3D-GIS for Urban Purposes - fulltext.calis.edu.cnfulltext.calis.edu.cn/kluwer/pdf/13846175/2/159994.pdf3D-GIS for Urban Purposes ... * estimation of effects of development and their

GeoInformatica 2:1, 79±103 (1998)

# 1998 Kluwer Academic Publishers, Boston. Manufactured in The Netherlands.

3D-GIS for Urban Purposes

ALEXANDER KOÈ NINGER

Information Services, RUS Computing Center, University of Stuttgart, Allmandring 30, 70550 Stuttgart,Germany1

[email protected]

SIGRID BARTEL

Department of Geodesy and Geoinformatics, University of Rostock, Justus-von-Liebig-Weg 6, 18051 Rostock,[email protected]

Received August 30, 1997; Revised November 30, 1997; Accepted December 4, 1997

Abstract

New developments in urban planning, especially in environmentally oriented analysis including noise, air

pollution, urban climate etc., call for new demands on authorities and planners. Due to the increasing availability

of informations systems and of 3D-data, planners and municipalities emphasize modeling the urban space in three

dimensions. While the visualization aspect is often and detailed considered, only a few investigations about

interactive aspects on urban planning are available.

In this paper we present a framework for a 3D-urban-GIS. This includes conceptual aspects and a ®rst outline

and implementation of an application prototype. For this representation, new scopes have to be considered from

data acquisition to modeling and to storage. First, the urban object space is classi®ed in an hierarchical 3D object

structure. In accordance to different planning levels (i.e., levels-of-detail), several data acquisition methods are

fused to obtain 3D datasets. The results show that a context speci®c methodology has to be de®ned. This includes

planning aspects that are traditionally not available in GIS. Based on test sites in Rostock and Stuttgart, a 3D-

urban-GIS prototype is in development, joining aspects of a 3D-visualization interface and a database for 3D

objects.

Keywords: 3D-GIS, urban planning, object hierarchy, level-of-detail, urban analysis

1. Introduction and motivation

One of the main tasks for urban planners is still some kind of drawing. The analogous

urban design uses plans, maps and other handmade sketches that are extended by 3D-

models made of paper and wood, in order to visualize the potential effects of urban

development. Besides this traditional planning process (®gure 1), a modern planning

practice exists. However, most of these approaches use 2D or 2.5D data, only a few utilize

real 3D data. The majority of these information systems (CAD, GIS) are dealing with

administrative tasks, focusing on representation and administration of graphical data. Due

to the increased use of such information systems in municipalities and planning bureaus

and the availability of 3D-data in urban areas, authorities and planners emphasize

modeling the urban object space in three dimensions. As a ®rst approach and consequent

continuation, various 3D-city models (``virtual cities'') represent an obvious extension to

the analogous planning process. Here some examples:

* Graz: (cf. [9])* Wien: (cf. [24], [12])* ZuÈrich: ([15])* Los Angeles: (cf. [19])* Stuttgart: (cf. [13])

Using photorealistic textures, which are mapped on the surface of more or less simple

geometrical objects, these models take up the task of analogous pasteboard models by

visualizing our urban areas via computer animation (CA). CA, as an essential tool,

permits evaluation and cognition of complex spatial circumstances:

* visualization from an architectural and urban design perspective,* estimation of effects of development and their integration in existent settings,* aestethic assessment of an existing neighborhood.

Further aspects are described by [23]. However, extensive manual work on the datasets

and enormous computer resources are needed [10]. Some interactive aspects are

described in literature: planning premanufactured variants [22], [24] and in the sense of

free camera position or movement in the city [9]. From our experience applying

comparable software tools,2 CA provides a high level of interaction but hardly any

interactivity. The results are very impressive visualizations (images and video of

the design idea) but they are not well suited for an ongoing feedback into the design

process.

Discussions with municipalities clearly show the need for mechanisms that go far

beyond 3D-visualization. Recent projects concerned with environmental issues (air

pollution, urban climate, etc.) produce 3D-/4D-measurements (including time), which

should in the future be incorporated in an adequit data structure. The interpretation of such

data and the forecast with realistic simulations strongly requires a 3D urban model. This

implies new methods capable of including such new datasets or the provision of

extendability in a further stage.

One of the main goals of our interdisciplinary research is the development of general

concepts on 3D-GIS and their application in urban planning and design. On the starting

point we were confronted with the following situation:

Figure 1. Scheme of the analogous planning process.

80 KOÈ NINGER AND BARTEL

* The project staff had to create their own 3D data as there was no suitable data

available.* The future task for both geodesy and geoinformatics as data suppliers is to provide

such 3D-data.* Current GIS support 2 or 2.5D data structures only. They cannot handle a 3D city

model.* 3D-CAD packages are able to edit such data. However, they are not suitable for data

mangement.* Both data suppliers (geoinformatics) and data users (urban planning) need a 3D-GIS

for storage, management and editing. Additionally, in such a system geometry and

attribute data has to be included.* Urban planning requires speci®c capabilities for analysis and a suitable data structure.

Summarizing the given feedback, the new tool should provide the user with

comprehensive information and should support the urban planning process. In

comparision with the actual 3D-city-models, our approachÐthe

3D-urban-GIS � 3D-city model

� thematic information

� effective data storage and administration

� planning analysis functionality

Ðincludes several new aspects:

* The 3D-urban-GIS acts with objects in a 3D-space, 3D-city models often add only

faces without any object relations.* Visualization with the 3D-GIS allows for a representation that is close to reality due to

the selection of important aspects for imagination and evaluation.* Identi®ability and analysis are further main goals of the tool. In this sense visualization

is not the most important part, rather one component of many.* The 3D-urban-GIS should pro®t and include progresses of modern data acquisition

methods. The structure of the urban space should be automatically created and

transferred into the new data structure.* Finally, the 3D-urban-GIS is a future-oriented technology, even when the requirments

on hardware are still very high.

This paper is structured as follows: In the following sections we discuss aspects of urban

abstraction levels (2) and their implementation in a hierarchical data structure. The next

section treats the 3D-database (3), focusing on geometric and semantic object modeling

and on acquisition of 3D data. Section 4 deals with modeling of 3D-urban-structures and

aspects of a 3D-urban-GIS prototype followed in Section 5 by new perspectives in urban

planning as consequences to this frame concept. In the ®nal section, we present some short

conclusions from the present state of research.

3D-GIS FOR URBAN PURPOSES 81

2. The urban object space

Talking about hierarchies we ®nd that planners and scientists/engineers surprisingly often

mean different things. Urban planners generally use semantics: They talk about street

hierarchy in the sense of i.e., traf®c ¯ow or size of connectivity, etc. In this context,

connectivity means the importance of a road depending on the connections it provides to

other important points, roads, areas, etc. Scientists/Engineers use this term in a sense of

classi®cation hierarchies: Vertical relations between objects and object classes.

The urban (object) space is object-related. It is composed of several small, medium, and

large structures and in plainly obvious and in rather hidden ones. These individual objects,

for example buildings, streets, green areas, public and industrial areas, but also open space,

roofs and facades are related and connected to each other. They form ensembles of

combined objects that contain particular detail at different scales. These object classes

contain structural ``positive'' elements, like buildings, directly besides ``negative'' ones,

such as public places. In addition to this evident object structure, a strong intuitive

component of urban planning has to be recognized. The planning process is strongly

in¯uenced by terms like quality of life, quality of shape, attractiveness or aesthetics. To

take this into account, a detailed representation of the urban area needs to be supportedÐ

including street decoration like fountains, pillars, showcases, park benches and

``negative'' ones like hydrants, transformer stations or public conveniences.

Furthermore, the urban area is classi®ed in pathways, areas, focal points and boundary

lines which can be structured into semantical hierarchies (cf. [20], [27]). Penetration and

combination occurs as well. As the ®rst step, the object space and its inventory have been

analyzed and partially implemented into an object-oriented data structure. The result is a

vertical hierarchy, which is quite complex and widely segmented. Figure 2 represents an

example for the object class building. Getting closer to the building, more and more

details are distinguishable. At this level, this leads to an increase of the currently important

data structureÐthe details of house fronts and buildings (eaves, dormers, sills, mullian,

transom, etc.) will be of greater importance. We found the following (trivial) object

classes, buildings, streets, green areas, public places, terrain surface, which can be

combined into greater structural elements, like quarter and district, andÐinto a wider

contextÐa city.

For example, the description of a street consists of data on the surrounding buildings, in

addition to geometrical information about the height of the curb and the sewerage cover.

For planning processes, the amount of free space in the street (``street volume'') is as

important as the position and arrangement of parking areas, the green of marginal zones,

street inventory (which can be quite manifold) and the infra-structure above and under the

street level. All these subobjects combine information about geometry and material

(texture, color), which should be available or have to be de®ned. Thematical data and

level-of-detail information must be supplied for further analysis.


2.1. Abstraction levels in planning

Due to the structure of the planning process, the usage of different levels-of-abstraction is

of great importance in urban planning. Based on several map scales, each level contains

different methods, which have a pronounced in¯uence on the visual representation of

urban objects. Therefore, the main subject of planning is not a perfect virtual replication of

the city structures, rather it should convey a strong idea of the real project. These

abstractions can be converted into visible representations that are called levels-of-detail

(LOD). The literature provides several LOD mechanisms (cf. [1]):

1. Pixel area. Closer to the object, the number of visible pixels increases. After reaching

a threshold value, the LOD switches to a higher resolution of details.

2. Distance to object. In analogy to item one, threshold values for distance exist. This

Figure 2. Approach for the object class building. Objects, which can be seen as complex structures, are

surrounded by a frame. Dashed frames characterize undetermined structures. Objects or classes are described

through individual attributes (compare with object box on top). The items LOD mark transition switches to a

lower/higher level-of-detail.


method is important for different sized objects at the same distance from an observer.

Here, the LOD will change simultaneously.

3. Dependence on visual angle. The LOD decreases with an increasing lateral distance.

This method is similar to the usage of architectural hand sketches. Discarding

unimportant information, characteristic project aspects in the image center are

stressed.

4. Explicite choice. For individual objects/subobjects, structures and/or classes, the

LOD information can be de®nied selectively.

In a ®rst approach, we use three different levels-of-detail (®gure 3). For the ®rst LOD, we

consider the bounding boxes of urban objects, based on ground plans, as suf®cient. The

roads are drawn without any inventory, green areas are represented through green shaded

areas. It is planned to support bounding boxes for greater districts and quarters, like

shown in [18]. The second LOD includes a precise positioning of the objects based on

their ground plan with generalized fronts and roofs. Roads are presented with sidewalks

and traf®c-line marking, green areas contain simple trees. In addition, phototextures can

be used if provided. In the most detailed LOD, urban objects will be represented with all

geometrical data stored. Depending on availability and context of the project, the building

fronts will be shown as simple geometry or as phototextures.

It may be useful to represent house fronts schematically, without phototextures (®gure

Figure 3. Levels-of-detail and their characteristics.


5). Object dependent thematical information is only available if the object is visible, that

means identi®able. General thematic data are available in all LODs. We have recognized

from our investigation that this abstraction is not suf®cient for the planning process. For

example, to discuss shape de®ning characteristics, it is necessary to underline ornamentic

aspects of a building in a way that requires LOD 3, even if the rest is simpli®ed and shows

only LOD 1. A typical example is architectural hand sketches. We interpret this situation as

a mixture of different LODs applied to one object simultaneously (®gure 4). Such mixed

forms of penetrating LODs play a very important role in urban planning processes (®gure

5). New methods for handling these aspects are required. As a consequence, we examine

Figure 4. Examples of context dependent LOD. (Left) contour analysis, (middle) sculptural structure, (right)

ratio openings to mass.

Figure 5. Analysis of cityscape and the relation to the levels-of-detail. LOD combination: used LOD (with

characteristics of another one).


an user-de®nable context. This enables the user to stress important characteristics or to

neglect less important ones. For this purpose, each object class (i.e., building) has to be

realized as a complex structure, containing identi®able subobjects. For example, the

complex method ornamentic will emphasize the sculptural features of a building while

ignoring material properties. As a further extension we see individual LOD representations

for object groups or even individual objects. In this way, adjacent town districts, that are in

different planning stages, can be discussed. This interesting idea is particularly useful in

areas which are in early planning stages and where only sparse information is available.

2.2. Relations to other GIS hierarchies

To compare the 3D-GIS object hierarchy with other thematically related topics, we

analyzed both structures for dependencies. In the upper part there is a close relation to

corresponding hierarchical GIS structures (e.g., land register, of®cial statistics; cf. ®gure

6) with the connection node building. Even if the interior of buildings is neglected at this

stage, the complex hierarchy tree could be extended at this node through a comparable

structure from a building information system (cf. [3], [4]).

In comparison to other GIS structures, the urban area re¯ects non-trivial links of

different hierarchy types. In addition to a vertical structure (cityÐdistrictÐbuildingÐ

front of building), which is evident and describes classes which have the same attribute

structure, different class attributes, the planning process and its different stages also

follows topological aggregation and associative hierarchical structures [21].

Figure 6. Context of different semantical hierarchies and relations. The node building represents an

elementary connection.


The classi®cation hierarchy describes classes which have the same attribute structure

and respresents a stepwize introduction of terrain objects. Topological hierarchies are

based on connectivity/disconnectivity rules which are related to the geometric object

description (dormer isconnectedto roof ). An aggregation hierarchy represents a partoflink between elementary and composite objects, again linked to other composite objects. It

describes how composite objects of one level are constructed through elementary objects

of the next lower level ( for example a city-block consists of several buildings). Finally,

in associative hierarchies no topological constraints are de®ned; the `àssociations'' built

in that manner are loose without clearly de®ning relationships to each other. Their

connection consists of identical attribute values identi®able by search operations.

3. Aspects of the 3D-database

In this section we discuss 3D-object data representation and the semantic modeling of

urban space objects, as well different acquisition methods and data sources. Finally,

approaches towards the DBMS of our 3D-GIS are described.

3.1. Data acquisition and data sources

The different requested levels-of-detail can only be produced by fusion of several input

sources. While the digital city map delivers the basic geometrical information, ( position of

topographical objects, ground plan of the buildings, height points of the elevation model),

thematical data may be delivered by additional building measures and by municipal

registry.

Since real 3D-data are still very rarely available, we had to produce and manipulate our

own data sets. Different data sets were collected and fused to an integral 3D-dataset with

respect to different resolutions of each method:

* Digital city map represents the position of urban objects, trees, manhole covers and

others. Additionally, it also delivers the ground plan of the buildings. All other

methods use this 2D digital map as reference data. Simple height information is used

for a ®rst approach of a surface model.* Thematic data are available for single objects or object-classes in a 3D-GIS. Examples

are: building age and condition, type of usage (optionally per ¯oor), number of ¯oors,

building volume, ¯oor space index, etc.* Satellite images can be used as additional information, particularly in large city areas.

It will be of greater use in the near future when high resolution images (4 1 m) will be

available.* Aerial images deliver input to digital elevation models and for 3D-reconstruction of

objects. The obtained data represent simple models (LOD 1 or 2) depending on scale

and image resolution.* Close-up images or geodetic methods (tachymetry, laser) can be used at close


distances. The resolution is generally high and is applicable for LOD 3. After

preparation and correction the resulting image can be used as additional textural

information for mapping in LOD 2 and 3.* Thermal images (close-up thermal infrared thermography) reveals heat storage and

transmission of buildings.

Approaches on automatic digital creation of elevation models and building extraction are

the topic of current research [7], [11], [14], [28]. Although various approaches for

automatic data processing exist ( parametric models, point sets, edge sets grouped over

geometric and topological constraints), dense built-up urban areas are still problematic.

An alternative is semiautomatic approaches (cf. [6]) with a typically resolution of 15 cm

to 1 m.

A higher resolution is achieved with geodetic methods and terrestrial images. The

system we used for our studies3 provides 3D line models (cf. ®gure 7) in DXF-Format with

a high accuracy in the range of 2 to 5 cm. Before and after data conversion we encountered

several problems:

* Invisibility of some object parts due to the point of view with other objects in the

foreground, like cars, traf®c signals, trees or building parts.* Bad recognition of the veri®cation markers in case of low color contrasts.* Problems in conversion and processing of the DXF data. Polygons may have the

incorrect orientation, so that the backfaces appear actually in the front due to incorrect

vertex ordering. Faces which enclose others in the same plane should be modeled

correctly.

Figure 7. Original urban situation (left) and resulting 3D line model (right).


To use the images as facade textures as well we applied a recti®cation. Furthermore, a

correction of light condition and an elimination of foreground objects should be applied.

3.2. Geometric and semantic object modeling

3.2.1. Geometric object modeling. To describe the geometric behavior of a building a

variety of geometric models (®gure 8) can be used (cf. [5], [8]): Firstly, parametricdescription represents ®xed shaped objects with a ®xed number of parameters (e.g., a

cube as height, width, length). A few basic objects (cube, sphere, cone, etc.) can be

described in a very compact form. The second data structure, Boundary Representation(BRep), includes faces, edges and vertices explicitly. Therefore BRep can be manipulated

directly. The polyhedron as a special, but frequently used form, represents edges as

straight lines and faces being planar. Handling and design of the resulting data structure is

much easier through the use of many existing algorithms for analysis and rendering. In the

Constructive Solid Geometry (CSG), basic solid objects are composed by Boolean

operation (union, difference, intersection). Together with the transformation matrices and

rotation of partial objects, the result is stored in a binary tree. The leaves of the tree contain

information about the basic solids. The related boolean operations are stored in the

intermediate nodes. The advantage of CSG is a very compact storage together with

the history of the object construction. Unfortunately, only simple operations concerning

the whole object are supported. Local manipulations are very dif®cult to realize.

Furthermore, the whole tree needs to be traversed every time the shape of the object is

Figure 8. A simple building, in the upper row as parametric model, and as boundary representation, in the

lower row as CSG model, cell model and spatial enumeration.


evaluated. To conclude this method is a rather unfamiliar approach for urban planning

problems. In the fourth model, the cell model, the objects are de®ned by non-overlapping

cells without holes. This method is very common in scienti®c computing. The resolution

strongly depends on the size of each cell. A special case of the cell model is spatialenumeration. It is based on a ®xed raster of voxels. The size of a voxel can depend on the

required resolution and the available memory. Exact representations are possible for a

small number of objects only. Simple operations like volume calculation or neighborhood

functions are very easy to handle. An octree can be used for storage reduction. Due to

advantages and disadvantages in all models, none is convenient for all object types,

operations and scale levels. In low levels, buildings are best described by parametric

description or BRep, in special cases and on high scaling levels by CSG. For analysis of

street space or voluminetric questions spatial enumeration provides the best method.

Simple basic objects and BReps are an integral part of the choosen software platform

Open Inventor, even though the software does not allow for explicit storage of topological

relations between corners, edges and faces. Parametric models and voxels could be added

as individual object classes. A BRep description of urban objects is also delivered through

the herein described data acquisition methods.

3.2.2. Semantic object modeling. For some basic objects of the urban space we de®ne

new object classes using the nodekit constructor of Open Inventor. With this mechanism

different objects can be grouped hierarchicallyÐthe resulting object classes take effect as

self-contained units which involve geometry, different levels-of-detail and related

thematic data (®gure 9). As a result internal handling of this complex object is easy.

New object classes were introduced for the following urban basics:

Figure 9. New de®ned object classes for green and street in Open Inventor symbolism. Objects of these

classes are selectable by db_oid.


* Building with street, house number, and 3 abstraction levels: bounding box, polyhedra

or polyhedra with textured faces and detailed 3D-geometry.* Street with type name and two abstraction levels: median line or side-marker,

pavement, lantern and signal nadirs.* Green with base area.* Tree with type, age and damage classi®cation, at ®rst only for spherical tree-crowns.* Terrain model as a gridded 3D-net.

New datasets of these structures can be added to the database. The representation in

different LODs are based on the general aspects described in Section 2 and in Section 3.

While in LOD 1 the objects are described by geometric bounding boxes consisting of

simple geometry and transformation infos, LOD 2 includes arrays with vertex indices of

faces, ground plan and additional color information. LOD 3 additionaly contains texture

information: direction vectors, face vertices, image data as texture oids, etc. For each

object a picture4 is storable as a binary large object.The change of LOD are realized through, so called, switch nodes. This special node is

able to ``choose'' and switch between nodes which are hierarchical below it. For access

management of thematical attributes an own nodetype is de®ned, which includes the

attributes of the data®elds. This node is not involved in the visualization process of the

scenery. Each nodekit-type includes ®nally a node called label which stores the database

object-id (db_oid) of the concerning object.

3.3. Approaches towards a 3D-GISÐthe DBMS

For the realization of a 3D-urban-GIS we see three different possible starting points: (1)

An extension of a 2D-GIS to a 3D-GIS. The 2D-datamodel and the related functions have

to be extended to three dimensions. For this solution an open application system is

required.5 The de®cit is the non-integrated 3D-rendering and interaction technique. Due to

the expected extensive data requirements and visualization as an important system

component, we decided to follow an approach between the following two points. (2) The

extension of a 3D computer graphics environment to a 3D-GIS. Here, structures for

thematical data, hierarchies and convenient 3D functions have to be added. The de®cit is

the a priori non-existent 2D-GIS functionality. (3) The extension of a 3D database

management system (DBMS) to a 3D-GIS. Such DBMSs for 3D objects are subjects of

current research [2], [8]. The DBMS with its 3D query functions needs additions by a

graphical user interface, visualization and analytical functionality.

For the graphics environment we use Open Inventor which provides an object-oriented

progamming interface/library and an interactive 3D graphics application environment

[29]. Originally developed by Silicon Graphics Inc., it is now available for various

hardware platforms. In addition to some geometrical basic objects, user-de®ned structures

and classes can be incoorporated. Based on a scene database, several options for

interaction, manipulation and illumination are available, including elements for user-

interface development (scene-viewer, material editor, print dialog, etc.). The system is


expandable through a customary de®nable functionality, e.g., new object types and

classes. Data exchange with other systems is also possible through the Open Inventor 3D

Interchange File Format (IV).6 Several data conversion utilities are available (DXF, OBJ-

Wavefront, etc.).

In combination with a fast DBMS this features meet the demands of the planner with

respect to an integrated, interactive, three-dimensional presentation of the urban space. In

a relational DBMS spatial data administration is very dif®cult due to inevitable data

redundance. Therefore, the DBMS has to meet the following criteria:

* An object-oriented access structure, which supports inheritance of class features,

object identity and user de®ned abstract object data types.* Spatial access index, like e.g., an R-tree.

but also the existence of an programmable interface (SQL, C++). The database system

Postgres95 ( public domain) ful®lls these criteria and has been used for our investigations.

The development of a 3D-DBMS and the connection to our 3D-GIS interface was

investigated by [17] as a part of the project. The known R-tree was enhanced to the

R*-Tree and the Hilbert-R-Tree as an additional spatial extension. The new Open

Inventor classes where transformed into 3D database structures. Phototextures are

represented through image pyramids which are calculated and stored on insert into the

database. This minimizes the size of large datasets and hence the transfer time in

dependence to the view distance. A database query can depend on a speci®c object class,

level-of-detail, a 2D-area and a current view volume which is projected in a xy-plane.

While loading the data from the database, the object-LOD can also be determined

automatically by analyzing the size of the object bounding box on the screen.

Finally, we take a closer look at the amount of data we expect. From the following

investigations we conclude, that the data volume for urban space modeling can be

extremely extensive:

* Model of the main building of the University of Rostock, comprising a high level-of-

detail, requires about 8 MB.* Pilot study of the Univeristy of Vienna for a building block in Vienna (58 buildings,

partly texturized) produced 12 MB of data [9].

Therefore an exact, high resolution model of the entire urban city space is in general not

possible, but useful for certain projects.

4. Modeling the urban-space: The 3D-urban-GIS

4.1. The test sites

As our test sites we comprised quarters in Rostock and Stuttgart. In Stuttgart, digital 2D-

data (ground plan) have been available since 1993 while in Rostock such datasets are still


under construction. Therefore, we had to acquire our own data from selected city districts.

The city block KroÈpeliner Torvorstadt (1000� 500 m) is part of the city of Rostock.

Constructed in the early 20th century, massive urban development and reconstruction has

been done since the German reuni®cation in 1990. The 3D-data set covers about 350

buildings at LOD 1, ten houses at LOD 2 and some ®ve houses in LOD 3.

The ®rst test site in Stuttgart, Stuttgart-Berg (1000� 1000 m), consisting of about 430

buildings, is located on a small hill in the eastern part of the city. The second test site is one

of the main traf®c arteriesÐHauptstaÈdter Straûe (both ®gure 10). This area (600� 300 m)

with around 750 buildings was chosen due to ongoing urban pollution and noise

measurements along this street. In both areas, the available 3D-data is suf®cient for LOD 1

and LOD 2, but not for LOD 3 yet. The dataset consists of streets, buildings, border lines,

and topography. In addition, thematic data for some blocks are available: area, usage, form

of roofs, height of eaves and ridges, number and type of ¯oor, etc.

Figure 10. Test sites in Stuttgart: From a municipal dataset automatically generated VRML-model of the areas

HauptstaÈdter Straûe and Berg.


4.2. Structure of the 3D-GIS

The modeling of the 3D-urban-space has to be seen as an integral concept, consisting of

several independent system components. Figure 11 shows the conceptual outline in which

the database and the user interface, as the immediate communcation platform, play the

most important roles. Several data ®lters were implemented to reduce manual work on

data preparation. We applied data pipelines for ARC/INFO, DXF and IGES to obtain an

Open Inventor compatible data format. In particular, municipal dataformats (i.e., GATE)

were automatically converted to an object-related VRML- or IV-model.

The 3D-GIS application currently consists of one process corresponding directly with

the postmaster-process of the database. Considering that our approach is a prototype, it is

considered as a priori suf®cient. Some of the key functions required are provided by Open

Inventor, like navigation in the planned new world, i.e., walking and ¯ying, illumination in

dependence of daytime, view position, different LODs which should change somehow

Figure 11. Planned concept and data¯ow for the urban 3D-GIS.


automatically and identi®ability of selected objects. These functions describe a rather

technical ability of the system.

4.3. Urban planning analysis

From our experience, in order to be an useful and accepted instrument, the product has to

support the quiet intuitive analogous working process of planners. For this reason a clear

and intuitive interface is required which supports the playful component. It must allow

experiencing the newly planned sceneries by walking through it. Further, it comprises

methods and possibilities which are not yet included in the planning process, i.e., aspects

of the third dimension and analysis which are not immediately obvious for our senses. The

latter aspect also covers the in¯uence of randomness and coincidence, which play an

interesting role in planning as a human factor, but are barely quanti®able. Transformed to

the planning interface we receive the following issues:

* Development of a context-dependent user interface, which is visible as a panel inside

the planning interface. It contents all the necessary functionality of a given context.* Structuring of the planning process in context areas. We understand context for

example as different hierarchies or as the processes of data input or update. Context

speci®c functions will be available in dependence of the actual state. This also leads to

a simpli®cation of the user interface.* Support of the user competence. We intend to accelerate the handling of the planning

tool with increasing knowledge of the user. Key shortcuts and command chains will be

supported. An example is user de®niable reports for complex database queries.

This shows, that the same thematical methods may have different meanings in a different

context, i.e., LOD. Further 3D-speci®c methods have to be de®ned to determine planning

speci®c parameters: volumes, densities, etc. Examples are shown in ®gure 12. One of our

goals is to ®nd an optimum between on-line determination and storage of parameters

with respect to performance. For example, the LOD 1 geometry of an object could be

detemined from the most detailed dataset available.

Here is an incomplete list of useful methods:

* Variants: External planned projects (CAD-system, 2.5D-GIS, etc.) are integrable into

the system. It is possible to analyze different planning projects with respect of

reasonability.* Comparative planning: Various planning stages of different projects can be displayed

and evaluated in parallel to the actual project.* Interactive grouping: Aggregation of elementary objects by reorganizing the

scenegraph due to provision of geometric and thematic information.* Data and object editor: Easy modi®cation of object data.

In addition we cannot neglect ``traditional'' GIS-methods like topological (InsideOf,


PartOf, ConnectedTo), manipulative (insert, delete, select, update) and visual ones

(showobject, showgroup, etc). Hence, two groups of methods can be distinguished: ®rst, a

group of obvious and visible methods that represent the architectural and planning

element and second, a group of hidden methods which support the design process.

4.4. Visualization aspects

Visualization is a fundamental feature of a 3D-urban-GIS. Similar to the real model, 3D

visualization is a tool that permits cognition and evaluation of complex spatial

circumstances.

* Visualization of an existing city or of a plan with respect to an urban planning or

design perspective.* Aesthetic assessment of an existing neighborhood or a development.* Effects of developments and their integration in existent settings.* Visualization of the external (bird's eye, appearance from outside) and internal view

(human perspective).

The tool provides the means to display areas and objects at different levels-of-detail

focusing the visualization on the interesting problem and on objects in question. The user

Figure 12. Example for urban analysis: Volume representations and spatial structure analysis. (A) Building

blocks, (B) street space, (C) non-built-up areas and (D) built-up urban areas.


is able to structure the visualization process with his or her viewing habits. This allows a

freely envision of space which is in contrast to computer animation (CA). That means CA

doesn't support the planning process in a direct mannerÐit gives a designed but ®xed and

statical view. The resulting images or videos of a scenery haven't any interactive input

possibilities. Hence follows that planning presentation. General aspects of interactive

manipulation and user acceptance are described in [16].

Actually, we see the 3D-GIS still as an analytical and evaluation tool. We can act in

space, move objects, realize situations immediately, and experience measure and compare

spatial situations. We can abstract of draining essentially aspects. The visual process of

learning is controllableÐwith an adjustable LOD it is possible to neglect objects which

sophisticate or blur our spatial impression. In conjunction with quantitative questions the

controllable visual information supports the process of analysis and evaluation and

improves the planning process. Different sceneries and planning projects are now

comparable. An example view on such a possible interface is shown in ®gure 13.

In addition to 3D-visualization, knowledge of quantitative and qualitative conditions are

as important for an assessment of an existing urban setting or only a blueprint. The design

plan of the 3D-GIS includes the following interactive possibilities: (1) A quantitative

analysis of the spatial conditions by measures and numbers. This functionality is rather

analytical than intuitive and determines urban space parameters from their geometrical

and thematical values. (2) Volume oriented analysis of building density and its distribution

in the urban area. A quarter-based 3D-plan for urban density is projected. (3) Spatial

analysis of public and open spaces between buildings (non-built on areas) and, the

contrary, analysis of built-on areas. (4) Spatial analysis of greenery and its ecological

signi®cance. Here the relation to buildings and their individual meaning is going to be

Figure 13. Possible 3D-GIS interface, viewing a spatial database query and additional image query for an

selected building.


evaluated. (5) Analysis and evaluation of form and shape by decomposition of details. This

also includes terms like aesthetics, attractiveness of an urban environment, quality of life,

etc. (6) Analysis of light and shadow conditions as a qualitative aspect of an urban setting.

(7) Thematic aspects, e.g., the spatial distribution of a particular urban thematical

functionality. (8) Analysis of different planning stages of a project in their chronological

order.

5. ConclusionsÐNew perspectives in urban planning

The 3D-urban-GIS is still under developmentÐhence our experiences are too small to

put a ``®nal'' note, in comparision with traditional tools. Anyhow, we can show some

interesting results. As shown above, we can act in space, change object situations, put

questions about thematical information. With the ¯exibility of the system such an interface

becomes a ¯exible tool which supports the design process in adjustment to the different

planning stages. The usage of computer based planning tools enables the planner and other

decision makers to assess the consequences of this actual work before actual realization.

This will in¯uence future projects much more than now expected. Not only decison

makers could pro®t from such a planning tool. As you can see from ®gure 14, citizens

could also be informed about new developments. With an interactive interface this could

happen in a much more individual wayÐby own selection.

5.1. Environmental analysis

On the other hand, new planning requirements like ecological aspects could be included

in the near future.7 In addition to the previous described cognitive aspects of pure

Figure 14. 3D-urban-GIS and its users.


visualization, qualitative aspects such as shadowing, lighting, and ventilation gain

importance for the evaluation of urban cities. The planning of planting development is not

more only an artistical process. Related environmental factors will be taken into account

including noise, air, energy balances, pollutants and urban climate. These prevailing new

aspects to the traditional planning process will be included in an immeditate senseÐthe

question will be: How to visualize processes which are ®rstly invisible to human senses or

for which we don't have senses at all. This leads to an integration of another important

component in this process: Time. As shown above, the possibility of viewing different

planning stages is somehow related to this problem. These snapshots represent different

time stages and a rough sketch of the development process. Since a continous process

requires a much higher discretization this will be not enough for e.g., air pollution

simulations. Currently, these data are stored as external ®les. As a next step the 3D-GIS

database could be used for storage with regard to a faster accessability. In this way, in

earlier times determined parameters and models can be demonstrated and evaluated.

The extension of the 3D-GIS to environmental aspects is also supported through

advances and applications in related ®elds. New developments in remote sensing and

photogrammetry provides new methods for data capture. Multi-sensoral aerial image data

does not only deliver information on the physical urban space, but also may detect climate

and air pollution data. This will extend ground based measurements. The consideration of

such new methods will enhance and change the planning process, resulting in new

methods for assessment and evaluation of planning outcomes. This is topic of current

research [26]. One of the project objectives is the simulation and visualization of the

spread of noise and air pollutants in a 3D city model (®gure 15). The simulations are based

on a scale of 1 m to 2 m, i.e., surely in LOD 3.

5.2. 3D-GISÐAn integrated tool?

In its current stage, the 3D-urban-GIS covers the built-up areas of our cities. Extended

through environmental components, it could represent an integrated tool. All currently

separated system components could be joined together at data level (®gure 16).

Figure 15. Simulations of the spread of air pollutants under various building structures (cf. [26]).


Specialized individual tools can consider only one ``speci®c factor'' at a time, e.g., air

pollution and/or traf®c noise. A future aim of the 3D-urban-GIS is the integration of at

least all three-dimensional urban factors. The traditional planning process could then be

considered with new environmental analyzing and viewing possibilities.

Acknowledgments

We wish to thank our colleagues of the Institute of Photogrammetry in Bonn, particularly

Eberhard GuÈlch, for their support on extracting a 3D-building-model for Rostock, and

Charly Anders of the Institute of Photogrammetry in Stuttgart for his activities on the 3D-

datasets for Stuttgart.

Furthermore, thanks are due to the Deutsche Forschungsgemeinschaft for ®nancial

support of our research studies in the interdisciplinary two-year project ``3D-GIS im

StaÈdtebau'' (reference no. Bi 467/3-1 and Bo 1346/1-1).

Notes

1. Former address: Institute of Urban Planning, University of Stuttgart, Keplerstr. 11, 70174 Stuttgart, Germany.

2. For example, Explore from TDI/Wavefront, SGI Performer

3. Architectural photogrammetric system ELCOVISION with camera Leica R5 and evaluation software (cf. [30]).

4. Unstructured data with a size that exceeds the maximum Postres tupel-size of 8 KB.

5. For example, Smallworld; cf. [25].

6. The Open Inventor File Format (IV) is compatible with VRML 1.0.

7. Research project WUMSÐWege fuÈr eine umweltvertraÈgliche MobilitaÈt am Beispiel der Region Stuttgart at

University of Stuttgart. Joint venture of several institutions.

Figure 16. Several factors in¯uencing the urban planning process could be joined together to an integrated

planning tool.


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Alexander KoÈninger studied Geology and Geophysics at the University of Stuttgart, Germany and gratuated

with his diploma thesis in 1987. In the following years his work focused on optimization methods in the scope of

complex earthquakes, in which he earned his Ph.D. in 1996. During this period, his interest shifted to computer

science. From 1985 to 1990, he was member of the consulting departement of RUS Computing Center, University

of Stuttgart. In 1991 he switched to industry and became head and co-founder of a small software development

enterprise. From 1991 to 1994 his particular responsibility in this position were database applications and process

automatization projects. In 1995 he changed again to a research position, working at the project ``3D-GIS for

urban planning'' at the Institute for Urban Planning, University of Stuttgart. Since the end of 1997, he is member

of the Information Services department of RUS Computing Center, University of Stuttgart, responsible for the

areas ``WWW and databases'' and `Ìntranet''.


Singrid Bartel studied computer science at the University of Rostock and completed her diploma thesis in

1991. During the next 4 years she was a research assistant at the institute for computer graphics. Her research on

improving the photorealistic rendering algorithms for frame-to-frame computation results gained her a Ph.D.

thesis in 1995. In the following two years her research area was the extension of GIS in 3D for urban applications.

Since August of 1997 she is working for MarineSoft, Rostock and is now responsible for user interface design and

development.


Documents

3D-GIS for Urban Purposes - fulltext.calis.edu.cnfulltext.calis.edu.cn/kluwer/pdf/13846175/2/159994.pdf3D-GIS for Urban Purposes ... * estimation of effects of development and their