Figure 2 - Regions that have more 200 inhabitants per km? 
  
um à a 208 
BE 200 a 2000 
3. GENERATING MAPS WITH DISTINCTION 
CLASSIFICATION 
In producing DTM's from population density data 
sets, the user can retrieve information about a specific 
geographic position for the study region. Moreover, the 
user can visualize any classification that he/she wants, or 
specific geographic analyses, through DTM slicing. Each 
DTM slicing operation generates a thematic layer that 
represents a population density map. 
In this work, some maps were obtained with 
DTM slicing, to exemplify this possibilities of choropleth 
mapping. In the first exemple (Fig.2) it is shown the map 
698 
    
  
of regions that have more than 200 inhabitants per km?, 
in 1991. This map was generate classifying the DTM with 
the following classes: O to 200, and 200 to 2000 inhab. 
per km?. Other maps were obtained, with the DTM slicing 
operation, using the following methods for data 
classification (DENT, 1985): constant intervals, natural 
breaks and iterative method. The figures 3 and 4 present 
choropleth maps with constant intervals classification. In 
the first, we consider Sao Paulo population density, to 
observe its influency in the others data. The natural 
breaks classification, analized through the iterative 
method, was developed to generate the choropleth map 
of the figure 5. 
International Archives of Photogrammetry and Remote Sensing. Vol. XXXI, Part B4. Vienna 1996