Multi-Resolution Raster (MRR), MapInfo Pro's raster data format, is a unifying format that
handles all types of data and provides capabilities to improve the user experience when
visualizing and processing raster data.
Spectrum Spatial Support
Spectrum Spatial provides the following support for MRR via a TAB file:
- render MRR rasters as maps and tiles using the Mapping Service and Tiling Service that
have the same visual styling as in desktop products such as MapInfo Professional
- query a cell value using the existing functions MI_GridValueAt or MI_GridValueAtPixel in
the Feature Service (see Raster / Grid Functions in the
MapInfo SQL Language Reference Guide)
We recommend copying all MRR
companion files (.ghx and .pprc) along with the .mrr file to the same directory to avoid
any instability. These files should be generated using MapInfo Pro Raster 1.0 or 2.0. If
these files are not copied then the first query or rendering request will take a
significant amount of time to process.
The query API functions support only band 0 for
classified, image, and image palette raster files. Also, for continuous raster files, the
query of the cell value is limited to the single band value persisted in the ghx file. You
cannot specify the field or band to retrieve through the API.
supports the reading of a cell value at base level (resolution
This support is provided on Windows 64-bit and the following Linux environments:
- Oracle Linux 6.5 and 7.1
- CentOS 6.4 and 7.1
- Ubuntu 14.04
A sample MRR named map, table, and layer are included in the repository, under the
- On Linux machines, GCC version 4.9 and LIBC to version 2.17 are required for MRR files.
See Configuring a Linux Machine for MRR in
the Spectrum Spatial Administration Guide for instructions.
- On Linux, all files (.TAB, .ghx, and .pprc) must share the same case as the MRR file name.
You must modify the file names to have the same case, otherwise Spectrum Spatial will
regenerate the .ghx file so that it matches the case of the MRR file name.
- Anti-aliasing does not currently work for MRR.
- Open native handles for MRR are cached to improve
When rendering or querying an MRR file, the handle is opened then cached. The same handle
is used for subsequent requests. If the time period between subsequent requests is large,
the handle becomes ready for automatic closure. In addition, when the server is stopped
the cache is invalidated and all handles are closed before JVM exits.
Benefits of MRR
The MRR file format offers the following key benefits:
- Extremely large raster/grid datasets - The MRR format has been designed to
address the difficulty of handling extremely large datasets by providing multiple
optimizations to minimize storage requirements and provide efficient ways of accessing
data in extremely large files. It has also been designed to deliver an enhanced
visualization experience by using tiling and by maintaining a data pyramid to enable
efficient data visualization at any given scale.
- Unified data - The MRR format is capable of storing all types of raster/grid data
in common use, and it removes the distinction between numeric or classified data and
colored imagery etc.
- Sparse data - Sometimes raster/grid datasets can be extremely large but only
sparsely populated with valid data. An example of such a dataset is a LiDAR survey which
follows along a pipeline for several 100 km but is only 100 m wide. In cases such as
these, the MRR format does not store values for the regions containing no data, but still
remains flexible enough to add additional data to the source file any time. This allows
extremely sparse datasets to be stored efficiently on disk, be rapidly accessed and easily
Capabilities of MRR
The MRR file format has the following capabilities:
- Removes virtually all restrictions on the size of raster datasets.
- Extends the concept of a raster from a simple 2D array of cells to an extensible sparse
matrix of tiles.
- Contains a binary data pyramid enabling data access at any scale.
- Achieves efficient storage using lossless and lossy compression techniques via industry
standard compression codecs.
- Supports the temporal dimension, allowing data to be accumulated and accessed by
- Supports image data, thematic data (of virtually unlimited size) and continuous and
- Supports a wide and extensible number of data types including complex numbers.
- Stores one or more multi-banded fields.
- Supports local registration and cell size for each field.
- Contained within a single file on disk.