Raster data organization

There are four ways to organize your raster data (raster data models): the raster dataset, the mosaic dataset, the raster catalog, and rasters that are attributes of a feature.

One of the major design decisions in managing raster data is whether to store all the data in a single dataset or as a cataloged collection of many datasets. In some cases, the application requirements will dictate which approach to use, while in other cases, the choice may not be as obvious. The mosaic dataset provides an excellent solution to this decision, as it is a catalog of raster data that can be viewed as a single raster dataset (mosaicked image).

Raster datasets

A raster dataset is any valid raster format organized into one or more bands. Each band consists of an array of pixels (cells), and each pixel has a value. A raster dataset has at least one band. More than one raster dataset can be spatially appended (mosaicked) together into a larger, single, continuous raster dataset. Note that when partially overlapping raster datasets are mosaicked, the overlapping area contains only one set of cell values. Below is an example of a raster dataset.

There are many geoprocessing tools specifically for working with raster datasets. These are listed in An overview of the Raster toolset's Raster Dataset tools.

Mosaic datasets

A mosaic dataset is a collection of raster datasets (images) stored as a catalog and viewed as a mosaicked image. The raster datasets can also be viewed individually. These collections can be extremely large both in total file size and number of raster datasets. The raster data is added according to its raster type—which identifies metadata, such as georeferencing, acquisition date, and sensor type, along with a raster format. The raster datasets in a mosaic dataset can remain in their native format on disk or, if required, be loaded into the geodatabase. The metadata can be managed within the raster record as well as attributes in the attribute table. Storing metadata as attributes enables parameters such as sensor orientation data to be managed easily as well as enabling fast queries to enable selections.

Like a raster catalog, each raster within the mosaic dataset can have its own coordinate system, but it will be reprojected to the coordinate system of the mosaic dataset when displayed. Additionally, any footprints or other calculated attributes, such as pixel sizes, will be created using the coordinate system of the mosaic dataset.

The raster data in a mosaic dataset does not have to be adjoining or overlapping but can exist as unconnected, discontinuous datasets. For example, you can have images that completely cover an area or you can have many strips of images that may not join together to form a continuous image (such as along pipelines).

The data can even be completely or partially overlapping but be captured over different dates. The mosaic dataset is an ideal dataset for storing temporal data. You can query the mosaic dataset for the images you need based on time or dates and use a mosaic method to display the mosaicked image according to a time or date attribute.

Mosaic datasets are not limited to one particular type of raster data. Like with a raster catalog, you can add raster data in different projections, resolutions, pixel depths, and number of bands. Unlike with a raster catalog, you can generate overviews (like pyramids) for the entire data collection. This allows for faster viewing of the data and allows you to easily serve these datasets. There are also many additional properties for viewing, including setting a mosaicking method, that make these datasets unique and functional in many situations. You can also query a mosaic dataset based on your spatial and nonspatial query constraints. The results of that query can be a set of images that you could process one by one, or it could be a dynamically generated mosaicked image.

There are many geoprocessing tools specifically for working with mosaic datasets. These are listed in An overview of the Raster toolset's Mosaic Dataset tools.

Raster catalogs

A raster catalog is a collection of raster datasets defined in a table format in which each record represents an individual raster dataset in the catalog. A raster catalog can be large and contain thousands of images. A raster catalog is typically used to display adjacent, fully overlapping, or partially overlapping raster datasets without having to mosaic them into one large raster dataset. Below is an example of a raster catalog in which the yellow line is the outline of each of the single raster datasets. This outline is often referred to as the footprints of the raster datasets or the wireframe. You can see there are many overlapping raster datasets of different sizes that represent different types of data in this raster catalog display.

Each raster in a catalog can have its own coordinate system that can be used to project each image for map and globe displays on the fly.

There are many uses for raster catalogs. You can use raster catalogs to hold a time series of raster images, for example, weather images for a point in time. You can use a raster catalog to hold any pattern of image footprints, for example, those that do not follow a tiled pattern. You can also use a raster catalog to hold any image collection that makes sense in terms of your workflow.

There are many geoprocessing tools specifically for working with raster catalogs. These are listed in An overview of the Raster toolset's Raster Catalog tools.

Comparing raster data storage models

When working with multiple raster datasets, there are four possible storage models: store each raster dataset individually, mosaic them into one large raster dataset, store them as members of a mosaic dataset, or store them as members of a raster catalog.

Storing the raster datasets individually is often the best method when the datasets are not adjacent to each other or are rarely used on the same project. Mosaicking your inputs together to form one large, single extent of raster data is appropriate for many applications, but a mosaic dataset or raster catalog may be desired for any of these reasons:

• The extents of the raster datasets partially or fully overlap and you want the common areas to be preserved.
• The raster datasets represent a collection of observations of the same area at different times in a time series.
• You do not need to see the entire area at one time (raster catalogs display a wireframe at smaller scales); however, if you do need to see the entire area, use a mosaic dataset.
• You want to manage a collection of images as an integrated set but keep their individual states.
• You want to record and manage additional attribute columns that describe each image.

	Raster dataset	Mosaic dataset	Raster catalog
Description	A single picture of an object or a seamless image covering a spatially continuous area. This may be a single original image or the result of many images appended (mosaicked) together.	A collection of raster datasets stored as a catalog that allows you to store, manage, view, and query collections of raster data. It is viewed as a mosaic, but you have access to each raster dataset in the collection.	A collection of raster datasets displayed as a single layer. They can be in different coordinate systems and can have different data types.
Map layers	One map layer.	One map layer.	One map layer.
Homogeneous or heterogeneous data	Homogeneous data: a single format, data type, and file.	Heterogeneous data: multiple formats, data types, file sizes, and coordinate systems.	Heterogeneous data: multiple formats, data types, file sizes, and coordinate systems.
Metadata	Stored once and applies to complete dataset.	Can be stored within the raster record and as attributes in the raster catalog table.	Stored as attribute columns for each raster dataset item in the raster catalog.
Pyramiding	A single pyramid on the entire raster dataset.	Pyramids for each raster dataset, as well as overviews (like a pyramid) for the entire collection.	A pyramid for each raster dataset in the raster catalog.
Geoprocessing and image analysis	Can be used as a data source in many geoprocessing and analysis tools. Can be used in the Image Analysis window.	Can be used as a data source in many geoprocessing and analysis tools. Can be used in the Image Analysis window.	Cannot be used as a data source in many geoprocessing and analysis tools. Cannot be used in the Image Analysis window.
Pros	Fast to display at any scale. Mosaic saves space, since there is no overlapping data.	Manages large collections of raster data. Fast to display at any scale. No loss of data to create mosaic. User has access to full content of collection. Properties can be set to control the mosaicked display. On-the-fly processing.	Can manage multirow raster tables for many purposes. Can specify one or more raster datasets for display.
Cons	File and personal geodatabase raster datasets are slower to update because the entire file has to be rewritten.	Overviews can take time to generate.	File-based raster catalogs with different data types may not render well. Displaying many raster dataset items from a raster catalog can be time consuming.
Serving	Can be served directly as an image service.	Can be served directly as an image service.	Can be served as an image service by first creating a referenced mosaic dataset that references the raster catalog.
Recommendations	Use raster datasets when overlaps between mosaicked images do not need to be retained and for fast display of large quantities of raster data.	Use a mosaic dataset for managing and visualizing raster data. It's good for multidimensional data, querying, storing metadata, and overlapping data, and it provides a good hybrid solution.	Use a raster catalog for massive image repositories, to retain overlaps between datasets, to manage time series data, and when differences among adjoining images prevent mosaicking.

A comparison of the raster data storage models

A mosaic dataset and raster catalog are good ways to manage a large number of raster datasets; however, mosaic datasets are the recommended choice. By using an mosaic dataset or unmanaged raster catalog, you can maintain a directory or listing of your data holdings. Also, a referenced mosaic dataset can be stored outside a geodatabase as an *.amd file.

Raster attributes

Rasters can also be an attribute of a feature in a feature class. This means that a field of type raster can exist as one of the columns within a feature class (geodatabase feature classes only). This is similar to having a hyperlink of a file-based image in a field, except the raster image is stored and managed within the geodatabase. For example, you could add a photograph of the commercial property as an attribute of a parcel feature.

For information on raster dataset file formats supported in ArcGIS, see Supported raster dataset file formats.