A GIS-BIM Approach for the Evaluation of Urban Transformations. A
Methodological Proposal
M. GRIMALDI*, C. GIORDANO, G. GRAZIUSO, S. BARBA, I. FASOLINO
Department of Civil Engineering, University of Salerno, via Giovanni Paolo II 132, 84084,
Fisciano, SA, ITALY
Abstract:- The implementation and monitoring of the urban transformations provided by the planning tools
require a control by the responsible territorial authorities on the compliance of the proposed transformations
with the technical and binding rules of the current plans. Considering the complexity of the urban and territorial
scale, professionals need a tool capable of satisfying the planning, design and management needs of urban
space. The large amount of data and the possibilities of managing the multiple information contained in a BIM
model can, indeed, be integrated usefully and declined at higher scales than the single building one, since they
can be extended from the sphere of pure architectural design to planning sector. In such a wide context, the
GIS-BIM approach can represent a real shift of paradigm aimed at managing the complexity of urban processes
more effectively.
Key-Words: - Urban Plan, GIS, BIM, urban indicators, urban transformations evaluation.
Received: June 17, 2021. Revised: November 18, 2021. Accepted: December 20, 2021. Published: January 17, 2022.
1 Introduction
Planning actions can be defined as the result of all
anthropic processes that produce a physical
transformation of cities. These actions have different
impacts, depending on the urban transformation they
define. It is possible to distinguish actions that
create new objects, actions that can modify existing
objects and actions that aim to remove completely
objects [1]. The effects that the combination of these
actions determine are very complex, considering
also the spatial component of the objects affected by
the transformation.
The formalization of the relationships between
the effects and the actions become essential to
support the decision maker in selecting a suitable set
of actions and contributing to an efficient urban
transformation [2]. To achieve this goal, it is
necessary to build a system for assessing the impact
of these actions based on the simulation of the urban
transformation, which can be defined according to
the urban indicators that the Urban Plan provides.
The simulation of the application of the threshold
values attributed by the Urban Plan to each indicator
results in the n design configurations that the
specific area can assume. It is, therefore, necessary
to build a model of knowledge of the territory that
combines transformations on the urban scale and on
the building scale dynamically. The aim of tying
together the different components of knowledge of a
territory, inside and outside the built environment, is
similar to look carefully at both the ways of
representing them and the tools to govern them. This
means to be equipped with a syncretic vision to
reconcile aspects apparently very distant in time,
space and nature [3]. The knowledge of a territory,
indeed, can be defined with its representation and
performed in various ways, i.e. using different
formal modelling techniques and parametric data
representations [4].
Currently, the representative models of digital
cities are based on geospatial data deriving from a
Geographic Information System (GIS), that can be
considered an indispensable tool for the
development of the territory and, in general, for
spatial governance [5]. Certainly, it marks an
evolution in the world of urban planning but
planning often requires data that GIS alone cannot
provide.
Conversely, Building Information Modelling
(BIM) can support the detailed semantics of parts of
buildings or other functional parts of the city [6].
Indeed, a 3D model created in a BIM environment is
based on a smart representation of the object that
allows a systematic association of data, attributes
and parameters [7-12]. The model, intended as a
complete and centralized information repository,
can be used during the entire life cycle of a building
and data from such a model can be updated and
shared promptly [13].
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M. Grimaldi, C. Giordano,
G. Graziuso, S. Barba, I. Fasolino
E-ISSN: 2224-3496
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Each discipline involved in the knowledge of a
territory has its own scope and, therefore, focuses
differently on the things that are modelled and on
the way in which they are modelled [14, 15].
However, the interoperability, i.e. the ability of a
system to exchange data and information with other
systems or programs, opens an interesting
connection between the urban and the building scale
[16]. The data coming from a GIS environment and
those deriving from a BIM model, indeed, can be
integrated with the consequent advantage of
managing the planning information in a coordinated
manner [17, 18]. Thus, it is possible to move from
the simple concepts of GIS and BIM to the one of
City Information Modelling (CIM) that is
characterized by a multidisciplinary union of all the
spatial data of the model [19]. In addition, the CIM
can involve a multiplicity of actors in order to
collaborate in the development of sustainable,
participatory and competitive cities [20].
Starting from these considerations, in this paper a
methodology of integration of GIS and BIM is
described and applied to a case study in the
municipality of Nocera Inferiore (South Italy) in
order to design new dynamic spatial scenarios of the
urban transformations, with a real time control on
both the urban and the building scale.
2 Methodology
In order to create a parametric model useful in the
urban planning phase, a methodology that allows the
association of the classic urban indicators with BIM
system was defined. This parametric model,
integrated with the data coming from a GIS system,
allows the creation of a database able to facilitate
the stakeholders in the management of information
and in the evaluation of the urban transformation
processes.
The methodology can be divided into three
phases (figure 1), i.e.:
1. GIS environment modelling;
2. BIM environment modelling;
3. Scenarios construction and assessment of urban
transformations.
Each phase is organized in several steps. While
the first two phases are related to the urban and the
buildings contexts respectively, the third phase
contribute to define the model for the generation of
different scenarios.
Fig. 1: Methodology for the CIM definition and the construction of dynamic scenarios.
The first phase, which is implemented in GIS
environment, can be divided into two steps. The first
step concerns the acquisition and systematization of
all the information deriving from the planning
system of the study area, from the cognitive layers
about the use of the soil, the morphology and
geology of the soil. The second step involves the
synthesis with overlay map operations of the
information layers and the construction of suitability
maps of the transformation in terms of distribution
of the lots and their appropriate urban functions.
The second phase can be, also, divided into two
steps and includes the definition of levels of detail
(LoD), for step 1, and definition of parametric
families (PFs), with regards to step 2. In the BIM
environment, the geometric representation of the
construction elements can vary in granularity,
depending on the design state, with the definition of
several LoDs, such as the symbolic (LoD A),
generic (LoD B), defined (LoD C), detailed (LoD
D), specific (LoD E), performed (LoD F) and
updated (LoD G) ones (figure 2). To support the
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dynamic nature of the design process, step 2 of the
second phase is connected with the generative
modelling approach of BIM, which allows the
changes of object models quickly and efficiently by
creating parametric families. For example, the
thickness of a wall component can be simply
changed by adjusting the only width parameter,
while the change of geometry is implicit [21]. The
parametric model, that is the output of the second
phase, allows the modelling of objects intended as
datasets, interchangeable through the Industry
Foundation Classes (IFC) data model, i.e. the
international BIM standard for interoperability with
more chance of success.
Fig. 2: Definition of Levels of Detail (LoDs)
Finally, the third phase is characterized by two
levels of implementation, with reference to the
design and the approval phases. In the design phase,
indeed, it provides for the simulation of different
configurations in compliance with the set threshold
limits while, during the approval phase by the public
administration, the model allows the verification of
compliance with the technical implementation
standards.
3 Case Study
The case study is an urban sector located in the
municipality of Nocera Inferiore in South Italy
(figure 3). It is characterized by three sub-sectors
planned to urban regeneration, with the central one
characterized by the presence of an abandoned
building.
Applying the methodology defined in section 2,
the first phase is characterized by an analysis of the
master plan of the area in order to identify which
aspects need to model in BIM, that are useful for the
compliance control of the automated zoning. The
urban transformation envisaged by the master plan
was determined on the basis of the technical
standards of the Municipal Urban Plan, which refer
to both the urban context and buildings (table 1).
Figure 4 represents the spatial distribution of all the
structures, urban facilities and infrastructures
defined by the master plan for the case study.
The configuration includes areas for residential,
office and commercial functions, as well as areas to
accommodate public parking lots, public parks and
structures of common interest. There are no areas
for education, given the presence of primary and
secondary schools close to the sector. The design
hypothesis also provides for a road system, which
consists of two almost perpendicular road arches
that divide the central sub-sector into three parts.
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Fig. 3: Case Study: territorial framework.
Table 1. Indicators for urban context and buildings.
level
Indicators /Abbreviations / Formulas
settlement
- Territorial area1: St= Sf + Sv + Sst
lot
- Land area: Sf = Sc + Ssc
- Covered area: Ssc = Sc + Spav + Sp + Spp
building
- Sc = covered area
- Np = no. floors
- H = building height
- Hi = inter-floor height
- SlpR = gross residential area
- SlpNR = gross non-residential area
- Snr = non-residential area
- Nall = no. Accomodations
- dslpR=per capita provision of SlpR for each theoretical inhabitant of settlement
lot derived
- Land use ratio: Ruf = Slp / St
- Territorial coverage ratio: Rct = Sc / St
- Territorial permeability ratio: Rpt = Sp /St
- Territorial tree planting index: Ialb = Nalb /Sf
- Territorial shrub planting index: Iarb = Narb / Sf
building
derived
- Number of theoretical settlers: Nab = SlpR / dslpR
1 Sf = land area (m2); Sv = road surface (m2); Sst= Urban standard area (m2)
In relation to phase 2, a parametric 3D model of
the study area can be created to conduct BIM-GIS
data coupling and create the required dataset for the
compliance check process. For this application, the
software BIM used is Revit® by Autodesk. The
level of detail of the model, with reference to the
Italian legislation, is equal to a LoD B, i.e. the
entities graphically virtualized as a generic
geometric system or an encumbrance geometry [22,
23]. Specifically, the model can be performed by
creating appropriate PFs. Since these are specific
families, they sacrifice their general use quality and
react parametrically with the entire model.
Particularly, the territorial area, the road surface and
the other indicators are modelled as a conceptual
mass family in the model (figure 5(a)). This choice
derives from the consideration that the total floor
area is available among the parameterized values.
Thanks to this item, this value is immediately
available in the schedule and can be combined in
turn using formulas to obtain other values. In the
BIM software, some concepts mentioned in the
building regulations are not represented either as
defined geometric entities or as specific families.
Therefore, it is necessary to model specific families
as a hierarchy of elements to obtain the data
necessary for the implementation of schedules at the
basis of the calculation of urban indicators. For the
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case study, specific families were created for
modelling the territorial area, land area and road
surface. In this way, the area values can be
calculated automatically. Similarly, for buildings it
is possible to create a specific family, where it is
possible to parameterize some fundamental entities
such as height, width and depth. In this way these
parameters can be modified quickly from the
properties window without necessarily having to
remodel the reference building block (figure 5 (b)).
Fig. 4: Case Study: territorial framework.
(a) (b)
Fig. 5: (a) Parametric 3D Model representation in Revit®; (b) Building parameterization.
Thanks to the creation of PFs, it is possible to
extrapolate appropriate schedules with intrinsic
information of the created geometric model (figures
6 (a)). This information includes the total floor area,
which allows the identification of other indicators of
each building, such as the covered and the land area.
Indeed, the buildings modelling carried out with the
PFs permits also to obtain automatically the
dimensions of the buildings, such as height, width
and depth (figures 6 (b)).
This information, recombined in turn with other
parameters defined by suitable formulas, generates
part of the data necessary for the urban planning
(figures 7 (a) and (b)) in the third phase. The
integration of the GIS with the BIM environments
defines the representation of the configuration at the
urban scale of the development project, which is
characterized by the association of the urban
indicators to each lot. The visualization of the
spatialized indicators (figure 7 (c)), indeed, allows
the rapid control of the assumed value with respect
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to that imposed by urban planning regulations.
Moreover, thanks to the indicators spazialization, it
is possible to monitor different project
configurations to define the layout of the most
suitable configuration for the urban transformations.
(a) (b)
Fig. 6: Schedule properties: (a) defined parameters (b) data deriving from the model.
(a) (b)
(c)
Fig. 7: GIS-BIM integration for urban planning: (a) schedule visualization (b) indicators derived
from the model data; (c) indicators spatialization.
4 Conclusions
In this paper, a methodology of integration between
models created in GIS and BIM environments has
been presented. The main advantage of this
integration consists in the significant reduction of
times related to the calculation of urban planning
standards, surfaces and volumes. Indeed, changes
made to the model geometry are automatically
reflected in all parameters. This immediate
numerical control allows changes in real time until
the set objectives are reached, without long time
calculation and verification processes as occurs
with traditional computer-aided drafting (CAD)
systems. Finally, all the data relating to the models
can be exported in Excel sheets and then merged
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into an information database to which data from
other sources, such as data from GIS, can also be
added.
In a few simple steps, it is possible to create a
BIM model of an area, consisting of an enormous
information structure, which can be further
increased simply by increasing the LoDs of the
model. A model with more information, indeed,
permits the identification of a greater number of
new urban parameters. For example, for buildings
modelled with a LoD D, it could be possible to
obtain data, which in turn, combined in specific
formulas, could allow the definition of
environmental indicators for the territorial
governance.
A future development of this research is the
integration of the defined model with a spatial
decision support system. This could be useful for
the strategic environmental assessment procedures
for areas in relation to their detailed forecasts
defined by the municipal urban plan. Moreover,
this integration could provide quantitative
information on the effects induced by urban
choices on the environment, stimulate participative
contributes, that can become an indispensable
element to support decision-making processes in
the definition of priorities and in the selection of
possible alternatives of the urban transformations.
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