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Raster basics

Release 9.3
Last modified May 27, 2010
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Note: This topic was updated for 9.3.1.

Raster datasets represent geographic features by dividing the world into discrete square or rectangular cells laid out in a grid. Each cell has a value that is used to represent some characteristic of that location.

Raster -- One of three primary datasets in the Geodatabase

Raster datasets are commonly used for representing and managing imagery, digital elevation models, and numerous other phenomena. Often rasters are used as a way to represent point, line, and polygon features. In the example below, you can see how a series of polygons would be represented as a raster dataset.

Feature classes can be represented and used as raster layers in GIS

Rasters are interesting for at least two reasons: one, they can be used to represent all geographic information (features, images, and surfaces) and two, they have a rich set of analytic geoprocessing operators. Therefore, in addition to being a universal data type for holding imagery in GIS, rasters are also heavily used to represent features enabling all geographic objects to be used in raster-based modeling and analysis.

Rasters in the geodatabase

A raster is a set of cells arranged in rows and columns and is a commonly used dataset in GIS. Users typically employ many raster files, yet many users see an increasing need to manage raster data along with their other geographic information in a DBMS. The geodatabase provides a very effective means for raster data management in both file and ArcSDE geodatabases.

Raster management strategies

Two data management strategies for rasters are important:

Geographic properties of raster data

Four geographic properties are typically recorded for all raster datasets. These become useful for georeferencing and help explain how raster data files are structured. This concept is important to understand. It helps explain how rasters are stored and managed in the geodatabase.

Raster datasets have a special way for defining geographic location. Once the cells or pixels can be accurately georeferenced, then it's easy to simply have an ordered list of all the cell values in a raster. This means that each raster dataset typically has a header record holding its geographic properties, and the body of the content is simply an ordered list of cell values.

Geographic properties for a raster typically include

This information can be used to find the location of any specific cell. By having this information available, the raster data structure simply lists all the cell values in order from the upper left cell along each row to the lower right cell as illustrated below.

Conceptual diagram showing the key dataset properties stored in a raster. The main content in each raster file is an ordered list of cell values.

The raster block table in the geodatabase

Raster data is typically much larger in size than features and requires a side table for storage. For example, a typical orthoimage can have as many as 6,700 rows by 7,600 columns (more than 50 million cell values).

To get high performance with these larger raster datasets, a geodatabase raster is cut up into smaller tiles (referred to as blocks) with a typical size of around 128 rows by 128 columns or 256 x 256. These smaller blocks are then held in a side table for each raster. Each separate tile is held in a separate row in a block table as shown below.

Images are tiled into small blocks which are stored in a side table
This simple structure means that only the blocks for an extent need to be fetched when they are needed instead of the entire image. In addition, resampled blocks used to build raster pyramids can be stored and managed in the same block table as additional rows.

This enables rasters of enormous sizes to be managed in a DBMS and to produce very high performance and multiuser, secure access.

Extending rasters

Rasters are heavily and increasingly used in GIS applications. The geodatabase can manage rasters for many purposes: as individual datasets, as logical collections of datasets, and as picture attributes in tables.

A number of geodatabase capabilities enable users to extend how they manage their raster information as follows:

Working with rasters in the geodatabase
Use If you need to
Raster Datasets

Manage very large, continuous image datasets and image mosaics.
Raster dataset

Raster Catalogs

Accomplish a number of purposes, including
  • Manage a tiled image layer, where each tile is a separate image.

  • Raster catalog of tiled images
  • Manage any series of images in a DBMS.
  • Raster Catalog ofa Random Collection of Images
  • Manage a raster time series.
  • Raster Catalog for a Time Series of Images
Raster Attribute Columns in Tables

Store pictures or scanned documents as attributes in tables.
Rasters and pictures as attributes in tables

Image Service Definition Publish image services for raster data collections in files on disk, in image catalogs, and in geodatabases.

An Image Service Definition specifies the collection of raster datasets, a series of image processing steps, and their display properties.

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