[DM3-3] Grid compression methods

Grid data models can contain millions of discrete values. This leads to very large datasets. Depending on the way values change over the grid, different methods can be used for an optimal (lossy or lossless) data compression. Type of data, computer power needed, application of the data, method of transport and storage all contribute to the choice of compression method.

External resources

• Silver, J. D., & Zender, C. S. (2017). The compression–error trade-off for large gridded data sets. Geoscientific Model Development, 10(1), 413-423.

Skills

• 663 - Illustrate the existing methods for compressing gridded data (e.g., run length encoding, Lempel-Ziv, wavelets)
  Illustrate the existing methods for compressing gridded data (e.g., run length encoding, Lempel-Ziv, wavelets)
• 664 - Differentiate between lossy and lossless compression methods
  Differentiate between lossy and lossless compression methods
• 665 - Evaluate the relative merits of grid compression methods for storage
  Evaluate the relative merits of grid compression methods for storage
• 666 - Explain the advantage of wavelet compression
  Explain the advantage of wavelet compression

Status

Outgoing relations

• [DM3-3] Grid compression methods is subconcept of [DM1-5] Data compression techniques
• [DM3-3] Grid compression methods is subconcept of [DM3] Tessellation data models