Extensions > Spatial Analyst > Understanding raster data
The composition of a raster dataset |
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Release 9.1
Last modified April 18, 2005 |
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Raster data is generally divided into two categories, thematic data and image data. The values in thematic raster data represent some measured quantity or classification of a particular phenomenon, such as elevation, transportation, pollution concentration, population, and land cover. For example, in a land cover map the value 5 may represent forest and the value 7 may represent water. The values of cells in an image represent reflected or emitted light or energy, such as that of a satellite image or scanned photograph. In most cases, they require interpretation prior to use in analysis. The ArcGIS Spatial Analyst analysis tools are primarily intended for use on thematic raster data. All Spatial Analyst functions process the first band of any raster dataset.
This topic provides an overview of raster data and how it is created.
A raster dataset, like a map, describes the features and characteristics of an area and their relative positions in space. Because a single raster typically represents a single theme, such as land use, soils, roads, streams, or elevation, multiple raster datasets should be produced to fully depict an area.
A raster dataset is made up of cells. Each cell is a square that represents a specific portion of an area. All cells in a raster dataset must be the same size. The cells in a raster dataset can be any size that you want, but they should be small enough to accomplish the most detailed analysis. A cell can represent any size of area, for example, 30 hectares, a square kilometer, 10 square meters, or even a square centimeter.
Cells are arranged in rows and columns, an arrangement that produces a Cartesian matrix. The rows of the matrix are parallel to the x-axis of the Cartesian plane, and the columns are parallel to the y-axis. Each cell has a unique row and column address. All locations in a study site are covered by the matrix.
Each cell is assigned a specific value to identify or describe the class, category, or group to which the cell belongs (categorical data). Examples of categorical data include soil type, soil texture, land use class, water body type, road class, and housing type. Categorical data is often referred to as discrete data.
A value can also represent the magnitude, quantity, distance, or relationship of the cell on a continuous surface. Elevation, slope, aspect, noise pollution from an airport, and pH concentration from a bog are all examples of continuous surfaces.
For rasters representing images and photographs, the values can represent colors or spectral reflectance.
Both integer and floating-point values are supported in Spatial Analyst. Integer values are best used to represent categorical (discrete) data, and floating-point values to represent continuous surfaces.
Learn more about discrete and continuous data
Learn more about values and what they represent
Any two or more cells with the same value belong to the same zone. A zone can consist of cells that are connected, disconnected, or both. Zones whose cells are connected usually represent a single feature of an area, such as a building, lake, road, or water body. Assemblages of entities, such as forest stands in a state, soil types in a county, or the single-family houses in a town, are features of an area that will most likely be represented by zones made up of many disconnected groups of connected cells (regions).
Every cell on a raster belongs to a zone. Some raster datasets contain only a few zones, while others contain many.
Each group of connected cells in a zone is considered a region. A zone that consists of a single group of connected cells has only one region. Zones can be composed of as many regions as necessary to represent a feature—the number of cells that make up a region has no practical limits. ArcGIS Spatial Analyst provides the tools needed to turn regions into individual zones. In the previous raster dataset example, Zone 2 consists of two regions, Zone 4 of three regions, and Zone 5 of one region.
If a cell is assigned the NoData value, then no information is available or insufficient information about the particular characteristics of the location that the cell represents. The NoData value, sometimes referred to as the null value, is treated differently from any other value by all operators and functions.
Cells with NoData values are processed in one of two ways:
- Spatial Analyst will assign NoData to the output cell location if a NoData value exists for the location in any of the inputs in an operator or local function, in its neighborhood in a focal function, or in its zone in a zonal function.
- Spatial Analyst will ignore the NoData cell and complete the calculations with all valid values. This second option, to ignore the NoData cell, is not possible when using operators between two datasets or with local functions. When a NoData cell is within the neighborhood of a cell in a focal function or a zone of a zonal function, by default, the sum, median, variety, majority, or minority of all cells with known values can be calculated and assigned to the output raster dataset (this default can be overridden).
The associated table
Integer (discrete or categorical) raster datasets usually have an attribute table associated with them. The first item in the table is Value, which stores the value assigned to each zone of a raster. The second item is Count, which stores the total number of cells in the dataset that belong to each zone. Both Value and Count are mandatory items.
Floating-point (continuous) raster datasets usually do not have a table associated with them because most, if not all, cell values are unique, and the nature of continuous data excludes other associated attributes.
An essentially limitless number of optional items can be incorporated into the table to represent the other attributes of the zone.
Each raster dataset must have a name to distinguish it from the other raster datasets in a database. All access to a raster dataset is performed through its name, which must be used consistently in all expressions.
