University Precincts in Lisbon Metropolitan Area: A Morphological description

UNIVERSITY PRECINTS IN LISBON METROPOLITAN AREA: A MORPHOLOGICAL DESCRIPTION

Cannas da Silva, Luísa and Heitor, Teresa

Instituto Superior Técnico

Abstract

This paper was carried out as part of the framework of IN_LEARNING research project (http://in‐

learning.ist.utl.pt) and aims at exploring an exploratory tool to map and describe university

facilities. The main purpose is to understand their morphological features and spatial integration

patterns within the urban territory, considering both the metropolitan area scale and the city‐

university interaction. Lisbon is therefore used to test the proposed tool.

This paper is organized in four parts. The first one reviews the key themes involving university

facilities planning and design in contemporary urban societies and justifies the relevance of

designing an exploratory tool to map and describe their location and morphological features. The

second introduces the descriptive strategies applied in the design of the exploratory tool and the

corresponding spatial and non‐spatial variables that were selected. The third part illustrates the

application of the proposed tool to map and describe university facilities in the Metropolitan Area

of Lisbon. In the fourth part, nine university precincts were used as case studies to test the

capabilities of the technique.

The proposed tool reveals a high level of performance to explore how university facilities turn out

to be integrated into the urban structure. In particular it allows understanding the extent of their

spatial concentration versus spatial dispersion and the definition of inner city locus versus city

nodes or outskirt.

Keywords: university precincts, morphological description, descriptive tool

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1.INTRODUCTION

Accompanying the expansion of higher education systems worldwide, beginning in the 1950’s and

60’s in the western societies and recently pronounced in many developing regions, university

facilities were established not only in, but also outside the city core, i.e. the morphological center

(Heitor, 2006) and, above all, in urban edges, facilitating new urban expansions. When conceived

as autonomous entities, universities facilities cause the isolation of academic communities,

highlighting ruptures within the urban fabric and originating unsustainable mobility patterns

(Hillier, 2007). On the other hand, one can argue that when universities facilities are built within

the city core, the preservation of their uniqueness and distinctive features may be easily affected

by the surrounding environment thus requiring special consideration.

Since the late 20th century, the role of university facilities in the urban dynamics has become a

focus of research within the framework of urban revitalization (Wievel and Perry, 2008). Research

has involved the identification and debate of the effects of university facilities on the process of

urban development, such as employment, housing, mobility, leisure and consumer activities

(Indovina 1998) as well as the discussion on gains from developments and broader institutional

relationships with the city in which university facilities are located (RIBA 2008). These studies have

emphasised the ambiguous and contingent role often played by university facilities in the process

of urban development worldwide, which are not always explicitly incorporated into the strategy of

the main urban agents and planning decisions.

Yet it becomes consensual that Universities’ activities impact in many ways on their vicinity and

wider communities to the mutual benefit of both. In addition to educational and R&D activities, a

third strand, that of civic engagement, is progressively becoming more significant in today’s

universities mission. This may have substantial implications for the built environment since the

wider community will have access and make use of university facilities for a range of activities.

Besides, universities can contribute to urban regeneration, by directly improving the quality of the

urban fabric, and helping to reclaim parts of cities and leverage funds from public regional players.

Equally, there is evidence, that the spatial structure of university facilities has a major impact on

the “flow of technology” (Allen 1977) and can act as catalysts for the transformation process from

an industrial to a knowledge based society. Policy research over the last two decades highlights

the role of knowledge in economic and social developments (Conceição and Heitor, 1999; Barnett

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and Temple, 2006), and some authors suggest that higher education sector will become one of the

main drivers of emerging economies in the next decades (Duderstadt, 1999)

Furthermore, the increasing democratization of higher education, student enrolment and diversity,

and advances in technology, the spectrum and scope of knowledge‐based environments are

expected to continue to transform and evolve, putting pressure on existent university facilities

(Thomas and Brown, 2011; Wagner, 2012).

Research suggests that a paradigm shift is required to ensure modernizing university learning

environments in coming decades and points out that university facilities must be reconfigured to

better support changes, foster the production of innovative knowledge to support

competitiveness and promote exchanges with the local economy.

Actually, higher education excellence requires universities facilities that provide the academic and

scientific community with resources and services, which not only support education and research

in their respective fields but also lead its development into new directions and create an attractive

environment for those who use them. A research study conducted in England by CABE (CABE,

2005) focused upon the quality, functionality and impact of built space from the perspective of the

academic community, shows that students who indicated that the physical environment had an

influence upon their learning performance stated that it has contributed in three main ways. First,

it helped to motivate students in their work. Second, it facilitated inspiration amongst students,

and finally it provided key facilities critical to the course. Staff indicated that academic factors

associated with their job (including interest in the type of work and the quality of their fellow staff

and support staff), together with the facilities they had access to, (including the quality of the

office and support facilities) impacted equally upon their performance.

Besides rethinking university‐learning spaces at the architectural design scale, it becomes critical

to reassess university facilities in terms of their spatial integration within the urban territory,

considering both the metropolitan area scale and the city‐university interaction, which should be

understood as an inevitable component of university collective life.

The purpose of this paper is to contribute to such efforts by developing a specific exploratory tool

to map spatial and non‐spatial data concerning existing or proposed university facilities and

relating their morphological features to the urban territories where they are located.

Such analytical tool was developed within the framework of IN_LEARNING research project

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(http://in‐learning.ist.utl.pt), which concentrates on the design of learning facilities including the

definition of a typological classification for learning spaces and the evaluation of future needs for

universities facilities.

2. THE ANALYTICAL TOOL RATIONALE

The analytical tool was specifically designed as a mapping profile, aiming at:

• compiling spatial and non‐spatial information on existing university facilities

• creating a base map upon which to place the information

• building a comprehensive data base inventory ;

• defining a typological classification of university facilities;

• understanding which spatial features are relevant;

• developing a spatial benchmarking system, making possible comparisons between

university facilities

2.1. METHODOLOGY: THE UNIVERSITY MAPPING PROFILE

The mapping profile was developed to operate on two scales by combining a macro analysis of the

urban structure with a microanalysis of the internal structure of the university facilities. It

combines spatial network analysis (space syntax), with documentary analysis complemented by in‐

situ observations.

At the macro scale, Depthmap software (Turner 2004) was used in order to build a topological

map (axial map), which is used as a base map, considering the scale of the metropolitan area

under analysis.

The axial map description (Heitor and Pinelo, 2006) operates as a macro analysis of the urban

structure. It allows a representation of information on a plane in topological relationship and with

measurable horizontal distances, i.e. a metric analysis of the catchment area and an angular

segment analysis of global integration (closeness centrality) and global choice (betweeness

centrality). At same time it has sufficient geographic reference information to identify the location

of each university infrastructure.

At the micro‐scale, the university infrastructure was analysed taking into consideration spatial and

non‐spatial data. The analysis was carried out in two different stages. The first one considered

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direct observations and fieldwork. It includes the survey of spatial and non‐spatial data. Variables

were chosen in order to create an objective and accurate analysis and to allow the definition of

ratios in order to identify spatial patterns, (e.g the average space available for student).

The second stage was focused on the data analysis. Spatial data were manipulated and presented

in a graphical support, based on physical‐analogue representations, in order to provide a clear and

legible communication tool in a simple and informative manner.

3. THE MACRO ANALYSIS: UNIVERSITY FACILITIES IN THE LISBON METROPOLITAN AREA

The Lisbon Metropolitan Area, with a total area of 2.962,6 Km2 and a population of about

2.815.851 inhabitants (2011 census), has been growing since the 60s until the late 80's according

to a centre‐periphery model, based on a process of suburbanization highly dependent on road and

public transport networks leading to the dispersion of population with lower together with less

qualified urban activities. From the eighties on, the evolution of the metropolitan structure was

characterized by the fragmentation of its economic, urban, natural and social dimensions and the

constellations of new central places, no longer coincident with the conventional urban centres. In

the nineties this dynamic was reinforced by a demographic and functional reshaping of the

metropolitan area due to the decrease of population in the city centre and the relocation of new

activities on more peripheral areas, such as university/science and technology parks, office parks

and large shopping malls.

The spatial pattern of university facilities in the LMA is related with this process of urban growth.

It comprises a total of 92 university facilities, of which 46 (50%) are public, 36 (40%) private, 5 (5%)

concordate and 5 (5%) military.

These facilities are located in only 8 of the 19 municipalities that compose the LMA. Their

dispertion is extremely uneven, since 92 (80%) of the university buildings are located in the city of

Lisbon, while Almada and Oeiras host 6 (6,5%) each, Amadora, Loures and Odivelas host 1 (1%)

and Cascais and Sintra both host 2 (2%) university facilities, as observed in the picture below

(Figure 1).

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Figure 1 - Distribution of university facilities within the LMA

The university location pattern shows a higher degree of concentration towards the city centre in

opposition to a more disperse pattern in the surrounding areas with a tendency to become more

disseminated as the distance from the city centre increases. While the oldest facilities are placed

in the city core, universities founded from the late 1960s up to 1980s are positioned on the edges

of the city or adjacent to city nodes and those established after the 1990s can be found on the

outskirts of the city in sparsely populated areas, often integrated, or adjacent to science and

technology parks.

These university facilities were classified in two main groups: isolated buildings and precincts. Due

to the ambiguous meaning of “university campus” and its connotation with the American model

(Turner, 1984) it was decided to adopt the term “precinct” to designate all the university facilities,

which involve more than one isolated building whether they are located within a gated territory or

imbedded in the urban tissue (Cannas da Silva, 2011). The precincts size vary between 6 700m2

and 140 000m2.

Public higher education Private higher education Concordat higher education Military higher education

+ integration -

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It is also possible to infer a connection between the location and the size of the university precinct,

with a tendency for the largest and most recent precincts to be located outside of the city core. In

the late 20th century, university facilities were also developed from the conversion of existing

facilities, which were vacant and deteriorating such as military barracks, hospitals or industrial

buildings.

About 52% of university precincts occupy privileged areas in terms of accessibility, being located

within the integration core i.e. the 25 % of the most integrated spaces (Hillier and Hanson 1984).

61% of the analysed precincts show integration values above the average value (0.222)

considering the whole spatial system. The precincts located outside the city centre tend to exhibit

a lower density of occupation.

>100 000 m2 30 000 – 100 000 m2 10 000 – 30 000 m2 5 000 – 10 000 m2 <5 000 m2

Figure 2 - Relation integration/area of the university precincts in the LMA

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Chart 1 - Campus integration value

4. THE MICRO ANALYSIS: INTERNAL STRUCTURE OF THE UNIVERSITY FACILITIES

The microanalysis was focused on the internal structure of university facilities. It was tested in a

set of nine public university precincts, illustrated in the picture below. (Figure 4)

Figure 3 - Location of the case studies

1 – University City of Lisbon; 2 – Alto da Ajuda Campus; 3 – ISA Campus; 4 – IST Alameda Campus; 5 – IST Taguspark Campus; 6 – Campolide Campus; 7 – FCT Campus; 8 – Benfica Campus; 9 – ISEL Campus

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Spatial data includes location, shape and dimension, geo‐morphological attributes, land use

patterns of university facilities as well as their accessibilities to road network and to public

transports network. In order to apply the same basis of analysis, quantifiable and measurable

variables were chosen, such as surface and net floor area, open space area, number of users, type

of physical boundaries and accessibility. Non‐spatial data considers information regarding the

institution’s mission, history, and development process, previous uses and structures, university

population, admissions records and census data.

The microanalysis was organized in the form of a study chart, focusing on different spatial

variables as shown in Figures 4‐6.

Figure 4 – University City of Lisbon analysis

A – Main axis; B – Relation with the environment; C – Built/Void; D – Outdoor areas; E – Road network system; F – Land morphology

These study charts emphasize the study of the precinct morphology. Therefore, the graphic

analysis presented focuses on physical characteristics, along with historical notes on what

influenced the development of each precinct. A build/void plan is presented (C) as an attempt to

understand the volumes within the precinct, their geographical dispersion and the facilities

included in each one.

The analysis of the outdoor areas (D) aims to give further detail and information on the precincts

life according to its outdoors areas. It allows not only understanding the relation between interior

and exterior and outdoors leisure areas but also shows the spaces whose uses could be adjusted

into better fulfilling the needs of each particular precinct.

A B C

D E F

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Figure 5 - ISA Campus analysis


As far as insertion in the road network system (E) is concerned, this analysis complements the

integration analysis observed in the macro analysis chapter, showing a closer scale, informing on

accesses, boundaries and connections.

Land morphology is also analysed, in aspects such as topography, remarkable elements and

special features and characteristics, aiming to understand the conditions prior to the design of a

university precinct and their influence in it.

Figure 6 – IST Alameda Campus analysis


A B C

D E F

A B C

D E F

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These nine precincts were selected to test the analytical tool and assess its capabilities. Besides

the range of dimension (area), types, number and density of buildings and facilities, which are

contained within their grounds, their location within the LMA urban network reveals different

levels of accessibility, density regarding built fabric and population, connectivity regarding

transport systems, especially multimodal areas which allow their insertion into the metropolitan

network and diversity regarding heritage, type of facilities and functional, and uses condition This

variety allows the extrapolation to other situations, as it characterizes different precinct types and

morphologies.

Table 1 - Case studies comparison

These nine case studies prove that the university precincts can assume different morphologies and

typologies. It is shown that the majority of them are located in central areas of the city and/or in

areas with good integration levels, in what accessibility and mobility are concerned. Despite this

fact, analyzing the urban morphology, most precincts show differences from their close

environment, behaving as isolated entities, even when their location is central.

5.CONCLUSION

The proposed exploratory tool reveals a suitable level of performance to explore how university

facilities turn out to be integrated into the urban structure. In particular it allows understanding

the tendency of their spatial concentration versus spatial dispersion and gives information to

further explore the concept of inner city locus versus city nodes or outskirt.

At the macro scale, the data obtained will be used as part of future steps of IN_LEARNING project

to explore to what extent the university facilities are integrated into the urban fabric and have the

potential for exchange with the local economy, as a prerequisite to act as a driver of change in the

surrounding area. At the micro scale, it will be used to assess the performance of the university

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facilities and in particular to understand the impact of the university physical environment in the

process of new knowledge generation and its transmission. The axial map description applied as a

base map in the macro analysis can also be used to explore the variable form‐space of the

precincts in order to reveal their internal accessibility, the physical and visual barriers and the level

of permeability of the internal space, as well as the distribution of uses and the patterns of

movements and encounters.

The mapping tool provides a collaborative environment that promotes information sharing, data

visualization, interpretation and analysis. It also detects relationships between spatial and non‐

spatial variables and association rules and recognizes spatial distribution and clustering patterns.

As it was organized and accessed in an inventory format and computerized as a data base

inventory, the data collected can be integrated within a GIS platform in a user‐friendly manner

and combined with spatial data mining techniques so as to select as many variables for analysis as

appropriate, to define spatial attributes hierarchy and control thresholds in different levels.

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ACKNOWLEDGEMENTS

This research has been carried out within the framework of the IN_LEARNING project. It was

funded by the Portuguese Science Foundation (FCT). We FCT). We thank the FCT for supporting

our work.

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University Precincts in Lisbon Metropolitan Area: A Morphological description

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