You are using an outdated browser that does not fully support the intranda viewer.
As a result, some pages may not be displayed correctly.

We recommend you use one of the following browsers:

Full text

Proceedings, XXth congress

rate the
| ortho-
ted and
these 3-
ing with
e model
th other
ance its
ion and
fect. To
nd other
ained by
ch, only
oofs can
porate it
as wire-
ly GIS
' used in
such as
cts with
n of the
odel and
the wire
ymbol in
International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XXXV, Part B-YF. Istanbul 2004

the wire frame model stands for the closing vertex of a polygon,
based on which the faces for rendering are generated. The
surface model is an advanced wire frame model. The object is
represented not only by edges but also by surface components
called patches, each of which may consist of several polygons.
These polygons can be simply represented by vertices and their
topology if necessary. The data structure is simple so it can
ensure fast rendering. However, as a trade-off, the polygon-
based surface modeling may not be adequate to show the curve
objects with high fidelity because the number of segments
required to compose the curve is increased proportional to the
radius of curvature (Foley, et, al, 1993). After comparing both
modeling methods, we decide to apply the surface model in this
paper. The reasons are its simplicity and good supportability by
GIS tools. Also, attribute data can be directly associated to the
building object because it consist of polygons. In addition,
buildings in GIS are usually not considered as solid objects and
are mostly composed of straight edges or boundaries. Therefore,
the advantage of the solid model and disadvantage of the
surface model are marginal in case of modeling the buildings
for visualization applications.

Figure 1. Wire Frame model (a) and Surface Model (b) for
Geometric Building Model
Once the modeling method is selected, we consider its
association with the corresponding image textures. In general,
3-D graphic software use the directional projection method for
texture mapping so we need to avoid that the patches are
overlapped when they are projected on the plane. For this
reason, the geometric building model is separated into roof and
wall two parts. In our approach the shapefile format of ESRI
(Environmental System and Research Institute) is adopted and
enhanced for 3-D building modelling and visualization. This
file structure consists of a main file, an index file, and a dBASE
table. The main file is a direct access, variable-record-length
file in which record describes the shape with a list of its vertices.
The index file contains the offset of the corresponding main file
record and the dBASE table contains the feature attributes.
(ESRI White Paper, 1998) The main file supports shape types in
3-D space such as PointZ, MultiPointZ, PolyLineZ, PolygonZ
and MultiPatch. Usually the MultiPatch shape is good and
suitable for 3-D drawing. However, it is difficult to include
various topology and spatial analysis functionalities provided
by GIS and to directly link the attribute data to geometric object.
Therefore, we choose PolygonZ type and modity it to fit to our
objective for building modeling and visualization. This will be
addressed in the next sections.
The shapefile containing polygons with z-value is created when
digitizing a pair of aerial stereo images using the Stereo Analyst
of Erdas IMAGINE. The initial data from the Stereo Analyst for
the building models contains the 3-D coordinates of roof
vertices and z-values of building footprint at the ground level.
The coordinates of walls can be automatically generated using
such information in shapefile based on the assumption that
walls are vertical to ground. Hence, if some parts of building
have no vertical relationship with ground foot, they are
considered as a roof in terms of model structure even they are
walls in real. These geospatial data of vertical walls is added
into the roof shapefile. The main file structure of the modified
shapefile for building is shown below in Figure 2. In this way,
we successfully integrate all building components in to one
compact data model, which will benefit the texture mapping
and model rendering process in the subsequent steps.

Spatial data structure for building model
Double Box //Bounding Box
Integer Num parts //Number of parts
Integer Num points //Total Number of points
Integer Parts //[ndex to first point in part
Point Points //Coordinates of points for roof parts
Point Points //Coordinates of points for wall parts
Double Z Range //Bounding z range
Double Z Array //Z Values for roof points
Double Z Array //Z Values for wall points
Double M Range //Bounding measure range
Double M Array //Measures

Figure 2. The Data Structure of Main File for Building Model
For the photorealistic building modeling, each building façade
(a planar face, either vertical or not vertical) requires an
association to a realistic texture that is possibly composed of a
colour image with three bands, or the RGB colour intensities in
the simplest case (Gülch, E, 1997). Two different ways are used
to acquire and associate the images to building objects,
respectively for roof and walls. As mentioned earlier, a building
is separated to roof and walls for geometric model and texturing.
For roof texture, the ortho-rectified aerial image, created using