187
How Does the Scale of the Data Affect the Map (and Vice Versa)?
as a representative fraction (RF). An example of an RF would be a map scale
of 1:24000—a measure of one unit on the map would be equal to 24,000 units
in the real world. For instance, measuring one inch on the map would be the
same as 24,000 inches in the real world or one foot on the map is equal to
24,000 feet in the real world (and so on).
Maps are considered large-scale maps or small-scale maps depending
on that representative fraction. Large-scale maps show a smaller geographic
area and have a larger RF value. For instance, a 1:4000-scale map would be
considered a large-scale map—due to the larger scale, it would show a smaller
area. The largest-scale map you could make would be 1:1—where one inch
on the map was equal to one inch of measurement in the real world (that is,
the map would be the same size as the ground you were actually mapping—a
map of a classroom would be the same size as the classroom itself). Conversely, a small-scale map would have a smaller RF value (such as 1:250,000) and
show a much larger geographic area.
For instance, on a very small-scale map (such as one that shows the entire
United States), cities would be represented by points, and likely only major
cities will be shown. On a slightly larger-scale map (one that shows all of the
state of New York), more cities are likely to be shown as points, along with
other major features (additional roads can be shown as lines, for example). On
a larger-scale map (one that shows only Manhattan), the map scale allows for
more detail to be shown—points will now show the locations of important features and many more roads will be shown with lines. On an even larger-scale
map (one that shows only a section of lower Manhattan) buildings may now
be shown as polygon shapes (to show the outline or footprint of the buildings)
instead of points, and additional smaller roads may also be shown with lines.
The choice of scale will influence how much information the map will be
able to convey and what symbols and features can be used in creating the map
in GIS. Figure 7.1 on page 188 shows a comparison between how a feature (in
this case, Salt Lake City International Airport) is represented on large-scale
and small-scale maps. The actual sizes of the maps greatly vary, but you can
see that more detail and definition of features is available on the larger-scale
map than on the smaller-scale one (also see Hands-on Application 7.1: Powers
of 10 – A Demonstration of Scale, page 188, for a cool example of visualizing
different scales).
The same holds true for mapping of data—for instance, the smaller-scale
map of all of the state of New York could not possibly show point locations of
all of the buildings in Manhattan. However, as the map scale grows larger, different types of information can be conveyed. For instance, in Figure 7.1, the
large-scale map can convey much more detail concerning the dimensions of
the airport runways, while the smaller-scale map has to represent the airport
as a set of simplified lines. If you were digitizing the lines of the airport runways, you’d end up with two very different datasets (one more detailed, one
very generalized).
This relationship between the scale of a map and data that can be derived from a map can be a critical issue when dealing with geospatial data. For
RF representative
fraction—a value
indicating how many
units of measurement
in the real world are
equivalent to how
many of the same units
of measurement on a
map.
large-scale map a
map with a higher
value for its
representative fraction.
Such maps will usually
show a small amount of
geographic area.
small-scale map a
map with a lower value
for its representative
fraction. Such maps will
usually show a large
amount of geographic
area.
How Does the Scale of the Data Affect the Map (and Vice Versa)?
as a representative fraction (RF). An example of an RF would be a map scale
of 1:24000—a measure of one unit on the map would be equal to 24,000 units
in the real world. For instance, measuring one inch on the map would be the
same as 24,000 inches in the real world or one foot on the map is equal to
24,000 feet in the real world (and so on).
Maps are considered large-scale maps or small-scale maps depending
on that representative fraction. Large-scale maps show a smaller geographic
area and have a larger RF value. For instance, a 1:4000-scale map would be
considered a large-scale map—due to the larger scale, it would show a smaller
area. The largest-scale map you could make would be 1:1—where one inch
on the map was equal to one inch of measurement in the real world (that is,
the map would be the same size as the ground you were actually mapping—a
map of a classroom would be the same size as the classroom itself). Conversely, a small-scale map would have a smaller RF value (such as 1:250,000) and
show a much larger geographic area.
For instance, on a very small-scale map (such as one that shows the entire
United States), cities would be represented by points, and likely only major
cities will be shown. On a slightly larger-scale map (one that shows all of the
state of New York), more cities are likely to be shown as points, along with
other major features (additional roads can be shown as lines, for example). On
a larger-scale map (one that shows only Manhattan), the map scale allows for
more detail to be shown—points will now show the locations of important features and many more roads will be shown with lines. On an even larger-scale
map (one that shows only a section of lower Manhattan) buildings may now
be shown as polygon shapes (to show the outline or footprint of the buildings)
instead of points, and additional smaller roads may also be shown with lines.
The choice of scale will influence how much information the map will be
able to convey and what symbols and features can be used in creating the map
in GIS. Figure 7.1 on page 188 shows a comparison between how a feature (in
this case, Salt Lake City International Airport) is represented on large-scale
and small-scale maps. The actual sizes of the maps greatly vary, but you can
see that more detail and definition of features is available on the larger-scale
map than on the smaller-scale one (also see Hands-on Application 7.1: Powers
of 10 – A Demonstration of Scale, page 188, for a cool example of visualizing
different scales).
The same holds true for mapping of data—for instance, the smaller-scale
map of all of the state of New York could not possibly show point locations of
all of the buildings in Manhattan. However, as the map scale grows larger, different types of information can be conveyed. For instance, in Figure 7.1, the
large-scale map can convey much more detail concerning the dimensions of
the airport runways, while the smaller-scale map has to represent the airport
as a set of simplified lines. If you were digitizing the lines of the airport runways, you’d end up with two very different datasets (one more detailed, one
very generalized).
This relationship between the scale of a map and data that can be derived from a map can be a critical issue when dealing with geospatial data. For
RF representative
fraction—a value
indicating how many
units of measurement
in the real world are
equivalent to how
many of the same units
of measurement on a
map.
large-scale map a
map with a higher
value for its
representative fraction.
Such maps will usually
show a small amount of
geographic area.
small-scale map a
map with a lower value
for its representative
fraction. Such maps will
usually show a large
amount of geographic
area.