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Mapping with Satellite Data (Beyond Landsat and Sentinel-2) - Robert Simmon

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Science and Nature

The video presented by Robert Simmon discusses advanced mapping techniques using satellite data, focusing on tools beyond the commonly used Landsat and Sentinel-2 datasets. The main emphasis is on the use of a command-line library called GLL (Geospatial Library) for handling complex geospatial data formats.

Key Scientific Concepts and Discoveries:

  • Satellite Data Sources: Various international space agencies, including NASA, ESA, and JAXA, produce extensive datasets that can be used for mapping and analysis.
  • Data Formats: Commonly encountered formats include NetCDF, HDF, and GRIB, which are multi-dimensional and flexible but can be challenging to work with.
  • Metadata Interpretation: Understanding the metadata of datasets is crucial for effective data manipulation and analysis.
  • Georeferencing Issues: Many datasets have complex georeferencing that may require adjustments for accurate mapping.
  • Batch Processing: The ability to automate processing of multiple datasets through command-line tools.

Methodology for Using GLL:

  1. Installation: Use a package manager like Miniconda to set up an environment for GLL.
  2. Reading Metadata: Utilize the GLL info command to understand the file structure and parameters.
  3. Parsing Data: Use GLL translate to extract specific sub-datasets into a more manageable format (e.g., GeoTIFF).
  4. Scaling Data: For visualization, scale floating-point data to a byte range (0-255) for grayscale representation.
  5. Fixing Georeferencing:
    • Adjust the spatial reference system using GLL translate or GLL warp.
    • Specify the upper left and lower right coordinates to ensure proper mapping.
  6. Handling Multi-Dimensional Data: For datasets with multiple parameters and time steps, extract individual bands and remap them for conventional projections.
  7. Batch Processing: Automate the processing of multiple datasets using scripting in a Unix shell.

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