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The following results are related to Rural Digital Europe. Are you interested to view more results? Visit OpenAIRE - Explore.

  • Rural Digital Europe
  • 2019-2023
  • Open Access
  • Research data
  • Other research products

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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Bradtke, Katarzyna; Herman, Agnieszka;

    Results of the WorldView-2 (WV2) panchromatic image analysis, described in Herman and Bradtke 2023 "Fetch-limited, strongly forced wind waves in waters with frazil and grease ice — spectral modelling and satellite observations in an Antarctic coastal polynya". The image, which cover part of the polynya in Terra Nova Bay, was taken on September 19, 2019 at 21:22 UTC. The spatial resolution of source data is 0.5 m. The zip file contains: “AOI” folder with the analyzed area outline in SHAPEFILE format “whitecaps” folder with breaking wave signatures (polygons) in SHAPEFILE format Sea ice (1) - water (2) mask in GeoTIFF format (0 means NoData) Data are provided in WGS 1984 / UTM Zone 58S projection (EPSG:32758)

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ ZENODOarrow_drop_down
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    ZENODO
    Dataset . 2023
    License: CC BY
    Data sources: ZENODO
    ZENODO
    Dataset . 2023
    License: CC BY
    Data sources: Datacite
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ ZENODOarrow_drop_down
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      ZENODO
      Dataset . 2023
      License: CC BY
      Data sources: ZENODO
      ZENODO
      Dataset . 2023
      License: CC BY
      Data sources: Datacite
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Bradtke, Katarzyna; Herman, Agnieszka;

    Results of high-resolution (pixel size 10–15 m) visible satellite imagery analysis, described in Bradtke and Herman 2023 "Spatial characteristics of frazil streaks in the Terra Nova Bay Polynya from high-resolution visible satellite imagery" (https://tc.copernicus.org/articles/17/2073/2023/). The source data for analysis came from three satellite sensors: ALI (Advanced Land Imager), OLI (Operational Land Imager), and MSI (Multispectral Instrument). The dataset includes: results of frazil streaks detection in polynya, ice_water (ice =1, water=2, NoData=0) maps of spatially averaged characteristics of ice in polynya (NoData = -100): ice concentration, Cfs (-), frazil streaks orientation, Thetafs (degrees clockwise from the north) width of frazil streaks, Wfs (m) maps of spatially averaged wind-wave characteristics obtained from the Fourier analysis (NoData = -100): peak wave length, Lpeak (m) peak wave direction, Thetapeak (degrees clockwise from the north) Data are provided in WGS 1984 / UTM Zone 58S projection (EPSG:32758), in raster grid with 10m resolution, in GeoTIFFformat. File name convention is: sensor_YYYYMMDD_variable.tif

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    ZENODO
    Dataset . 2023
    License: CC BY
    Data sources: ZENODO
    ZENODO
    Dataset . 2023
    License: CC BY
    Data sources: Datacite
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      ZENODO
      Dataset . 2023
      License: CC BY
      Data sources: ZENODO
      ZENODO
      Dataset . 2023
      License: CC BY
      Data sources: Datacite
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    Authors: Liu, Tianjia; Randerson, James T.; Chen, Yang; Morton, Douglas C.; +5 Authors

    The GOES-Observed Fire Event Representation (GOFER) algorithm uses geostationary satellite observations of active fires from GOES-East and GOES-West to map the hourly progression of large wildfires (over 50,000 acres or 202 sq. km). GOES observes North and South America with a spatial resolution of 2 km at the equator and at a frequency of 10-15 minutes for the full disk view. Along with the fire perimeter, we derive the active fire lines and fire spread rates. We tested the GOFER algorithm on a set of 28 wildfires in California from 2019-2021 and produced three versions of the product: GOFER-Combined, GOFER-East, and GOFER-West. GOFER-Combined uses both GOES-East and GOES-West observations, while GOFER-East and GOFER-West use only GOES-East and only GOES-West observations, respectively. We find that GOFER performs reasonably well compared to final perimeters from California's Fire and Resource Assessment Program (FRAP) and 12-hourly perimeters from the Fire Event Data Suite (FEDS), derived from 375-m active fire observations. See our GOFER Visualization app on Earth Engine Apps for an overview of the dataset, alongside other datasets, such as FEDS and FRAP perimeters and 30-m burn severity from Monitoring Trends in Burn Severity (MTBS). Please refer to the corresponding GitHub repository for the code and detailed dataset description.

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    ZENODO
    Dataset . 2023
    License: CC BY
    Data sources: ZENODO
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    ZENODO
    Dataset . 2023
    License: CC BY
    Data sources: ZENODO
    ZENODO
    Dataset . 2023
    License: CC BY
    Data sources: Datacite
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      ZENODO
      Dataset . 2023
      License: CC BY
      Data sources: ZENODO
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      ZENODO
      Dataset . 2023
      License: CC BY
      Data sources: ZENODO
      ZENODO
      Dataset . 2023
      License: CC BY
      Data sources: Datacite
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Ajuntament de Barcelona; Federació Catalana de Voluntariat Social;

    Aprovat entre l'Ajuntament de Barcelona i la Federació Catalana de Voluntariat Social el 29-12-2023.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Repositori Obert de ...arrow_drop_down
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    Authors: Fidai, Yanna Alexia;

    This dataset includes the spectral reflectance of each morphotype (S. natans I, S. natans VIII, S. fluitans III) collected in situ in Ghana (Sanzule) and Barbados (Consett Bay) in 2022. It also includes reflectance data for freshly deposited (<1 day) and recently deposited (<3 days) mixed species/morphotypes of sargassum in Barbados. For more information on the methods of data collection, see: Fidai et al. (2023) 'Innovative spectral characterisation of beached pelagic sargassum towards remote estimation of biochemical and phenotypic properties', Science of the Total Environment.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ ZENODOarrow_drop_down
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    ZENODO
    Dataset . 2023
    License: CC BY
    Data sources: ZENODO
    ZENODO
    Dataset . 2023
    License: CC BY
    Data sources: Datacite
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      ZENODO
      Dataset . 2023
      License: CC BY
      Data sources: ZENODO
      ZENODO
      Dataset . 2023
      License: CC BY
      Data sources: Datacite
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: He, Ze;

    This dataset provides multi-cycle rice harvesting dates for southern China in the year 2021, with a spatial resolution of 10 meters. The dataset comprises three folders labeled with the suffixes 1, 2, and 3, corresponding to the first, second, and third rice growth cycles, respectively. For fields with a single rice-crop intensity, the pixels have values exclusively in the '1' suffix folders. Fields with double rice-crop intensity have pixels with values in both the '1' and '2' suffix folders. Similarly, fields with triple rice-crop intensity have pixels with values in the '1', '2', and '3' suffix folders. The pixel values represent Day of Year (DOY) values, with most values ranging from 0 to 365. A few values are less than 0 or greater than 365. Values less than 0 indicate events that occurred in the previous year, while values greater than 365 indicate events in the following year.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Mendeley Dataarrow_drop_down
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    Mendeley Data
    Dataset . 2023
    License: CC BY
    Data sources: Datacite
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    Mendeley Data
    Dataset . 2023
    License: CC BY
    Data sources: Datacite
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      Mendeley Data
      Dataset . 2023
      License: CC BY
      Data sources: Datacite
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      Mendeley Data
      Dataset . 2023
      License: CC BY
      Data sources: Datacite
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    Authors: He, Ze;

    This dataset provides multi-cycle rice heading dates for southern China in the year 2021, with a spatial resolution of 10 meters. The dataset comprises three folders labeled with the suffixes 1, 2, and 3, corresponding to the first, second, and third rice growth cycles, respectively. For fields with a single rice-crop intensity, the pixels have values exclusively in the '1' suffix folders. Fields with double rice-crop intensity have pixels with values in both the '1' and '2' suffix folders. Similarly, fields with triple rice-crop intensity have pixels with values in the '1', '2', and '3' suffix folders. The pixel values represent Day of Year (DOY) values, with most values ranging from 0 to 365. A few values are less than 0 or greater than 365. Values less than 0 indicate events that occurred in the previous year, while values greater than 365 indicate events in the following year.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Mendeley Dataarrow_drop_down
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    Mendeley Data
    Dataset . 2023
    License: CC BY
    Data sources: Datacite
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Mendeley Data
    Dataset . 2023
    License: CC BY
    Data sources: Datacite
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      Mendeley Data
      Dataset . 2023
      License: CC BY
      Data sources: Datacite
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      Mendeley Data
      Dataset . 2023
      License: CC BY
      Data sources: Datacite
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    Authors: He, Ze;

    This dataset provides multi-cycle rice transplanting dates for southern China in the year 2021, with a spatial resolution of 10 meters. The dataset comprises three folders labeled with the suffixes 1, 2, and 3, corresponding to the first, second, and third rice growth cycles, respectively. For fields with a single rice-crop intensity, the pixels have values exclusively in the '1' suffix folders. Fields with double rice-crop intensity have pixels with values in both the '1' and '2' suffix folders. Similarly, fields with triple rice-crop intensity have pixels with values in the '1', '2', and '3' suffix folders. The pixel values represent Day of Year (DOY) values, with most values ranging from 0 to 365. A few values are less than 0 or greater than 365. Values less than 0 indicate events that occurred in the previous year, while values greater than 365 indicate events in the following year.

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    Mendeley Data
    Dataset . 2023
    License: CC BY
    Data sources: Datacite
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    Mendeley Data
    Dataset . 2023
    License: CC BY
    Data sources: Datacite
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      Mendeley Data
      Dataset . 2023
      License: CC BY
      Data sources: Datacite
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      Mendeley Data
      Dataset . 2023
      License: CC BY
      Data sources: Datacite
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    Authors: Morell Monzó, Sergio; Sebastiá Frasquet, María Teresa; Estornell Cremades, Javier;

    This dataset contains georeferenced agricultural citrus parcels with information on crop status (non-productive, productive or abandoned) for the years 2019, 2020 and 2021 in GeoJSON format. The dataset is divided into 7 subsets (OLV_19, LSF_20, LSF_21, PV_21, TV_21, BP_21, and NL_21) in different locations of the Comunitat Valenciana (Spain). However, most of the data are located in the region of La Safor. Each of these subsets has its own characteristics in terms of sampling/classification method, date of acquisition and number of parcels. In total there are 1676 agricultural parcels labeled. The boundaries of the parcels are defined by the Geographic Information System of Agricultural Parcels (SIGPAC) database, which corresponds to the cadastral limits (“parcela” in SIGPAC nomenclature). Each parcel may contain one or more subplots ("recinto" in SIGPAC nomenclature) but with only one crop status. Data are derived from: Morell Monzó, S. (2023). “Desarrollo de procedimientos para la detección del abandono de cultivos de cítricos utilizando técnicas de teledetección” [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/193058

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    RiuNet
    Dataset . 2023
    Data sources: RiuNet; Crossref
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      RiuNet
      Dataset . 2023
      Data sources: RiuNet; Crossref
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    Authors: European Food Safety Authority;

    This manual provides an introduction to the regulatory framework for the submission of applications and the related data requirements for chemical pesticide active substance. The manual can be used by applicants when preparing an application for an "EU PPP Active substance application (product)" and by evaluators when reviewing these applications. The manual describes the working context for an active substance application and the information required in each field for every IUCLID 6.7 document it includes. IUCLID documents are based on standardised formats and several sections, called common blocks, are reused in many documents throughout the dossier (e.g. information on the test material). The manual also describes how to provide the information in Entities e.g. the literature reference entity, which can be reused in different IUCLID documents. For the documents which use common blocks and entities the manual additionally highlights where specific/additional information is required to summarise a chemical safety study. This manual is updated annually to ensure alignment with the latest IUCLID format release, the last one being April 2023.

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    ZENODO
    Other ORP type . 2023
    License: CC BY
    Data sources: ZENODO
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      ZENODO
      Other ORP type . 2023
      License: CC BY
      Data sources: ZENODO
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Bradtke, Katarzyna; Herman, Agnieszka;

    Results of the WorldView-2 (WV2) panchromatic image analysis, described in Herman and Bradtke 2023 "Fetch-limited, strongly forced wind waves in waters with frazil and grease ice — spectral modelling and satellite observations in an Antarctic coastal polynya". The image, which cover part of the polynya in Terra Nova Bay, was taken on September 19, 2019 at 21:22 UTC. The spatial resolution of source data is 0.5 m. The zip file contains: “AOI” folder with the analyzed area outline in SHAPEFILE format “whitecaps” folder with breaking wave signatures (polygons) in SHAPEFILE format Sea ice (1) - water (2) mask in GeoTIFF format (0 means NoData) Data are provided in WGS 1984 / UTM Zone 58S projection (EPSG:32758)

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    ZENODO
    Dataset . 2023
    License: CC BY
    Data sources: ZENODO
    ZENODO
    Dataset . 2023
    License: CC BY
    Data sources: Datacite
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      ZENODO
      Dataset . 2023
      License: CC BY
      Data sources: ZENODO
      ZENODO
      Dataset . 2023
      License: CC BY
      Data sources: Datacite
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    Authors: Bradtke, Katarzyna; Herman, Agnieszka;

    Results of high-resolution (pixel size 10–15 m) visible satellite imagery analysis, described in Bradtke and Herman 2023 "Spatial characteristics of frazil streaks in the Terra Nova Bay Polynya from high-resolution visible satellite imagery" (https://tc.copernicus.org/articles/17/2073/2023/). The source data for analysis came from three satellite sensors: ALI (Advanced Land Imager), OLI (Operational Land Imager), and MSI (Multispectral Instrument). The dataset includes: results of frazil streaks detection in polynya, ice_water (ice =1, water=2, NoData=0) maps of spatially averaged characteristics of ice in polynya (NoData = -100): ice concentration, Cfs (-), frazil streaks orientation, Thetafs (degrees clockwise from the north) width of frazil streaks, Wfs (m) maps of spatially averaged wind-wave characteristics obtained from the Fourier analysis (NoData = -100): peak wave length, Lpeak (m) peak wave direction, Thetapeak (degrees clockwise from the north) Data are provided in WGS 1984 / UTM Zone 58S projection (EPSG:32758), in raster grid with 10m resolution, in GeoTIFFformat. File name convention is: sensor_YYYYMMDD_variable.tif

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    ZENODO
    Dataset . 2023
    License: CC BY
    Data sources: ZENODO
    ZENODO
    Dataset . 2023
    License: CC BY
    Data sources: Datacite
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      ZENODO
      Dataset . 2023
      License: CC BY
      Data sources: ZENODO
      ZENODO
      Dataset . 2023
      License: CC BY
      Data sources: Datacite
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    Authors: Liu, Tianjia; Randerson, James T.; Chen, Yang; Morton, Douglas C.; +5 Authors

    The GOES-Observed Fire Event Representation (GOFER) algorithm uses geostationary satellite observations of active fires from GOES-East and GOES-West to map the hourly progression of large wildfires (over 50,000 acres or 202 sq. km). GOES observes North and South America with a spatial resolution of 2 km at the equator and at a frequency of 10-15 minutes for the full disk view. Along with the fire perimeter, we derive the active fire lines and fire spread rates. We tested the GOFER algorithm on a set of 28 wildfires in California from 2019-2021 and produced three versions of the product: GOFER-Combined, GOFER-East, and GOFER-West. GOFER-Combined uses both GOES-East and GOES-West observations, while GOFER-East and GOFER-West use only GOES-East and only GOES-West observations, respectively. We find that GOFER performs reasonably well compared to final perimeters from California's Fire and Resource Assessment Program (FRAP) and 12-hourly perimeters from the Fire Event Data Suite (FEDS), derived from 375-m active fire observations. See our GOFER Visualization app on Earth Engine Apps for an overview of the dataset, alongside other datasets, such as FEDS and FRAP perimeters and 30-m burn severity from Monitoring Trends in Burn Severity (MTBS). Please refer to the corresponding GitHub repository for the code and detailed dataset description.

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    ZENODO
    Dataset . 2023
    License: CC BY
    Data sources: ZENODO
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    ZENODO
    Dataset . 2023
    License: CC BY
    Data sources: ZENODO
    ZENODO
    Dataset . 2023
    License: CC BY
    Data sources: Datacite
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      ZENODO
      Dataset . 2023
      License: CC BY
      Data sources: ZENODO
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      ZENODO
      Dataset . 2023
      License: CC BY
      Data sources: ZENODO
      ZENODO
      Dataset . 2023
      License: CC BY
      Data sources: Datacite
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    Authors: Ajuntament de Barcelona; Federació Catalana de Voluntariat Social;

    Aprovat entre l'Ajuntament de Barcelona i la Federació Catalana de Voluntariat Social el 29-12-2023.

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    Authors: Fidai, Yanna Alexia;

    This dataset includes the spectral reflectance of each morphotype (S. natans I, S. natans VIII, S. fluitans III) collected in situ in Ghana (Sanzule) and Barbados (Consett Bay) in 2022. It also includes reflectance data for freshly deposited (<1 day) and recently deposited (<3 days) mixed species/morphotypes of sargassum in Barbados. For more information on the methods of data collection, see: Fidai et al. (2023) 'Innovative spectral characterisation of beached pelagic sargassum towards remote estimation of biochemical and phenotypic properties', Science of the Total Environment.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ ZENODOarrow_drop_down
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    ZENODO
    Dataset . 2023
    License: CC BY
    Data sources: ZENODO
    ZENODO
    Dataset . 2023
    License: CC BY
    Data sources: Datacite
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