Shoichi Horiguchi
ed an set extracted from DEM. Gray points are Boundary type entities. The right image shows the corresponding digital 2D
lough map. It is obvious that characteristic structures are well matched.
roads,
1seful
a ms A Meet #
¥ Ov
Qt
"m
— yr x.
(b) Digital 2D map
(a) Image of Boundary point set extracted from DEM
Figure 2. Result of matching DEM with map
2.2 Extracting Intersection surface model and Reconstructing
Figure 3 shows how to extract an intersection
with 4 roads. Top image shows the road
network on the DEM. A circle means a node,
that is to say, an intersection. A line means a
link, i.e. a road. Pl and P2 are lines used to
acquire the cross section of an intersection.
The middle image shows typical cross sections
as extracted by Pl and P2. We use heuristic
construction knowledge that intersections are
almost flat and lie between tall buildings.
Based on this knowledge we acquire the basic
parameters, that is to say, the radius and
elevation of each intersection. Intersection
radius and elevation, Rave and Eave in Figure
3, are acquired by analyzing the DEM. Radius
(a) Orthographic
Rave is the average of R1 and R2. The Pl R
intersection is taken as the polygon formed by > Rove
r new the 8 points shown. Elevation Eave is the
average of El and E2. Most intersections in
urban areas are flat, so our intersection model 3 E1
is reconstructed as a flat plane. »
2.3 Extracting Road surface model 2R;
2
Figure 4 shows how to extract a road between
road, two intersections: C and D. Top image shows
nmon the road network on the DEM. Road length L
y grid is acquired as the distance between i E2
efore. intersection C and intersection D. P1 and P2 >
are the lines used to acquire road cross "m
ndary sections. We use heuristic construction e
type knowledge that roads lie between tall buildings (b) Cross section (c) Intersection model
roach and that roads is virtually flat across their
ament width. Based on this knowledge, road width, Figure 3. Reconstructing Intersection surface model
W1 and W2, and road elevation, El and E2,
point are acquired by analyzing the DEM. Road
width Wave is the average of Wi (i=1,2,..., n). Road elevation is the data set of Ei (i=1,2,..., n). In this case, data set Ei
International Archives of Photogrammetry and Remote Sensing. Vol. XXXIII, Part B3. Amsterdam 2000. 415