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Hydrography

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  • The Global WaterPack is a dataset containing information about open surface water cover parameters on a global scale. The water detection is derived from daily, operational MODIS datasets for every year since 2003. The negative effects of polar darkness and cloud coverage are compensated by applying interpolation processing steps. Thereby, a unique global dataset can be provided that is characterized by its high temporal resolution of one day and a spatial resolution of 250 meter. This collection includes yearly composites of the dataset with information on how often a pixel was detected as open surface water with pixel values between 0 and 365 (366 for leap years). Furthermore, a reliability layer provides information on the quality of each Global WaterPack pixel.

  • The PolarLakes dataset provides bi-weekly observations of supraglacial lakes on Antarctic ice shelves, utilizing imagery from Sentinel-2 and Sentinel-1 to address time series gaps caused by frequent cloud cover. These observations detect the extents of supraglacial lakes with a U-Net model for every two weeks from November to March, with each sensor operating independently before the data is merged. The resulting bi-weekly product reflects the maximum lake extents for the first and second halves of each month. When combined for an entire season, the dataset consolidates all bi-weekly records over these five months, allowing for analysis of the maximum lake extent per season and the frequency of lake formation, which can occur up to ten times (5 months á two weeks). The year indicated in the dataset corresponds to January of the melt season, as this month typically experiences the highest melt rates (e.g., 2023 refers to the season from November 2022 to March 2023). The aggregation of all annual datasets creates a recurrence layer that illustrates the frequency of lake presence throughout the entire observation period, which spans from 2014 to 2024, depending on satellite data availability for each ice shelf. The PolarLakes dataset provides valuable insights into the dynamics of supraglacial lakes and serves as a crucial resource for hydrological and climate modeling.

  • The Global WaterPack is a dataset containing information about open surface water cover parameters on a global scale. The water detection is derived from daily, operational MODIS datasets for every year since 2003. The negative effects of polar darkness and cloud coverage are compensated by applying interpolation processing steps. Thereby, a unique global dataset can be provided that is characterized by its high temporal resolution of one day and a spatial resolution of 250 meter. This collection includes monthly composites of the dataset with information on how often a pixel was detected as open surface water with pixel values between 0 and 31. Furthermore, a reliability layer provides information on the quality of each Global WaterPack pixel.

  • SWIM Water Extent is a global surface water product at 10 m pixel spacing based on Sentinel-1/2 data. The collection contains binary layers indicating open surface water for each Sentinel-1/2 scene. Clouds and cloud shadows are removed using ukis-csmask (see: https://github.com/dlr-eoc/ukis-csmask ) and are represented as NoData. The water extent extraction is based on convolutional neural networks (CNN). For further information, please see the following publications: https://doi.org/10.1016/j.rse.2019.05.022 and https://doi.org/10.3390/rs11192330

  • The drainage divides of ice sheets separate the overall glaciated area into multiple sectors. These drainage basins are essential for partitioning mass changes of the ice sheet, as they specify the area over which basin specific measurements are integrated. In (Krieger et al., 2020) we developed a modified watershed algorithm for delineating individual glaciers and applied it to the Northeast Greenland sector. Here we extended the processing to the entire Antarctic Ice Sheet.

  • The present Single Beam Echosounder Data were recorded within the framework of the hydrographic survey of the Federal Maritime and Hydrographic Agency, but were not subjected to any further quality assurance or validation. Please note that these data sets are raw data.

  • The present Single Beam Echosounder Data were recorded within the framework of the hydrographic survey of the Federal Maritime and Hydrographic Agency, but were not subjected to any further quality assurance or validation. Please note that these data sets are raw data.

  • The present Single Beam Echosounder Data were recorded within the framework of the hydrographic survey of the Federal Maritime and Hydrographic Agency, but were not subjected to any further quality assurance or validation. Please note that these data sets are raw data.

  • The present Single Beam Echosounder Data were recorded within the framework of the hydrographic survey of the Federal Maritime and Hydrographic Agency, but were not subjected to any further quality assurance or validation. Please note that these data sets are raw data.

  • The present Single Beam Echosounder Data were recorded within the framework of the hydrographic survey of the Federal Maritime and Hydrographic Agency, but were not subjected to any further quality assurance or validation. Please note that these data sets are raw data.