=Paper=
{{Paper
|id=Vol-2557/paper-07
|storemode=property
|title=Urban data application towards quality of life optimization in Indian cities
|pdfUrl=https://ceur-ws.org/Vol-2557/paper-07.pdf
|volume=Vol-2557
|authors=Shubhi Sonal,Santhanam Kumar
}}
==Urban data application towards quality of life optimization in Indian cities==
https://ceur-ws.org/Vol-2557/paper-07.pdf
Urban data application towards quality of life
optimization in Indian cities
Shubhi S.1 [0000-0001-5565-515X] and S. Kumar2
1
School of Architecture, REVA University, Bangalore, India
2
JNAFAU, Hyderabad, India
shubhisonal@reva.edu.in
skumarjnafau@gmail.com
Abstract. The study aims to explore the dynamics of neighbourhood quality of
life in urban residential neighbourhoods in Indian cities. Large scale urban data
on various facets of neighbourhood become major stakeholders in such an anal-
ysis. The study utilizes data on prioritization of neighbourhood attributes for es-
tablishing a framework for optimization of neighborhood Quality of life. Quali-
tative research tools such as literature review and analysis is utilized initially to
establish a theoretical framework for evaluation of quality of life at the neigh-
bourhood level. A major chunk of the study relies on empirical studies with
primary data collection to construct an empirical framework in conjunction with
the theoretical base established earlier using SPSS software and Microsoft Ex-
cel for data visualization and analysis. Artificial neural networks analysis is
used to decode the multivariate data and establish a predictive model towards
neighbourhood quality of life. Grassroots level urban planning can be institu-
tionalized using the framework along with crowd sourced data on resident’s
perception of their neighbourhoods.
Keywords: Quality of life, urban planning, artificial neural networks analysis
1. Quality of life in urban environments
According to the World Health Organization, Quality of Life(QoL) is defined as
“an individual's perception of their position in life in the context of the culture and
value systems in which they live and in relation to their goals, expectations, standards
and concerns.” WHO’s conceptualization of Quality of life comes across as a broad
ranging concept bearing complex relationships with the person's physical health, psy-
chological state, personal beliefs, social relationships and their interactions with sali-
ent features of their environment. Research literature acknowledges that neighbour-
hoods are acceptable unit of analysis to efficiently measure the local conditions that
impact various domains of human life. (Bardhan R 2011, Sawicki and Flynn 1996,
Greenberg ,1999 and Meersman 2005). The neighbourhood is the building block of
the city and can become the springing point for initiatives towards a bottom up ap-
proach in urban planning. In pragmatic terms, most urban planning schemes can at
Copyright © 2020 for this paper by its authors. Use permitted under Creative
Commons License Attribution 4.0 International (CC BY 4.0).
best aspire for improvements at neighbourhood level to achieve a cumulative impact
at the city level. Furthermore, opportunities to design cities from scratch are limited
and it is improvement of existing cities through neighbourhood planning that becomes
the primary task of the urban planner.
From a planning perspective, a neighbourhood can be defined as a composition of
people, place and identity. Consequently, Quality of life for the neighbourhood should
be composed of people’s preferences, physical attributes which contribute to the place
and community attributes which define the neighborhood’s identity. There is a clear
research gap when it comes to the scale, context and conceptual expanse of the con-
cept quality of life when applied to urban residential neighbourhoods of a thriving
Indian city. Research literature appears to be severely conflicted when it comes to a
comprehensive formulation of the concept of quality of life at the neighbourhood
level. Most studies present a piecemeal view whereby they cover only one aspect of
the people-place-identity triad. Most importantly, we find that the indicators used in
these studies can be best evaluated at the city level and efforts to measure them at the
neighbourhood scale may often give inconclusive results. Lastly, most of the studies
originate in the global north where the socio cultural and urban form constraints are
vastly different from the global south. It will perhaps be erroneous to apply the same
in the context of dense, bustling neighbourhoods in Indian cities.
Urban Planning literature has abundant references to terms like Urban Quality of
life, Liveability, area attractiveness, Social sustainability, neighborhood satisfaction.
Each term in its own way tries to measure the desirability of living conditions in a
given area. The variables included within each concept differ with the scope and the
overall bent of the study.
1.1 Review of literature on Quality of life in urban environments
Mulligan, Carruthers (2005) define QoL as the satisfaction that a person receives
from surrounding human and physical conditions which are scale-dependent and can
affect the behavior of individual people, groups such as households and economic
units such as firms. Marans, Stimson (2011) stress upon the importance of QoL in
estimating life satisfaction and happiness for individuals as well as communities. The
broad based nature of QoL was further summed up by El Din, Serag, et al. (2013)
where they termed QoL as a multi-dimensional, ambiguous, complex concept, repre-
sented by a reticular relationship between various dimensions. Man being a social
animal, social Urban Quality of life is possibly the most direct translation of day to
day life and user satisfaction in a residential area. This concept is often termed as
social sustainability and is used interchangeably with the term social quality of life.
Dempsey, Brown, Bramley (2012), Bramley, Power (2009) underline that concepts at
the core of social sustainability are social equity issues (access to services, facilities,
and opportunities) and issues to do with the sustainability of community itself. Satu,
Shammi Akter (2014) defines liveability as a concept that points towards issues of
quality of life that are important to the long-term well-being of people and communi-
ties. The term encompasses issues such as environmental quality, safety, health, af-
fordability, neighborliness, convenience, and the presence of neighborhood facilities
such as parks, open space, sidewalks, provisions stores and restaurants. Hence, it may
be understood that Livability is directly related to the characteristics or quality of a
place that individuals and communities enjoy.
1.1.1 Review of Indices and Indicators used for evaluation of quality of life
A review of literature related to the above three concepts suggest that though simi-
lar in overall intent there are significant differences between the concepts. While QoL
is a broad based, multi dimensional concept, it is not necessarily place based. Livea-
bility, on the other hand is an entirely place based concept which is usually employed
for large urban areas. Liveability takes into account a large number of diverse indica-
tors many of which may be slightly beyond the realm of urban planning itself. Social
sustainability appears to be a community based concept which looks at both physical
as well as social components of community life. A large number of diverse indicators
have been suggested for measuring social sustainability and liveability in research
literature.
1.1.2 Review of Methods to measure quality of life
There is an equal amount of confusion and contradictions when it comes to quanti-
tative measurement of QoL and its allied concepts. The following table highlights
some of the main methods specified in literature to quantify these concepts. The indi-
cator approach seems to be the most popular amongst researchers where the broader
concept is broken down into a series of quantifiable indicators (Marans S, 2011, An-
delman r et al, 1998, Burnell & Galster, 1992).
Table 1: Methods of measuring Quality of life from review of literature
Burnell & Galster(1992)- Liveability comparisons versus market/resident approach
The market/resident approach in
The liveability comparisons approach
which housing price and/or wage dif-
which focuses on comparing different
ferentials are theorized to compensate
urban areas according to a number of
for quality-of-life differences between
objective indicators assumed to reflect
urban areas. Theoretical weighting
quality of life. Ad hoc weighting schemes
based on resident’s preferences were
were employed.
used.
Andelman et al. (1998)- Objective versus subjective approach
The objective approach which is most The subjective approach which is
typically confined to the analysis and specifically designed to collect primary
reporting of secondary data – usually data at the disaggregate or individual
aggregate data at different geographic or level using social survey methods
spatial scales – that are available mainly where the focus is on the peoples’ be-
from official governmental data collec- haviors and assessments, or evaluations
tions, including the census. This is an of aspects of QOL.
approach that is often associated with
social indicators research.
Marans, Stimson (2011)- Indicator based versus modeling approach
Monitoring QOL/QOUL through a set Modeling relationships between
of indicators –usually over time – derived characteristics of the urban environment
from aggregated spatial data using official and measures of peoples’ subjective
sources, such as the census, that are said assessments of QOL domains, includ-
to be related to perceived QOL ing their satisfaction with specific phe-
nomena and with life as a whole. This
approach typically involves data col-
lected through survey research methods
and analyzed using techniques such as
regression analysis or structural equa-
tion models.
Blečić, Ivan, Talu. (2013)- Countability versus capability approach
Countability approach: based on inputs Capability approach: actual possibil-
or outputs ity every person has to ‘use’ the city.
1.2 Linking neighbourhood attributes to quality of life
Several researchers have tried to assess the quality of life offered by urban residen-
tial neighbourhoods. Research literature suggests that the neighbourhood attributes
that ascertain preference for one neighborhood above other branch out into distinct
categories. Social features such as community satisfaction (Sirgy,M J & Cornwell
T,2002) and social integration (Connerly, CE & Marans, R W, 1985) are seen to be
important for assessing the quality of the neighborhood. In addition, several studies
emphasize on the role of accessibility factors (Jun H.J. & Morrow-Jones, H A, 2011)
in determining neighborhood QoL and residential location choice.
The multitudes of attributes which determine the character of a neighbourhood
have been well documented in literature. Galster, G. (2001) portrays a neighbourhood
as a bundle of spatially based attributes associated with clusters of residences, some-
times in conjunction with other land uses.
Table 2. Spatially based attributes of a neighbourhood. SOURCE: Galster, G. (2001)
Spatially based attributes of a neighbourhood
Structural Type, scale, materials, design, state of repair, density,
characteristics landscaping, etc. in the neighbourhood
Infrastructural Roads, sidewalks, streetscaping, utility services, etc.
characteristics
Demographic Age distribution, family composition, racial, ethnic, and
characteristics religious types, etc. Of the resident population:
Class status Income, occupation and education composition of the resident
characteristics population
Tax/public The quality of safety forces, public schools, public
service package administration, parks and recreation, etc., in relation to the local
characteristics taxes assessed
Environmenta Degree of land, air, water and noise pollution, topographical
l characteristics features, views, etc.
Access to major destinations of employment, entertainment,
Proximity
shopping, etc., as influenced by both distance and transport
characteristics
infrastructure.
The degree to which local political networks are mobilised,
Political
residents exert influence in local affairs through spatially rooted
characteristics
channels or elected representatives
Local friend and kin networks, degree of inter household
Social- familiarity, type and quality of interpersonal associations,
interactive residents’ perceived commonality, participation in locally based
characteristics voluntary associations, strength of socialisation and social control
forces, etc.
Sentimental Residents’ sense of identification with place, historical
characteristics significance of buildings or district, etc.
With the exception of demographic, class status and political and sentimental char-
acteristics, all other categories in the table shown above, fall into the realm of Urban
Planning. However, when viewed at the neighbourhood scale we find that Environ-
mental and Proximity characteristics are inconclusive since these are macro operators
which depend on city scale and structure. Of the remaining characteristics, Infrastruc-
tural and Tax/public service (to a large extent) characteristics are mostly dependent on
the whims of the government, often constrained by monetary considerations in the
Indian scenario even though ideally they should be under control of the urban planner.
Overall, the structural, socio interactive and infrastructural characteristics continue to
be the areas of intervention from the point of view of urban planning in the context of
existing urban residential neighbourhoods. An assessment of quality of life at the
neighbourhood level necessitates an investigation of the above attributes along with
their components and sub components.
Table 3. Neighbourhood attributes selected for study. SOURCE-author
Neighbourhood Components Sub components
attributes
1 Structural char- Housing characteris- Condition of census houses used as
acteristics tics residence, Predominant material of
the roof, wall and floor, Type of
structure of census houses, Number
of dwelling rooms , Occupancy rate,
dwelling unit size etc.
Housing typology
Urban form Spatial character
Density
Development controls
Visual character
2 Infrastructural Physical infrastructure Roads, water supply, drainage, sew-
characteristics age systems, solid waste manage-
ment systems, public transit stops
etc.
Social Infrastructure Parks, Playgrounds, schools, health
facilities, small retail, chemist shop
etc.
3 Socio Interac- Place based Quality and quantity of public space
tive characteris- People based Community interaction
tics
2. Neighbourhood quality of life- establishing a theoretical
framework for evaluation
A glance at the neighbourhood attributes and their multiple relationships with qual-
ity of life in the neighbourhood shows that there is a need for a clear empirical
framework to evaluate QoL. Though we cannot undermine the impact of qualitative
attributes, it is the quantitative attributes which can be directly included in the master
planning process. It is clear from the review of literature that Housing characteristics,
spatial character, Density, development controls; Infrastructural characteristics and
socio interactive characteristics are necessary ingredients in formulation of any
framework to evaluate QoL at the neighbourhood level. Density appears to be a dom-
inant factor and though it has clear links with QoL, the exact nature of the relationship
(whether positive or negative) is inconclusive in literature. Density also finds itself as
a backdrop for most QoL studies because it is in stressed conditions that QoL studies
find their real relevance. The findings suggest that perhaps High density environments
would be the best context to carry out Quality of life studies in the urban setting. Vis-
ual character and housing typology are often the perceptual and physical manifesta-
tions of density. Hence these can also be treated as context for carrying out QoL stud-
ies. Of the remaining attributes, the infrastructural (social) and socio interactive at-
tributes need a tool for empirical evaluation and quantification. Overall we can con-
clude that, Quality of life at the neighborhood level may be expressed as an aggregate
of the impact of structural, infrastructural (social) and socio interactive characteristics.
Overall satisfaction with the neighbourhood as reported by the residents may be treat-
ed as a surrogate for the overall quality of life offered by the neighbourhood.
Aggregated Manifestation of
Structural Characteristics Socio
Neighbourhood Infrastructural
= + + Interactive
Quality of life Characteristics
Characteristics
In High density Housing Typology Urban Social Physical People Place
environments Characteristics Form based Based
categorized by P - P P - P P
specific visual Structural Quality of Life Social Quality of Life
character and
typology
Fig 1. Method and Tools employed for Formulation of NQI. SOURCE: Author
Bringing back our initial conceptualization of neighbourhood quality in terms of
people, place and identity, we find that spatial character and development control
impacts give a true representation of the place. The identity/community aspect is more
or less revealed in the socio interactive characteristics and the access to social infra-
structure. An examination of most of these attributes from the resident’s opinion facil-
itates the fulfilment of the people aspect. Most of the studies in literature attempt to
visualize neighbourhood quality of life using either one or two of the people-place-
identity triad. An attempt at consolidating all the attributes mentioned above into an
empirical framework can be a significant contribution of this study.
2.1 Neighbourhood Quality Index
Neighbourhood Quality Index is proposed as a composite index that aggregates the
structural, social infrastructural and socio interactive characteristics of the neighbour-
hood.
Neighbourhood Quality Index= ∑ (Pi X Wi)...............................................Eq. 4.1
Where, Pi- Normalized value of neighbourhood quality parameter
Wi- Normalized weightage of neighbourhood Quality parameters based on its
relative contribution towards overall satisfaction with neighbourhood.
The following indicators were identified for evaluating neighbourhood social quality
after review of literature-
Table 4. List of neighbourhood attributes and their indicators. SOURCE Author
Neighbourhood Indicator for social quality of life Units
attribute
Mix of available housing types %
Diversity in
housing choice Perceived satisfaction with living Yes/no
space within DU
Occupancy/ Avg. Floor area(Sq.m) per person Average BUA(sq.m)
Amount of living and HH size(no of
space ppl)
Housing quality Age and quality No of years
Access to natural Average plot size or DU size(Sq.m) Sq.m/person
light & ventilation Average ground coverage of buildings %
(%)
Average height of building No of storeys
Average setback Meters
Architectural Variety of architectural styles
diversity
Safe, comfortable, Street pattern, connectivity,
interesting streets integration
and squares for the
pedestrian.
Mixed use
Neighbourhood as Perceived satisfaction with Rating by residents
a place to live in neighborhood
Perceived reputation of neighborhood Rating by residents
Perception of convenience in the Rating by residents
neighborhood
Perception of area attractiveness Rating by residents
Tenure type Rented/owned/govt
Crowding Footfall at public places No. Of people/ Sq.m
Perception of crowding Yes/no or rating
Social Diversity Income groups mix % of HIG, MIG,
LIG, EWS
Access to No of primary schools in No.
education neighborhood
Travel distance to nearest primary Minutes
school
Access to health Travel time to health care/ chemist Minutes
care shop
Access to play No of playgrounds No.
space No of parks No.
Area of play spaces and quality Sq.m/person
Travel time to nearest play space Minutes
Private open space within home Yes/no
Access to shopping Travel time to nearest small retail Minutes
Access to Public Travel time to transit stops(bus/ Minutes
transit metro)
Frequency of use of public transit Frequency
Preserving and No of social contacts in the No.
facilitating social neighborhood
network
Sense of No of years of living in the No. of years
belongings on neighborhood
community / Participation in community activities Yes/no
stability in past year
Desire to move out of the Yes/no
neighborhood
Amount of Frequency of meeting neighbours Frequency
neighbouring
Safety and security Vandalism/ theft cases in the locality No. of cases/year
No of accidents in the locality No.of cases/year
Perceived safety within neighborhood- Rating by residents
day/ night
2.1.1 Selection of Indicators for NQI
These indicators formed the basis for preparation of structured questionnaires for
an expert opinion survey (EOS). The EOS questionnaire asked the experts to rate the
listed given indicators on a scale of 1 to 5 based on the importance of the given indi-
cator in determining the social quality of an urban residential neighborhood. A total of
52 surveys were conducted each with ratings for a set of 38 indicators. In order to
make the sample variable ratio more focused for further analysis, an initial screening
of the indicators was carried out on the basis of mean values of importance ratings as
given by the experts. Indicators which scored less than 3.5 as mean importance rating
were removed from the matrix put forward for further analysis. Furthermore indica-
tors related to travel times to social infrastructure were excluded in favor of indicators
which judged the qualitative aspects of the social infrastructure.
Four High density neighbourhoods in Bangalore namely Mattikere, Mahalaksh-
mipuram, Gurappanapalya and Kammanahalli were selected as case study areas for
data collection regarding the individual indicators. These 4 neighbourhoods have
several common characteristics in terms of homogeneity in population density, area,
plotted development(non slum) and primarily residential landuse. A reconnaissance
survey during the initial stages of the research had shown that despite their common-
alities the neighbourhoods offered varying quality of life to its residents. A total of
270 household surveys were conducted using random sampling to collect data regard-
ing the shortlisted neighbourhood attributes. The final data set with 8 indicators (52 X
8=416 data points) was further put through SPSS for statistical data reduction through
factor analysis.
Fig 2. Factor Analysis results generated in SPSS
Figure 3. Scree plot showing factors generated in SPSS
SPSS was used to generate a correlation matrix where it was seen that several cor-
relations in the matrix were above the minimal thumb rule value of ±0.3 and above.
The results of KMO and Bartlett test for sampling adequacy revealed a KMO measure
of 0.55 and significance <0.05 which verified the adequacy of the data for proceeding
with factor analysis (William B, Onsman & Brown, T, 2010). Factor analysis was
further carried out using the principal components analysis method.
Table 5. Rotated component Matrix generated in SPSS. SOURCE- Author
Rotated Component Matrix
Component
1 2 3
Street pattern VAR00001 .922
Access to play spaces VAR00010 .922
Built open relationship VAR00011 .878
No of social contacts in the VAR00015 .653
area
Average floor area per per- VAR00016 -.485
son
% Of mixed use VAR00017 .824
Neighborhood as a place to VAR00018 .896
live in
Participation in community VAR00020 .757
activities
Table 6. Neighbourhood quality parameters generated through factor analysis
Factor 1 Factor 2 Factor 3
Access to space Community linkage Urban form
Access to play spaces No of social contacts Street pattern
in the area
Living space (Average Participation in Built open
floor area per person) community activities relationship(Average
ground coverage )
Neighborhood as a place to % of Mixed use
live in
The analysis revealed that a total of 3 factors (components) account for around
69.612% of variance in the data. The above factor analysis gave us the indicators
which are deemed necessary for defining neighborhood quality. Based on the authors’
understanding each of the factors has been allocated a name viz. Access to Space,
Community Linkage, Urban Form. To reduce the multitudes of components into a list
of prioritized components and allocate weightages to each component, the procedure
shown in Table 8 has been followed. The structural validity for the index has been
further reinforced on the basis of artificial neural networks based modeling.
2.1.2 Artificial Neural networks analysis
A neural network is a powerful computational data model that is able to capture
and represent complex input/output relationships. The motivation for the development
of neural network technology stemmed from the desire to develop an artificial system
that could perform "intelligent" tasks similar to those performed by the human brain
such as:
1. A neural network acquires knowledge through learning.
2. A neural network's knowledge is stored within inter-neuron connection strengths
known as synaptic weights.
The true power and advantage of neural networks lies in their ability to represent
both linear and non-linear relationships and in their ability to learn these relationships
directly from the data being modeled. The most common neural network model is the
Multilayer Perceptron (MLP). This type of neural network is known as a supervised
network because it requires a desired output in order to learn. The goal of this type of
network is to create a model that correctly maps the input to the output using histori-
cal data so that the model can then be used to produce the output when the desired
output is unknown.
Artificial Neural networks analysis has been used to generate a Predictive model
that determines the relationship between overall satisfaction with neighborhood and
parameters of neighborhood quality. The ANN analysis also helps in Estimation of
relative importance of each parameter in determining overall satisfaction with neigh-
borhood.
2.2 Predictive modeling of overall satisfaction with neighborhood and
parameters of neighborhood quality
The neighbourhood quality parameters selected through statistical analysis on ex-
pert opinion survey data manifest themselves in the neighbourhood in form of overall
satisfaction with the neighbourhood. The parameters selected are a hybrid mix of
physical and social components of neighbourhood quality of life. In order to assess
the selected parameters and their relative contribution towards overall satisfaction
drawn from the neighbourhood we need to carry out multivariate analysis and data
modeling. The model proposes that Overall satisfaction with neighbourhood is a
function of the neighbourhood quality parameters. Here, the Dependent variable is
Overall satisfaction with neighbourhood derived from household survey data. Neigh-
bourhood quality parameters from Household survey data constitute the Independent
variables. A 3-layer feed forward Artificial Neural networks analysis employed to
verify the validity of the proposed model. The ANN analysis studies the underlying
data structure and derives the structural relationship for use in predictive modeling. A
total of 239 x 7=1673 data points were input the neighbourhood quality parameters.
The ANN analysis is a two stage analysis where it was reported that the model was
able to predict with an accuracy of 84.8% in the training phase. In the testing phase,
the model achieved an accuracy of prediction amounting to 76.7%. The ANN analysis
also generates normalized importance for the independent parameters based on their
relative contribution towards the Dependent variable. These values may be used as
weightages for formation of Neighbourhood Quality Index.
Table 7. ANN Analysis Results generated in SPSS
Case Processing Summary
N Percent Cross Entropy Error 79.590
Training 164 69.2% Percent Incorrect Predictions 15.2%
Sample
Training
Testing 73 30.8% Stopping Rule Used 1 consecutive step(s)
with no decrease in
error
Valid 237 100.0% Training Time 0:00:00.106
Excluded 2 Test Cross Entropy Error 47.914
Total 239 ing Percent Incorrect Predictions 23.3%
Figure 4. ANN analysis hidden layers generated in SPSS
Table 8. Normalized importance for parameters generated through ANN analysis in SPSS
Independent Variable Importance Parameters
Importance Normalized
Importance
x1 0.152 47.6% no of social contacts
x2 0.074 23.3% participation in community activities
x3 0.086 26.9% access to play spaces
x4 0.130 40.7% average ground coverage
x5 0.090 28.1% living space (average floor area per person)
x6 0.319 100.0% perception of neighborhood convenience
x7 0.151 47.3% perception of neighborhood attractiveness
Table 9. Weightages of Neighbourhood Quality parameters derived from ANN analysis in
SPSS
Parameter (pi) Weightage from ANN (wi)
P1 No of social contacts 0.152
P2 Participation in community activities 0.074
P3 Access to play spaces 0.086
P4 Average ground coverage 0.130
P5 Living space -average floor area per person 0.090
P6 Perception of neighborhood convenience 0.319
P7 Perception of neighborhood attractiveness 0.151
The study contributes in a twofold way to the knowledge and practice of urban
planning. On the theoretical level, the major contributions of the study would be to
propose a new paradigm for evaluation of quality of life offered by a neighbourhood
in the context of Indian cities. A neighbourhood is composed of people, place and
social life within the place. An evaluation of each of these components is necessary in
order to present a holistic picture of the quality of life offered by the neighbourhood.
The study introduces a new paradigm for the same, namely- Neighbourhood Quality.
The concept of neighbourhood quality aims at an empirical formulation of an other-
wise subjective concept. The second contribution of the study is towards the practice
of urban planning at the neighbourhood as well as city level. Quantification of neigh-
bourhood quality and its various sub components can then be used as a guiding tool
towards optimization of quality of life in the city. The urban planning guidelines
which emerge out of the study can be active contributors towards ensuring well being
and quality of life at the neighbourhood level despite rapid intensification in popula-
tion and building. The Neighborhood Quality concept described here can become an
active tool for micro level planning and allocation of city resources towards targeted
development of the disadvantaged neighbourhoods.
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