GHOST GHOST TO TO HOST HOST?
Context
In the coming decades, urbanization will become a decisive trend. Today, 50% of the world’s 7 billion people live in cities, and by 2050 this proportion will rise to 70%. Cities are home to extreme poverty and environmental degradation, and one billion people live in slums. In the past few years, the number of slum dwellers in many countries has increased significantly, while urban inequality has become increasingly serious. At the same time, about 75% of global economic activity is urban activity, and as the urban population grows, the city's share of global GDP and investment will also increase. Experts even predict that the land used to build cities will double in the next 20 years. To become a sustainable city in urban development, it is necessary to establish strong transportation, infrastructure and other systems, and gradually reduce the shortage of infrastructure in the city, stimulate public and private actions, promote comprehensive thinking and strengthen accountability. Since many future towns have not yet been built, their design and shape must be actively guided to achieve long-term sustainability. A positively designed guidance and predictive vitality value, a dedicated, independent urban sustainable development goal for mobilizing stakeholders, promote a comprehensive approach at the city level and accelerate the realization of this goal. So The aim of “GHOSTtoHOST� tool is to measure the value of urban vitality which presents a major sustainable development opportunity , especially in areas with vacant spaces and low urban vitality.
Urban Vitality
The Urban Vitality is the urban synergy from “variety" of social , economical opportunities and environment. The more the citizens are active in
Measuring urban vitality is the most important and basic information in sustainable development opportunities.
SynergiCity: Reinventing the Postindustrial City
the urban, the more the urban is a vivid and living place. The city is a phenomenon of structured complexity. Good cities tend to be a balance of a reasonably ordered and legible city form, and places of many and varied comings and goings, meetings and transactions. This kind of space is the successful result of the process of place making for people. - - SynergiCity: Reinventing the Postindustrial City
urban vitality
Environment UV
URBAN VITALITY
Economy
Social
A balanced environment. Respect nature spaces ďźŒ density of buildings andhabitation.
Transportation networks support citizens ’connectivity between environment and economic activities.
Create a urban life that needs a rich combination of sustains economicsocial activity.
https://architizer.com/blog/inspiration/industry/lessons-from-brazil-urban-acupuncture-with-architect-turned-mayor-jaime-lerner/
Sustainable systems in urban vitality
Sustainbale systems
Vegetation
Trees contribute to good mental health by improving people’s quality of life and wellbeing and establishing links between people and nature.
Construction
The physical aspect of urbanism, emphasizing building types, thoroughfares, open space, frontages, and streetscapes
Mobility Accessibility
It measures weight of distance between livingspaces and stations
Community
Measure level of economical activities for citizens in city.
Service
Measure level of urban functions for citizens
Planning urban landscapes with trees can increase property value, and attract tourism and business ďźŒby up to 20%.
http://www.fao.org/zhc/detail-events/en/c/454543/
Crime Reduction,Researchers have discovered reductions in both violent and petty crime, including domestic violence through the therapeutic, calming influence of mature tree planting.
https://www.smartcitiesdive.com/ex/sustainablecitiescollective/why-we-need-trees-our-cities/1100050/
Vegetation
Construction
Construction happening in the environment have both negative and positive effect on the natural and built environment. Open spaces and living spaces are important organization for sustainable urban.
Mobility assessibility
Based on the capacity of an urban built environment to boost lively social activities, a framework has been developed for measuring urban vitality using the dimensions of built environment, human activities and human-environment interaction. a key component of compact liveable communities where everything is within reasonable distances.
Community
In the community especially the economies point to the phenomena where large urban regions are more productive. Urban area with high levels of urbanization tend to contribute to the strongest urban GDP growth.
Service
The service reflects the demand of the city. The higher the consumption in the reaction area, the higher the rate of economic growth.
Urban vitality framework and Key Performance Indicator
Mob Acce ility ssibi li
Environment UV
URBAN VITALITY
Economy
Social
Habitation density Commerical density Service density Urban fabric density
y sit den ix nt m me use art Ap lding i Bu
ty
NDVI
Urban Vitality
?
“GHOSTtoHOST” tool
State of art strategies
Reference project strategy plan
The Rust Belt North America
Known as the industrial heartland of the U.S., the Northeast region along the Midwest and the Great Lakes, spanning up to New York and New Jersey in the East, is nowadays often referred to as Rust Belt, indicating the shrinkage of its once-powerful industrial sector, the ensuing economic decline and population loss. It’s name can be derived from the abandoned factories and urban decay that have marked the region since the 1970s. Affected cities suffered several difficulties, including population loss, lack of education, declining tax revenues, high unemployment and crime. However, recent reports suggest that the Great Lakes region has a sizable potential for transformation.
+ Community + Innovation Park + Local Economy + Residential + Education
Reference Reference projectproject strategy plan
NDSM Netherland
In 1984, the shipyard went bankrupt after years of changing economic times, mergers and reorganisations. Within a few years, more and more artists and creatives started taking up resi-
dence on the vast site.
In the years ahead, the NDSM site will once again take on an increasingly residential character. Amsterdam’s ‘Koers 2025’ (‘Towards 2025’) city plan calls for some 1,300 homes to be built at the NDSM-werf by the year 2025.
+Community +Local Economy+ Residential+ Port
Reference project strategy plan Vegetation Structure organization
Mobility Accessibility Community Service
Based on indicators, in projects how did they design strategies and set up new identity to improve regional vitality ?
Ability
Low urban vitality spaces and empty spaces for local people have much more potential ability to develop a sustainable and Socio-environmental-economy spaces . 1.Creating a land use strategy for spaces is of central importance. 2.Finding which indicator is the most important help urban planners simulate strategies in Low urban vitality spaces or empty spaces. 3.Reshape area.
Project ideas
+
Score of urban vitality
“GHOST to HOST”Tool
Project
To illustrate this tool, this paper takes Barcelona city as an example.
Current Situation
9.1% of still developable 52% of vacant land
48% land use
https://urbanresiliencehub.org/city-dimensions/barcelona/
Barcelona Metropolitan Area (AMB) includes 36 municipalities, is home to 3.2 million people and exhibits a land use rate of 48% – against a 52% of vacant land. The latter totals 40.124 hectares – 17,5% of which are still developable – and is mainly composed by made of woodland, beaches and non-occupied land.
The region analysed includes the city of Barcelona and 9 surrounding townsďźŒon urbanism activist Jane Jacobs' ideas on how cities should be configured to become vital spaces: 23% of the area presents a high level of vitality, while 34% is moderate, and a significant part is classified as little (25%) or none (17%).
17% of none
23% high
25% little
34% moderate
https://www.uab.cat/web/newsroom/news-detail/mapping-the-urban-vitality-of-barcelona-1345668003610.html?noticiaid=1345767359608
Current Situation
Project Aim
The project identifies KPIs to measure and spatially map urban vitality in cities. This allows us to identify Low urban vitality areas, and also identify strategically what actions can be taken in these areas to enhance the urban vitality (which KPIs and parameters are lacking). To be able to act on these, the project in parallel maps vacant spaces, and overlapping these 2 maps to locate areas in which we can act to enhance the urban vitality of the area. Also to identity urban land-use and set up relationships fomulas with urban vitality which explain KPIs in diversity of land use has different of influenced weight that is the basis for strategic planning decisions for urban planners . Finally the project simulation diverse development stratgies and setting a libarary in tool to reshape spaces. In process, to investigate and begin on KPIs through Artificial Nerual Network(ANN) algorithm to predict the score of urban vitality . to find which indicator is the most important to impact urban vitality by features importanc ,and measure urban land use by k-nearest neighborhood classification .
Thesis framework
NDVI Habitation density Apartment density Density of urban fabric(%) Building-use mix index Commercial density Service density Accessibility
Residential Commercial Nature Industry Transport
K-n Art ific a
l ne ura
l ne
two
rk
Identity low + what parameters urban vitality are missing
Measure Score of urban vitality low
Vacant spaces
influenced weight feature in different urban land use + importance (multiply linear regreesion)
high
Map to locate
Overlap
identiy urban spaces to act and enhence urban vitality
Urban land use
KPIs
d
hoo
bor
igh
ne est ear
Measure diversity of urban land use
Strategy simulate tool
Decision making
Data collection
NDVI Habitation density Apartment density Density of urban fabric(%) Building-use mix index Commercial density Service density Accessibility
Residential Commercial Nature Industry Transport
K-n Art ific a
l ne ura
l ne
two
rk
Identity low + what parameters urban vitality are missing
Measure Score of urban vitality low
Vacant spaces
influenced weight feature in different urban land use + importance (multiply linear regreesion)
high
Map to locate
Overlap
identiy urban spaces to act and enhence urban vitality
Urban land use
KPIs
d
hoo
bor
igh
ne est ear
Measure diversity of urban land use
Strategy simulate tool
Decision making
Data Collection
Barcelona
(41째 23' 24.7380'' N / 2째 9' 14.4252'' E)
GRID:133.3m*133.3m
metro/bus stop
site
41째 23' 24.7380'' N / 2째 9' 14.4252'' E
NDVI Habitation density
KPIs
Apartment density Density of urban fabric(%) Building-use mix index Commercial density Service density Accessibility
ood orh
hb neig est ear K-n Art ific al n eur al n etw ork
Measure diversity of urban land use Residential Commercial Nature Industry Transport
Measure score of urban vitality low
high
influenced weight in different land use + (multiply linear regreesion)
feature importance
Identity low + what parameters urban vitality are missing
analysis + data in BCN
NDVI(Normalized difference vegetation index)
green vegetation ground cover
NDVI
Mob Acce ility ssibil it
y
y sit den ix nt m me use art Ap lding i Bu
Environment
Apartment density(number/m2)
UV
URBAN VITALITY
Economy
Social
Habitation density Commerical density Service density Urban fabric density
apartment number 133.3*133.3
Building-use mix(residential ratio /service ratio /other ratio)
apartment service area area ratio ratio
other area ratio
analysis + data in BCN
Accessibility
NDVI
Mob Acce ility ssibil it
y
y sit den ix nt m me use art Ap lding i Bu
Environment UV
URBAN VITALITY
Economy
Social
Habitation density Commerical density Service density Urban fabric density
People Bus/ Metro station
analysis + data in BCN Habitation density
Habitation number 133.3*133.3
Commercial density NDVI
Mob Acce ility ssibil it
y
y sit den ix nt m me use art Ap lding i Bu
Environment UV
URBAN VITALITY
Economy
shop number 133.3*133.3
Social
Habitation density Commerical density Service density Urban fabric density
Service density
market number 133.3*133.3
Urban fabric density(%)
artificially surfaced areas land coverage
KPI
NDVI
Habitation density
Apartment density
Service density
Building-use mix
Commercial density
Accessibility
Urban fabric density
Methodology of research
Urban description of space and identity urban vitality
NDVI
Apartment density Building-use mix Accessibility Habitation density Commercial density
Score of urban vitality
Service density Urban fabric density
0
100
urban vitality - Methodology
[1.0] [0.75] [0.5] [0.25] [0.0]
Data samples (test file)
Assign urban vitality score
Artificial neural network
Trained model
[0 -10 ] [ 1 0 - 20 ] [ 20 - 30 ] [ 30 - 40 ] [ 40 - 50 ] [ 50 - 60 ] [ 60 - 70 ] [ 70 - 80 ] [ 80 - 90 ] [ 90 - 1 00]
Data samples (training file)
Measure diversity of urban land use
NDVI Habitation density
KPIs
s ean
K-m
Apartment density Density of urban fabric(%) Building-use mix index Commercial density Service density Accessibility
Residential Commercial Nature Industry Transport
Art
ific
al n eur a
l ne
two
rk
Measure score of urban vitality low
high
Trained model
Predict score
influenced weight feature in different land use + importance (multiply linear regreesion) Identity low + what parameters urban vitality are missing
Urban vitality Map
0
0 -10 1 0 - 20 20 - 30 30 - 40 40 - 50 50 - 60 60 - 70 70 - 80 80 - 90
100
90 - 1 00 %
low urban vitality
0
100
0 -10
Real street pictures
Transportation railway Transportation
Pedralbes Residential
0
Parc de la Ciutadella Park
100
0 -10
It needs to seperate different urban land use in order to find which indicator is the most important reason for urban vitality and give different direction of development.
Commercial
Industry Transport
Residential Nature
Diversity of urban landuse - methodology
Start
Input define K
Calculate distance
(test sample and training sample)
class and visualization Take K-nearest neighbours
Sort distance
Measure diversity of Urban land use
NDVI Habitation density
KPIs
s ean
K-m
Apartment density Density of urban fabric(%) Building-use mix index Commercial density Service density Accessibility
Residential Commercial Nature Industry Transport
Art
ific
al n eur a
l ne
two
rk
Measure score of urban vitality low
high
Apply the simple majority
influenced weight feature in different land use + importance (multiply linear regreesion) Identity low + what parameters urban vitality are missing
Commercial
Industry Transport
Residential Nature
K1
K2
Residential
Commercial
K3
K4
Nature
Industry
K6 Transport
urban fabric service density accessibility commercial density
K6
BUM
Industry
urban fabric service density accessibility BUM
service density
commercial density HD NEW AD NEW
NDVI
commercial density
Service density
Commercial density
Habitation density
HD NEW
NDVI
Nature AD NEW
Apartment density
K4 BUM
Habitation density
K3 urban fabric
Commercial density
accessibility
Apartment density
BUM
Building use mix
Commercial
Building use mix
Residential
Urban fabric
K2
Accessibility
Building use mix
Accessibility
importance
importance
K1
Service density
importance
Building use mix
NDVI
Urban fabric
Apartment density
NDVI
Apartment density
AD NEW
Building use mix
NDVI
Apartment density
HD NEW
Building use mix
NDVI
Commercial density
AD NEW
Accessibility
Habitation density
Habitation density
Service density
service density
NDVI
commercial density
Habitation density
commercial density
Accessibility
Urban fabric
commercial density
NDVI
HD NEW
Apartment density
Accessibility accessibility
Commercial density
service density
accessibility
Habitation density
Service density
importance urban fabric
Service density
Urban fabric
Transport importance
Urban land use
The classification of urban vitality
NDVI
NDVI
K2
importance
accessibility
commercial density
Commercial density
NDVI
NDVI
Service density
Commercial density
Habitation density
Apartment density
Building use mix
service density
BUM
commercial density
HD NEW
AD NEW
NDVI
NDVI
accessibility
Apartment density
service density
Habitation density
Urban fabric BUM
Building use mix
NDVI
Accessibility
AD NEW
NDVI
HD NEW
Apartment density
service density
Service density
urban fabric
Habitation density
streetscapes, buildings, soft and hard landscaping, signage, lighting, roads and other infrastructures surfaced areas
Urban fabric
Transport
commercial density
streetscapes, buildings, soft and hard landscaping, signage, lighting, roads and other infrastructures surfaced areas
urban fabric
K6
HD NEW
Commercial density
Building use mix
Building use mix
Apartment density
Apartment density
NDVI
NDVI
Habitation density
Habitation density
Accessibility
commercial density
Commercial density
Service density
accessibility
AD NEW
Building use mix
Local market
BUM
Accessibility
Industry importance
Nature importance
K4
urban fabric
Urban fabric
accessibility
BUM
K3
service density
bus/metro station and walking streets
Accessibility
NDVI
Commercial
Building use mix
AD NEW
NDVI
HD NEW
Apartment density
service density
Habitation density
commercial density
Service density
accessibility
commercial density
Urban fabric
urban fabric
Accessibility
importance
streetscapes, buildings, soft and hard landscaping, signage, lighting, roads and other infrastructures surfaced areas
Service density
Residential
importance
K1
NDVI Habitation density Apartment density Density of urban fabric(%) Building-use mix index Commercial density Service density Accessibility
Residential Commercial Nature Industry Transport
K-n Art ific a
l ne ura
l ne
two
rk
Identity low + what parameters are missing urban vitality
Measure Score of urban vitality low
Vacant spaces
influenced weight feature in different urban land use + importance (multiply linear regreesion)
high
Map to locate
Overlap
identiy urban spaces to act and enhence urban vitality
Urban land use
KPIs
d
hoo
bor
igh
ne est ear
Measure diversity of urban land use
Strategy simulate
Decision making
Vacant spaces
Measure diversity of urban land use
NDVI Habitation density
KPIs
s ean
K-m
Apartment density Density of urban fabric(%) Building-use mix index Commercial density Service density Accessibility
Art
ific
al n eur a
l ne
two
rk
Identity low + what parameters urban vitality are missing
Measure score of urban vitality low
Vacant spaces
influenced weight in different land use (multiply linear regreesion)
high
Map to locate
Overlap
identiy urban spaces to act and enhence urban vitality
strategy simulate
Decision making
Vacant spacesin grid
Low urban vitality+empty space in grid low urban vitality
+ emprt spaces in grid
0
100
0 -10
NDVI Habitation density Apartment density Density of urban fabric(%) Building-use mix index Commercial density Service density Accessibility
Residential Commercial Nature Industry Transport
K-n Art ific a
l ne ura
l ne
two
rk
Identity low + what parameters urban vitality are missing
Measure Score of urban vitality low
Vacant spaces
influenced weight feature in different urban land use + importance (multiply linear regreesion)
high
Map to locate
Overlap
identiy urban spaces to act and enhence urban vitality
Urban land use
KPIs
d
hoo
bor
igh
ne est ear
Measure diversity of urban land use
Strategy simulate tool
Decision making
Sites with different urban land use
K1
K2
Residential
Commercial
K3
K4
Nature
Industry
K6 Transport
Simplify the relationship in different urban land use Multiply Linear Regression
Apartment density(num/area)
Building-use mix index
Commercial density(num/area)
a5
a6
a7
a8
Service density
a4
Accessibility
a3
Density of urban fabric(%)
a2
NDVI
a1
Habitation density(num/area)
Regression Coefficients X Independent Variable of the Regression
+ Y-intercept
b
Level of Urban Vitality
Simplify the relationship in different landuse Multiply Linear Regression
#residential
108.58
Habitation density(num/area)
81.01
Apartment density(num/area)
-0.69
Building-use mix index
31420.67
Commercial density(num/area)
-28.92
NDVI
13.72
Density of urban fabric(%)
-2.8
Accessibility
-807.76
Service density
-30.95
=
urban vitality(residential)
Simplify the relationship in different landuse Multiply Linear Regression
#commercial
-194.69
Habitation density(num/area)
1452.69
Apartment density(num/area)
0.47
Building-use mix index
91131.08
Commercial density(num/area)
-42.98
NDVI
-4.5
Density of urban fabric(%)
1.83
Accessibility
15022.58
Service density
-7.79
=
urban vitality(commercial)
Simplify the relationship in different landuse Multiply Linear Regression
#industry
116.1
Habitation density(num/area)
18.28
Apartment density(num/area)
-0.38
Building-use mix index
39286.39
Commercial density(num/area)
-5.03
NDVI
4.87
Density of urban fabric(%)
-1.17
Accessibility
16287.57
Service density
-0.49
=
urban vitality(industry)
Simplify the relationship in different landuse Multiply Linear Regression
#nature
34.21
Habitation density(num/area)
-56.35
Apartment density(num/area)
-0.02
Building-use mix index
10148.99
Commercial density(num/area)
6.35
NDVI
5.32
Density of urban fabric(%)
1.22
Accessibility
27561.86
Service density
-11.21
=
urban vitality(nature)
TOOL
NDVI Habitation density Apartment density Density of urban fabric(%) Building-use mix index Commercial density Service density Accessibility
Residential Commercial Nature Industry Transport
K-n Art ific a
l ne ura
l ne
two
rk
Identity low + what parameters urban vitality are missing
Measure Score of urban vitality low
Vacant spaces
influenced weight feature in different urban land use + importance (multiply linear regreesion)
high
Map to locate
Overlap
identiy urban spaces to act and enhence urban vitality
Urban land use
KPIs
d
hoo
bor
igh
ne est ear
Measure diversity of urban land use
Strategy simulate tool
Decision making
User
Site
identity urban land use
strategies simulate
PLAY!
Objects relate to indicators for Urban vitality- object library Ve g
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Ma
Sid
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lk
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Sh
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St
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Ap
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Be nc h
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Bu s & S /me tre tro et sta t
ion
www.GHOSTtoHOST.com
g
HOST
ghost to host
name
User Urban vitality Urban land use
Suggestion
Play!
0 -10 1 0 - 20 20 - 30 30 - 40 40 - 50 50 - 60 60 - 70 70 - 80 80 - 90 90 - 1 00 %
www.GHOSTtoHOST.com
name
User Low UV Urban land use
Suggestion
Play!
0 -10 1 0 - 20 20 - 30 30 - 40 40 - 50 50 - 60 60 - 70 70 - 80 80 - 90 90 - 1 00 %
www.GHOSTtoHOST.com
name
User Low UV Urban land use
residential commercial industry nature transport
Suggestion
Play!
0 -10 1 0 - 20 20 - 30 30 - 40 40 - 50 50 - 60 60 - 70 70 - 80 80 - 90 90 - 1 00 %
www.GHOSTtoHOST.com
name
User Low UV Urban land use
residential commercial industry nature transport
Suggestion
Play!
0 -10 1 0 - 20 20 - 30 30 - 40 40 - 50 50 - 60 60 - 70 70 - 80 80 - 90 90 - 1 00 %
www.GHOSTtoHOST.com
name
User Low UV Urban land use
residential commercial industry nature transport
Suggestion
Play!
0 -10 1 0 - 20 20 - 30 30 - 40 40 - 50 50 - 60 60 - 70 70 - 80 80 - 90 90 - 1 00 %
www.GHOSTtoHOST.com
name
User Low UV Urban land use
residential commercial industry nature transport
Suggestion
Play!
0 -10 1 0 - 20 20 - 30 30 - 40 40 - 50 50 - 60 60 - 70 70 - 80 80 - 90 90 - 1 00 %
www.GHOSTtoHOST.com
name
User Low UV Urban land use
residential commercial industry nature transport
Suggestion
Play!
0 -10 1 0 - 20 20 - 30 30 - 40 40 - 50 50 - 60 60 - 70 70 - 80 80 - 90 90 - 1 00 %
www.GHOSTtoHOST.com
name
User Low UV Urban land use
residential commercial industry nature transport
Suggestion
Play!
0 -10 1 0 - 20 20 - 30 30 - 40 40 - 50 50 - 60 60 - 70 70 - 80 80 - 90 90 - 1 00 %
www.GHOSTtoHOST.com
name
User Low UV Urban land use
Suggestion
Vegetation index: 0.063299982(<0.3)
Urban land use: industry
vegetation accessibility service commercial urban fabric apartment Building-use mix
Play!
strategy simulation Increase vegetation index and basic infrastructures
www.GHOSTtoHOST.com
name
User Low UV Urban land use
Suggestion
Play! predict
Ve g
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Li
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Ma
Be n
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Sh op et
Ap
St
Sid
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Bu s & S /me tre tro et sta t
ion
www.GHOSTtoHOST.com
name
User Low UV Urban land use
Suggestion
Play! predict
urban vitaity
control varibales
Actual (Mean)
Predicted
100
100
80
80
60
60
40
40
20
20
0
0 0
5
urban fabric
10
0
0.001
0.002
0.003
service density
0
20
accessibility
40
−600
−400
−200
BUM
0
0
0.001
0.002
commercial density
0
0.5
HD NEW
1
0
0.1
0.2
AD NEW
0.3
0.4
0
0.5
NDVI
Future
urban vitality
+
Enegy production
Flow of Energy
Waste consumption
Energy Recycling
GDP
land use value
...
...