data user. Certain features may be omitted from the map or spatial database through oversight,
or by design.

Other errors in quantitative accuracy may occur from faulty instrument calibration used to
measure specific features such as altitude, soil or water pH, or atmospheric gases. Mistakes
made in the field or laboratory may be undetectable in the GIS project unless the user has
conflicting or corroborating information available.

c. Sources of variation in data

Variations in data may be due to measurement error introduced by faulty observation, biased
observers, or by mis-calibrated or inappropriate equipment. For example, one can not expect
sub-meter accuracy with a hand-held, non-differential GPS receiver. Likewise, an incorrectly
calibrated dissolved oxygen meter would produce incorrect values of oxygen concentration
in a stream.

There may also be a natural variation in data being collected, a variation that may not be
detected during collection. As an example, salinity in Texas bays and estuaries varies during
the year and is dependent upon freshwater influx and evaporation. If one was not aware of
this natural variation, incorrect assumptions and decisions could be made, and significant error
introduced into the GIS project. In any case, if the errors do not lead to unexpected results,
their detection may be extremely difficult.

3. Errors Arising Through Processing

Processing errors are the most difficult to detect by GIS users and must be specifically looked
for and require knowledge of the information and the systems used to process it. These are
subtle errors that occur in several ways, and are therefore potentially more insidious,
particularly because they can occur in multiple sets of data being manipulated in a GIS project.
a. Numerical Errors

Different computers may not have the same capability to perform complex mathematical
operations and may produce significantly different results for the same problem. Burrough
(1990) cites an example in number squaring that produced 1200% difference. Computer
processing errors occur in rounding off operations and are subject to the inherent limits of
number manipulation by the processor. Another source of error may from faulty processors,
such as the recent mathematical problem identified in Intel's Pentium(tm) chip. In certain
calculations, the chip would yield the wrong answer.

A major challenge is the accurate conversion of existing to maps to digital form (Muehrcke
1986). Because computers must manipulate data in a digital format, numerical errors in
processing can lead to inaccurate results. In any case, numerical processing errors are
extremely difficult to detect, and perhaps assume a sophistication not present in most GIS
workers or project managers.