WÊÊÊÊÊÊÈËttÈÊÊÊÊÊÊtÊtÊ&
conceptual models involving geographic relationships
can be performed (i.e. land suitability/capability).
This facilitates both scientific investigation and
policy analysis criteria over large areas in short
periods of time.
7) Change analysis can be efficiently performed
for two or more different time periods.
8) Interactive graphic design and automated
drafting tools can be applied to cartographic design
and production.
9) Certain forms of analysis can be performed cost
effectively that simply could not be done
efficiently if performed manually.
10) There is a resultant tendency to integrate data
collection, spatial analysis, and decision-making
processes into a common information flow context.
This has great advantage in terms of efficiency and
accountability.
Evaluating the capability of the techniques, as
well as understanding the limitations of the
systems, will permit the spatial scientist
(assessor) to determine if a GIS can provide answers
to spatial assessment questions. Knowledge of the
basic data elements will help in the design of
future GIS and avoid duplication or "reinvention of
the wheel." The capabilities of a GIS for
geographic problem solving are tremendous if systems
are designed properly and output is optimally
utilized. Uses of Geographical Information Systems
are then only limited to the articulation of the
problem to be studied and the availability of
reliable data.
Many GIS have six primary functions in common: 1)
data entry, 2) encoding, 3) preprocessing, 4) data
base management, 5) spatial/statistical analysis and
modeling and 6) statistical/graphic output (Myers,
1985, Brumfield, 1983, 1985) (fig. 2; see next
page).
5 DATA GATHERING
Data gathering (i.e., selection) procedures of GIS
development are the most important methodological
consideration for GIS design outside of establishing
the overall information needs of the user. This
step is vital, because the type of data included and
the scale of data resolution will determine the
quality and usefulness of the information generated.
Data accuracy must also be considered in terms of
data gathering procedures, for accuracy is relative
to the scale of data compilation (fig. 3).
6 DATA ENTRY/ENCODING/PREPROCESSING
The largest portion of time and energy invested in
developing a GIS system is in obtaining, entering,
converting, and storing data. Useful data exist in
various forms such as tabular, graphical, digital
and remotely sensed video/digital. A primary
problem of a GIS system, therefore, becomes the
integration of these various forms into a single
computer compatible format (fig. 4).
Spatial data are referred to as layers, fields or
variables. Representation of these spatial entities
must retain two basic characteristics of the
original when the information is to be utilized in
automated GIS processing: 1) the actual variable or
characteristic, such as its name or value, and 2)
its spatial location, or where it resides in
geographical space (Dangermond, 1984).
Spatial data layers exist as information in one of
four possible states: points, lines, surfaces, and
polygons. These layers have their geographic
components encoded by one of two basic techniques:
vector/polygon format or raster/grid cell format.
Vector form is created by assigning x,y coordinates
to various points along a line or polygon.
Cartographic entries into digital format are
translated point for point and line for line (Marble
and Peuquet, 1983). Raster form is located by its
position on a predetermined spatial lattice or grid
cell system.
These two forms of data transformation or geo
coding each have their advantages and limitations.
Vector format depicts spatial information more
accurately since it is point referenced data in N
dimensional math coordinate space (e.g. x,y) and is
more compatible with statistical analysis (Marble
and Peuquet, 1983). Vector format results in less
data volume, however, it requires more computer
processing time for analysis. Raster format results
in a loss of geographic specificity, however,
manipulation and processing efficiency is higher.
Vector representation refers to points whose
positions are defined by the number of axis in
coordinate space. Raster format represents a
defined area, including the point position in
coordinate space (e.g., AVHRR pixels). Spatial data
modeling procedures are less complicated with raster
because it provides more accurate registration, yet,
Figure 4
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