Background & Technology
The US Naval Research Laboratory detachment at Stennis Space Center has developed GRIN, a fast, flexible, and highly efficient means of compressing geospatial datasets by thinning points while maintaining a high degree of accuracy for the remaining data points. The technology removes grid data points in areas of low variability, while retaining the most valuable topography, bathymetry, or other X, Y, and Z data points. For example, a plateau may be represented with fewer data points, since elevation is relatively constant over an area – thus unneeded grid data points can be eliminated. Reducing the size of data sets results in smaller files that requires less storage space, are easier to transfer, enable more frequent data updates, and require less computing power to process.
GRIN is a new algorithm for calculating Right Triangulated Irregular Networks (RTINs) that preserves the positional integrity of the remaining original grid points. GRIN is designed for charting, navigation, and other high-precision applications. Data sets have been compressed with greater than ten-fold reduction with full accuracy retention of the source data. The compression/thinning level is customizable by user-selected fixed or percentage Z-value thresholds. Fixed values flatten out areas that vary less than the threshold (e.g. 10m or 10°C), and percentage threshold helps the algorithm retain points that are close to zero but would otherwise be removed by the fixed metric. GRIN is written primarily in platform independent JAVA and runs quickly on standard workstations.
- Efficient: Data compression of greater than 10x has been achieved
- Fast: A 1025x1025 grid (2°x2° @ 200m resolution) can be compressed or re-gridded in about 1 minute
- Customizable: User specified thresholds allow control over the desired level of compression
- High Fidelity: The full integrity of the remaining un-thinned data points is retained
Status and Opportunity
- Pending US patent application available for license
- Potential for collaboration with NRL Stennis Space Center researchers
Back to Oceanography