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  • 1
    Call number: 6/M 15.0018
    In: International Association of Geodesy symposia
    Type of Medium: Monograph available for loan
    Pages: viii, 183 S.
    ISBN: 9783319108278
    Series Statement: International Association of Geodesy symposia 140
    Classification:
    Geodesy
    Location: Reading room
    Branch Library: GFZ Library
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  • 2
    Publication Date: 2023-01-13
    Description: This dataset contains time series of the water level, the areal extent and the volume change of the four large lakes Tanganyika, Turkana, Tonle Sap and Constance. For each lake, the time series cover a time-span of many years at a variable temporal resolution between several days and approximately one month: Lake Tanganyika: October 1992 - February 2015 Lake Turkana: October 1992 - September 2017 Lake Tonle Sap: June 2002 - September 2017 Lake Constance: July 2002 - May 2016 The data are based on satellite observations. Lake levels have been estimated from multi-mission satellite altimetry within DGFI-TUM's Database for Hydrological Time Series of Inland Waters (DAHITI; Schwatke et al., 2015). The areal extent of the water bodies has been derived from optical remote sensing data (Landsat 7/8 images with land/water classification). The relation between water level, areal extent and water volume change has been analyzed for these four lakes in the frame of the related DFG-project WLDYN (Assessing the spatiotemporal dynamics of water volumes in large wetlands and lakes by combining remote sensing with macro-scale hydrological modelling; grant No. SE 1916/4-1). Except for Lake Constance, where the change in areal extent was not mensurable in Landsat images, a linear relationship between water level and areal extent was found for the lakes in this data set. Based on this linear relationship, the areal extent of the lakes Tanganyika, Turkana and Tonle Saphas been interpolated to unobserved epochs. Changed in water volume were subsequently computed from combining water level and areal extent via the so-called truncated pyramid approach.
    Type: Dataset
    Format: application/zip, 4 datasets
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  • 3
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    PANGAEA
    In:  Supplement to: Sánchez, Laura; Völksen, Christof; Sokolov, Alexandr; Arenz, Herbert; Seitz, Florian (2018): Present-day surface deformation of the Alpine region inferred from geodetic techniques. Earth System Science Data, 10(3), 1503-1526, https://doi.org/10.5194/essd-10-1503-2018
    Publication Date: 2023-01-13
    Description: We provide a present-day surface-kinematics model for the Alpine region and surroundings based on a high-level data analysis of a network of about 300 continuously operating GNSS (GPS+GLONASS) stations with observations collected over 12.4 years. Based on the network station velocities, a continuous kinematic field is derived using a geodetic least-squares collocation approach with empirically determined covariance functions. Main results are (1) a deformation model, (2) a continuous surface-kinematic (velocity) field, and (3) a strain field consistently assessed for the entire Alpine mountain belt. The core contribution of this work is the homogeneous analysis of a large number of freely available data from GNSS stations located in the Alpine region, using unified processing standards and a common reference frame for the complete time-span covered by the observations. The GNSS network solution refers to the reference frame IGb08, epoch 2010.0. The mean precision of the station positions at the reference epoch is ±1.1 mm in N and E and ±2.3 mm in height. The mean precision of the station velocities is ±0.2 mm/a in N and E and ±0.4 mm/a in the height. The averaged accuracy of the horizontal and vertical deformation models inferred from the pointwise station velocities are ±0.2 mm/a and ±0.3 mm/a, respectively. The deformation model as well as the continuous velocity and strain fields are given in a grid of 25 km x 25 km covering the region between longitudes 4°E and 16°E and latitudes 43°N and 49°N.
    Keywords: AlpineRegion; File content; File format; File name; File size; Uniform resource locator/link to file
    Type: Dataset
    Format: text/tab-separated-values, 50 data points
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  • 4
    Publication Date: 2023-01-13
    Keywords: Area; DATE/TIME; Germany; Lake_Constance; Water level; Water volume change
    Type: Dataset
    Format: text/tab-separated-values, 315 data points
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  • 5
    Publication Date: 2023-01-13
    Keywords: Area; DATE/TIME; Lake_Tanganyika; Water level; Water volume change
    Type: Dataset
    Format: text/tab-separated-values, 1866 data points
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  • 6
    Publication Date: 2023-01-13
    Keywords: Area; DATE/TIME; Lake_Turkana; Water level; Water volume change
    Type: Dataset
    Format: text/tab-separated-values, 3546 data points
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  • 7
    Publication Date: 2023-01-13
    Keywords: Area; DATE/TIME; Lake_Tonle_Sap; Water level; Water volume change
    Type: Dataset
    Format: text/tab-separated-values, 2151 data points
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  • 8
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    In:  Supplement to: Singh, Alka; Kumar, Ujjwal; Seitz, Florian (2015): Remote sensing of storage fluctuations of poorly gauged reservoirs and State Space Model (SSM)-based estimation. Remote Sensing, 7(12), 17113-17134, https://doi.org/10.3390/rs71215872
    Publication Date: 2023-01-13
    Description: The Aral Sea is located in an arid region with much sand and salt deposits in the surrounding barren open land. Hence, significant displacements of sediments into the lakebed by the action of wind, water, gravity, or snow are likely. The bathymetry of the lake was last observed in the 1960s, and within the last half century, the structure of the lakebed has changed. Based on satellite observations of the temporal changes of shoreline (Landsat optical remote sensing) and water level (multi-mission satellite altimetry) over more than one decade an updated bathymetric chart for the East Basin of the Aral Sea has been generated. During this time, the geometry of the shallow East Basin experienced strong fluctuations due to the occurrence of periods of drying and strong inflow. By the year 2014 the East Basin fell dry. The dynamic behavior of the basin allowed for estimating the lake's bathymetry from a series of satellite-based information. The river mouth made its impression in the present East Aral Sea, because its shrinking led to the inflow of much sediment into the lake's interior. In addition, salt deposits along the shorelines increased the corresponding elevation, a phenomenon that is more pronounced in the reduced lakebed because of increased salinity. It must be noted that height estimates from satellite altimetry were only possible down to a minimum elevation of 27 m above sea level due to a lack of reliable altimetry data over the largely reduced water surface. In order to construct a complete bathymetric chart of the lakebed of the East Aral Sea heights below 27 m were obtained solely from Landsat optical images following the SRB (Selected Region Boundary) approach as described by Singh et al. (2015).
    Keywords: Aral_Sea; Kazakhstan, Uzbekistan, Central Asia; MULT; Multiple investigations
    Type: Dataset
    Format: application/zip, 156.7 MBytes
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  • 9
    Publication Date: 2023-01-13
    Description: The DTRF2014 is a realization of the the fundamental Earth-fixed coordinate system, the International Terrestrial Reference System (ITRS). It has been computed by the Deutsches Geodätisches Forschungsinstitut der Technischen Universität München (DGFI-TUM). The DTRF2014 consists of station positions and velocities of 1712 globally distributed geodetic observing stations of the observation techniques VLBI, SLR, GNSS and DORIS. Additionally, for the first time, non-tidal atmospheric and hydrological loading is considered in the solution. The DTRF2014 was released in August 2016 and incorporates observation data of the four techniques up 2014. The observation data were processed and submitted by the corresponding technique services: IGS (International GNSS Service, http://igscb.jpl.nasa.gov) IVS (International VLBI Service, http://ivscc.gsfc.nasa.gov) ILRS (International Laser Ranging Service, http://ilrs.gsfc.nasa.gov) IDS (International DORIS Service, http://ids-doris.org). The DTRF2014 is an independent ITRS realization. It is computed on the basis of the same input data as the realizations JTRF2014 (JPL, Pasadena) and ITRF2014 (IGN, Paris). The three realizations of the ITRS differ conceptually. While DTRF2014 and ITRF2014 are based on station positions at a reference epoch and velocities, the JTRF2014 is based on time series of station positions. DTRF2014 and ITRF2014 result from different combination strategies: The ITRF2014 is based on the combination of solutions, the DTRF2014 is computed by the combination of normal equations. The DTRF2014 comprises 3D coordinates and coordinate changes of 1347 GNSS-, 113 VLBI-, 99 SLR- and 153 DORIS-stations. The reference epoch is 1.1.2005, 0h UTC. The Earth Orientation Parameters (EOP) - that means the coordinates of the terrestrial and the celestial pole, UT1-UTC and the Length of Day (LOD) - were simultaneously estimated with the station coordinates. The EOP time series cover the period from 1979.7 to 2015.0. The station names are the official IERS identifiers: CDP numbers or 4-character IDs and DOMES numbers (http://itrf.ensg.ign.fr/doc_ITRF/iers_sta_list.txt). The DTRF2014 solution is available in one comprehensive SINEX file and four technique-specific SINEX files, see below. A detailed description of the solution is given on the website of DGFI-TUM (http://www.dgfi.tum.de/en/science-data-products/dtrf2014/). More information can be made available by request.
    Keywords: Comment; File content; File name; Uniform resource locator/link to file
    Type: Dataset
    Format: text/tab-separated-values, 43 data points
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  • 10
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    In:  Technische Universität München | Supplement to: Müller, Felix L; Dettmering, Denise; Wekerle, Claudia; Schwatke, Christian; Passaro, Marcello; Bosch, Wolfgang; Seitz, Florian (2019): Geostrophic currents in the northern Nordic Seas from a combination of multi-mission satellite altimetry and ocean modeling. Earth System Science Data, 11(4), 1765-1781, https://doi.org/10.5194/essd-11-1765-2019
    Publication Date: 2023-10-28
    Description: The data set contains combined Dynamic Ocean Topography (DOT) and geostrophic velocity components for the northern Nordic Seas between 1995 and 2012. It was produced in the frame of the DFG project NEG-OCEAN: Variations in ocean currents, sea-ice concentration, and sea surface temperature along the North-East coast of Greenland. The data is provided as Format 4 Classic NetCDF files on an unstructured triangular, Finite Element formulated grid. The data are characterized by daily sampling between 18.5.1995 and 3.4.2012 including data gaps and a consistent spatial resolution up to 1 km. More details can be found in the related User Manual. The dataset is based on Dynamic Ocean Topography (DOT) elevations from a combination of along-track satellite altimetry measurements with simulated differential water heights from the Finite Element Sea-ice Ocean Model Version 1.4 (FESOM, Wekerle et al., 2017, doi:10.1002/2017JC012974). The combination approach is described in detail in the related publication. The altimetry data include observations of the ESA satellites Envisat and ERS-2. The high-frequent altimetry range observations are retracked using the ALES+ algorithm (Passaro et al., 2018, doi:10.1016/j.rse.2018.02.074) and are classified into open-water/sea-ice conditions by applying a classification algorithm (Müller et al., 2017, doi:10.3390/rs9060551). All applied atmospheric and geophysical altimetry corrections are listed in Müller et al., 2019 (doi:10.5194/tc-13-611-2019).
    Keywords: Dynamic Ocean Topography; File format; File name; File size; Geostrophic Currents; MULT; Multiple investigations; NEG-OCEAN; NordicSeas; North Atlantic; northern Nordic Seas; Ocean Modeling; Principal Component Analysis; Satellite altimetry; Uniform resource locator/link to file; Variations in ocean currents, sea ice concentration, and sea surface temperature along the North-East coast of Greenland
    Type: Dataset
    Format: text/tab-separated-values, 72 data points
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