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Population density and car ownership levels.

Population density and car ownership levels.
Looking a comparisons between 2001 and 2011 (before and after the London Congestion Charge, Low Emissions zone and other car ownership curbing policies)
I will need to use the program QGIS to produce a map 2001 and 2011 comparing the population densities and a histogram with statistical analysis using SPSS 21.
Please tell me if this is possible and if you need more prior coursework and course related materials such as lectures and all to help complete this assignment. I am looking for a B+ or safe A. Please provide me the essay back in a word document and all the program files.
Harvard Referencing system
ENVS2005: GIS for Planners – Project Assessment Mark Scheme
80-100
(Distinction)
70-79
(Distinction)
60-69 (Merit) 50-59 (C) 40-49 (D) 1-39 (Fail)
Quality of
writing –
spelling,
punctuation,
grammar and
structure
Exceptionally well
written; stylish with
no errors in spelling,
punctuation or
grammar. The piece of
work is clearly and
logically structured
and is a joy to read.
Engaging introduction
and conclusion.
Very well written with
virtually no errors in
spelling, punctuation
or grammar. The piece
of work is clearly and
logically structured
and flows well. Good
introduction and
conclusion.
A good, well written
piece of work with few
errors in spelling,
punctuation or
grammar. The work
shows structure and is
clearly presented.
Clear introduction and
conclusion.
A more-or-less
competent piece of
work but may contain
some errors in
spelling, punctuation
or grammar. The may
lack structure and
presentation could be
improved. Weak
introduction and
or/conclusion.
A more-or-less weak
piece of work
containing a number
of errors in spelling,
punctuation or
grammar. The piece
may lack any kind of
structure. Missing
introduction and
conclusion.
A poor piece of work.
Written English is very
poor, with numerous
errors in spelling,
punctuation and
grammar. No
structure.
Research topicrelevance,
question
formulation,
identification of
data
Research topic original
and ambitious, with
clear relevance to
urban planning and
the course material.
Research question indepth,
incisive and
precisely defined with
definite aims, and
applicability for
empirical testing.
Extensive relevant
data identified at
appropriate spatial
extent and resolution.
Research topic
advanced and welldefined,
with clear
relevance to urban
planning and the
course material.
Research question has
clear aims and
applicability for
empirical testing.
Relevant data
identified at
appropriate spatial
extent and resolution.
Research topic well
defined, with
relevance to urban
planning and course
material. The aims of
the research are clear,
though may be a little
basic. Some prospects
for empirical testing
are understood.
Relevant data
identified, though
extent and resolution
may not be fully
explained.
Research topic more
loosely defined, with
more limited
relevance to planning
and course. Aims not
entirely clear, and
limited framework for
empirical testing.
Some data identified,
but problems in terms
of extent, resolution
and/or missing data.
Research topic lacks
any real context or
justification. The aims
of the research are
unclear or the
problem poorly
chosen. Data is
inappropriate.
An effort at something
has been made, but it
is devoid of any
context or urban
planning relevance.
Very weak data.
Knowledge,
understanding,
appreciation of
limitations
The project shows
extensive knowledge
of the topic chosen
and an in-depth
understanding of the
links between the
question, data and
spatial analysis
methods. Limitations
of research and data
clearly understood,
and pathways for
future research to
address limitations set
out.
The work shows good
knowledge of the
topic chosen and a
clear appreciation of
the links between the
problem, data and
method(s) employed
to solve it. Limitation
of research and data
clearly understood,
with some future
research suggestions.
The work shows good
knowledge of the
chosen topic although
there may be some
issues with the choice
of data and/or
methods at the lower
end of the scale. At
the upper end of the
scale, matching data
and/or method to the
problem is sound.
Some research
limitations identified.
The work shows
adequate knowledge
of the chosen topic
but choice of data
and/or methods could
have been better.
Little understanding of
research limitations at
the upper end of the
scale, or lacking
entirely at the lower
end of the scale
The work shows poor
knowledge of the
chosen topic and the
choice of data and/or
methods is illogical.
Limitations absent.
The work shows that
lectures were either
not attended or not
understood at all.
Limitations absent.
Spatial and
statistical
analysisapplicability,
competency
and
sophistication
The spatial and
statistical analysis
methods are entirely
appropriate and
insightful for the
problem as it is
defined. The
techniques used are
very advanced and
correctly
implemented. The
discussion of the
results is engaging and
scientific. Excellent
technical knowledge
and skills are
demonstrated,
indicative of additional
independent learning.
The spatial and
statistical analysis
methods are
appropriate and
relevant for the
problem as it is
defined. The
techniques used are
advanced and
correctly
implemented. The
discussion of the
results is engaging and
scientific. Good
technical knowledge
and skills are
demonstrated,
indicative of an
advanced
understanding of the
course materials.
The spatial and
statistical analysis
methods are
appropriate for the
problem as it is
defined. The
techniques used are at
the level of the main
course materials, and
are implemented
correctly. The
discussion of the
results is relevant and
shows some scientific
understanding. Good
technical knowledge
and skills are
demonstrated,
indicative of a solid
understanding of the
course materials.
The spatial and
statistical analysis
methods are
reasonably
appropriate for the
problem as it is
defined. The
techniques used are
more basic, and miss
some of the course
materials, and/or are
implemented
incorrectly. The
discussion of the
results is basic.
Limited technical
knowledge and skills
are demonstrated,
indicative of an
incomplete
understanding of the
course materials.
The spatial and
statistical methods are
very basic or nonexistent,
failing to
address the problem
as defined. Very little
understanding of the
course materials is
shown. Discussion of
results is very flawed
or missing.
The spatial and
statistical methods are
non-existent, failing to
address the problem
as defined. No
understanding of the
course materials is
shown. Discussion of
results is absent.
Cartography,
figures and
diagrams
Figures and diagrams
are of very high
quality, showing
excellent graphic
design and
communication skills,
with the results lucid,
insightful and
scientific. Maps
demonstrate
exemplary design,
classification and data
selection skills.
Figures and diagrams
are of high quality,
showing excellent
graphic design and
communication skills,
with the results lucid,
insightful and
scientific. Maps
demonstrate strong
design, classification
and data selection
skills.
Figures and diagrams
are of good quality,
showing good graphic
design and
communication skills,
with the results clear
and relatively
scientific. Maps
demonstrate
competent design,
classification and data
selection skills.
Figures and diagrams
are of acceptable
quality, showing
limited graphic design
and communication
skills, with the results
somewhat flawed.
Maps demonstrate
limited design,
classification and data
selection skills.
Figures and diagrams
are of very poor
quality, showing poor
graphic design and
communication skills,
with no meaningful
results. Maps
demonstrate the
absence of design,
classification and data
selection skills.
Figures and diagrams
absent with no graphic
design and
communication skills
shown.
Bibliography/
references
Background reading is
very extensive and
shows a very
impressive
appreciation of the
wider literature, far
beyond that on the
prescribed reading list.
Few or no inaccuracies
in bibliography and
citation of references.
Background reading is
extensive and shows
an excellent
appreciation of the
wider literature. There
are few or no
inaccuracies in the
bibliography and the
citation of references.
Background reading is
reasonably broad and
shows a good
appreciation of the
wider literature. There
may be some
inaccuracies in the
bibliography and the
citation of references.
Background reading is
limited. There may be
obvious inaccuracies
in the bibliography
and the citation of
references
Very little background
reading is evident.
Bibliography may be
incomplete or
inconsistent and
citations poor.
There is no evidence
of wider background
reading at all.
ENVS2005: Urban Lab II, GIS For Planners- Project Assessment Example
New Public Transport Infrastructure and Income Deprivation in Rio de
Janeiro
Duncan A. Smith
In advance of hosting the Olympic Games in 2016, the city of Rio de Janeiro is building an extensive
new public transport network of Bus Rapid Transit (BRT) lines (Brazilian Olympic Committee, 2008).
Currently Rio has only limited public transport infrastructure and, in combination with the city’s
mountainous topography, this results in a fragmented urban environment where it can take several
hours to reach the city centre from peripheral locations. The new BRT network is intended to
improve accessibility, and should benefit the many residents who do not own cars.
The BRT network also has to fulfil the role of transporting tourists and visitors to the Olympic Park
site during the games, and providing accessibility for the large property developments connected to
the Olympic Park. The Olympic Park is situated in Barra da Tijuca, a wealthy expanding district to the
south-west of Rio city centre (see Figure 1). It will be a challenge for the new BRT network to serve
both the demands of the Olympic developments, and provide a more comprehensive and equitable
public transport service for Rio’s residents (Gaffney, 2010).
This research project investigates the spatial relationship between the location of the new public
transport infrastructure and the geography of deprivation in Rio. Deprivation is defined in terms of
income using the average monthly household income from the Brazilian 2010 census. The scale of
analysis used is the smallest available- census sectors- so that fine grained spatial variation in income
is represented (there are 10,000 census sectors in Rio averaging 600 residents). The relationship
between the location of new BRT stations and poorer residents is explored by measuring
populations residing within 2km of new stations.
Figure 1: Map of existing transport network, new public transport network and urban areas in Rio
de Janeiro. Data: IPP, 2013.
Commented [DS1]: This document is intended to help you with
the structure and write up of the project assessment. The specific
content is not so important. This example is a bit more advanced
than the material covered in the course.
Commented [DS2]: Try to introduce your topic, why it might be
interesting in terms of city planning. References can help with your
overview.
Commented [DS3]: It’s good to spell out exactly what you are
doing in terms of the analysis and definitions. Include items like the
data you are going to use, the scale, and the analysis techniques if
you can.
Commented [DS4]: Include where the data came from. Legends
and scale bars are needed in most cases.
The basic geography of the existing public transport network and BRT network is shown in Figure 1.
Most of existing network runs north and west from the city centre, covering the most populous
urban area of the city. It is clear however that currently east-west connections are poor, and that the
south-west and west areas of the city are isolated from the public transport network, as is the main
international airport. The routes of the new BRT system are also shown in Figure 1. These routes fill
in significant gaps with improved east-west connections, better airport connectivity and the creation
of a new transport hub at Barra da Tijuca where three of the lines meet, close to the Olympic Park
site. The massive scale of the new infrastructure is apparent, with 159km of BRT lines under
construction. Only one of the BRT lines directly connects with the city centre, which limits the
opportunities for the BRT to support inner-city regeneration.
Next the geography of income in Rio de Janeiro is mapped in Figure 2. There is a strong spatial
pattern of wealth segregation in the city, with wealthier residents concentrated along the coast in
the Zona Sul areas of Copacabana and Ipanema. Additionally the expanding area of Barra da Tijuca is
reinforcing this pattern of wealthy residents situated along the coast. The new BRT lines will
significantly boost accessibility in Barra da Tijuca. The lines also provide new links in poorer
residential areas north of Barra, and to the western suburbs. This mapping analysis indicates that the
new transport infrastructure serves a mix of both rich and poor residents.
Figure 2: Map of average monthly household income (census 2010) and public transport stations
with 2km buffer of accessibility. Data: IBGE, 2010.
The distribution of income deprivation and relationship with public transport accessibility can also
be explored by graphing these variables, as shown in Figures 3 and 4. The income distribution is
skewed toward the lower end of the scale, with average monthly wages in Rio of R$2,000 per
month. The national minimum wage for Brazil in 2010 was R$545 per month, and 380,000 residents
in Rio live in census sectors with average household wages below this threshold.
Commented [DS5]: If you include maps, try and summarise the
patterns and how these relate to the topic you are investigating.
Commented [DS6]: You might want to label areas in the map if
they are important parts of the discussion.
Commented [DS7]: The analysis here is based on looking at the
properties of locations near public transport stations, and comparing
these to the city as a whole. This is done using a ‘buffer’ operation,
which draws circles of a fixed distance around station points (in this
case 2km distance).
To produce a buffer from a point file in QGIS go toVector
-> Geoprocessing Tools -> Buffer
Figure 3 shows the distribution of the population within 2km of public transport stations before the
new BRT routes are developed, and Figure 4 shows the distribution of population within 2km of
public transport stations after the BRT routes are added. The 2km accessibility threshold has been
defined using a GIS straight-line buffer operation (Gutiérrez and García-Palomares 2008) and
selecting all the census sector centroids within the buffer. There is a big change in accessibility, with
900,000 additional residents within 2km of stations as shown in Table 1. It is also apparent that
there are significant gains amongst the lower end of the graph scale, i.e. the lowest income groups,
as well as for more affluent residents. This can be explored in Table 1 by looking at the average
income and standard deviation of residents with 2km of stations before and after the BRT. We can
see that the mean income increases slightly, indicating that the investment marginally favours more
affluent residents, but the standard deviation also increases, indicating that a wider spectrum of
income groups are covered. This reflects the polarised population groups living around the Barra da
Tijuca area, as shown in Figure 2.

Figures 3 & 4: Histograms of average census sector incomes 2010 showing total population and
populations within 2km of public transport stations before BRT development (left) and after BRT
development (right)
Table 1: Population and income of residents accessible to public transport stations before and after
BRT developmentAll
Rio de Janeiro
Population Within 2km of
Public Transport Stations
before BRT Development
Population Within 2km of
Public Transport Stations
after BRT Development
Total Population
(000’s) 6,283 4,103 5,001
Mean Census Sector
Income (R$) 1,994 1,850 2,004
Census Sector Income
Standard Deviation (R$) 2,073 1,719 2,033
This research project has investigated the relationship between new transport infrastructure in Rio
de Janeiro and the geography of income deprivation. The high degree of income segregation across
the city has been shown, with affluent groups concentrated in the south along the attractive coastal
Commented [DS8]: Try and define any spatial analysis methods
you are using precisely. A GIS reference from the course textbook or
another academic paper can help with this.
Commented [DS9]: Statistics and tables help to put some
numbers on the trends you have identified. This provides evidence
for the conclusions you draw and makes your analysis stronger.
Commented [DS10]: This particular project is making a before
and after comparison, so it makes sense to spell this comparison out
in the table.
Commented [DS11]: Provide a short conclusion summarising
what you have found, and how this relates to your research aims.
areas. The new BRT transport infrastructure under construction attempts to integrate these
polarised residential areas more closely together through improved accessibility. The research
results found the BRT network to be generally progressive, with significant accessibility
improvements for poorer residents in several areas, particularly in the western suburbs of the city.
Yet the average income of residents with good public transport access increases when the new
infrastructure is included, reflecting the fact that the very wealthy area of Barra da Tijuca is at the
centre of the Olympic transport developments. Additionally the new infrastructure provides only
limited access to Rio’s city centre to boost regeneration.
This research has a number of limitations that could be improved on in future work. The price of
public transport was not included, which can be a major barrier for poorer residents in Brazil. Also
service frequencies, differences between modes of transport and local severance created through
BRT infrastructure were not included in the analysis. The geography of the street network was not
considered (Gutiérrez and García-Palomares 2008), and further accessibility distances in addition to
2km were not tested. It would also be interesting to explore the geography of public transport
accessibility in relation to car ownership and patterns of employment.
References
Brazilian Olympic Committee, 2008, Rio de Janeiro 2016: Volume 3. Rio de Janeiro: Brazilian Olympic
Committee.
http://www.rio2016.com/en/organising-committee/transparency/documents
Gaffney, C., 2010, Mega-events and socio-spatial dynamics in Rio de Janeiro, 1919-2016. Journal of
Latin American Geography 9.1: 7-29.
Gutiérrez, J., & García-Palomares, J. C. (2008), Distance-Measure Impacts on the Calculation of
Transport Service Areas Using GIS. Environment and Planning B: Planning and Design 35.3: 480–503.
Instituto Pereira Passos, 2013, Transport network geographical data. Rio de Janeiro: IPP.
http://ipprio.rio.rj.gov.br/rio-em-dados/portal-geo/
Instituto Brasileiro de Geografia e Estatística, 2010, Brazil census 2010, Rio de Janeiro: IBGE.
http://censo2010.ibge.gov.br/en/resultados
Commented [DS12]: It’s good to show awareness of limitations
and how the research could be improved. Again references could be
helpful here.
Commented [DS13]: You need to show evidence of background
reading to receive a good mark.

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