ISPRS, Vol.34, Part 2W2, “Dynamic and Multi-Dimensional GIS", Bangkok, May 23-25, 2001
5
Ps and goes across
into segments. For
tance between OPs
e the local distance
ength to the whole
, the local skeleton
in Figure 7. The
celeton length, k the
skeleton width.
on skeleton takes
atial distribution and
ling A and B keeps
ting in the distance
ition, we can feel in
eft due to C position
computation will get
>serer than that of A
insistent with visual
ed for one skeleton
ind the normal line
rection between two
used in next section
GENERALIZATION
jping, displacement,
ing model is able to
its. From high level
:tion discusses the
i detail.
condition of conflict
ts : conflict skeleton
rith weighted width
lentified as conflict
ted to one or more
Iding objects. Figure
skeleton and conflict
ifiict skeletons,
ig displacement
nd dark dot.
ject can be assigned
lacent distance, and
d other non-distance
The judgement of conflict building object answers the question of
who will displace. The further question is how far and what
direction the conflict building moves.
If the conflict object has only one conflict skeleton, then the
adjacent direction serves as moving direction. Otherwise, using
vector add operation computes the integrated moving direction.
We suppose each conflict building is attracted by its neighbor
conflict building and the attraction force is equal. When one
building is attracted by neighbors from two opposite direction, or
surrounded by conflict buildings (it means all skeleton related to
one building are conflicted), it will keep unchanged. In actual
application, when the added vector length is shorter than a
threshold, we can think no one direction attraction is strong
enough over other directions and also regard the object as fixed.
Figure 9 expresses the movement direction of conflict object, the
dark arrow symbol representing the displacement direction and
the dark dot representing the building fixed.
For offset length of displacement, firstly we suppose the position
accuracy is not less than half of conflict distance. It means
conflict building moving face to face and meeting together in one
position is not against position accuracy. Parallel with the
displacement direction, draw an extended line from each vertex
of conflict OP and compute the distance between start vertex
and intersection point of extended line and GP boundary. Select
the shortest distance as displacement offset length. This process
guarantees each building moving within its own GP range, not
overlapping with other building’s GP. It means the displacement
will not result in new conflict. This point is very important in
displacement generalization research (Mackness 1994).
The purpose of displacement in building cluster generalization is
to maintain statistic area balance. But generally after
displacement, it is not yet to get two buildings that exactly share
a common seamless boundary, still existing gap area. An
improvement is to execute rotation, but rotation angle and
rotation scope is complex to decide and yet can not resolve
problem completely.
4.4 Progressive Generalization Workflow
The above sections investigate the decision analysis and
Generalized result and growth polygon
4.3 How to Aggregate?
Considering the square characteristics of building shape, the
a 99 re 9 ai ion of displaced buildings has to maintain orgothonal
nature. We use the method of two vertical direction scanning and
filling on the basis of raster data structure, including 6 steps:
finding MBR, rasterizing, scanning and filling lines, scanning
and filling columns, vectorizing, rotating. The whole procedure is
shown in Figure 10.
1> finding MBR, 2> rotating and,
rasterizing
3>scanning and
filling lines
4> scanning, 5> vectorizing
and filling columns
6> rotating to
original direction
Fig. 10. Six steps of building aggregation
This method applies two vertical direction of MBR edge to scan
and fill raster element using the suppose that the MBR edge
direction can represent the main direction of building cluster. It
guarantees that the gap area between neighbor buildings is filled
in the shortest connection.
Fig. 11. An illustration of progressive generalization