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International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XXXV, Part B4. Istanbul 2004 
  
Settlement areas (residential area, industrial and commercial 
area etc.) are formed by close (indiscernible at target scale) 
buildings in dense areas during data collection or 
generalization. General character of an area (urban area, 
suburban area, rural area) is preserved. A long list on 
generalization constraints for buildings and settlement areas 
is given in AGENT Cons. (1998). Surrounding roads of 
settlement areas must be generalized because they create 
border for building blocks. Geometric accuracy and road 
characteristics are preserved within scale limits. Besides, 
internal conflicts must be eliminated, being generated by 
symbology and important parts of roads should be 
emphasized especially in sinuous roads. Another critical 
question is how to generalize road networks since it will be 
very dense otherwise. Perceptual grouping principles 
proposed by Thomson and Richardson (1999), and structural 
representation by graph principles proposed by Jiang and 
Claramunt (2002) can be considered for this purpose. 
Miller (1990) analysed German topographic map series and 
found some facts about buildings and settlement areas, given 
in Table 1 and Table 2. His research shows us contextual 
character of cartographic generalization with the different 
changes in building quantity in dense and scattered settlement 
areas and also different size changes of buildings. 
  
  
  
  
  
  
Scale Roads Buildings Settlement 
Areas 
1:5K no change | no change no change 
125K | x2-x4 little change no change 
1:50K | x4-x8 x 1.5-x2 x12 
1:100K | x6-x16 x2-x4 x].5 
1:200K | x 32 x4-x8 x 2 
  
  
  
  
  
  
Table 1. Size changes for roads, buildings and settlement 
areas (Müller, 1990). 
  
  
Scale Dense Settlement Scattered 
Areas Settlement Areas 
1:5K no change no change 
  
1:25K | 96 60-80 preserved 
1:50K | % 30-40 preserved 
1:100K | % 10 amalgamated 
in blocks 
1:200K | % 0-3 amalgamated 
in blocks 
no change 
% 80 preserved 
% 30-50 preserved 
  
  
  
% 0-10 preserved 
  
  
  
  
  
Table 2. Changes in building quantities in dense and scattered 
settlement areas (Müller, 1990). 
Ormbsy and Mackaness (1999) propose phenomenological 
approach for generalization regarding geometry, semantic 
meaning and interrelationships of objects. Mackaness and 
Ruas (1997) states that decisions of generalization depend on 
an understanding of geographical situation (context) and 
geographical context must be made explicit for successful 
automated cartography. Brassel and Weibel (1988) 
mentioned from this in their generalization model as structure 
recognition. 
189 
3. A CASE STUDY FOR CARTOGRAPHIC 
GENERALIZATION OF BUILDINGS AND 
* SETTLEMENT AREAS 
3.1 General Considerations and Approaches for the 
Generalization 
In this case study, LAMPS2 software and its programming 
language Lull is used. Here generalization of roads and road 
networks are given in a limited focus while generalization of 
buildings and settlement areas are dealt with in detail. 
Sequence and selection of generalization operations, and 
parameter selection are important since they can cause 
different design solutions for target map. Therefore, a logical 
approach should be used in determining generalization 
sequence and parameters considering possible effects on each 
other. 
In road generalization, basic operations are simplification, 
smoothing and selection (of subset of road network) 
respectively. Besides, displacement and local enlargement 
can sometimes be necessary. 
In building and settlement area generalization, operations are 
collapse, symbolization, simplification, enlargement, 
amalgamation, aggregation,  typification, elimination, 
displacement. 
To characterise the buildings, some shape measures are 
generated, which are compactness, rectangularity, convexity, 
elongation, corner number, granularity, orientation. 
In the first approach we tried, settlement areas were collected 
and stored as a whole and they have no direct interaction with 
roads. In general roads create boundaries for settlement 
blocks and give a possibility for controlling the 
generalization in manageable parts. Independent 
generalization of roads, buildings and settlement areas can 
create some problems such as very small parts of settlement 
area objects falling within a settlement block i.e. the area 
surrounded by roads, after road generalization and 
symbology. Besides we did not have the possibility of 
analysing the areas bounded by roads for the decisions in 
some building generalization operations such as aggregation, 
amalgamation, typification and displacement. So, the results 
were partly satisfactory. To solve these problems, we create 
settlement blocks using road segments after creating buffers 
on generalized roads at the symbol sizes giving in the 
specification (GCM, 2002) by regarding target scale and then 
partition existing settlement areas according to these blocks. 
Thus, building and settlement area generalization problem is 
converted to giving appropriate generalization decisions 
within each block. 
To characterise the blocks, density, number of buildings, 
number of dominant buildings, biggest building, average 
building, smallest building, common building type, common 
building total area, total settlement area, number of 
settlement area object, black and white ratio etc. are 
computed. 
Another question rising is how we will give these decisions 
optimally. As stated before, geographical context must be 
made explicit for successful generalization decisions. Among 
solutions to this problem are minimum spanning tree 
(Regnauld, 1996), Delaunay triangulation (Jones, 1997;