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SHOPPING FOR UTOPIA


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_INTRODUCTION & CONTEXT 14 _WPA_2.0_COMPETITION 28 _DATA&_DATA SCAPE 46 _DESIGN DEVELOPMENT 70 _PROPOSAL


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INTRODUCTION

INTRODUCTION

The history and current theory of urbanism and landscape – the studio unit was introduced to a series of critical texts which illustrated contemporary notions of the city aligned to the studio agenda. As a result we developed an understanding of properties of the urban, conditions of the city, cultures within the periphery, implementation of policy agendas, notions of nostalgia and {authenticity} of heritage – which established a basis from which to fully realise the potential opportunities of the city, conduct research, articulate our own design theory and evaluate the design studio projects.


INTRODUCTION

“With today’s heightened fear of upcoming environmental disasters, “ecological urbanism” seems the natural first utopia of the 21st century. Projecting today’s questions about what consti-tutes an ideal “ecological city” on to the idealized cities of the past, 49 Cities examines a numberof relationships—from the relationship of form to ideology to that of form to performance—generating a fresh outlook and a new framework from which to re-engage the discourse on the city today.” - 49 Cities “Competition places increased demands in the corporate world and capital markets as well as directlt on cities, which compete with one another. This environment increasingly rewards proposals for novel ownership structures that take advantage of laws and loopholes as well as those that generate persuasive arguements for regulatory variance in the name of responsive urbanism.” - Autonomous Urbanism

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CONTEXT

LIVERPOOL BIRKENHEAD

THE WIRRAL


CONTEXT

CONTEXT

The Wirral Peninsula, bounded to the west by the River Dee and to the east by the River Mersey. Located in North West England, the “Wirral� is situated in close proximity to the city of Liverpool, on the otherside of the River Mersey. This results in a symbiotic between the two urban areas, which has directly influenced the cultural, economic and industrial charateristics of these two places. Birkenhead, which is located along the west bank of the River Merseye. Is a town which has strong historic links to the ship building industry and can compared with most other postwar seaports around the shores of England, such as Glassgow, Portsmouth and Barrow-inFurness.

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OVERALL UNEMPLOYMENT RATE OF

8.2%

BOMBED IN

1940-1941

[UK] EXTERNAL DEBT

9.041 TRILLION

[2008]


[UK] PUBLIC DEBT

51.8% OF GDP

[UK] POPULATION BELOW POVERTY LINE

14%


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_INTRODUCTION & CONTEXT 14 _WPA_2.0_COMPETITION 28 _DATA&_DATA SCAPE 46 _DESIGN DEVELOPMENT 70 _PROPOSAL


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WPA_2.0_COMPETITION

WPA 2.0 COMPETITION

WPA 2.0: an open design competition for working public architecture organized and sponsored by cityLAB. cityLAB, an urban think tank at UCLA’s Department of Architecture and Urban Design, announces a call for entries to “WPA 2.0: Working Public Architecture.” WPA 2.0 is an open competition that seeks innovative, implementable proposals to place infrastructure at the heart of rebuilding our cities during this next era of metropolitan recovery. WPA 2.0 recalls the Depression-era Works Projects Administration (1935-43), which built public buildings, parks, bridges, and roads across the nation as an investment in the future—one that has, in turn, become a lasting legacy. We encourage projects that explore the value of infrastructure not only as an engineering endeavor, but as a robust design opportunity to strengthen communities and revitalize cities. Unlike the previous era, the next generation of such projects will require surgical integration into the existing urban fabric, and will work by intentionally linking systems of points, lines and landscapes; hybridizing economies with ecologies; and overlapping architecture with planning. This notion of infrastructural systems is intentionally broad, including but not limited to parks, schools, open space, vehicle storage, sewers, roads, transportation, storm water, waste, food systems, recreation, local economies, ‘green’ infrastructure, fire prevention, markets, landfills, energy-generating facilities, cemeteries, and smart utilities. http://wpa2.aud.ucla.edu/


    

    

      

      

    

    

  

  

   

   

                                       15                                      

WPA_2.0_COMPETITION

                                  





                                   

 



 


16

WPA_2.0_COMPETITION

MANIFESTO [intent]

_[1] The Machined Landscape... Efficiency, mechanised processes and Taylorism – these are the systems we propose for the re-organisation, re-use and re-investment of a modern city. Our proposal is defined by a quest for optimisation, a notion of distribution of resources [material & urban properties] in the most efficient arrangement achievable – the principle of ‘supply and demand’ forms the densities of the urban. We embrace industrial machinery, warehouses and sheds – all artefacts generally found at the periphery, in our scheme they are the cultures of the urban, the drivers, the enablers, the infrastructure.


WPA_2.0_COMPETITION

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THE MACHINED LANDSCAPE THE STRIP | Las Vegas

CORN FIELDS | Illinois

DRY DOCKS | Suez Canal

SUBURBIA | Las Vegas

COASTAL HOMES | New York

SUBURBS | Amsterdam

CAR PARKING | Birkenhead

HAMILTON SQUARE | Birkenhead

BOEING FACTORY | Washington

SUBURBIA | Chicago

COMBINE HARVESTER | Norfolk

FARMLAND | Detroit

SHIPPING | Hong Kong

FARMLAND | Miami

WAREHOUSES | Miami

CENTRAL PARK | New York

COAL | Richards Bay SA

JUNCTION | Miami

GOLDEN GATE PARK | San Fran

SEAWEED FARM | Bali

ASPIRATION OF ORDER


18

WPA_2.0_COMPETITION

MANIFESTO [intent]

_[2] Aspiration of Order... Order is life. We propose to drive a policy of organisation of typologies within our cities which departs from the organic growth evidenced in existing cities. We apply an order to the landscape, demand shapes the scope, machinery defines the characteristic interrelationships and order is key. When we grow, we grow in systematic order. When we die, we die in systematic order.


BINE HARVESTER COMBINE| Norfolk HARVESTER | FARMLAND Norfolk | Detroit FARMLAND | Detroit

SHIPPING | Hong SHIPPING Kong | Hong Kong

FARMLAND | Miami FARMLAND | Miami

WAREHOUSESWAREHOUSES | Miami | Miami

COMBINE| Norfolk HARVESTER | FARMLAND Norfolk FARMLAND | Detroit BINE HARVESTER | Detroit

SHIPPING SHIPPING | Hong Kong | Hong Kong

FARMLAND | Miami FARMLAND | Miami

| Miami WAREHOUSESWAREHOUSES | Miami

WPA_2.0_COMPETITION

TRAL PARK CENTRAL | New York PARK | New York COAL | RichardsCOAL Bay SA | Richards Bay SA JUNCTION | Miami JUNCTION | Miami

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GOLDEN GATEGOLDEN PARK | San GATE FranPARK | San SEAWEED Fran FARM SEAWEED | Bali FARM | Bali

ASPIRATION ASPIRATION OF ORDER ORDER ASPIRATION OF ORDER ASPIRATION OFOF ORDER

CENTRAL PARK | New York | Richards Bay SA JUNCTION | Miami JUNCTION | Miami TRAL PARK | New York COAL | RichardsCOAL Bay SA

GATE Fran SEAWEED FARM | Bali GOLDEN GATEGOLDEN PARK | San FranPARK | San SEAWEED FARM | Bali


20

WPA_2.0_COMPETITION

MANIFESTO [intent]

_[3] Stripped City

How long is a strip of our city? How ever large the demand!


WPA_2.0_COMPETITION

SORTED

21


22

WPA_2.0_COMPETITION

POLICY STRATEGIC DRIVERS_ The following illustrate policy diagrams which define a series of generic ‘top-down’ strategic mechanisms implemented within the masterman of the proposed utopia vision.

Industry_policy

Infrastructural_policy

Expansion and contraction of industrial strips efficiently responding to supply and demand.

Cranes facilitating efficient temporary links between strips to manage fluctuations in production.


WPA_2.0_COMPETITION

Housing_policy Household waste fertilizer used to grow boi-fuel crop. Canals used both for irrigation and transport of this crop.

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WPA_2.0_COMPETITION

FINAL PRESENTATION BOARD_ “the unremitting efficiency of the URBAN MILL, the efficiency of the factory line achieved through aggressive, dispassionate policy� Strips prescribed across the Wirrel swell with industry, and commercial ventures fed by ruthless infrastructure systems and thousands of workers. Homes, leisure and necessary food sources are also organised into strips to maximise the efficiency of living. Items and places of cultural worth, when arranged into a strip, concentrate and intensify the experience of nostalgia.


WPA_2.0_COMPETITION

25


04

_INTRODUCTION & CONTEXT 14 _WPA_2.0_COMPETITION 28 _DATA&_DATA SCAPE 46 _DESIGN DEVELOPMENT 70 _PROPOSAL


Data Formating + Convertion x, y, z, convertion

areacode

data set#1 data set#2

areacode

data set#1 data set#2

areacode

X,

Y,

001 002 003 004 005 006 007 008 009 010 011

8935 8427 8283 8640 5929 5620 8457 8725 2840 5892 ...

001 002 003 004 005 006 007 008 009 010 011

0.992 0.965 0.945 0.972 0.792 0.728 0.964 0.971 0.320 0.790 ...

001 002 003 004 005 006 007 008 009 010 011

3234.0 7474.4 9827.2 3094.4 6983.2 0558.3 3098.5 2044.4 0869.2 9492.2 ...

0585.3 4958.2 0598.3 0494.l 5958.3 0509.3 2734.2 2859.5 4028.4 0685.1 ...

data sets are converted into percentage valuations using highest values

9347 2820 6839 9742 3078 2944 4850 9957 9492 2947 ...

data formating

output .dat files

data sets are converted into 3D cloud points, % are converted to z values

0.929 0.293 0.709 0.927 0.459 0.104 0.684 0.937 0.992 0.237 ...

data convertion

x, y, z, values are saved into .dat using the Comma delimited file format

Z,

X,

9383.1 2094.2 7942.1 9494.2 4503.2 1030.3 6749.5 9384.3 9839.3 2934.3

Y,

Z

3234.0, 0585.3, 9383.1 7474.4, 4958.2, 2094.2 9827.2, 0598.3, 7942.1 3094.4, 0494.l , 9494.2 6983.2, 5958.3, 4503.2 0558.3, 0509.3, 1030.3 3098.5, 2734.2, 6749.5 2044.4, 2859.5, 9384.3 0869.2, 4028.4, 9839.3 9492.2, 0685.1, 2934.3 ..., ..., ...

vector convertion

provides a composite comparative tool of quanitative data

percentage convertion

data from census was input into a catagorised table structure

3D Data Scape

medium super output area

output format

VB Script macro .dat script

x, y, z, values are saved into .dat using the Comma delimited file format. The use of a macro allows for all stages of the data convertion to be automated, the output of which are a series of .dat files. (001 = data set #1) Sub export_data() ' ' export_data Macro ' ' ActiveWorkbook.SaveAs Filename:= _ "Wirral_Data_001.xlsm" _ , FileFormat:=xlOpenXMLWorkbookMacroEnabled, CreateBackup:=False

exported data

.DAT Files

Sheets("001").Select Range("A1").Select ActiveCell.FormulaR1C1 = "=Wirral_Data_003!R[1]C[1]" Range("A1").Select Selection.AutoFill Destination:=Range("A1:A88"), Type:=xlFillDefault Range("A1:A88").Select Selection.AutoFill Destination:=Range("A1:C88"), Type:=xlFillDefault Range("A1:C88").Select Range("A89").Select

automation of convertion + export

"Cloud_Outputs\" ActiveWorkbook.SaveAs Filename:= _ "Cloud_Outputs\001.dat" _ , FileFormat:=xlCSV, CreateBackup:=False Range("A89").Select Workbooks.Open Filename:= _ "Wirral_Data_001.xlsm" Windows("Wirral_Data_001.xlsm").Activate Windows("001.dat").Activate ActiveWorkbook.Close End Sub

workspace generation

SOA values

physical data

input 3D vectors

3D Data Scape

output files

provides a composite comparative tool of quanitative data

Sheets("001").Select Range("A14:C18").Select Selection.ClearContents Range("A10:C10").Select Selection.ClearContents Range("A1:C1").Select Selection.ClearContents ActiveWindow.SmallScroll Down:=-12 Range("A1").Select

input 3D vectors

Meta-Spacial Data Scape Gerenation

z

3D Grid Matrix

x,y,z matrix for input of cloud data files at origin coordinate

Super Output Areas

SOA are plotted for the Wirral giving x,y, coordinates

X,Y, Data Input

none quanitative data sets are input into matrix

.Dat Files Input (x,y,z)

x,y,z coordinates from .dat files are input into matrix

3D Data Scape

provides a composite comparative tool of quanitative data

3D Data Scape

y

provides a composite comparative tool of quanitative data

x


DATA&

DATA&

DATA SCAPE METHODOLOGY_ Interrelations of a synthesis of meta-spacial data scape generation, data information handeling and mapping of programmatic distribution. To the right, illustrates the strategic methodology developed during the processing of various data sets, with the aim to output - a analytical mapped data scape.

29


DATA&

30

r Su Lowe

Data Formating + Convertion x, y, z, convertion

areacode

data set#1 data set#2

areacode

data set#1 data set#2

areacode

X,

Y,

001 002 003 004 005 006 007 008 009 010 011

8935 8427 8283 8640 5929 5620 8457 8725 2840 5892 ...

001 002 003 004 005 006 007 008 009 010 011

0.992 0.965 0.945 0.972 0.792 0.728 0.964 0.971 0.320 0.790 ...

001 002 003 004 005 006 007 008 009 010 011

3234.0 7474.4 9827.2 3094.4 6983.2 0558.3 3098.5 2044.4 0869.2 9492.2 ...

0585.3 4958.2 0598.3 0494.l 5958.3 0509.3 2734.2 2859.5 4028.4 0685.1 ...

9347 2820 6839 9742 3078 2944 4850 9957 9492 2947 ...

data sets are converted into percentage valuations using highest values

data formating

0.929 0.293 0.709 0.927 0.459 0.104 0.684 0.937 0.992 0.237 ...

data convertion

output .dat files

data sets are converted into 3D cloud points, % are converted to z values

x, y, z, values are saved into .dat using the Comma delimited file format

Z,

X,

9383.1 2094.2 7942.1 9494.2 4503.2 1030.3 6749.5 9384.3 9839.3 2934.3

Y,

Z

3234.0, 0585.3, 9383.1 7474.4, 4958.2, 2094.2 9827.2, 0598.3, 7942.1 3094.4, 0494.l , 9494.2 6983.2, 5958.3, 4503.2 0558.3, 0509.3, 1030.3 3098.5, 2734.2, 6749.5 2044.4, 2859.5, 9384.3 0869.2, 4028.4, 9839.3 9492.2, 0685.1, 2934.3 ..., ..., ...

vector convertion

provides a composite comparative

percentage convertion

data from census was input into a catagorised table structure

output format

VB Script macro .dat script

x, y, z, values are saved into .dat using the Comma delimited file format. The use of a macro allows for all stages of the data convertion to be automated, the output of which are a series of .dat files. (001 = data set #1) Sub export_data() ' ' export_data Macro ' '

exported data

.DAT Files

ActiveWorkbook.SaveAs Filename:= _ "Wirral_Data_001.xlsm" _ , FileFormat:=xlOpenXMLWorkbookMacroEnabled, CreateBackup:=False Sheets("001").Select Range("A1").Select ActiveCell.FormulaR1C1 = "=Wirral_Data_003!R[1]C[1]" Range("A1").Select Selection.AutoFill Destination:=Range("A1:A88"), Type:=xlFillDefault Range("A1:A88").Select

ut

2 t er 0 0 Ches re Port e Ellesm re Port e m Elles or ere P m s Elle o ere P Ellesm re Po e Ellesm re P e m Elles ere m s Elle ere Ellesm r e Ellesm e Ellesm e m Elles m s Elle Flints Flint Flin Flin Fl L 3D Data Scape

medium super output area

per O


6 165 22.03 409 256.1 0 7 0 16 43 15.66 389 174.9 3 12 2 5 1 9 4 46 900.7 240 205. 0 1 8 6 6 109 . 5 8 5 . 2 1 3 3 7 379 201 0 26 1045 1 3 61 11 . 1 1 5 8 28.71 29 14 12 107 2270 32 00+8 8 5 0 3 3 6 . 0 2 8 4 0 35.74 3 2 2 29 1 .29 5 e/ 75 1 4 g 1 2 1 n 3 9 2 a 6 7 5 =R 17 69 691.7 585 128.9 0 Value 56 5.57 51 338 2 1 1 a 2 1 8 t 9 8 7 1 2 a . 0 1 8 . D 2 5 15 8 216 357 0 Area 1.84 2834 545 963 2 475 2 1 6 5 7 4 1 5 tput 1 5 . 5 1 8 47.17 26 148 730 58 3196 24.13 389 2990 1518 44 3 3 3 8 5 6 . 1 1 4 2 0 15.43 4 2 18 63 6 2593 585 677 17.92 0 353 3 0 1 3 8 5 9 12 55 299 191.8 860 5 n 001 4 749 01 57 0.48 3 o 2 0 t 6 1 1 7 3 s 0 1 9 0 8 e 3 1 1 8 1 5 &N 370 002 540 6 3511 782 851 49.24 0 923 3 ston 0 1 0 2 0 e 4 2 5 4 N 7 1 5 17 t& 003 680 0 76 3293 24.84 0 2260 ston 0 1888 3 0 e 2 1 4 N 9 1 7 4 0 4 2 50 rt & 0 850 n 00 6 22 72 6.61 2 4 o 9 8 t 4 0 2 2 s 0 1 3 0 e 2 N 14 40 230 500 4 0 ort & eston 005 407 82 41 3.26 5 2 4 5 2 1 3 1 0 6 0 1 . 2 N 1 49 41 7 290 880 0 ort & eston 006 2474 387 804 52.03 8 010 2 1 2 5 1 9 0 6 2 N . 1 5 7 48.93 & 310 162 530 31 Port Neston 00 31 2780 801 276 27.99 1 2 3 1 6 7 3 0 0 2 2 . 1 2 7 9 8 & 215.9 24 15 490 1 Port Neston 00 3011 53.21 319 2892 1384 50 .4 0 2 0 4 3 9 9 . 2 0 1 7 6 9 0 1 & 2 t 22 62 8 n 00 2 232 99 80 6.34 8 o 3 3 4 t 2 3 2 e Por s 1 3 2 1 e 5 1 15 46 35.35 200 156.8 010 820 rt & N 8 7.21 3966 702 802 2 149 2 1 3 4 re Po & Neston 11 8 5 2 1 0 2 3 1 5 39.0 187 185. 740 ort n0 39 5.98 2522 954 342 5 492 2 1 9 6 2 8 1 ere P t & Nesto 012 0 7 9 . 8 1 3 363.9 19 214 450 n or 13 3388 10.96 3926 1515 15 1542 6 8 9 1 ere P t & Nesto 3 8 3 . 9 1 5 5 0 99. 1 3 19 66 25 4.03 Por 2876 436 3277 1557 40 2 2 7 9 7 5 . 7 1 3 mere 4 9 0 79 4 6 1 1 1 5 10 3927 00 52.98 129 3548 2251 1 3 104 .4 9 5 4 2 5 shire 5 0 1 6 1 3 1 0 4 6 0 406 005 202 3966 2108 126.0 163 88 27 .07 8 2 6 0 5 5 tshire 07 2 0 1 2 1 2 5 6 2 3 6 29 33. 521 341 2333 60 re 0 0 101 272 5.38 7 9 1 2 2 ntshi 008 1 1 430 7 0 1 8 4 . 9 1 1 2 50 55 372 301 58 3 re 165 222 229 ntshi 009 237.1 440 13 38 14 4.45 17 2707 2 3 7 6 3 4 2 2 e 0 2 3 r 1 i 16 40 232 299.4 370 lintsh l 009 8 90 5.38 33 3084 370 6 0 1 7 3 2 1 6 1 o 8 3 3 1 9 o 5 9 . 2 p 3 444 179 450 Liver ol 012 24 2596 948 737 18.61 6 632 2 2 7 8 4 0 1 2 o 3 9 . 2 3 p 3 1 32 14 380 Liver ol 014 11 3790 29.31 661 3340 2756 11 0 8 0 1 4 8 o 7 . 1 2 p 4 4 0 r 2 2 15 44 5 Live 17 1936 52.68 672 4146 2574 8 ol 01 3 9 351 5 5 o 7 1 . 6 1 p 4 6 0 r 9 7 8 e 2 6 1 3 Liv 52 19 3.03 191 72 011 018 3 3 5 2 4 l 2 0 2 1 o 7 0 1 6 3 3 o 0 3 p 2 149 132. 390 Liver ol 019 1697 177 748 447 88.64 9 862 4 2 5 0 8 7 3 9 o 5 . 4 1 p 4 36 148 360 Liver ol 022 14 3077 54.26 506 3121 3036 19 8 2 1 2 9 1 o 9 . 0 2 p 1 5 0 r 3 3 18 43 3 Live 10 2677 17.28 4517 4534 21 2169 ol 02 2 3 5 1 7 o 2 2 . 2 1 p 4 7 0 r 8 7 9 e 1 1 3 Liv 28 09 0.44 20 3087 040 024 5 7 8 3 3 l 3 4 2 o 0 1 6 6 o 3 1 p 2 409 148. 370 9 Liver ol 028 3285 50.83 3755 3353 33 1409 61 12 2 2 po 3 0 r 0 4 e 3 3 2 169. v 4 5 i 6 3 L 22 34 399 93. 5 113 323 l 030 2 2 2 o 1 1 0 o 5 1 1 p 3 0 30 190 44 0 Liver ol 031 2155 65.21 489 2954 4173 75 1 9 4 o 4 2 1 p 3 0 r 7 3 19 39 Live 11 3311 033 61.52 325 3809 2637 96 175 p ool 396 336 6 24 410 5 2 0 7 . Liver ol 035 6 827 8 1 6 5 1 7 5 3 28 74 10 25 13 3 1 po 4 0 r 1 4 e 4 9 7 2 v 3 i 6 0 L 34 037 60.7 378 3924 2167 71 26 2 123 p ool 4 0 r 0 2 e 2 8 9 v 5 i 9 9 8 8 5 0 . L 27 03 41 0 387 254 311 101 p ool 361 286 460 0 8 .25 Liver ol 039 315 0 73 1 6 2 3 8 4 4 3 3 7 0 4 6 o 5 1 p 3 0 r 8 e 350 9 3 0 Liv 42 378 48.22 336 3354 1472 272 52 ool 0 99 1 p 6 0 r 6 e 316 1 7 4 v 0 Li 292 043 32.0 2900 2307 89 6553 30 50 1 p ool 4 0 r 5 e 405 7 9 6 v 0 i 1 5 4 L 50 30 51. 259 l 04 336 2187 78 o 8 9 o 1 8 1 p 4 0 r 469 51 8 5 Live 3436 29.62 356 3678 1879 86 ol 04 6 9 o 3 0 1 p 5 0 r 4 e 288 5 9 7 Liv 3525 20.83 230 3830 2023 3 ol 04 0 102 3 o 5 1 p 6 0 r 8 e 287 5 2 6 7 Liv 347 050 65.2 408 3556 2551 68 17 02 1 p ool 5 0 r 5 e 334 8 6 v 6 . 3 i 9 L 51 25 616 0 438 3244 l 052 2 1 1 4 o 2 1 3 o 3 1 p 4 0 245 38 Liver ol 053 13 3928 73.45 279 3483 1874 14 4 1 2 o 6 1 p 5 0 r 179 46 6 8 Live 3247 33.51 189 3509 1827 6 ol 05 4 300 8 o 3 p 4 0 r 2 e 25 8 5 3 Liv 60.2 331 3396 1871 3522 118 35 14 n 037 1 3 0 o t 2 18 f 3 1 5 e S 46 358 8 77.7 406 2702 1951 15 102 479 0 on 03


vector convertion

output format

DATA&

32

VB Script macro .dat script

x, y, z, values are saved into .dat using the Comma delimited file format. The use of a macro allows for all stages of the data convertion to be automated, the output of which are a series of .dat files. (001 = data set #1) Sub export_data() ' ' export_data Macro ' ' ActiveWorkbook.SaveAs Filename:= _ "Wirral_Data_001.xlsm" _ , FileFormat:=xlOpenXMLWorkbookMacroEnabled, CreateBackup:=False Sheets("001").Select Range("A1").Select ActiveCell.FormulaR1C1 = "=Wirral_Data_003!R[1]C[1]" Range("A1").Select Selection.AutoFill Destination:=Range("A1:A88"), Type:=xlFillDefault Range("A1:A88").Select Selection.AutoFill Destination:=Range("A1:C88"), Type:=xlFillDefault Range("A1:C88").Select Range("A89").Select Sheets("001").Select Range("A14:C18").Select Selection.ClearContents Range("A10:C10").Select Selection.ClearContents Range("A1:C1").Select Selection.ClearContents ActiveWindow.SmallScroll Down:=-12 Range("A1").Select

"Cloud_Outputs\" ActiveWorkbook.SaveAs Filename:= _ "Cloud_Outputs\001.dat" _ , FileFormat:=xlCSV, CreateBackup:=False Range("A89").Select Workbooks.Open Filename:= _ "Wirral_Data_001.xlsm" Windows("Wirral_Data_001.xlsm").Activate Windows("001.dat").Activate ActiveWorkbook.Close End Sub

provides a composite comparative tool of quanitative data

export

provides a co tool of quanit

0869.2, 4028.4, 9839.3 9492.2, 0685.1, 2934.3 ..., ..., ...

3D Data S

9839.3 2934.3

3D Data Scape

4028.4 0685.1 ...

W W Wir Wir r Wir ra Wir ra Wir l ral 0 Wir ra Wir l 01 ral 0 19 Wir ra Wir l 020 ra Wir l 021 ral 0 22 Wir ra Wir l 023 ra Wir l 024 ral 0 25 Wir ra Wir l 026 ra Wir l 027 ral 0 28 Wir ra Wir l 029 ra Wir l 030 ral 0 31 Wir ra Wir l 032 ral 0 33 Wir ra Wir l 034 r


34 587 012 44 .21 238 verp 630 287 134 7 209 6 2 0 Live ool 01 6.34 23 851 280 30 500 392 151 4 rpoo 1 7 5 4 Live l 01 191 7.21 463 289 0 430 406 155 5 rp 2 0 7 0 2 Live ool 01 5 4 559 2 . 6 9 4 2 399 0 8 225 40 962 8 rpoo 31 1 10.9 Live l 01 583 270 0 370 297 0 210 6 9 rp 2 2 201 8 1 Live ool 02 4 544 2 . 0 03 450 270 0 9 2 2 rpoo 5 1 3 4 33 7 52.9 8 Live l 135 31 742 392 380 308 8 301 rpoo 023 1 6 1 4 126 8 8 319 Live l 402 327 .04 440 259 8 233 rpoo 024 1 7 5 6 3 2 8 33.3 9 382 Live l 02 496 354 61 380 379 1 269 8 rp 113 8 0 1 4 0 5 3 1 Live ool 03 0.11 49 529 396 50 390 193 273 0 rp 143 6 6 25 7 74.4 492 Live ool 03 132 720 341 360 191 5 2 1 rpoo 121 7 2 5 6 1 1 1 6 0 0 5 Live l 03 132 5.38 42 790 372 430 169 257 3 rp 161 0 7 4 18.6 0 436 Live ool 03 195 4 4 390 307 65 2 2 1 5 rpoo 1 2 352 3 23 7 29.3 6 129 Live l 115 532 337 370 267 1 274 rpoo 037 130 0 7 1 8 5 4 2 Live l 03 2.68 02 398 294 40 440 308 303 8 rp 152 8 2 7 14 6 33.0 521 Live ool 03 104 5 3 440 328 39 3 3 4 9 4 rpoo 108 534 0 2 5 1 8 8 551 Live l 04 163 8.64 357 414 390 345 350 2 rp 106 6 200 3 24 9 5 3 Live ool 04 4 17 553 401 60 .26 410 215 335 3 rp 136 1 187 5 11 173 3 17.2 Live ool 04 227 58 417 3 340 331 2 8 4 rpoo 172 3 7 1 9 1 98 1 9 7 7 6 Live l 04 126 0.44 32 272 312 520 182 417 8 rp 1 319 91 7 1 3 5 9 6 Live ool 04 1 0 6 222 61 451 .83 1 460 346 263 9 rp 7 147 447 88 9 7 93.3 672 Live ool 05 176 403 304 380 279 2 2 0 rpoo 101 8 0 162 6 17 8 14 2 6 2 Live l 05 1 5 72 393 11 375 .21 460 231 216 2 rp 165 5 158 5 10 7 135 61.5 862 Live ool 05 390 323 650 378 1 3 2 3 rpoo 160 1 6 2 1 9 70 2 5 5 8 5 Seft l 05 105 6.26 06 470 295 510 292 381 6 o 253 4 229 1 2 0 6 9 1 Seft n 037 0 6 479 59 .77 380 9 540 300 147 o 334 9 232 7 22 2 1 41.8 320 Wir n 038 219 200 378 680 343 9 2 ral 0 240 3 5 4 07 6 4 1 2 4 4 0 4 01 Wir 3 1 6.25 09 457 21 392 650 352 218 ra 158 4 322 5 11 7 2 4 1 Wir l 002 9 1 8 1 1 9 4 2 . 3 22 380 347 91 8 549 187 ra 331 221 5 9 179 32.0 0 489 Wir l 003 4 3 3 4 2 2 .9 3 3 7 202 60 538 ra 5 73 130 296 3 141 51.5 0 325 Wir l 004 125 2 3 520 392 3 . 3 2 2 9 ral 0 0 5 212 551 4 149 8 105 154 8 29.6 0 0 Wir 312 75 290 6 520 324 .88 261 2 ral 0 5 123 0 3 7 6 6 1 2 4 8 3 0 Wir 76.5 0.83 78 351 96 336 560 331 187 ral 0 6 1 1 3 6 8 3 2 4 132 3 65.2 0 0 387 0 Wir 349 367 74 620 358 .37 2 182 ral 0 7 261 8 1 3 8 7 1 2 0 0 Wir 48.9 51.6 396 383 71 0 470 438 1 ral 0 8 1 8 0 4 0 7 9 09 50 2 1 185 8 73.4 336 0 Wir 413 355 550 304 .9 0 5 195 ral 0 9 1 6 3 4 5 0 6 1 1 177 8 33.5 2 5 553 1 Wir 426 324 74 510 288 . 7 1 1 ral 0 0 1 9 4 301 75 93 8 148 2 7 259 1 Wir 272 60.2 361 348 430 332 .6 160 ral 0 1 1 3 3 2 1 72 5 8 169 9 77.7 7 356 3 8 3 430 271 5 . 9 5 rral 12 2 1 2 4 0 123 018 9 336 4 01 190 6 15.0 9 230 699 339 78 460 214 .59 11 4 212 ral 0 3 101 6 413 7 1 9 1 6 3 4 14 96.4 1 08 450 270 86 .71 430 288 192 44 1 8 al 01 2 2 6 5 0 1 0 6 246 2 8 438 102 60.9 5 489 325 500 229 .65 233 33.1 152 9 286 2 016 4 2 2 3 2 10.0 2.99 79 509 346 68 710 330 266 76.1 130 2 350 4 46 017 2 202 2 28.8 189 110 6 2 630 329 5 .67 8 469 2 4 0 5 1 3 9 3 1 3 6 1 1 .12 3 8 0 2 21.0 6 1 522 18 01.9 502 14 344 580 336 6 135 52.3 136 7 5 4 6 0 0 2 4 5 1 4 9 0 3 1.43 06 9 432 2.12 00 348 410 361 176 51.0 133 2 469 9 11 4 2 4 3 1 8 4 5 6 1 3 . 7 93 620 246 61 .2 8 430 193 29.7 117 288 5 31 8 259 1 23.1 518 2 434 259 15 570 382 . 8 3 2 1 8 6 6 2 51.1 3 6 6 87 19 484 4 3 194 116 27.6 3 3 8 470 352 1 . 3 4 1 4 2 37.2 124 836 0 334 8 148 185 4 24.9 1 3 479 67 326 9 570 222 .02 205 5 32.2 7 2 8 4 4 1 6 2 1 4 5 6 3 9 1 0 5 3 9 6 4 . 1 4 440 354 3 . 5 0 8 206 4 7 44 43.3 135 179 3 6 177 7 29.1 4 889 2 535 14 318 560 341 .66 7 209 86.1 102 0 2 1 6 5 4 2 1 3 2 0 2 2 4 1 8 0 4 2 4 3 . 5 4 680 361 7 .9 8 436 5 255 9 93.7 149 186 171 7 8 199 8 29.5 0 35 414 269 43 650 416 .94 140 9 3 196 1 0 2 1 7 7 2 .2 0 2 180 46.9 1 0 214 658 509 409 440 403 .45 288 5 9 211 125 6 344 0 . 2 7 7 2 6 2 5 37.5 2.75 25 368 415 35 590 242 117 7 183 141 8 476 4 .64 9 198 9 16.4 2 167 5 8 3 420 313 4 . 0 6 9 2 3 7 2 66.2 148 141 5 377 8 18 258 8 31.4 7 9 4 3 0 890 243 8 .1 0 677 5 195 7 33.8 125 218 3 17 148 4 236 2 33.9 9 3 3 2 7 520 318 4 . 0 1 7 7 2 9 56 84.0 127 457 344 5 129 217 9 17.4 5 5 107 374 312 4 610 322 .83 4 187 42.3 9 348 8 2 3 1 2 4 0 4 2 1 1 0 4 5 6 4 3 . 2 7 51 26 0 . 5 6 4 3 6 2 4


DATA&

34

"Cloud_Outputs\" ActiveWorkbook.SaveAs Filename:= _ "Cloud_Outputs\001.dat" _ , FileFormat:=xlCSV, CreateBackup:=False Range("A89").Select Workbooks.Open Filename:= _ "Wirral_Data_001.xlsm" Windows("Wirral_Data_001.xlsm").Activate Windows("001.dat").Activate ActiveWorkbook.Close End Sub

workspace generation

SOA values

physical data

input 3D vectors

mer rt & Elles ere Po t & m s Por Elle ere ort m s e l El eP mer r Elles ere Po m s o e l P l E e mer Elles ere P m Elles ere m Elles hire s n i l F t hir s n Fli t h s Flint h s n i Fl t Flint Live Liv L

3D Data Scape

Selection.ClearContents Range("A10:C10").Select Selection.ClearContents Range("A1:C1").Select Selection.ClearContents ActiveWindow.SmallScroll Down:=-12 Range("A1").Select

output files

input 3D vectors

Meta-Spacial Data Scape Gerenation

z x

3D Grid Matrix

x,y,z matrix for input of cloud data files at origin coordinate

Super Output Areas

SOA are plotted for the Wirral giving x,y, coordinates

X,Y, Data Input

none quanitative data sets are input into matrix

.Dat Files Input (x,y,z)

x,y,z coordinates from .dat files are input into matrix

3D Data Scape

provides a composite comparative tool of quanitative data

3D Data Scape

y


1 4 & .9 n 1 18 9 108 138 363 3 .72 301 490 8 9 esto 239 532 6.34 132 8 214 8 0 6 414 .8 & N ston 00 98 2 8 0 9 1 2 3 0 4 1 9 0 8 2 2 1 1 3 6 27 39 92 09 7.2 Ne 195 95.8 6 4 9 9 1 2 6 3 1 6 0 3 9 3 t & eston 0 0 4 1 7 .0 18 .92 396 820 2 .98 295 15 9 539 4 1 5 N 1 6 5 0 .3 3 7 1 2 2 1 2 & 1 2 14 6 17 rt 15 t on .4 134 252 740 40 392 357 0.96 N es n 0 1 1 154 6 436 5 2 1 5 1 . & 2 6 8 1 9 5 1 7 t 8 0 o 5 5 0 t 1 or 33 45 9 327 .03 04 6.07 553 2 4 N es n 0 1 2 1 2 3 1 0 8 2 3 7 8 . & 1 5 6 8 1 8 8 to 8 155 194 3 287 660 Port 354 227 N es 163 95.3 202 0 0 52.9 1 6 1 1 & . 7 7 5 0 5 2 t 6 2 0 2 3 1 r 2 89 .1 39 51 Po .04 396 60 272 521 6 237 2 8 .64 126 1 0 229 165 4 210 117 1 8 412 .4 22 406 630 3 1 . 5 3 9 2 5 3 9 e 00 5 4 2 3 2 3 0 .4 1 3 2 3 6 2 2 0 6 0 3 8 1 0 2 2 1 1 .9 05 29 50 37 403 126 317 50.1 179 8 re 0 7 .35 14 44 18 53 1 4 3 72 0 0 2 1 1 3 9 3 3 5 2 1 2 1 . 0 9 2 4 4 4 0 3 16 733 8 2 74. 141 8 8 4 1 0.8 2 7 3 3 4 hire 08 3 0 0 0 3 3 7 0 7 4 2 2 4 33 0 39 32 5.38 176 54.8 6 4 1 0 1 0 0 .17 2 2 1 4 9 4 hire 09 7 2 8 2 26 1 11 .53 308 370 294 470 111 661 18.6 176 7 re 0 7 8 .94 11 96 6 3 5 0 2 0 9 0 7 1 3 4 9 5 tshi l 009 5 1 2 3 2 4 33 47 72 9.3 351 32. 8 6 7 9 2 1 1 o 6 1 1 4 o 0 5 3 1 1 6 p 9 0 3 7 .7 27 er 37 38 2 .68 414 05 8.98 012 200 7 2 1 l 4 3 2 9 4 5 1 o 8 4 0 2 . 1 6 o 6 6 3 1 8 13 257 3 103 2 193 440 verp ol 014 59 401 457 85.9 862 . 7 0 33.0 1 2 2 1 4 3 6 o 5 1 4 4 3 7 1 p 0 3 2 2 r 5 2 19 38 6 .64 417 19 7.7 191 0 8 2 7 Live ool 01 5 4 2 8 1 18 8 3 . 1 8 7 1 1 12 rp 8 274 6 116 2 .69 169 390 312 425 121 Live ool 01 169 0 9 54.2 148 6 6 2 2 .8 1 0 7 3 6 4 4 7 7 p 0 0 1 4 1 r 9 3 8 .2 30 36 45 230 148 Live ool 01 320 17.2 169 9 .12 28 02 7 34 61 3 3 0 7 p 0 5 2 3 4 r 2 2 6 3 4 4 5 e 0 3 . 1 2 2 4 4 3 3 3 Liv 409 9 1 70. 190 8 ol 0 9 2 1 .15 0 7 o 0 0 6 3 5 8 p 0 5 1 7 5 r 3 1 0 3 3 39 37 35 13 0.83 125 96.4 Live ool 02 1 2 2 5 1 3 1 .1 2 7 5 5 4 9 3 6 1 rp 4 33 2 46 .65 328 370 75 323 349 Live ool 02 489 0 93.3 246 2 9 5 .3 36 3 9 7 2 3 4 5 p 0 3 1 5 r 5 8 6 4 4 2 1 0 3 4 96 29 39 25 5.2 10. Live ool 02 3 1 3 6 2 3 5 1 1 5 7 2 1 4 9 5 p 0 1 5 r 0 41 2 .67 21 44 6 74 380 413 Live ool 03 0 61.5 202 7 7 105 1 202 123 2 rp 1 6 263 6 9 785 1 . 2 331 390 2 8 3 . 7 1 4 7 6 0 Live ool 03 3 0 5 2 286 27 0 817 2 101 24 rp 3 1 8 1 7 2 1 e 9 0 . 3 6 1 4 7 7 v . 3 2 0 3 i l L 38 0 60 20 7 9 350 9 160 rpoo 5 9 216 .21 346 340 0 254 74 354 Live ool 03 8 6 41.8 236 8 5 2 1 8 1 5 3 3 p 9 0 1 1 r 7 7 9 7 2 3 5 e 3 2 .8 3 9 2 5 2 6 v . 3 7 9 0 6 i 3 2 l L 3 0 46 25 0 5 405 130 rpoo 8 381 9 354 .44 50 231 460 22 3 . 8 3 4 4 5 8 9 Live ool 03 5 0 9 4 1 6 46 89 0 472 118 rp 00 9 9 7 8 1 7 e 8 9 .02 3 8 3 3 0 9 v . 7 2 5 0 4 i 5 2 L 2 3 18 50 1 ool 07 36 288 1 2 p 0 3 1 r 6 2 9 9 6 2 9 e 6 3 .87 4 0 2 4 5 6 8 3 5 l0 Liv 35 5 51. 199 6 7 7 287 133 rpoo 3 0 218 2 678 2 .6 5 300 650 6 0 3 . 0 7 6 3 9 1 7 Live ool 04 2 7 2 1 9 6 334 0 117 rp 4 187 .98 343 510 8 .83 383 68 2 502 0 0 4 Live ool 04 4 7 5 2 1 3 4 5 24 13 rp 8 2 2 202 556 0 .94 3 352 540 2 8 . 3 1 9 4 3 5 1 9 Live ool 04 9 6 1 14 179 75 0 551 124 rp 44 9 1 4 8 2 6 e . 4 2 .4 4 6 3 6 9 v 1 1 3 0 0 5 i 5 l L 27 18 6 13 8 86 252 rpoo 0 4 261 5 483 0 3 253 650 4 9 . 3 0 7 4 8 3 3 3 Live ool 05 1 8 6 7 2 4 8 18 9 135 rp 2 187 1 392 380 2 350 314 118 Live ool 05 3 33.5 19 352 71 7 27 02 2 6 4 p 0 8 1 9 r 3 9 2 6 1 2 e 3 . 5 5 7 3 4 3 1 4 60 Liv 406 6 4 2 ol 0 1 9 4 4 8 o 7 4 3 2 1 p 0 8 1 0 r 6 1 33 52 27 16 337 47 7.71 1 Live ool 05 1 6 7 1 0 1 7 3 5 1 4 9 1 rp 4 19 358 520 67 325 535 Live n 037 518 1 15.0 3 9 377 125 o 9 199 1 462 5 7 438 560 7 8 . 3 6 4 4 1 1 Seft n 038 8 1 6 8 1 4 1 5 0 4 218 9 1 o 16 304 620 9 14 285 414 60.9 Seft l 001 8 8 148 31 8 1 4 344 5 8 0 0 a 1 4 9 r 8 7 2 9 2 4 34 50 51 2.9 148 Wir l 002 9 2 9 5 1 1 2 2 348 2 2 0 1 ra 21 4 33 55 348 43 368 Wir l 003 889 1 28.8 6 7 4 2 2 208 0 1 0 9 a 1 3 7 r 7 1 6 1 r 2 5 34 54 658 Wi 04 205 6 21.0 4 3 0 1 7 3 8 l 493 6 4 0 3 a r 3 2 21 43 5 259 35 487 Wir l 005 4 41.4 2 2 713 5 6 0 1 305 0 8 0 6 a 1 2 9 r 8 3 2 3 r 0 3 4 2 4 8 3 3 8.9 Wi 06 214 0 0 4 0 4 2 3 l 0 1 376 7 9 0 3 a 2 r 2 0 22 46 326 374 25 3.13 Wir l 007 5 0 2 0 2 2 4 5 2 46 4 1 ra 13 330 430 21 404 504 27.6 Wir l 008 167 0 4 6 2 6 6 4 3 0 9 0 7 a 1 8 5 r 2 1 5 3 50 31 53 90 107 Wir l 009 2 24.9 53 6 66 0 938 1 3 5 ra 3 1 1 4 r 4 5 2 3 7 i 4 7 3 5 14 W 10 2 40. 3 148 9 91 0 ral 0 266 361 630 269 48 696 94 9.17 Wir l 011 2 8 2 6 1 1 5 3 6 6 100 ra 5 18 24 580 46 409 366 Wir l 012 442 38.4 2 17 6 5 8 2 0 0 a 121 5 1 r 8 1 2 3 3 4 0 40 41 38 Wir l 013 5 29.5 6 8 6 75 5 2 0 0 a r 2 9 35 62 2 362 371 188 Wir l 014 0 46.9 2 122 4 9 28 7 2 0 0 a 1 7 0 r 2 7 2 5 r 8 6 2 5 7 3 41 Wi 15 200 0 62.7 8 0 2 1 3 5 l 81 6 4 0 5 a r 2 3 0 35 47 305 507 Wir l 016 452 16.4 23 4 9 16 0 962 1 2 8 ra 4 7 5 1 r 1 0 5 3 5 i 3 4 3 18 W 17 8 31.4 7 0 7 1 l 7 1 0 1 a 1 3 r 7 2 36 44 36 42 435 Wir l 018 241 0 33.9 9 7 2 ra 183 416 560 0 .44 363 84 492 0 7 1 Wir l 019 4 5 1 1 0 ra 214 6 9 001 403 680 7 3 . 7 3 438 9 0 Wir l 020 4 4 10 5 24 0 954 1 ra 4 5 1 5 r 6 2 2 6 i 2 9 . 5 3 511 W 21 35 11 7 22 8 ral 0 245 4 8 455 313 440 1 5 . 2 2 481 6 9 Wir l 022 3 6 4 2 33 0 871 4 ra 4 9 1 2 r 5 4 2 5 i 3 4 3 . 1 535 W 23 12 5 30 9 5 ral 0 4 207 .7 096 5 318 420 7 4 3 8 466 7 4 Wir 2 3 3 0


36

DATA SCAPE

DATA SCAPE


DATA SCAPE

37


38

DATA SCAPE

DATA SCAPE_DATA SETS_

industry of employment [hotel]

population density [persons]

floorspace [retail premises]

average weekly income [household]

economic active [persons]


DATA SCAPE

industry of employmeny [retail]

retail premises [count]

existing hotel assets

existing supermarket / retail assets

dwellings [count]

39


40

DATA SCAPE

DATA SCAPE PROCESSES_

Plan

Matrix Grid


DATA SCAPE

Data Sets

Composite Data Scape

41


42

DATA SCAPE

Composite Data Scape_

20%

40%

60%

80%

20%

40%

60%

80%

20%

40%

60%

80%


DATA SCAPE

100%

43


04

_INTRODUCTION & CONTEXT 14 _WPA_2.0_COMPETITION 28 _DATA&_DATA SCAPE 46 _DESIGN DEVELOPMENT 70 _PROPOSAL


46

DESIGN DEVELOPMENT

DESIGN DEVELOPMENT

DESIGN DEVELOPMENT_DIAGRAM_ The design development has utilised the conclusions of the data scape – the representation of data and information upon the physical condition of Birkenhead, has allows for an understanding to be constructed which informs the direction of specific design intentions and decisions. To the right, a associative diagram which illustrates the links and connections of certain local and global agency, together with elements of economic and infrastructural entities.


DESIGN DEVELOPMENT

47


SHOP


PPING


50

DESIGN DEVELOPMENT

Existing rail network station Proposed rail network station Existing rail network assets Proposed rail network assets Hyper-connections pipelines Strategic / directed connectivity Proposed hotel assets Consumer fulfillment centre Diversity voids (P1) Population density Household income (>60%) Existing retail assets

Discarded CFC iteration Wealth voids (P1A) Household weekly income


52

DESIGN DEVELOPMENT

Existing rail network station Proposed rail network station Existing rail network assets Proposed rail network assets Hyper-connections pipelines Strategic / directed connectivity Proposed hotel assets Consumer fulfillment centre Diversity voids (P1) Population density Household income (>60%) Existing retail assets

Discarded CFC iteration Wealth voids (P1A) Household weekly income


54

DESIGN DEVELOPMENT

Existing rail network station Proposed rail network station Existing rail network assets Proposed rail network assets Hyper-connections pipelines Strategic / directed connectivity Proposed hotel assets Consumer fulfillment centre Diversity voids (P1) Population density Household income (>60%) Existing retail assets

Discarded CFC iteration Wealth voids (P1A) Household weekly income


56

DESIGN DEVELOPMENT

Existing rail network station Proposed rail network station Existing rail network assets Proposed rail network assets Hyper-connections pipelines Strategic / directed connectivity Proposed hotel assets Consumer fulfillment centre Diversity voids (P1) Population density Household income (>60%) Existing retail assets

Discarded CFC iteration Wealth voids (P1A) Household weekly income


58

DESIGN DEVELOPMENT

Existing rail network station Proposed rail network station Existing rail network assets Proposed rail network assets Hyper-connections pipelines Strategic / directed connectivity Proposed hotel assets Consumer fulfillment centre Diversity voids (P1) Population density Household income (>60%) Existing retail assets

Discarded CFC iteration Wealth voids (P1A) Household weekly income


60

DESIGN DEVELOPMENT

Existing rail network station Proposed rail network station Existing rail network assets Proposed rail network assets Hyper-connections pipelines Strategic / directed connectivity Proposed hotel assets Consumer fulfillment centre Diversity voids (P1) Population density Household income (>60%) Existing retail assets

Discarded CFC iteration Wealth voids (P1A) Household weekly income


62

DESIGN DEVELOPMENT

Existing rail network station Proposed rail network station Existing rail network assets Proposed rail network assets Hyper-connections pipelines Strategic / directed connectivity Proposed hotel assets Consumer fulfillment centre Diversity voids (P1) Population density Household income (>60%) Existing retail assets

Discarded CFC iteration Wealth voids (P1A) Household weekly income


64

DESIGN DEVELOPMENT

Existing rail network station Proposed rail network station Existing rail network assets Proposed rail network assets Hyper-connections pipelines Strategic / directed connectivity Proposed hotel assets Consumer fulfillment centre Diversity voids (P1) Population density Household income (>60%) Existing retail assets

Discarded CFC iteration Wealth voids (P1A) Household weekly income


Existing Urban Fabric

Analysis / Indicators Population Access Map Retail Assets Map Services Access Map Financial Access Map

+ + + +

strategic action

Decision-Making Tool Stakeholders Policy Makers

Planners

Developers

Citizens

Component Tool For Urban Strategic Planning and Determination of Retail Growth

=

Wirral Buisness Plan

Retail Area per Person

Cooperative Competitive

criteria: Physical Variables Goods Diversity InfrastructuralConnectivity

mp co an

g c

acity

x 1.2

Investment Sectors Percentage of growth required to facilitate demand for europe in 2050

Retail Property Assets Infrastructure Assets

Gruen Principles 1. 2. 3. 4. 5.

safeguard surrounding areas against blight. expose retail facilities to maximum foot traffic. separate various mechanized traffic types from each other and from foot traffic. create a maximum of comfort and convenience for shoppers and merchants. achieve orderliness, unity and beauty.

y inve e stm nt

yin

ap

Projected Growth

stra

2%

Risk Management Sustained Growth ‘To Big To Fail’

carr

Volumetric data required to facilitate consumption of total european demand

Economic Strategy

m p an co

g

European Retail Demand

y

50%

ic teg ai

rn ove m

in

t cen ive

en t

ms

Volumetric data required to facilitate consumption of total national demand

50%


DESIGN DEVELOPMENT

STRATEGY_POLICY TOOL_

A decision making tool - combining population and service accessibility metrics with analyses of commercial retail area and infrastructural capacity - capitalizes on the Wirral’s potential existing retail assets to provide a quantitative means of analyzing and iteratively improving, product (goods) diversity, and infrastructuralcapacity. This strategy gives policy makers, planners, developers and citizens a common understanding of the underlying patterns that shape their community’s carbon-footprint, and can inform consensus-driven systemic action, such as the zoning of Padestrian, Transport and Traffic.

67


04

_INTRODUCTION & CONTEXT 14 _WPA_2.0_COMPETITION 28 _DATA&_DATA SCAPE 46 _DESIGN DEVELOPMENT 70 _PROPOSAL


70

PROPOSAL

PROPOSAL

The Wirral Peninsular, as the study of re-processed landscape, is to be the subject of the applications of a policy of systematic re-composition. The existing landscape, in the context of infrastructural systems to enable consumerism, has the traits of generic suburban conditions. However the proximity and symbiotic relationship with Liverpool, presents a source of bigger consumer base from which to expand, in order supplant existing retail areas from Liverpool to the Wirral Peninsular. The proposition would implement shopping malls as units for adaptive system attractors, the theme of shopping as the field of condition and of the organisation which defines the programmatic distribution across urbanity. The generated scenario would create a utopia, the urban forms and patterns of which would be reactionary to consumerism, managed through density of retail area and vibrancy of products, these towers of shopping density become urban artefacts which are physical valuations to the commercial success of the utopia.


Designer’s Republic

PROPOSAL 71


72

PROPOSAL

GRUEN’S MALL _ A UNIT OF PLANNING_

Mall

Neighborhood

x 20 = Town

x 10 = City

x 10 = Metropolis


PROPOSAL

The success and competence is achieved by implementing the thematic of shopping as the matrix to direct urbanity, and the embrace of techniques of genetic research to enable the effective cloning and recombination of successful urban patterns. The mall as standard model for planning urban densities, which is programmatically (not form) driven, which is adaptive to demographic, dynamic market fluctuation and density of products, public realms and retail space. A composite decision making tool, generating a series of strategic maps , to inform stakeholders of near-future scenarios and potential areas of development. “Generic qualities are heightened to become emblematic. Similarity and consistency are produced by deploying erasure and replacement strategies to reconfigure both city and the individual psyche.”i

i Turnbull, D. (2002) ‘GMCity: The Genetically Modified City (2001)’. In: Leach, N. ‘Designing for a Digital World’. London, Wiley & Sons. p.76

73


74

PROPOSAL

ITERATIVE_DEVELOPMENT_

_iteration [01]

_iteration [02]


PROPOSAL

_iteration [03]

_iteration [04]

75


76

PROPOSAL

PROPOSED PLAN_

Existing rail network station Proposed rail network station Existing rail network assets Proposed rail network assets Hyper-connections pipelines Strategic / directed connectivity Proposed hotel assets Consumer fulfillment centre Diversity voids (P1) Population density Household income (>60%) Existing retail assets

Discarded CFC iteration Wealth voids (P1A) Household weekly income


Shopping_for_Utopia  
Shopping_for_Utopia  

Design studio work conducted during term 1 of the BArch program at Manchester School of Architecture.

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