scale and resolution of data results in a loss of information. As a general
rule, one should only compile data from larger cartographic scales to
smaller cartographic scales, except in special instances, such as using fieldcollected data to validate remotely sensed data. In other words, one cannot
add detail to data, whether it is spatial, temporal, or spectral. This is especially true with remotely sensed data (Lachowski et al. 2000).
With the proliferation of desktop GIS applications, a wealth of spatial
data has become available at our fingertips. This abundance of data may,
however, be a mixed blessing: “The great advantage of map data—that they
are prepackaged and ready for use—is also their chief disadvantage”
(Fosnight et al. 2000). Data can be obtained and used quite easily; however,
the scale and classification might not be suited to a particular project. The
most frequent misuse of map data “is to incorporate them into databases
at scales for which they are not designed” (Fosnight et al. 2000). It is necessary to remember that digital data have accuracies that are no better than
their source maps. For example, a 1 : 1,000,000-scale digital elevation model
(DEM) is not appropriate for use at a 1 : 5,000 scale.
10.2.7 Projections
The geographic projections of spatial data should be described in detail
within data documentation. Making assumptions regarding geographic projection can lead to inappropriate use of data and incorrect results. Spatial
data that are to be used together within the context of a GIS should be of
the same projection. Changing projections involves a resampling of data,
and information can be lost. Therefore, it is useful to know how many times
data have been reprojected and what methods were used.
10.2.8 Attribute Definitions
Good metadata should include concise definitions of data attributes. A
complete understanding of attributes is critical to determining the wise use
of data and the credibility of the results. Definition of variables can range
from simply a full name for a field that has been abbreviated, for example,
m = meters, to describing the criteria used for assigning a certain value, such
as, burn = parcel has burned for more than x amount of the time within the
y time period.
10.2.9 Data Limitations
Users must be made aware of data limitations. Some limitations on appropriate use may be inferred from the characteristics described above, while
others must be explicitly outlined within the documentation. While data
providers have the responsibility of disclosing information regarding the
known limitations of their data, the ultimate responsibility lies with the user
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rule, one should only compile data from larger cartographic scales to
smaller cartographic scales, except in special instances, such as using fieldcollected data to validate remotely sensed data. In other words, one cannot
add detail to data, whether it is spatial, temporal, or spectral. This is especially true with remotely sensed data (Lachowski et al. 2000).
With the proliferation of desktop GIS applications, a wealth of spatial
data has become available at our fingertips. This abundance of data may,
however, be a mixed blessing: “The great advantage of map data—that they
are prepackaged and ready for use—is also their chief disadvantage”
(Fosnight et al. 2000). Data can be obtained and used quite easily; however,
the scale and classification might not be suited to a particular project. The
most frequent misuse of map data “is to incorporate them into databases
at scales for which they are not designed” (Fosnight et al. 2000). It is necessary to remember that digital data have accuracies that are no better than
their source maps. For example, a 1 : 1,000,000-scale digital elevation model
(DEM) is not appropriate for use at a 1 : 5,000 scale.
10.2.7 Projections
The geographic projections of spatial data should be described in detail
within data documentation. Making assumptions regarding geographic projection can lead to inappropriate use of data and incorrect results. Spatial
data that are to be used together within the context of a GIS should be of
the same projection. Changing projections involves a resampling of data,
and information can be lost. Therefore, it is useful to know how many times
data have been reprojected and what methods were used.
10.2.8 Attribute Definitions
Good metadata should include concise definitions of data attributes. A
complete understanding of attributes is critical to determining the wise use
of data and the credibility of the results. Definition of variables can range
from simply a full name for a field that has been abbreviated, for example,
m = meters, to describing the criteria used for assigning a certain value, such
as, burn = parcel has burned for more than x amount of the time within the
y time period.
10.2.9 Data Limitations
Users must be made aware of data limitations. Some limitations on appropriate use may be inferred from the characteristics described above, while
others must be explicitly outlined within the documentation. While data
providers have the responsibility of disclosing information regarding the
known limitations of their data, the ultimate responsibility lies with the user
186
David Hohler et al.