13-jul-07 the urban audit – a combination of hard facts and a perception survey dr. berthold...
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![Page 1: 13-Jul-07 The Urban Audit – a combination of hard facts and a perception survey Dr. Berthold Feldmann Eurostat – the statistical office of the European](https://reader035.vdocuments.mx/reader035/viewer/2022062717/56649e445503460f94b3834f/html5/thumbnails/1.jpg)
13-Jul-07
The Urban Audit – a combination of hard facts and a perception survey
Dr. Berthold Feldmann Eurostat – the statistical office of the European Union
![Page 2: 13-Jul-07 The Urban Audit – a combination of hard facts and a perception survey Dr. Berthold Feldmann Eurostat – the statistical office of the European](https://reader035.vdocuments.mx/reader035/viewer/2022062717/56649e445503460f94b3834f/html5/thumbnails/2.jpg)
Name of the presentation2 / 26
International Forum on Metropolitan Statistics in Beijing
Structure of the talk
What is the Urban Audit
The perception surveys
Some examples
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13-Jul-07
Chapter 1
Since 1999: Comparable European Urban Statistics
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Name of the presentation4 / 26
International Forum on Metropolitan Statistics in Beijing
Dimensions of the Urban Audit dataset More than 260 indicators (derived series)
calculated
Reference years 1991 reduced data set 1996 reduced data set 2001 complete data set 2004 latest data set
We also use neighbouring
years, if th
e reference year
is not available
Three spatial units 321 cities in EU27, plus cities from NO, CH, HR and TR larger urban zones (LUZ) sub-city information
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Name of the presentation5 / 26
International Forum on Metropolitan Statistics in Beijing
Data availability (for the core city)
0%
10%
20%
30%
40%
50%
60%
70%
1991 1996 2001 2004
Reference year
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Name of the presentation6 / 26
International Forum on Metropolitan Statistics in Beijing
Covered domains
1. DEMOGRAPHY
1.1 Population
1.2 Nationality
1.3 Household Structure
2. SOCIAL ASPECTS
2.1 Housing
2.2 Health
2.3 Crime
3. ECONOMIC ASPECTS
3.1 Labour Market
3.2 Economic Activity
3.3 Income, Disparities and Poverty
4. CIVIC INVOLVEMENT
4.1 Civic Involvement
4.2 Local Administration
5. TRAINING AND EDUCATION
5.1 Education and Training (Provision)
5.2 Attainment of Education & Training
6. ENVIRONMENT
6.1 Climate/ Geography
6.2 Air Quality and Noise
6.3 Water
6.4 Waste Management
6.5 Land Use
6.6 Energy Use
7. TRAVEL AND TRANSPORT
8. INFORMATION SOCIETY
9. CULTURE AND RECREATION
9.1 Culture and Recreation
9.2 Tourism
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Name of the presentation7 / 26
International Forum on Metropolitan Statistics in Beijing
Examples of Indicators
Obvious indicators
Population
Income
GDP
Unemployment
Poverty
Unusual indicators Crime rate
Days of sunshine
Cinema places
Noise level
Mode of transport to work
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13-Jul-07
Chapter 2
The perception surveys
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Name of the presentation9 / 26
International Forum on Metropolitan Statistics in Beijing
The first Urban Audit perception survey 2004
Opinion poll in 31 cities of old MS, January 2004
Complementary to hard facts
For example: feeling of safety ≠ small number of recorded crime
300 respondents per city
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Telephone survey with many questions Perception of.. satisfied with public
transport
satisfied with schools
satisfied with hospitals
satisfied with doctors
satisfied with green space
satisfied with sport facilities
satisfied with cinemas
satisfied with cultural facilities
satisfied with public internet access
satisfied with internet access at home
it is easy to find a good job here
foreigner here are well integrated
administrative services help efficiently
air pollution is a big problem here
noise is a big problem here
this is a clean city
resources are spent in a responsible way
satisfied to live in this city
difficulty paying the bills at the end of the month
Feel safe in this neighbourhood
feel safe in this city
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International Forum on Metropolitan Statistics in Beijing
The perception survey 2006
Repeated in December 2006 for 75 cities in 29 countries
Instead of 31 cities in 15 countries
Exactly the same questions asked
Sample size increased to 500 telephone interviews per city
Again: use of fixed telephones only
bias of respondents?
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People are satisfied to live in this city
-50%
-30%
-10%
10%
30%
50%
70%
90%
Gro
ning
en (
NL)
Leip
zig
(DE)
Krak
ow (PL
)Aal
borg
(DK)
Kobe
nhav
en (DK)
New
cast
le (
UK)
Clu
j-Nap
oca
(RO
)Lu
xem
bour
g (L
U)
Ham
burg
(DE)
Gda
nsk
(PL)
Oul
u (F
I)Pi
atra
Nea
mt
Mun
chen
(DE)
Ovi
edo
(ES)
Gra
z (A
T)M
alag
a (E
S)Ren
nes
(FR)
Kosi
ce (SK
)Bur
gas
(BG)
Talli
nn (EE
)Ver
ona
(IT)
Bra
ga (PT
)Za
greb
(H
R)
Bel
fast
(UK)
Dor
tmun
d (D
E)St
rasb
ourg
(FR
)Hel
sink
i (FI
)Am
ster
dam
(NL)
Viln
ius
(LT)
Bor
deau
x (F
R)
Ljub
ljana
(SL
)W
ien
(AT)
Dub
lin (IE
)Car
diff
(U
K)St
ockh
olm
(SE
)Bar
celo
na (ES
)Bol
ogna
(IT
)Li
lle (FR
)Pr
aha
(CZ)
Bia
lyst
ok (PL
)O
stra
va (CZ)
Mal
mö
(SE)
Rom
a (I
T)Ant
wer
pen
(BE)
Gla
sgow
(UK)
Lisb
oa (PT
)Ir
akle
io (EL
)Es
sen
(DE)
Paris
(FR)
Man
ches
ter
(UK)
Rig
a (L
V)
Bra
tisl
ava
(SK)
Rot
terd
am (N
L)Li
ege
(BE)
Ber
lin (DE)
Torino
(IT
)Bru
ssel
(BE)
War
szaw
a (P
L)Ant
alya
(TR
)Ank
ara
(TR)
Mad
rid
(ES)
Mar
seill
e (F
R)
Sofia
(BG)
Bud
apes
t (H
U)
Mis
kolc
(H
U)
Lefk
osia
(CY)
Pale
rmo
(IT)
Val
etta
(M
T)Lo
ndon
(UK)
Fran
kfur
t an
der
Diy
arba
kir (T
R)
Buc
ures
ti (R
O)
Ista
nbul
(TR
)Nap
oli (
IT)
Ath
inia
(EL
)
Somewhat disagree Strongly disagree Somewhat agree Strongly agree
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It is easy to find a good job
-100%
-80%
-60%
-40%
-20%
0%
20%
40%
60%
Prah
a (C
Z)Ko
benh
aven
(DK)
Dub
lin (IE
)Aal
borg
(DK)
Bra
tisl
ava
(SK)
Car
diff
(U
K)Ant
wer
pen
(BE)
Man
ches
ter
(UK)
Am
ster
dam
(NL)
Hel
sink
i (FI
)Lo
ndon
(UK)
Rot
terd
am (N
L)Gla
sgow
(UK)
Lefk
osia
(CY)
Ver
ona
(IT)
Mun
chen
(DE)
Luxe
mbo
urg
(LU)
Paris
(FR)
Stoc
khol
m (SE
)W
arsz
awa
(PL)
Ren
nes
(FR)
Stra
sbou
rg (
FR)
New
cast
le (
UK)
Ljub
ljana
(SL
)Bol
ogna
(IT
)O
ulu
(FI)
Irak
leio
(EL
)Ta
llinn
(EE
)So
fia
(BG)
Bur
gas
(BG)
Bru
ssel
(BE)
Bel
fast
(UK)
Krak
ow (PL
)M
adrid
(ES)
Rig
a (L
V)
Wie
n (A
T)Clu
j-Nap
oca
(RO
)Li
lle (FR
)Ham
burg
(DE)
Gro
ning
en (
NL)
Viln
ius
(LT)
Gra
z (A
T)Li
ege
(BE)
Buc
ures
ti (R
O)
Bar
celo
na (ES
)Bor
deau
x (F
R)
Gda
nsk
(PL)
Val
etta
(M
T)M
alag
a (E
S)M
alm
ö (S
E)Bra
ga (PT
)Ath
inia
(EL
)Bud
apes
t (H
U)
Zagr
eb (H
R)
Ant
alya
(TR
)M
arse
ille
(FR)
Ovi
edo
(ES)
Esse
n (D
E)To
rino
(IT
)O
stra
va (CZ)
Lisb
oa (PT
)Is
tanb
ul (TR
)Rom
a (I
T)Dor
tmun
d (D
E)Pi
atra
Nea
mt (R
O)
Leip
zig
(DE)
Ber
lin (DE)
Ank
ara
(TR)
Kosi
ce (SK
)Bia
lyst
ok (PL
)M
isko
lc (H
U)
Diy
arba
kir (T
R)
Fran
kfur
t/O
der (D
E)Pa
lerm
o (I
T)Nap
oli (
IT)
Somewhat disagree Strongly disagree Somewhat agree Strongly agree
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Air pollution is a big problem
-100%
-80%
-60%
-40%
-20%
0%
20%
40%
60%
Gro
ning
en (
NL)
Bia
lyst
ok (PL
)Aal
borg
(DK)
Piat
ra N
eam
t (R
O)
Fran
kfur
t an
der
Ode
r (D
E)O
vied
o (E
S)Ren
nes
(FR)
Ham
burg
(DE)
Oul
u (F
I)New
cast
le (
UK)
Leip
zig
(DE)
Mal
mö
(SE)
Luxe
mbo
urg
(LU)
Wie
n (A
T)Car
diff
(U
K)Dor
tmun
d (D
E)Ank
ara
(TR)
Esse
n (D
E)Bor
deau
x (F
R)
Stoc
khol
m (SE
)Bel
fast
(UK)
Bra
ga (PT
)Dub
lin (IE
)Ir
akle
io (EL
)Diy
arba
kir (T
R)
Ant
alya
(TR
)M
alag
a (E
S)M
unch
en (
DE)
Hel
sink
i (FI
)Ko
sice
(SK
)M
isko
lc (H
U)
Ost
rava
(CZ)
Ber
lin (DE)
Gla
sgow
(UK)
Talli
nn (EE
)M
anch
este
r (U
K)Li
lle (FR
)Is
tanb
ul (TR
)Gda
nsk
(PL)
Bra
tisl
ava
(SK)
Kobe
nhav
en (DK)
Rig
a (L
V)
Ljub
ljana
(SL
)Li
ege
(BE)
Clu
j-Nap
oca
(RO
)Ant
wer
pen
(BE)
Krak
ow (PL
)Am
ster
dam
(NL)
Zagr
eb (H
R)
Mar
seill
e (F
R)
Gra
z (A
T)W
arsz
awa
(PL)
Bar
celo
na (ES
)Pa
lerm
o (I
T)Rot
terd
am (N
L)Bru
ssel
(BE)
Lefk
osia
(CY)
Bud
apes
t (H
U)
Prah
a (C
Z)St
rasb
ourg
(FR
)Viln
ius
(LT)
Lond
on (UK)
Lisb
oa (PT
)Nap
oli (
IT)
Paris
(FR)
Mad
rid
(ES)
Torino
(IT
)Bol
ogna
(IT
)Buc
ures
ti (R
O)
Ver
ona
(IT)
Sofia
(BG)
Bur
gas
(BG)
Rom
a (I
T)Val
etta
(M
T)Ath
inia
(EL
)
Somewhat disagree Strongly disagree Somewhat agree Strongly agree
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It is easy to find good housing at a reasonable price (only the capitals)
-100%
-80%
-60%
-40%
-20%
0%
20%
40%
60%
Ber
lin (
DE)
Mad
rid (
ES)
Ath
inia
(EL)
Budap
est
(HU
)
Anka
ra (
TR
)
Wie
n (
AT)
Bru
ssel
(B
E)
Sofia
(BG
)
Tal
linn (
EE)
Viln
ius
(LT)
Val
etta
(M
T)
Pra
ha
(CZ)
Ljubljan
a (S
L)
War
szaw
a (P
L)
Rig
a (L
V)
Lefk
osi
a (C
Y)
Lisb
oa
(PT)
Zag
reb (
HR
)
London (
UK
)
Am
ster
dam
(N
L)
Rom
a (I
T)
Koben
hav
en (
DK
)
Bra
tisl
ava
(SK
)
Hel
sinki
(FI
)
Sto
ckholm
(SE)
Bucu
rest
i (R
O)
Luxe
mbourg
(LU
)
Dublin
(IE
)
Par
is (
FR)
Somewhat disagree Strongly disagree Somewhat agree Strongly agree
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Satisfied with the cultural facilities (selection of cities)
-40%
-20%
0%
20%
40%
60%
80%
100%
Hel
sin
ki (
FI)
Mu
nch
en (
DE
)
Lei
pzi
g (
DE
)
Ko
ben
hav
en (
DK
)
Wie
n (
AT
)
Ou
lu (
FI)
New
cast
le (
UK
)
Am
ster
dam
(N
L)
Sto
ckh
olm
(S
E)
Gla
sgo
w (
UK
)
Par
is (
FR
)
Ber
lin
(D
E)
Tal
lin
n (
EE
)
Mal
mö
(S
E)
Pra
ha
(CZ
)
Du
bli
n (
IE)
Bru
ssel
(B
E)
Lo
nd
on
(U
K)
Bu
dap
est
(HU
)
Lu
xem
bo
urg
(L
U)
Lju
blj
ana
(SL
)
War
szaw
a (P
L)
Bar
celo
na
(ES
)
Lis
bo
a (P
T)
Ro
ma
(IT
)
Mad
rid
(E
S)
Mar
seil
le (
FR
)
Val
etta
(M
T)
Bu
cure
sti
(RO
)
Ath
inia
(E
L)
Lef
kosi
a (C
Y)
Ista
nb
ul
(TR
)
Bia
lyst
ok
(PL
)
An
taly
a (T
R)
An
kara
(T
R)
So
fia
(BG
)
Irak
leio
(E
L)
Bu
rgas
(B
G)
Diy
arb
akir
(T
R)
Rather unsatisfied Not at all satisfied Rather satisfied Very satisfied
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Name of the presentation17 / 26
International Forum on Metropolitan Statistics in Beijing
The synthetic index (SI)
In order to express the perception in the cities by 1 single figure, a simplified index was calculated:
srespondant allsatisfied) allat not dunsatisfie(rather satisfied)rather satisfied(very
This index is between -1 (all are unsatisfied) and +1 (all are satisfied). To make it more readable, it was multiplied by 50, then 50 added
Hence the SI can have values between 0 and 100. At the value of 50 half are satisfied, half are unsatisfied
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Foreigners are well integrated
0
20
40
60
80
100
Mal
mö
Stoc
khol
mBe
rlin
Wie
nG
raz
Dor
tmun
dRo
tter
dam
Athi
naAn
twer
pen
Ham
burg
Esse
nH
elsi
nki
Torin
oLe
fkos
iaKø
benh
avn
Vero
naAm
ster
dam
Paris
Brus
sels
Leip
zig
Aalb
org
Belfa
stM
ünch
enBa
rcel
ona
Mad
ridN
apol
iRo
ma
Bolo
gna
Talli
nnLo
ndon
Lièg
eSt
rasb
ourg
Dub
linM
arse
ille
Fran
kfur
t/O
der
Ost
rava
War
szaw
aD
iyar
baki
rLi
lleLi
sboa
Prah
aBi
ałys
tok
Bord
eaux
Luxe
mbo
urg
Pale
rmo
New
cast
leIs
tanb
ulRi
gaG
lasg
ow
Man
ches
ter
Anka
raZa
greb
Oul
uO
vied
oVi
lniu
sM
álag
aLj
ublja
naBu
cure
sti
Brat
isla
vaG
roni
ngen
Card
iffIr
akle
ioBr
aga
Gda
ńsk
Renn
esVa
llett
aSo
fiaKo
sice
Anta
lya
Buda
pest
Mis
kolc
Krak
ówBu
rgas
Piat
ra N
eam
tCl
uj-N
apoc
a
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Foreigners are well integrated(worst and best cases)
0
20
40
60
80
100
Mal
mö
Stoc
khol
m
Ber
lin
Wie
n
Gra
z
Dor
tmun
d
Rot
terd
am
Ath
ina
Ant
wer
pen
Ham
burg
Esse
n
Hel
sink
i
Tori
no
Lefk
osia
Køb
enha
vn
Ver
ona
Am
ster
dam
Par
is
Bru
ssel
s
Buc
ures
ti
Bra
tisl
ava
Gro
ning
en
Car
diff
Irak
leio
Bra
ga
Gda
ńsk
Ren
nes
Val
lett
a
Sofia
Kos
ice
Ant
alya
Bud
apes
t
Mis
kolc
Kra
ków
Bur
gas
Pia
tra
Nea
mt
Clu
j-N
apoc
a
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People feel safe in the city
0
20
40
60
80
100
Ista
nbul
Nap
oli
Sofia
Athi
naBu
cure
sti
Diy
arba
kir
Mar
seill
eLi
ège
Ost
rava
Prah
aLi
sboa
Burg
asTa
llinn
Anta
lya
Viln
ius
Brus
sels
Torin
oBr
atis
lava
Riga
Bolo
gna
Buda
pest
Rom
aW
arsz
awa
Mad
ridPa
lerm
oLo
ndon
Kosi
ce Lille
Berli
nG
dańs
kM
alm
öAn
kara
Zagr
ebKr
aków
Antw
erpe
nM
isko
lcM
anch
este
rVa
llett
aBa
rcel
ona
Stra
sbou
rgBi
ałys
tok
Dub
linLe
fkos
iaVe
rona
Irak
leio
Ljub
ljana
Dor
tmun
dEs
sen
Belfa
stFr
ankf
urt/
Od
Mál
aga
Renn
esG
raz
Card
iffLe
ipzi
gG
lasg
ow
Rott
erda
mBo
rdea
uxH
ambu
rgCl
uj-N
apoc
aW
ien
Paris
Stoc
khol
mBr
aga
Luxe
mbo
urg
Amst
erda
mPi
atra
Nea
mt
New
cast
leH
elsi
nki
Mün
chen
Købe
nhav
nG
roni
ngen
Ovi
edo
Oul
uAa
lbor
g
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People feel safe in this city(worst and best cases)
0
20
40
60
80
100
Ista
nbul
Nap
oli
Sofia
Ath
ina
Buc
ures
ti
Diy
arba
kir
Mar
seill
e
Lièg
e
Ost
rava
Pra
ha
Lisb
oa
Bur
gas
Talli
nn
Ant
alya
Viln
ius
Bru
ssel
s
Tori
no
Bra
tisl
ava
Rig
a
Leip
zig
Gla
sgow
Rot
terd
am
Bor
deau
x
Ham
burg
Clu
j-N
apoc
a
Wie
n
Par
is
Stoc
khol
m
Bra
ga
Luxe
mbo
urg
Am
ster
dam
Pia
tra
Nea
mt
New
cast
le
Hel
sink
i
Mün
chen
Køb
enha
vn
Gro
ning
en
Ovi
edo
Oul
u
Aal
borg
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Correlations:air pollution - noise
R2 = 0.700
0
10
20
30
40
50
60
70
80
90
0 10 20 30 40 50 60 70 80 90
noise is a big problem
air
polluti
on is
a big
pro
ble
m
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Weak correlations:unemployment – easy to find a job
R2 = 0.469
0
10
20
30
40
50
60
70
80
0 5 10 15 20 25
Unemployment rate (NUTS-3 regions)
it is
easy
to fi
nd a
good job
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No correlations:recorded crime – feeling safe
R2 = 0.103
0
10
20
30
40
50
60
70
80
90
100
0 50 100 150 200 250 300 350
Recorded crime / population
Peo
ple
fee
l sa
fe
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Name of the presentation25 / 26
International Forum on Metropolitan Statistics in Beijing
Comparison 2006 to 2004
On average, opinions remained stable from January 2004 to December 2006
There are however some significant changes of opinion in individual cities
For two questions, also the average opinion moved:
“it is easy to find a good job” 32% to 41%
“this is a clean city” 42% to 49%
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Thank you for
your attention!
Any questions?