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

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:

Installation: Use a package manager like Miniconda to set up an environment for GLL.
Reading Metadata: Utilize the GLL info command to understand the file structure and parameters.
Parsing Data: Use GLL translate to extract specific sub-datasets into a more manageable format (e.g., GeoTIFF).
Scaling Data: For visualization, scale floating-point data to a byte range (0-255) for grayscale representation.
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.
Handling Multi-Dimensional Data: For datasets with multiple parameters and time steps, extract individual bands and remap them for conventional projections.
Batch Processing: Automate the processing of multiple datasets using scripting in a Unix shell.