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    545 Lake dynamics (1992-2015) in arid and semi-arid areas of Asia utilizing multi-satellite observations

    DOI Info:

    • DOI: 10.18728/545.2
    • Citation suggestion: Fei Li (2020-09-15 ) Lake dynamics (1992-2015) in arid and semi-arid areas of Asia utilizing multi-satellite observations. IGB Leibniz-Institute of Freshwater Ecology and Inland Fisheries. dataset. https://doi.org/10.18728/545.2
    • Previous DOI version :10.18728/544.1

      • DOI history

      Date DOI PackageId Note
      2020-09-1510.18728/543.0543
      2020-09-1510.18728/544.1544
      2020-09-1510.18728/545.2545this package latest
    Title
    Lake dynamics (1992-2015) in arid and semi-arid areas of Asia utilizing multi-satellite observations
    Period
    1992-01-01 till 2015-12-31
    Period length
    23 years 11 months 30 days
    Sampling interval
    23 years Irregular Interval
    Keywords
    Lake level; Lake area; Water storage change; remote sensing; Climate change; Arid and semi-arid areas of Asia
    Study site
    Ahlenmoor bei Wanna
    Contact
    Fei Li
    Licence for data
    All rights reserved. Please send a request to Fei Li if you like to use this data. Mind our data policy: IGB Data Policy

    Data files (e.g. excel)

    TitlecreatedFiletypeActions
    31lakes-waterlevel.xlsx 15. Sep. 2020 17:31 datatable: .xlsx Download
    31lakes-area.xlsx 15. Sep. 2020 17:31 datatable: .xlsx Download

    Machine Readable Metadata Files

    FRED provides all metadata of this package in a maschine readable format. There is a pure XML file and one EML file in Ecological Metadata Language. Both files are published under the freeODC-ByLicence.

    • Lake_dynamics_(1992-2015)_in_arid_and_semi-arid_areas_of_Asia_utilizing_multi-satellite_observations.xml
    • Lake_dynamics_(1992-2015)_in_arid_and_semi-arid_areas_of_Asia_utilizing_multi-satellite_observations.eml

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    Parsing data File

    Estimated Time:

    Why does it take so much time?

    While parsing a file, the database has to perform various tasks, some of them needs a lot of CPU and memory for larger files.

    • preprocessing: means automatic detection of headlines, table body, format values or csv-separators
    • copying: means read the file cell by cell and copy all elements to the database. During this format settings can be calculated (for example iso-time)
    • analyzing: check out for different data types (can be time, numeric or text)