Mastering the Concepts
GIS Concepts
Representing real-world objects on maps
To work with maps on a computer requires developing methods to store different types of map
data and the information associated with them. Map data fall into two categories: discrete and
continuous.
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| Mastering ArcGIS |
Discrete data are objects in the real world with specific locations or boundaries, such
as cities, roads, or soils units. Continuous data represent a quantity that is measured and recorded
everywhere over a surface, such as temperature or elevation.
Many different data formats have been invented to encode data for use with GIS programs; however, most follow one of two basic approaches: the vector model, which is designed to store discrete data, or the raster model, which is designed to store continuous data. In either approach, the critical task includes representing the information at a point, or over a region in space, using x and y coordinate values (and sometimes z for height). The x and y coordinates are the spatial data. The information being represented, such as a soil type or a chemical analysis of a well, is called the attribute data. Raster and vector data models both store spatial and attribute data, but they do it in different ways.
Both data systems are georeferenced, meaning that the information is tied to a specific location on the earth’s surface using x-y coordinates defined in a standard way: a coordinate system. One can choose from a variety of coordinate systems, as we will see in Chapter 3. As long as the coordinate systems match, we can display any two spatial data sets together, and they will appear in the correct spatial relationship to each other. The vector model Vector data use a series of x-y locations to store information (Fig. 1.1). Three basic vector objects exist: points, lines, and polygons. These objects are called features. Point features are used to Chapter 1
10 Fig. 1.3. Each state is represented by a spatial feature (polygon), which is linked to the attributes. represent objects that have no dimensions, such as a well or a sampling locality.
Many different data formats have been invented to encode data for use with GIS programs; however, most follow one of two basic approaches: the vector model, which is designed to store discrete data, or the raster model, which is designed to store continuous data. In either approach, the critical task includes representing the information at a point, or over a region in space, using x and y coordinate values (and sometimes z for height). The x and y coordinates are the spatial data. The information being represented, such as a soil type or a chemical analysis of a well, is called the attribute data. Raster and vector data models both store spatial and attribute data, but they do it in different ways.
Both data systems are georeferenced, meaning that the information is tied to a specific location on the earth’s surface using x-y coordinates defined in a standard way: a coordinate system. One can choose from a variety of coordinate systems, as we will see in Chapter 3. As long as the coordinate systems match, we can display any two spatial data sets together, and they will appear in the correct spatial relationship to each other. The vector model Vector data use a series of x-y locations to store information (Fig. 1.1). Three basic vector objects exist: points, lines, and polygons. These objects are called features. Point features are used to Chapter 1
10 Fig. 1.3. Each state is represented by a spatial feature (polygon), which is linked to the attributes. represent objects that have no dimensions, such as a well or a sampling locality.
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Line features represent objects in one
dimension, such as a road or a utility line. Polygons are used
to represent two-dimensional areas, such as a parcel or a state.
In all cases, the features are represented using one or more x-y
coordinate locations (Fig. 1.1). A point consists of a single x-y
coordinate pair. A line includes two or more pairs of
coordinates—the endpoints of the line are termed nodes, and
each of the intermediate points is called a vertex. A polygon
is a group of vertices that define a closed area.
The type of object used to represent features depends on the scale of the map. A river would be represented as a line on a map of the United States because at that scale it is too small for its width to encompass any significant area on the map. If one is viewing a USGS topographic map, however, the river encompasses an area and would be represented as a polygon. In GIS, like features are grouped into data sets called feature classes (Fig. 1.2). Roads and rivers are different types of features and would be stored in separate feature classes. A feature class can contain only one kind of geometry—it can include point features, line features, or polygon features but never a combination. In addition, objects in a feature class have information stored about them, such as their names or populations. This information is called the attributes and is stored in a table (Fig. 1.3). A special field, called the Feature ID (FID) or ObjectID (OID), links the
spatial data with the attributes. Each feature’s attributes are stored in one row of the table, and each column has a different type of information, such as population or area. A river and a highway would not be found in the same feature class because their information would be different— flow measurements for one versus pavement type for the other—and would need to be stored in different tables with different columns.
When a state is highlighted on the map, its matching attributes are highlighted in the table, and vice versa. It is this live link between the spatial and attribute information that gives the GIS system its power. It enables us, for example, to create a map in which the states are colored based on an attribute field, such as population (Fig. 1.2). This technique is called thematic mapping and is one example of how linked attributes can be used to analyze geographic information.
Feature classes can be stored in several different formats. Some data formats only contain one feature class. Others, called feature datasets, can contain multiple feature classes that are in some way related to one another. For example, a feature dataset called Transportation might contain the feature classes Roads, Traffic Lights, Railroads, Airports, and Canals. The benefits of the vector data model are many. First, it can store individual features, such as roads and parcels, with a high degree of precision. Second, the linked attribute table provides great flexibility in the number and type of attributes that can be stored about each feature.
The type of object used to represent features depends on the scale of the map. A river would be represented as a line on a map of the United States because at that scale it is too small for its width to encompass any significant area on the map. If one is viewing a USGS topographic map, however, the river encompasses an area and would be represented as a polygon. In GIS, like features are grouped into data sets called feature classes (Fig. 1.2). Roads and rivers are different types of features and would be stored in separate feature classes. A feature class can contain only one kind of geometry—it can include point features, line features, or polygon features but never a combination. In addition, objects in a feature class have information stored about them, such as their names or populations. This information is called the attributes and is stored in a table (Fig. 1.3). A special field, called the Feature ID (FID) or ObjectID (OID), links the
spatial data with the attributes. Each feature’s attributes are stored in one row of the table, and each column has a different type of information, such as population or area. A river and a highway would not be found in the same feature class because their information would be different— flow measurements for one versus pavement type for the other—and would need to be stored in different tables with different columns.
When a state is highlighted on the map, its matching attributes are highlighted in the table, and vice versa. It is this live link between the spatial and attribute information that gives the GIS system its power. It enables us, for example, to create a map in which the states are colored based on an attribute field, such as population (Fig. 1.2). This technique is called thematic mapping and is one example of how linked attributes can be used to analyze geographic information.
Feature classes can be stored in several different formats. Some data formats only contain one feature class. Others, called feature datasets, can contain multiple feature classes that are in some way related to one another. For example, a feature dataset called Transportation might contain the feature classes Roads, Traffic Lights, Railroads, Airports, and Canals. The benefits of the vector data model are many. First, it can store individual features, such as roads and parcels, with a high degree of precision. Second, the linked attribute table provides great flexibility in the number and type of attributes that can be stored about each feature.
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