nbul 2004 
ing to 
ation” 
is for 
S obe: 
'ed, to 
letion 
imple 
) the 
novel 
e of a 
1 of a 
ertices 
street 
niques 
ed in 
type, 
tation 
ers of 
ids are 
SOK), 
f their 
blocks 
000 sq 
ria are 
secting 
ration, 
other. 
led. 
on are 
%. The 
> 1.65, 
<= area 
| before 
reserve 
=f. 
n sized 
416 sq 
m and 
see first 
io of its 
t square 
„m — in 
ng their 
z 
ers) of 
1e. The 
ads (see 
Create voronoi diagrams (polygons) using the vertices 
of buildings and blocks. and combine them if they 
intersect with the buildings in same cluster. In case a 
voronoi polvgon contains two buildings in different 
clusters. then divide the polygon. 
Compute voronoi density, i.e. the ratio of total area of 
single buffers of buildings at same cluster and area of 
voronoi polygon. 
Check block density, if very dense(>%90), copy block 
as settlement area. 
Find close buildings to settlement area, check voronoi 
density of the polygon which the clusters of buildings 
are within and if the density >= 55% and the number of 
remaining buildings in the cluster <= 2 then aggregate 
(re-classify and amalgamate) all buildings in the cluster 
with the settlement area, otherwise aggregate only close 
buildings with it. Remaining buildings will be typified if 
their shapes are similar otherwise amalgamated or 
displaced (see next step). 
Simplify settlement areas. ^ Aggregate holes with 
settlement area. 
Check voronoi density of each polygon in the blocks 
(Figure 2) and displace if the density « 5596, otherwise 
typify or amalgamate. Typification distance = 35 m 
(minimum symbol granularity / 2 + minimum separation 
distance — 1:50K) if 55% <= density < 90%, 
typification distance = 35 * Jvoronoi density [90 if 
density >= %90. What will happen in neighbouring 
polygons may sometimes have effect on decisions but 
not considered here. 
  
  
  
  
  
  
Figure 2. Density of voronoi polygons (voronoi_density) 
Apply amalgamation if the clusters have buildings with 
different from square or rectangle. Before 
amalgamation, orientations of buildings can be checked 
and small ones may be perpendicularly or parallelly 
rotated from its nearest point to the other building if 
their orientations are rather different or if it does not 
  
191 
International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XXXV, Part B4. Istanbul 2004 
intersect another building after rotation. This is another 
point that will be considered later. 
Before typification, check the cluster homogeneity 
according to shape and size. Buildings are mostly 
typified if their shapes are square and sometimes 
rectangle. Latter was not considered in the study, but 
average size may be determined using area and 
elongation, and typification distance can be computed. If 
the shapes are different from square or rectangle, re- 
create the clusters including similar shapes. We do not 
change parameter or voronoi polygon here. This might 
be considered before clustering we can then not have 
direct. information about conflicts if they are in a 
separate polygon. In the situation we preferred, the 
buildings important from semantic and/or geometric 
aspects will be given priority. In case of over density, 
unimportant buildings with different semantic meaning 
may be eliminated. This was also not considered in the 
study. 
Collapse relevant buildings, namely change their 
geometry to point. Hierarchical clustering by 
dendrogram is done using collapsed (changed to points) 
buildings before typification (Figure 3). The 
dendrogram is built by repeatedly finding the two 
closest points (according to typification distance) being 
considered by the process, adding them to the tree, 
creating a new node to represent the cluster defined by 
the two new nodes. This new, average node is then 
added back into the pool being considered for finding 
the closest pair. In this way, the number of nodes in the 
pool is always reduced, as two are replaced by one 
(Laser-Scan, 2001). 
  
  
  
  
Figure 3. Clustering of buildings using dendrograms 
Then, they are typified using mean points (average 
coordinates) (Figure 4). After typification, building 
symbols are rotated parallelly to the nearest road. In this 
case they may be close to each others. To prevent this, 
nearest distances among building polygons instead of 
points need to be considered, however this can possibly 
get the strategy more difficult.