averages: 2012 to 2019',Remote Sensing13(5), 922", "Obu, J., Westermann, S., Barboux, C., Bartsch, A., Delaloye, R., Grosse, G., Heim, B., Hugelius,G., Irrgang, A., K\u00e4\u00e4b, A. M., Kroisleitner, C., Matthes, H., Nitze, I., Pellet, C., Seifert, F. M., Strozzi, T., Wegm\u00fcller, U., Wieczorek, M. & Wiesmann, A. (2021a), 'ESA Permafrost Climate Change Initiative (permafrost_cci): Permafrost active layer thickness for the Northern Hemisphere, v3.0'.", "Obu, J., Westermann, S., Barboux, C., Bartsch, A., Delaloye, R., Grosse, G., Heim, B., Hugelius, G.,Irrgang, A., K\u00e4\u00e4b, A. M., Kroisleitner, C., Matthes, H., Nitze, I., Pellet, C., Seifert, F. M.,Strozzi, T., Wegm \u00fcller, U., Wieczorek, M. & Wiesmann, A. (2021b), 'ESA Permafrost Climate Change Initiative (permafrost_cci): Permafrost extent for the Northern Hemisphere, v3.0'.", "Obu, J., Westermann, S., Barboux, C., Bartsch, A., Delaloye, R., Grosse, G., Heim, B., Hugelius,G., Irrgang, A., K\u00e4\u00e4b, A. M., Kroisleitner, C., Matthes, H., Nitze, I., Pellet, C., Seifert,F. M., Strozzi, T., Wegm\u00fcller, U., Wieczorek, M. & Wiesmann, A. (2021c), 'ESA Permafrost Climate Change Initiative (permafrost_cci): Permafrost ground temperature for the Northern Hemisphere, v3.0", "Wang, S., Ramage, J., Bartsch, A. & Efimova, A. (2021), 'Population in the arctic circumpolar permafrost region at settlement level', Zenodo. 10.5281/ZENODO.45296", "Martha K. Raynolds, Donald A. Walker, Andrew Balser, Christian Bay, Mitch Campbell, Mikhail M. Cherosov, Fred J.A. Dani\u00ebls, Pernille Bronken Eidesen, Ksenia A. Ermokhina, Gerald V. Frost, Birgit Jedrzejek, M. Torre Jorgenson, Blair E. Kennedy, Sergei S. Kholod, Igor A. Lavrinenko, Olga V. Lavrinenko, Borg\u00fe\u00f3r Magn\u00fasson, Nadezhda V. Matveyeva, Sigmar Met\u00fasalemsson, Lennart Nilsen, Ian Olthof, Igor N. Pospelov, Elena B. Pospelova, Darren Pouliot, Vladimir Razzhivin, Gabriela Schaepman-Strub, Jozef \u0160ib\u00edk, Mikhail Yu. Telyatnikov, Elena Troeva (2019): 'A raster version of the Circumpolar Arctic Vegetation Map (CAVM)', Remote Sensing of Environment, Volume 232, 111297.", "Nitze, I., Grosse, G., Jones, B. M., Romanovsky, V. E. & Boike, J. (2018), 'Remote sensing quantifies widespread abundance of permafrost region disturbances across the Arctic and Subarctic', Nature Communications 9(1).", "Bartsch et al. (2021), Expanding infrastructure and growing anthropogenic impacts along Arctic coasts, ERL\u00a0https://iopscience.iop.org/article/10.1088/1748-9326/ac3176/meta"]} The SACHI (Sentinel-1/2 derived Arctic Coastal Human Impact) dataset has been primarily developed as part of the HORIZON2020 project Nunataryuk by b.geos (www.bgeos.com). It covers a 100km buffer from the Arctic Coast (land area), for areas with permafrost near the coast. It is based on Sentinel-1 and Sentinel-2 data from 2016-2020 using the algorithms described in Bartsch et al. (2020). It is a supplement to Bartsch et al. (2021 - https://iopscience.iop.org/article/10.1088/1748-9326/ac3176/meta). It consists of three shape files: 1) SACHI.shp - all identified objects with infrastructure/impact classes and auxiliary information (permafrost status and trends, nightlight radiance, vegetation zone, Normalized Difference Vegetation Index trends from Landsat, settlements names) 2) SACHI_100km_buffer - Buffer polygon (analyses extent) 3) SACHI_granules_acquisition_dates - processed Sentinel-2 granule extent polygons with dates of all used input data SACHI class values: 1=linear transport infrastructure, 2=buildings (and other constructions such as bridges), 3=other impacted area (includes gravel pads, mining sites) See README.TXT for description of data fields. Further support was received by ESA CCI+ Permafrost, HGF AI-CORE, and NSF Permafrost DiscoveryGateway. The processing scheme was developed on a highly performant virtual machine (VM) provided by the Copernicus Research and User Support (RUS). Results are based on modified Copernicus data from 2016 to 2020.

  • Restricted
    Authors: 
    Kristine Korzow Richter; Angela Maccarinelli; Jen Harland; Zoe Bottomley; Kenneth Ritchie; Matthew J Collins;
    Publisher: Zenodo
    Project: EC | MAFRI (660337)

    Images from all 46 archaeological test bones associated with the archaeological test set MALDI-TOF data. MALDI-TOF data from both reference and test sets. Reference sets are labeled with their species identification. Each set consists of .tex files. Files in the same folder are technical replicates of the same extract.

  • Restricted
    Authors: 
    Capet Arthur; Vandenbulcke Luc; Grégoire Marilaure;
    Publisher: Zenodo
    Project: EC | PERSEUS (287600)

    Data files provided in support of 'Global warming triggered a reduced and intermittent ventilation regime in the Black Sea', by Capet et al, 2018. Black_Sea_CIL_Cold_Content_Annual.nc contains the spatial and annual averages of the Black Sea cold intermediate layer cold content, as defined in the above reference, and derived from multiple in-situ and modelling sources, for the period (1955-2017). Black_Sea_CIL_Cold_Content_Weekly.nc contains the spatial and weekly averages of the Black Sea cold intermediate layer cold content, as defined in the above reference, and derived from the GHER3D model, for the period (1981-2017).

  • Restricted English
    Authors: 
    Pafilis, Evangelos; Pavlopoulos, Georgios; Satagopam, Venkata; Papanikolaou, Nikolas; Horn, Heiko; Arvanitidis, Christos; Jensen, Lars Juhl; Schneider, Reinhard; Iliopoulos, Ioannis;
    Country: Luxembourg
    Project: EC | MARBIGEN (264089)

    Retrieving all of the necessary information from databases about bioentities mentioned in an article is not a trivial or an easy task. Following the daily literature about a specific biological topic and collecting all the necessary information about the bioentities mentioned in the literature manually is tedious and time consuming. OnTheFly 2.0 is a web application mainly designed for non-computer experts which aims to automate data collection and knowledge extraction from biological literature in a user friendly and efficient way. OnTheFly 2.0 is able to extract bioentities from individual articles such as text, Microsoft Word, Excel and PDF files. With a simple drag-and-drop motion, the text of a document is extensively parsed for bioentities such as protein/gene names and chemical compound names. Utilizing high quality data integration platforms, OnTheFly allows the generation of informative summaries, interaction networks and at-a-glance popup windows containing knowledge related to the bioentities found in documents. OnTheFly 2.0 provides a concise application to automate the extraction of bioentities hidden in various documents and is offered as a web based application.

  • Other research product . Other ORP type . 2012
    Restricted English
    Authors: 
    Martinelli M.; Moroni D.; Salvetti O.;
    Country: Italy
    Project: EC | ARGOMARINE (234096)

    Based on the idea that contribution of volunteers might play a fundamental role in monitoring and protecting the environment, CNR-ISTI designed and developed a mobile application in order to allow people to timely report oil spills. By downloading the FREE app "ARGO Sentinel" volunteers are helping to monitor the health of our seas and the scientific research by demonstrating that the use of this new technology could be really important to combat pollution. Moreover this experiment suggests that this kind of technology can be applied in many other fields. Whoever at sea sights pollution by oil or hydrocarbons is now able to immediately report the event to the Laboratory of Signals and Images SI-LAB (si.isti.cnr.it) of the Institute of Science and Information Technologies of the Italian National Research Council (CNR-ISTI) in Pisa, allowing the realization of a detailed map of the health of our seas. This information is recorded in the Marine Information System (MIS) produced by CNR, able to collect geotagged data relating to critical and health issues of the sea from various sources (satellites, optical sensors, electronic noses, autonomous underwater vehicles systems) and integrate and generate predictive models to assist the authorities in the management of emergencies at sea. The application, distributed in Italian, English and Greek languages, for smartphones equipped of GPS is an easy to use tool designed for anyone, that for any reason, sail the seas. It allows you to send reports of suspected spills to the CNR specifying the precise point, severity and a description of the spill.

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