Skip To Content

Mosaic Datasets

Mosaic datasets are the basis of image management. This guide assumes that you have a basic knowledge of creating mosaic datasets from different types of imagery.

For simple collections of imagery, the general guidelines outlined here can be followed to create mosaic datasets (using default values) that can be used directly, served as image services, used for caching, or used as input to the raster analytics capability of ArcGIS Image Server.

Though not addressed in the Standard Workflow, raster functions can be applied to mosaic datasets, allowing you to define processing operations that will be applied to one or more rasters. Details and instructions for each of the available functions can be found in the ArcGIS Help.

Mosaic datasets can be used to manage a wide range of imagery types, from preprocessed orthophotos, to elevation data, to unprocessed satellite imagery. The volume and number of images can quickly become massive. To enable flexibility and scalability in managing such large volumes of imagery, there are many different tools to work with mosaic datasets, and many parameters that can be set to optimize them for different types of imagery. The imagery management workflows on the ArcGIS Imagery Workflows site outline best practices and provide scripts and sample data for working with different types of imagery.

These workflows assume that larger collections of imagery are to be managed. In such cases, it is often impractical to work with a single mosaic dataset for all imagery, so the workflows follow a pattern of using source, derived, and referenced mosaic datasets. These are described in Imagery Data Management Patterns and Recommendations. This pattern breaks a potentially complex task into smaller tasks, and makes it easier to manage multiple sources, perform quality assurance of the mosaic datasets, and maintain the services.

Although it is possible to create a single mosaic dataset from many collections of imagery, the best practice is to use a combination of different mosaic datasets, as is summarized in the following sections and diagrammed in the image below.

Source mosaic datasets

For each collection of similar images, a source mosaic dataset is created. A source mosaic dataset represents a single manageable unit typically used for checking that metadata is defined correctly, defining specific processes to be applied, or doing quality assurance. Each record in the source mosaic dataset defines a dataset with specific metadata. A source mosaic dataset could represent all imagery from a specific type of sensor, or represent imagery that was acquired as a part of a discrete project that covers a known extent or period in time. The number of images in each source mosaic dataset typically ranges from tens to hundreds of thousands of images. Source mosaic datasets are generally not made accessible to the end users or served as image services.

All imagery in a source mosaic dataset should have the following attributes:

  • Similar in terms of the number of bands, bit depth, and type of metadata
  • Require a single raster type when added to the source mosaic
  • Have similar scales or pixel size (though possibly in different projections)

Typically, if modifications to the raster item (within the mosaic dataset) are required—clipping images to a footprint for example, or applying a stretch or orthorectification—they are defined and refined in the source mosaic dataset.

The spatial reference of a source mosaic dataset should be the best choice to encompass all imagery. For example, do not use a state plane projection to contain data across an entire country. Instead, use a projection suitable to contain the entire country's data. The imagery to be added to the source mosaic should within the extent horizon of the selected spatial reference system.

The number of bands and bit depth of the source mosaic dataset are set to be suitable to contain all the data. For example, a source mosaic dataset with high-resolution satellite imagery, such as GeoEye-1, IKONOS, or QuickBird, would be defined as 4-band, 16-bit (not 1-band 8-bit).

In some but not all cases, overviews may be generated for a source mosaic dataset to enable visualization at smaller scales.

Source mosaic datasets do not have to be static; over time additional rasters can be added. In some workflows, source mosaic datasets are created manually, while for others the creation of source mosaic datasets may be fully automated.

Derived mosaic datasets

Derived mosaic datasets are created from multiple source mosaic datasets. The derived mosaic dataset typically defines an imagery product that is to be served for a specific purpose—for example, natural color imagery for visual interpretation, multispectral imagery for analysis, or digital surface models that best represent the terrain.

Imagery is added to the derived mosaic dataset primarily by using the Table raster type. This enables all records from one or more source mosaic datasets to be added. In some cases, only a subset of the source mosaic dataset(s) will be added to a derived mosaic dataset. For example, images with too much cloud cover may be excluded based on metadata provided in the source mosaic dataset. All properties and metadata from the source records are copied to the derived mosaic dataset. The spatial reference of the derived mosaic dataset is set to encompass all the imagery, and the number of bands and bit depth is set to be appropriate for all the data sources.

Optionally, functions can be applied to transform the data. For example, the Extract Bands function may be used to convert imagery from 4-band to 3-band, or a stretch might be applied to convert from 16-bit to 8-bit. In most cases, each derived mosaic dataset will have a range of functions added to define different products. For example, a mosaic dataset that provides elevation data may have a set of functions added to provide hillshade, slope, and aspect representations.

Multiple derived mosaic datasets may use the same source mosaic datasets. For example, a derived mosaic dataset for natural color imagery and one for enabling multispectral analysis may use the same source mosaic dataset from a high-resolution satellite.

In some cases, imagery is directly added to a derived mosaic dataset, rather than organized into a source mosaic dataset first. For example, an image source such as World Imagery or NaturalVue (available on ArcGIS Online as an image service or cached map serviceproviding global 15-meter resolution imagery) may be added to provide a background image for natural color imagery, or an overview image from some other source may be added to provide context at small scales. If no suitable overview exists for the derived mosaic dataset, then overviews may be built.

Derived mosaic datasets do not need to be static, and over time, the source mosaic datasets from which they are derived may change or new source mosaic datasets may be added. To update the derived mosaic datasets, two different approaches can be used. The Synchronize Mosaic Dataset tool can be used, which checks for changes in all sources and updates any changes. Alternatively, if the process of creating the derived mosaic dataset is automated, the derived mosaic dataset can be re-created, as the process is generally very fast.

Derived mosaic datasets may be directly served, but since serving a mosaic dataset can lock tables, often referenced mosaic datasets are used instead.

Referenced mosaic datasets

Referenced mosaic datasets are sometimes created by referencing derived mosaic datasets.

They define parameters that are either defaults or enforce specific rules to be applied when the imagery is accessed. For example, from a derived mosaic representing elevation data for the whole world, a referenced mosaic dataset may be created to define a hillshade or slope map product for a selected area.

Referenced mosaic datasets are also often created to define different restrictions. For example, downloading may be restricted in one service, but enabled in another that is used for geoprocessing.

Referenced mosaic datasets are also used to create subsets. For example, a referenced mosaic dataset may be defined with a limited boundary or query to limit access to a specific area or type of imagery.

Next: Overview of serving imagery