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Proceedings of the Symposium on Global and Environmental Monitoring

driven plotters, and new host minicomputers that the
staff needed to conduct the numerous activities asso
ciated with building and using the TIGER data base.
• To build a computer file containing every known
street and road in the United States (see Notes 1 and 3),
the name (or names) of each, and the range of address
numbers located along each segment of every street in
the 345 largest urban areas of the United States; all the
railroads in the United States; all significant hydro-
graphic features and their associated names; named
landmark areas such as major parks and military
bases; and essential “key geographic locations” such as
named apartment buildings, shopping centers, fac
tories, and office buildings that are important as
alternate ways to address mail.
• To enter and verify the boundaries, names, and
numeric codes for all the geographic entities used by the
Census Bureau to collect and tabulate the results of both
the 1980 and 1990 decennial censuses of the United
States. In doing this, the TIGER data base also includes
most of the more limited set of geographic entities used
for the economic and agriculture censuses of the United
States (U.S. Bureau of the Census, 1985a). (See Figure 1)
The Process
The Census Bureau derived the initial set of information
this data base contains from three primary sources:
1. The 1980 census GBF/DIME-Files — covering less
than 2 percent of the land area but 60 percent of the
people in the United States -- were the primary source
for the Nation’s major urban areas. The GBF/DIME-
Files contained the features, feature names, and ad
dress ranges compiled by the local officials who helped
the Census Bureau create those files over the course of
12 years and two decennial censuses — information
presumed to be basically correct except for changes since
the last update of the GBF/DIME-Files in 1976.
2. A cooperative program with the U. S. Geological
Survey (USGS) -- “the national mapping agency” for the
United States -- provided the primary source for most of
the remaining 98-plus percent of the Nation’s territory
(McKenzie and LaMacchia, 1987). The features in the
USGS files were compiled to National Map Accuracy
Standards using aerial photography that was no more
than 3 years old at the time a particular map was
prepared — and most were prepared during the 1983-1987
project period. This was in contrast to the 1980 census
when the maps used for the 98-plus percent of the Nation
outside GBF/DIME-File areas were “the best the Census
Bureau could find” — often state and local maps with
compilation dates 10, 20, or more years earlier.
3. For Alaska, Hawaii, Puerto Rico, and the other areas
for which the Census Bureau created the TIGER data
base (see Note 1), the Census Bureau digitized available
maps — typically published USGS quadrangles ranging
in scale from 1:20,000 for Puerto Rico to 1:250,000 for the
remote areas of Alaska. These maps varied widely in
To make the information in the initial TIGER data base
more current for 1990 census operations, the geographic
staff in the Census Bureau’s 12 regional offices collected
the latest available maps from local officials across the
United States. The geographic staff then compared the
information shown on those local maps with the
information contained in the developing TIGER data
base. Where there were differences, they inserted new
streets and roads, and appended street and road names
to those new features when the local maps showed
names for them. The geographic staff also used those
locally collected source maps to append names to all the
streets and roads that entered the TIGER data base from
the USGS files; those files came to the Census Bureau
with no names. This work was done over a period of 4
years, using quality control checks designed to keep the
number of clerically induced errors at “normal” levels
(Marx and Saalfeld, 1987).
This development task is complete; the goal of
supporting the 1990 census, nearly met. The resulting
computer file contains a latitude and longitude
coordinate value for each of the more than 28 million
feature intersection and end points that define the nearly
40 million feature segments that outline the approx
imately 12 million polygons in this giant "connect-the-
dots" map of the United States. The foregoing leads,
more logically at this point, to a discussion about
geographic information systems (GIS).
What is a GIS? The debate goes on endlessly. Some
argue that the only “true” GIS is a computer system that
processes “overlays” of information. Others contend that
a GIS must include natural resources data. Still others
debate the level of accuracy one needs in the coordinates
that define the features and data polygon boundaries
comprising the GIS. Without endorsing or excluding
any of these definitions, providing a more generic defini
tion may help the average citizen understand the value
of a GIS. The more generic definition is:
A computer system that helps people discover
relationships between and among sets of geographi
cally-referenced data that they could not see or
understand easily without the aid of this technology.
Whichever definition one accepts, the facts show that
GIS technology is helping the United States and many
other countries around the world study the numerous
environments and changes that surround us. These
enormous amounts of money and energy are being spent
under the rubric of “global change.”
In the more generic context suggested above, it seems
that the users of most GIS products available thus far
have focused on physical features and natural resources
data. In doing so, they typically have ignored one other
important factor that surrounds us — people!
People in a GIS
People inhabit almost every part of the earth. They
either affect what is going on or are affected by what is
going on. This is especially relevant if one accepts the
predictions of many demographic experts who project
that in the next 50 years, the earth’s population will
double (Torrey, et al., 1989). They also project that this
growth will continue the dramatic shift from rural
settlement to urban settlement with the urban pop
ulation likely to triple in the same 50 years. Certainly
these shifts are having — and will continue to have — a
significant effect on the world in which we live. For this
reason, it is desirable that people be a “layer” in a GIS.
Perhaps the omission of “people” information from most
GIS studies has resulted because this “people” infor
mation traditionally has not been in a form that com
puters could process conveniently in a GIS context.
With natural resources data from satellite imagery, the
opposite has been true. It streams down from the sky
with, as Carl Sagan would say, its "billions and billions”
of pixels. The pixels in a satellite image basically
portray little polygons or rectangular sections of the
earth’s surface. The resolution of those pixels varies
from “coarse” to “fine,” depending on the sensitivity of
the instruments in the satellite transmitting them.