Derived mosaic datasets

For simple image collections (use case A or B), this section is not required.

If you are working with multiple data collections (use case C), this next section discusses merging multiple source mosaic datasets into a single derived mosaic for the purpose of centralized data management. With all data collections managed in a single derived mosaic dataset, user applications can easily find all data available in an area of interest, or query the attribute table to access image metadata as needed, and then select imagery by date or any other attribute.

Creating a new mosaic dataset

Define the number of bands and pixel depth for the derived mosaic dataset based on the maximum number of spectral bands, and the maximum pixel depth, of any source dataset.

Set the spatial reference for the derived mosaic dataset to accommodate the maximum extents to be expected for your project. Web Mercator Auxiliary Sphere is typically used.

Adding rasters

As described in the Standard Workflow, all data ingested into the derived mosaic datasets should be contained within source mosaic datasets (no individual rasters should be added to the derived mosaic dataset), and the TABLE raster type should be used.

Ensure the Calculate Cell Sizes option is off when source mosaic datasets are ingested into the derived mosaic dataset, and also that the Update Boundary option is on.

Metadata

After the source mosaics have been ingested, ensure Dataset_ID and other key metadata fields have been copied into the derived mosaic dataset for all records.

Footprints and NoData

The source mosaic datasets should have footprints already defined, and the derived mosaic dataset properties should be set for Clip the raster to its footprint to equal YES. Do not define a NoData value.

Mosaic dataset properties

For the derived mosaic dataset, the recommended settings for properties are as follows:

• Transmission compression settings:
  • Default method: JPEG
  • JPEG with recommended quality: 80
• Default resampling method:
  • Bilinear Interpolation
• Allowed mosaic methods:
  • Lock Raster, By Attribute, Seamline, and None
• Default mosaic method: By Attribute
  • Set Order Field to YEAR with order DECREASING; define base year as 3000.
  Note:

  This presumes you are managing collections of imagery from different years and intend to always display the most recent image.

• Maximum size of requests: default is 15000x4100. The recommended maximum is 4000x4000 to restrict users from attempting to capture a local copy of your full data collection.
• Download:
  • If users require source data, and your network bandwidth is adequate, set Maximum Number of Items Downloadable to 20.
  • Otherwise set Maximum Number of Items Downloadable to 0 (disable download).
• Set BlendWidth to 0.
• Always Clip the Raster to its Footprint to Yes.
• Set Footprints May Contain NoData to No.
• Set Always Clip the mosaic dataset to its Boundary to No.
• Statistics: As above with the source mosaic datasets, it is not necessary to calculate statistics for the derived mosaic dataset. Nominal values for the statistics covering the entire project area should be stored in a configuration file and imported into the derived mosaic dataset using the Set Raster Properties function.
• Under Raster Information, set Source Type to Processed.

Overviews

Overviews for the derived mosaic dataset typically follow the same recommendations as those for the source mosaic dataset (see above), except that the base pixel size should be set to a value approximately equal to the average extent of a full data collection divided by 500. As an example, if you are managing imagery from multiple states (each in its own source mosaic dataset), and Kansas is included (~400 miles east to west), use a figure such as 4,000 feet (~1,500 meters) to define the base pixel size for overviews.

Note that small-scale views generated from high-resolution imagery often appear rather bland. As an alternative, it is recommended to use an independent data source more appropriate for the small-scale views—for example, a mosaic of Landsat data—to provide geographic context. If this approach is preferred to creating overviews, create an additional source mosaic dataset for the lower-resolution imagery (with appropriate overviews), and then add that to the derived mosaic dataset to provide the small-scale views.