Figure 5 - Population Density 1980 (inhab. per km?) - Natural breaks classification
acima de 1500
In the development of this work, it can observed
that the utilization of DTM's to visualize and classify
statistical information has some advantages. In the DTM
the unclassed information are stored, and the user can
access the data, without losing details that are
generalized and simplified when the data are classified.
The DTM is more useful to user, instead of a unclassed
choropleth map, because the user can generate any
classification map that he/she needs, without losing the
original data. In this way, the user doesn't need
interpreting the unclassed information, he/she will
interpret the results of the classification that he/she
automatically generated.
The result of the classification of statistical
information, using DTM slicing in this digital model, is
displayed in the screen, by a choropleth map, because
the digital model stores constant values in the
enumeration areas. When the DTM slicing is developed,
the result contours of the classification DTM are the
boundary areas itself. This fact permits to eliminate the
necessary work when the data are classified separately,
and then each class is associated with the correspond
enumeration unit to generate the map. Even with
automatic procedure, the DTM slicing avoids this search.
If the boundary enumeration units is stored in a
vector structure, it is possible overlap the classified image
with the boundary map. This permits the user to identify
the units that correspond represented classed, as shown
in figures 3, 4 and 5.
700
4. ARITHMETIC OPERATIONS WITH RECTANGULAR
GRIDS
In the SGI, it is possible to realize arithmetic
operations with two rectangular grids. Among this
operations are: subtraction, addition, multiplication,
division, mean. The subtraction operation between two
grids is advantageous for representation of statistical data
with DTM. If the user has statistical data of two different
periods, he/she can generate two grids, for each period,
and subtracting the grids, analyse the variation of
phenomena in that period.
A exemple that presents the population growth,
demonstrates this possibility to analyse statistical data.
This exemple about the period between 1980 and 1991 is
shown in figure 6. The procedure consists of:
e generating the two grids;
e subtrating from the 1991's grid the1980's grid values.
The resultant grid represents the population growth in
the period;
e visualizing this grids in 3D;
e slicing this DTM to observe the classes of population
growth.
This classes can be used to specific analyses
the user needs to develop. Figure 6 presents the
choropleth map that represents the population growth in
the periods mencioned above. This operation permit, for
exemple, to observe that there was populational reduction
in Adamantina region, between -3 to O inhab. per km”,
and high population growth in Säo Paulo and Campinas
regions, between 200 to 350 inhab. per km.
International Archives of Photogrammetry and Remote Sensing. Vol. XXXI, Part B4. Vienna 1996
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