Sixth International Workshop on Geographical Analysis ...paolillo.professor.polimi.it/files/Ricerca/Ppt paper Santander2003.pdf · The 2011 International Conference on Computational

Sixth International Workshop on "Geographical Analysis,

Urban Modeling, Spatial Statistics"

GEOG-AN-MOD 11 in conjunction with

The 2011 International Conference on Computational

Science and its Applications (ICCSA 2011)

June 20 th to June 23 th, 2011,

University of Cantabria, Santander, Spain

Pier Luigi Paolillo(1),

with Alberto Benedetti, Umberto Baresi, Luca Terlizzi, Giorgio Graj

(1) Politecnico di Milano

[email protected] - http://webdiap.diap.polimi.it/paolillo/

mailto:[email protected]

http://webdiap.diap.polimi.it/paolillo/

1. Why the historic centres: a

preliminar consideration

2. The methodological process:

from the selection of descriptor and

variables to the final synthesis in the

“suitability for change” map

3. Method for analysing and

assessing the characteristics of

centrality and socioeconomic

vitality

4. Assessing the values of the built

fabric

5. The final step:

the map of suitability for change

and the relative types of change for

the single built fabrics

Estimate:

(α) residential vitality

(β) commercial distribution

(γ) services accessibility

ASSUMPTION OF THE BEST SCENARIO FOR SUITABILITY FOR

CHANGE OF BUILT FABRICS

Results:

Socio/economic

characterization

5 scenarios derived from “f”

function

Regional

Laws

Support to

administration

Identify types of change

in built fabrics

(art. 27 Lr.12/05)

Classify priority of

intervent in historic

centre

Goal:

Define degrees of suitability for change

of single buildings

Goal:

Identify and quantify demographic,

economic, social tendency

Suitability for change Social and economic phenomena

Database organised to develop Gis analysis

Multi/dimensional analysis

Comparison between scenarios and socio/economic aspects, and selection of the best-one

),,,,,( FEDCBAf

Use an algorithm to create

scenarios of suitability for change

0. The framework assumed

Urban Planning Discussion-ANCSA:

Growing importance (since 50’s) of “historic

centres” issue, related today with a

generalised decay:

- RELATIONAL (population and vacancy)

- STRUCTURAL (appeal and economy)

- PHYSICAL (built fabrics)

1. Why the historic centres: a preliminar consideration

REGULATION assessment in LOMBARDY:

- LR.12/2005: NEW PLANNING

INSTRUMENT, PGT

Goals:

- identify HISTORIC CENTRES

- recognize Types of change for each

fabric

Structuring the method:

Necessity of a different approach based on quantitative analysis

Preliminar analysis of the case-study: territorial phenomena and

planning instruments;

Use of the database to develop analysis and evaluations with Gis

software

Como historic centre:

Worsening in terms of:

- weakness in human relations

- lost of attractivity

- Growing decline and vacancy

in built fabrics

Change of approach:

60’s * conservation of historic fabrics

Today * re-use of built fabrics, in order to:

- not use further free-soil

- use fabric nowadays vacant

Identifying the

variables

Grouping the variables into

summary indicesSocio/

economical aspects

Identifying the spatial units

of investigation

Historic/

architectural aspects

Multidimensional/

algorythm analysis

Areas of iso-

problematicity

Scenarios for

change

Identifying the

descriptor blocks

Selecting the most

suitable scenario for

change in this specific place

Spatialising the phenomena

(thematic mapping)

2. The methodological process: from the selection of descriptor and

variables to the final synthesis in the “suitability for change” map

3. Method for analysing and assessing the characteristics of centrality

and socioeconomic vitality

Function

indicating how various phenomenical

aspects flow together

into the socio/economical analysis

where:

A = tendency to accumulated centrality of

the historic centre;

B = instability of the fabric due to

monofunctionality;

C = density of localisation of the most

strongly attractive activities;

D = stability of the inter-relating residential

fabric;

E = urban landscape importance of

buildings

Innovative tools and applications

Multiple centrality assessment

- Porta et al., 2006; Cardillo et al., 2006;

Crucitti et al., 2006; Scellato et al., 2006

- Similar approach to configurational

analysis (Bill Hillier and the UC London

school)

- Moving from space configuration to recognize

structure and caracteristics of open urban

spaces

Viewshed

- Viewshed analyses: common function of

most Gis software. The analysis uses the

elevation value of each cell of the Dem to

determine visibility to or from a particular cell

- Application of viewshed to built fabric with

specific carachteristics (constraints, facades,

uniformity of a specific built-area)



Indices and variables

A) Mca (Multiple centrality

assessment)

Goal:

recognize the inclination towards

transformation of built fabrics

Indices:

Betweenness -> traffic long-radius

Local closeness -> traffic short-radius

Land use density -> concentration of

extra-residential buildings

Functional heterogeneity -> application of

Shannon index to calculate heterogeneity

Basis:

- Connection

from point to

point to create

Axial map

(ecuclidean

axis) with Mca

tools

Betweenness (x) Local

closeness (y)

Network

interaction (a1)

2

yx

Land use

density (x)

Functional

heterogeneity (y)

Vitality of the

economic fabric

(a2)

2

yx




B) Instability of the fabric due to

monofunctionality

Goal:

Recognize areas with potential risk of

becoming monofuncional and central

“banlieue”

Indices:

Index of ageing -> areas with old

inhabitants

Residential density -> areas with

inhabitants

Index of heterogeneity of non-residential

activities -> monofuncional areas

Basis:

- Make residential

and economical

data interacting

toghether using

Kernel Density

Index of ageing Residential density

Index of

heterogeneity

of non-

residential

activities

Thematic activities




C) Density of localisation of the

most strongly attractive activities

Goal:

Recognize the competitive areas from

the economic point of view

Indices:

Density of commercial activities

Density of service sector activities

Density of

commercial

activities

D) Stability of the inter-relating

residential fabric

Goal:

Recognize problematic residential areas

Indices:

Incidence of the non-Italian resident

population

Incidence of residential vacancy

Distribution of the population within

buildings (underoccupation –

overcrowding)

Density of

service sector

activities

Vacancy

Indices

Variables

Resident

nationality

Residential

buildings size

Roots

Census of

built fabric

Residential

dataset

Census of

built fabric




E) Urban landscape importance

of buildings

Goal:

Recognize buildings with particular

landscape values

Indices:

Building perception -> is the building

seen from relevant points of observation?

Characterisation of the perception -> how

is the building perception?

Basis:

- Advanced applications in Gis softwares:

* building the (Digital Elevation Model);

* selecting points of observations;

* building Viewshed

Building DEM

(DTM+Built fabrics)

Building

VIEWSHED

Points of

observation

Fabrics

with

positive

elements

Fabrics

with

negative

elements

Quantity

of fabric

percepted

Urban

landscape

importance

of buildings



Viewshed procedure

Decomposing the observation

points into a number of different

viewshed analyses

(e.g.: access points to the historic

centre, busiest historic streets,

open spaces for public socialising,

and so on)

Selecting

observation

points

Sifting

informational

strata

Summarising, referring as

necessary to the qualitative

characterisation of the

particular building (E)

Quantifying and

summarising the

degree of

visibility of any

given building

Refining the analysis as appropriate (e.g.:

distinguishing between buildings seen in

perspective and buildings seen in the

round)

Analysis:

if k = 1

the building is

visible



Applied multidimensional geostatistic analysis

i) correlational analysis, aimed at

reducing the number of variables to be

tested and used in the subsequent

stages;

ii) non-hierarchical analysis, which makes

it possible to identify the spaces that are

homogeneous in terms of the variables

adopted for describing the model

From variables and indices to

Multidimensional analysis

Use of dedicated software Addawin (prof.

Griguolo, IUAV of Venice) in the GIS

environment:

from aggregated indicators derived

estimating f (A, B, C, D, E),

to application of geostatistics procedures, in

particular multivariate analysis:

Facplan image:

step that analyses the distribution of the

centres of the stable profiles with respect

to the two axes that most effectively

explain the multivariate situation under

investigation

Phenomena

Clusters

4. Assessing the values of the built fabric

Function

indicating how various phenomenical

aspects flow together

into the built fabrics analysis

where:

F = suitability for retention, intrinsic in the

building itself

G = suitability for retention, in the

relationship between building and urban

blockH = the urban landscape importance of the

context in which the building stands

I = suitability for increases in volume

Assumption of descriptors block and variables


F) Suitability for retention,

intrinsic in the building

Goal:


transformation of built fabrics

Indices/variables:

F1 - presence of environmental and

historic/architectural constraints

F2 - persistence of buildings over time

F3 - the state of conservation of buildings

F4 - presence of facades to be retained

F5 - presence of excrescences

F1 - Contraints F2 - Datation

F3 - Conservation F4 - Facades

F5 - Excrescences



G) Suitability for retention, in the

relationship between building

and urban block

Goal:


transformation of built fabrics, in the

relation with the urban blocks

Indices/variables:

G1 - presence of transformed areas

(causing discontinuities in the urban

fabric)

G2 - degree of uniformity in respect to the

first historic threshold adopted

G3 - degree of uniformity in respect to the

number of storeys

G1 – Transformed

areas

G3 - Uniformity

(number of storeys)

G2 – Uniformity

(first historic

threshold)



H) Urban landscape importance

Goal:

recognize the built fabrics impact on

perception

Indices/variables:

H1 – presence of quality elements

H2 – presence of elements of contrast

H3 – index of perception of the building

H4 – incidence of the building on the

public space

H4 – Perception from public spacesH3 – Index of perception (from historic

roads, points of access, public places)

H2 – Contrast

factors

H1 – Quality

factors



I) Suitability for increases in

volume

Goal:

recognize the building that can be

raised as number of storeys

Indices/variables:

I1 – character of the existing built

frontage

I2 – possibility of adding extra storeys

1 – Built-front with at

least 50% fabrics with

same height

3 –Buildings useful for

raising storeys

4 –Buildings unuseful

(as reference) for

raising storeys

2 – Buildings with

specific characteristics


Algorhythm for assessing suitability for change


Assumption of an

algorithm to classify the

built fabrics

Classification of the result

values

Aggregation of variables

and indices in thematic

blocks

Assumption of different

classes of suitability for

change, for every built

fabrics of the historic centre

Devising the basic

algorhythm of suitability

for change

Creating

scenario 1

Types of change

permitted by the

regulations

Correlating the classes of suitability for change

to the consented methods of changes to buildings

Preparing the map of suitability for change

Devising

different

scenarios

Territorial

socioeconomicconfigurations

Comparing scenarios and selecting the scenario

that is most compatible with these territorial

configurations


Building and selecting scenarios of suitability for change


Classifying and

comparing different

scenario outputs

i) internal consistency:

correlation between suitability for change and the dataset

of variables adopted, identifying excessively high

interdependencies that would indicate a flattening of the

outcomes of the multivariate analysis

ii) external

consistency is the

correspondence

between the

general character of

the scenario, in

terms of suitability

for change, and the

real social,

economic, and

demographic

characteristics of

the territorial

configurations of the

historic core

Building and selecting scenarios of suitability for change

5. The final step:

the map of suitability for change and the relative types of change for the single built fabrics

Final scenario of

suitability for change Cartography

From classes to types of change on built fabrics

5. The final step:

Comparison between prescriptions of the old Prg and the new assessment recognized by Pgt

From a homogeneous

classification of buildings

To a new one, coherent

with the specific

characterization of the

single built fabrics

Previous planning instrument:

Prg -General regulator plan

(1975-1993)

New planning

instrument:

Pgt -Plan for territorial

government (2010)

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