This topic provides an overview of some of the terminology you are going to encounter when working with raster data in ArcGIS. Not all of these terms are specific to ArcGIS.
For more information, a glossary of remote sensing and image processing terms provides definitions of common terms used in ArcGIS, by image processors, analysts, and remote sensing professionals. A deeper understanding of the meaning behind the definitions and how they relate and affect each other in the broader context of remote sensing image processing will help you achieve optimum results for your applications.
Vocabulary | Description |
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Raster versus image | Raster and image are two terms that are often interchanged. An image (or imagery) is a two-dimensional, pictorial representation. It is not dependent on a wavelength or remote-sensing device, such as a satellite, aerial camera, or terrain sensor. An image is displayed on your screen or printed. You view images. A raster is the data model that describes how an image is stored. A raster defines the pixels (cells) in rows and columns, the number of bands, and the bit depth that compose the image. When you view a raster, you are viewing an image of that raster data. You might also hear rasters being referred to as cell-based datasets, but this is not typically used within ArcGIS documentation. |
Cells and pixels | Pixel is often used synonymously with cell. Both cell and pixel refer to the smallest unit of information in raster data. Pixel is an abbreviation for picture element and is often used when describing imagery, whereas cell is often used when describing raster data. Cells and pixels have a dimension and value. They represent information, such as temperature, soil types, elevation, and real-world features, such as parks, lakes, and buildings. |
Resolution, scale, and cell size | Resolution, scale, and cell (pixel) size can all refer to how large a feature is in raster data, but it's not that straightforward. For example, there are four types of resolution:
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Bands | Rasters can have one or more bands. Multiband rasters are often referred to as multispectral images, and rasters with up to hundreds of bands are often referred to as hyperspectral images. A single-band raster dataset represents a single phenomenon, such as elevation, or only one wavelength range within the electromagnetic spectrum, such as a black-and-white aerial photograph. Bands often relate to spectral resolution. |
Raster format versus raster type | A raster format defines how pixels are stored, such as number of rows and columns, number of bands, actual pixel values, and other raster format-specific parameters. The raster type helps identify metadata, such as georeferencing, acquisition date, and sensor type, along with a raster format. See the list of supported raster dataset formats. |
Raster product | Raster products are designed to make adding imagery from specific sensors or data providers to your map simpler because each raster product has a unique set of enhancements and band combinations to provide an optimal view of your data. Raster products appear in the Catalog in place of the metadata files associated with specific vendor products. It is the information in the metadata files that is used to generate the raster products, such as satellite imagery like Landsat 7 or QuickBird. A raster product appears in the Catalog with its own unique icon: . |
Rendering | Raster datasets can be displayed, or rendered, in your map in many different ways. Rendering is the process of displaying your data. How a raster dataset is rendered depends on what type of data it contains and what you want to show. Some rasters have a predefined color scheme—a color map—that ArcMap automatically uses to display them. For those that don't, ArcMap chooses an appropriate display method that you can adjust as needed. |
Functions | Functions enable you to define processing that will be applied to one or more rasters, but this processing is not permanently applied to the rasters; it is applied on the fly as the rasters are accessed. |
Methods of storage: Data models | |
Raster dataset |
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. Raster datasets are represented with the icon. |
Mosaic dataset |
A mosaic dataset is a collection of raster datasets (images) stored as a catalog and viewed or accessed as a single mosaicked image or individual images (rasters). 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 and allows fast queries to enable selections. Mosaic datasets are represented with the icon. |
Raster catalog |
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. Raster catalogs are represented with the icon. |
Managed versus unmanaged | Raster data can be stored in a geodatabase using either a managed or unmanaged model. Managed raster data follows the storage model of the enterprise or file geodatabase, and unmanaged raster data follows the storage model of the personal geodatabase. |
Using a mosaic in ArcGIS | |
There are several ways in which the term mosaic is used in ArcGIS:
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