Research mapping the density and function of commercial activities in Greater London, then exploring relationships with travel patterns. Part of my PhD research at CASA UCL. Presented at Regional Science UK and Ireland Section 2009.
To plan a city/region, we require base data on which information extrapolation & decisions may happen. Hence, Identify ‘data needed’, and Identify ‘needs of data’ collection
Inspection survey:
A) Direct :
Observe traffic count/ situation
Observe housing quality
Observe economic activity
Observe social parameters, etc.
B) Indirect:
Clubbing of directly observed ‘indicators’ to generate area’s possible ‘proxy’.
For e.g. housing condition + plot sizes + no. & types of vehicles + consumer goods = income range
. Personal interview/ Dialogue:
A questionnaire is designed beforehand at appropriate scale:
Nominal Scale : Yes or No
Ordinal Scale : Possible options or multiple choice questions
Interval Scale : Range/ intervals like age group or income group
Structured questions are precise and one-way
Semi-structure survey is a two-way information flow. It’s an informal dialogue in which the surveyor might receive new information from respondent/s. however, it depends on;
Behavioural factors of surveyor and respondents
Questions not to be ambiguous or long
Managing conversation and seeking pin-point answers
Judging responses without bias
Recording interview
Avoiding errors
Cross-checking with other respondents
Major land uses to be identified for analysing physical distribution and existing conditions:
Developed
Under-developed
Un-developed
Major uses marked on map are as per the defined regional/city level plans, like;
Urbanizable zone
Industrial zone
Transportation & Communication zone
roads, railways, MRTS, Seaports, Dockyards, Airports, Bus depots/ terminals, freight complexes, transmission and communication
Primary activity zone
Agriculture, poultry, rural settlements, brick kilns, extraction areas
Open area zone
Recreation zone, green buffer zone
Protected/ Eco-sensitive zone
Water bodies, forests, sanctuaries, coastal zone, wetlands, marshy zone
special area zone
Heritage & conservation zone, scenic value, tourism zone, defence area/ zone, border conflict zone
Data regarding demographic characteristics;
Population growth (natural, induced)
Population size (age-wise)
Population density
Population distribution
Gender ratio
Socio-Economic status
Religion
Marital status
Education ratio
School dropouts
Gender-wise enrolment in schools, colleges
Mortality rate (age-wise)
Birth rate
Health rate (in some surveys)
Sample types for doing household/ demographic surveys;
Simple Random sampling
Systematic sampling
Stratified sampling
Cluster sampling
Multistage sampling
There are nine steps involved in the development of a questionnaire:
Decide the information required.
Define the target respondents.
Choose the method(s) of reaching your target respondents.
Decide on question content.
Develop simple & clear wording of questions
Put the questions into a meaningful order and format.
Check the length of the questionnaire.
Pre-test the questionnaire
Develop the final survey form.
To plan a city/region, we require base data on which information extrapolation & decisions may happen. Hence, Identify ‘data needed’, and Identify ‘needs of data’ collection
Inspection survey:
A) Direct :
Observe traffic count/ situation
Observe housing quality
Observe economic activity
Observe social parameters, etc.
B) Indirect:
Clubbing of directly observed ‘indicators’ to generate area’s possible ‘proxy’.
For e.g. housing condition + plot sizes + no. & types of vehicles + consumer goods = income range
. Personal interview/ Dialogue:
A questionnaire is designed beforehand at appropriate scale:
Nominal Scale : Yes or No
Ordinal Scale : Possible options or multiple choice questions
Interval Scale : Range/ intervals like age group or income group
Structured questions are precise and one-way
Semi-structure survey is a two-way information flow. It’s an informal dialogue in which the surveyor might receive new information from respondent/s. however, it depends on;
Behavioural factors of surveyor and respondents
Questions not to be ambiguous or long
Managing conversation and seeking pin-point answers
Judging responses without bias
Recording interview
Avoiding errors
Cross-checking with other respondents
Major land uses to be identified for analysing physical distribution and existing conditions:
Developed
Under-developed
Un-developed
Major uses marked on map are as per the defined regional/city level plans, like;
Urbanizable zone
Industrial zone
Transportation & Communication zone
roads, railways, MRTS, Seaports, Dockyards, Airports, Bus depots/ terminals, freight complexes, transmission and communication
Primary activity zone
Agriculture, poultry, rural settlements, brick kilns, extraction areas
Open area zone
Recreation zone, green buffer zone
Protected/ Eco-sensitive zone
Water bodies, forests, sanctuaries, coastal zone, wetlands, marshy zone
special area zone
Heritage & conservation zone, scenic value, tourism zone, defence area/ zone, border conflict zone
Data regarding demographic characteristics;
Population growth (natural, induced)
Population size (age-wise)
Population density
Population distribution
Gender ratio
Socio-Economic status
Religion
Marital status
Education ratio
School dropouts
Gender-wise enrolment in schools, colleges
Mortality rate (age-wise)
Birth rate
Health rate (in some surveys)
Sample types for doing household/ demographic surveys;
Simple Random sampling
Systematic sampling
Stratified sampling
Cluster sampling
Multistage sampling
There are nine steps involved in the development of a questionnaire:
Decide the information required.
Define the target respondents.
Choose the method(s) of reaching your target respondents.
Decide on question content.
Develop simple & clear wording of questions
Put the questions into a meaningful order and format.
Check the length of the questionnaire.
Pre-test the questionnaire
Develop the final survey form.
Local policies and strategies designed to deal with urban decline, decay or transformation are termed as urban renewal.
It is a comprehensive and integrated vision and action which leads to the resolution of urban problems and which seeks to bring about a lasting improvement in the economic, physical, social and environmental conditions of an area that has been subject to change’
With the decision and authority of a governing municipality, rearranging land use, function and ownership features of a socially, economically or structurally decayed part of a certain city .
such as slum zones or brown fields, for the purpose of obtaining a desired, well organized neighbourhood.
Local policies and strategies designed to deal with urban decline, decay or transformation are termed as urban renewal.
It is a comprehensive and integrated vision and action which leads to the resolution of urban problems and which seeks to bring about a lasting improvement in the economic, physical, social and environmental conditions of an area that has been subject to change’
With the decision and authority of a governing municipality, rearranging land use, function and ownership features of a socially, economically or structurally decayed part of a certain city .
such as slum zones or brown fields, for the purpose of obtaining a desired, well organized neighbourhood.
A talk at the Urban Science workshop at the Puget Sound Regional Council July 20 2014 organized by the Northwest Institute for Advanced Computing, a joint effort between Pacific Northwest National Labs and the University of Washington.
Principles from urban design that can be applied to experience design, based on Kevin Lynch's book on Good Urban Form. (My presentation from An Event Apart 2011-2012)
Smart Urban Planning Support through Web Data Science on Open and Enterprise ...Gloria Re Calegari
Prediction of expensive datasets starting from a set of cheap heterogeneous information sources in smart city scenarios.
Prediction of the population and land use of Milano starting from data about Points Of Interest and phone activity.
Issues of Governance in Spatial PlanningRoberto Rocco
This is an updated version of a lecture I have prepared on GOVERNANCE and arising issues connected to governance in Spatial Planning and Design. This particular version was presented at the Department of Geosciences and Natural Resource Management of the University of Copenhagen, where I stayed I short while as research fellow.
Traffic crashes kill more than 1.2 million people every year. While most traffic safety initiatives tend to focus on behavioral approaches -- such as helmet- and seatbelt-wearing campaigns -- there’s an undervalued approach to making the world’s roads safer: good urban design.
CITIES SAFER BY DESIGN is a global reference guide to help cities save lives from traffic fatalities through improved street design and smart urban development.
Instead of seeing how we live as being a burden on the Earth, and the dire prospects of having to give up comfort, AVBP explores how tell the story of how to reverse the trend with a positive, feasible view of a sustainable future in a city?
An assessment-based process for modifying the built fabric of historic centre...Beniamino Murgante
An assessment-based process for modifying the built fabric of historic centres: the case of Como in Lombardy
Pier Luigi Paolillo, Alberto Benedetti, Umberto Baresi, Luca Terlizzi, Giorgio Graj -Polytechnic of Milan
Forecasting trip attraction based on commercial land use characteristicseSAT Journals
Abstract Trip Attraction is fundamental in planning of transportation facilities. It is important to the traffic engineer and urban planner in considering the impact of new development such as office complex, shopping center and residential development. This paper focuses its study on the formulation of a trip attraction model using multiple regression technique for the commercial land use in medium sized towns of Kerala. Questionnaire surveys are conducted for the eight selected commercial nodes from the three medium sized towns Tirur, Perinthalmanna, and Ponnani in Kerala. Socioeconomic surveys are conducted for the selected towns for obtaining the origin-destination data. The correlation and regression analysis are performed based on these surveyed data. The study showed that the multiple regression model with the three independent variables namely the number of commercial establishments, percentage of shops in the commercial node and percentage of banks in the commercial node with the R2 and Adjusted R2 value of 0.991 and 0.9844 respectively gives the better estimate of trip attraction. After model formulation, the model accuracy was also tested by examining the assumptions of multiple regression. The model is found to be accurate during the assumption examination process. This model would be very useful for estimating the trips attracted to a new or existing commercial center in any medium sized towns in Kerala, and thus aid to assess the traffic impact of the commercial center on the geometric design of roadways in the surrounding area. Index Terms: correlation, multicollinearity, multiple regressions, trip attraction
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
The presentation was illustrated at the CEEM CoP Webinar: “Achieving Low Carbon Mobility: Urban Transportation Modelling, Public Awareness and Behavioural Change" on tge 10th of October 2013
CEEM CoP stands for Community Energy and Emissions Modelling (CEEM) Community of Practice (CoP).
CEEM CoP is an informal group supporting CEEM practitioners and local governments in furthering greenhouse gas modelling, target-setting and action in communities across BC – www.toolkit.bc.ca/ceem
Mobility is an important part of daily life. Progressive community planning and transportation design can greatly reduce the need for automobile travel, instead providing a diverse range of active transportation alternatives.
This presentation on the CATCH project looks at how transportation-related data can be used to understand a city’s travel footprint and help to inform city planning and programs to promote individual behaviour change.
It reviews the findings and lessons learned from the ‘CATCH Project’ (Carbon Aware Travel Choice): a 2 million euro-funded project, involving 11 partners across 6 European Union countries, aimed to develop a knowledge platform to help urban communities move to less carbon-intensive transportation systems. This presentation touches on the important role of developing a system to compare and contrast best practices, identify the many motivators for change to low carbon mobility, and use tools for engaging the public and decision makers to support innovation and change.
Formulating a trip production prediction model for the residential land use i...eSAT Journals
Abstract Formulating of suitable travel demand forecasting models are the key elements for the development of a long-range transportation plan. This paper focuses its study on the formulation of a trip production model using multiple regression technique for the residential land use in medium sized towns of Kerala. The trip production model estimated the number of trips that will be produced from the residential land use of these medium sized towns. The Perinthalmanna, Tirur, and Ponnani towns of Kerala were selected as the study area based on certain criteria. The data on demographic and socio-economic characteristics these areas were collected through the administration household interviews. The quantitatively and qualitatively analysis of the results were done using the correlation and multiple regression analysis. The study showed that the regression model with the independent variables such as the percentage of automobile availability, percentage of persons employed, percentage of students and percentage of pucca type of dwelling with R2 and Adjusted R2 value of 0.878 and 0.859 respectively gives a better estimate of the trips produced. The model accuracy was also tested by checking the validity of the assumptions employed in the multiple regression technique. Since most of the work related to traffic and transportation planning requires an effective framework for the analysis of the present and future travel demand pattern, a model forecasting the trip produced based on the above mentioned characteristics shall be advantageous for a speedy travel demand forecast. Index Terms: Multiple Linear Regression, Residential Land Use, Socio-Economic Characteristics, Trip Production
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
This paper is a report on the recent special session of papers presented at the Regional Studies Association (RSA) Annual Conference in Dublin, entitled ‘Beyond Smart & Data-Driven City-Regions: Rethinking Stakeholder-Helixes Strategies’. The session was a collaboration between the Urban Transformations ESRC programme at the University of Oxford and the Future Cities Catapult.
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This will be used as part of your Personal Professional Portfolio once graded.
Objective:
Prepare a presentation or a paper using research, basic comparative analysis, data organization and application of economic information. You will make an informed assessment of an economic climate outside of the United States to accomplish an entertainment industry objective.
1. Polycentric Cities and Sustainable Development: A Multi-Scale GIS Approach to Analysing Urban Form Duncan Alexander Smith Regional Science 4th Sept 2009.
2. Polycentric Cities and Sustainable Development:A Multi-Scale GIS Approach to Analysing Urban Form Urban Theory of Polycentric Cities- What is driving polycentric structures? How can we measure this? Mapping Employment Geography- Techniques for the detailed mapping of economic activity and mix-of-uses applied to Greater London. Polycentricity and Commuting Efficiency- Are polycentric structures efficient in environmental and economic terms? Analysis applied to the South East.
3. Polycentric Cities- Evolution of Urban Form Globalisation and Information economy; gentrification, cultural/retail/tourism synergy. Airport attraction, manufacturing, large scale retail/leisure. Cities Enable Agglomeration Economic agglomeration allows specialisation, competition, share labour/info, economies of scale. Socially enables cultural development, ‘urban buzz’. Traditionally Monocentric Pre-industrial cities high density, maximise agglomeration. Public transport networks in 19th century cities reinforce monocentric structure. Polycentric Cities Rise of automobile, economic growth and restructuring. New urban forms evolve with multiple centres- multi-nucleated city (Harris and Ulman), 100 mile city (Sudjic), polycentric city (Gordon)… Monocentric and polycentric trends overlapping with multiple centres with competitive advantages for particular activities.
4. Polycentric Cities and Travel Sustainability Urban Task Force Key Diagram (1999) Monocentric Characteristics Monocentric structure supports public transport, but increases work-living separation and congestion with tidal commuting. Polycentric Advantages? Polycentric structures disperse employment closer to population, less congested outskirts. But often poor public transport access and produce car based orbital travel. Planning Policy Planners try to integrate with ‘concentrated dispersion’ policies. Is it working? Urban form and employment data integrated with travel patterns evidence base for this debate.
12. Rateable Value- floor-space multiplied by a rent factor indicative of quality of property. Relationships with Employment Strong relationships between rateable value and employment, but variations in intensity between functions (e.g. industrial vs. office). Methodology Classify data into functional groups- office, retail, industrial, local services… Address match data. Aggregate into 500m grid for visualisation across Greater London.
18. Outer Centres: Significant for retail, but lack major office agglomerations. Struggling to compete.
19.
20.
21. Commuting Carbon Emissions Measure Mode Split Analysis Simple centre-suburbs split. Ignoring distance travelled and energy used in public transport journeys. Features Needed Destination based to relate to employment, integrate distance and mode data. Composite Carbon Measure Possible to estimate average carbon per journey, using average carbon emissions per unit distance. (distance currently Euclidean, missing congestion) Walking and Cycling!
22. Travel and Sustainability- Outer London Diversity Edge City No longer centre-suburbs split, but edge city vs. rest split. Likely link to office parks identified earlier. Centre Sustainable? Central London public transport dominated but long distance. Outer Contrasts Outer Centres close live-work relationships, so efficient. Sharp contrasts to western corridor. South East Edge city extends west with similar commuting. Reading possible exception. Specialised jobs likely influencing commuting.
23. Employment Specialisation and Travel Patterns Economic Specialisation Proxy Proportion of jobs in top three categories for proxy. East-West Split Much lower specialisation in East London. Western Wedge Generally high productivity, comparable to Central London, not back office. Outer Town Centres Most Outer Centres lower productivity jobs. Specialisation and sustainability tension.
24.
25. Social and demographic considerations: Demographic considerations (family orientated environments, housing market divisions) big influence on live/work relationships.
26. Rent data: economic analysis of built environment links.
27.
28. Thank you for listening! Welcome comments and questions. Contact Email: duncan.a.smith@ucl.ac.uk Data providers for this research: Greater London Authority Ordnance Survey Valuation Office Infoterra
29. References Alexander, C. (1974). A city is not a tree. Alonso, W. (1964). Location and land use. Batty, M. (2000). "The new urban geography of the third dimension." Environment and Planning B: Planning and Design27: 483-484. Batty, M. (2007). "The creative destruction of cities." Environment and planning. C, Government & policy34(1): 2. Breheny,M.,Gordon,I.,Archer,S.(1998), ‘Building densities and sustainable cities’, Engineering and Physical Sciences Research Council (EPSRC), Sustainable Cities Programme, Project Outline No. 5, June 1998. Burton, E. (2002), Measuring urban compactness in UK towns and cities, Environment and Planning B: Planning and Design 2002, 29, pp 219 – 250. Urban Task Force (1999). Towards An Urban Renaissance, E & FN Spon. Foster (1999), Docklands: Cultures in Conflict, Worlds in Collision, UCL Press, London. Jane Jacobs (1961) The Death and Life of Great American Cities New York: Vintage Books (NA 9108.J17); Jenks, M, Burton, E., Williams, K. (2000) The Compact City: A Sustainable Urban Form?, (Spon. London). GORDON, P. and RICHARDSON, H. (1996) Beyond polycentricity: the dispersed metropolis, LosAngeles, 1970-1990, Journal of the American Planning Association, 62, pp. 289±295. Greater London Authority (2004), The London Plan: Spatial Development Strategy for London, GLA. Greater London Authority (2006), London Office Policy Review 2006, GLA. Hall, P. (2003). "The End of the City? The Report of My Death was an Exaggeration." City7(2): 141. Longley, P. A. (2002). "Geographical Information Systems: will developments in urban remote sensing and GIS lead to'better'urban geography?" Progress in human geography26(2): 231. Newman & Kenworthy (1989), Overcoming Automobile Dependence, Island Press, Washington. Sherlock, H. (1991). Cities are good for us. Talen, E. (2003). "Measuring Urbanism: Issues in Smart Growth Research." Journal of Urban Design8(3): 303.
35. Street Based Aggregation- Streets themselves are units used.
36.
37. Introduction to Urban Trends in Greater London Monocentric Structure London traditionally concentrated jobs in city centre with radial transport links to suburbs. Central Expansion in Boom Years Massive employment growth and immigration led population growth, particularly over last ten years. Policy directed growth to centre, global business services. Radial transport enhanced. Outer London Contrasts Significant growth around Heathrow and in ‘Western Wedge’, while traditional Outer Centres generally struggling.