on 
  
Figure 6 - Population growth between 1980 and 1991 (inhab. per km?) 
a 
a 
a 
a 
à a 
EX 100 a euug 
eps a 350 
5. CONCLUSIONS 
With the produced DTM's, from populational 
density data sets, the user can retrieve information about 
a specific geographic position of the study area. 
Moreover, the user can visualize any classification he/she 
wants through DTM slicing. This fact shows that 
conventional Cartography is more limited than eletronic 
Cartography, for certain types of phenomena. Also it 
becomes clear that this representation is feasible, when 
digitally modeled. In conventional Cartography, 
population density is usually displayed with choropleth 
maps. On those maps, before the data are presented, the 
information is classified, and, therefore, it is generalized. 
So, the user can retrieve only processed information, and 
this information is restricted to only one classification. 
In this work, populational density data are shown 
in some maps generated through DTM. But other kind of 
statistical information can be generating, classifing, 
analysing and operating with DTM techniques. In the 
same way that populational density was presented, 
analises using disease rate, infant mortality rate, crop 
yield per acre, and so on, can be performed. 
701 
  
REFERENCES 
BURROUGH, P. A., 1986. Principles of Geographical 
Information Systems for Land Assessment. Clarendon 
Press, Oxford, 193p. 
DENT, B.D., 1985. Principles of Thematic Map Desing. 
Addison-Wesley, Reading, Mass. 387p. 
ICG - Instituto Geografico e Cartografico, Secretaria de 
Estado de Economia e Planejamento, Estado de Sao 
Paulo, 1984. Mapa de Divisáo Municipal e Distrital do 
Estado de Sáo Paulo. 
SEADE - Fundaçäo Sistema Estadual de Análise de 
Dados, 1992. Anuario Estatístico do Estado de Säo 
Paulo. pp 70-71. 
SEADE - Fundaçäo Sistema Estadual de Anâlise de 
Dados, 1994. Anuario Estatístico do Estado de Säo 
Paulo. pp 9-14. 
International Archives of Photogrammetry and Remote Sensing. Vol. XXXI, Part B4. Vienna 1996