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URBAN DESIGN & DATA
Roy Lin
Aug.3 2013 Code for Tomorrow
EXAMPLE 1:
DATA FOR URBAN PROJECT DESIGN
MEGASTORAGE, QUEENS
Project by: Zhou Wu, Roy Lin
JUSTUFIED
ISSUE
INSIGHTS!
Observe Data Analyse Data
Colect Data
DomainKnowledge
Consultants,Experts,Authorities
Info Overlap
Future Forcast
Supporting Data
Client
Field Study
Site Visit
Interview
.
.
.
.
.
.
CONCEPT PROPOSALOPINION
STATEMENT DESIGN
(Subjective) (Objective)
Design Process and Data. by Roy Lin, 2013
JUSTUFIED
ISSUE
INSIGHTS!
Observe Data Analyse Data
Colect Data
DomainKnowledge
Consultants,Experts,Authorities
Info Overlap
Future Forcast
Supporting Data
Client
Field Study
Site Visit
Interview
.
.
.
.
.
.
CONCEPT PROPOSALOPINION
STATEMENT DESIGN
(Subjective) (Objective)
SUBWAY PASSENGER FLOW
INDUSTRIAL LAND
JUSTUFIED
ISSUE
INSIGHTS!
Observe Data Analyse Data
Colect Data
DomainKnowledge
Consultants,Experts,Authorities
Info Overlap
Future Forcast
Supporting Data
Client
Field Study
Site Visit
Interview
.
.
.
.
.
.
CONCEPT PROPOSALOPINION
STATEMENT DESIGN
(Subjective) (Objective)
30.1%
INDUSTRY
AUTO REPAIR
OFFICE
COMMERCE
PUBLIC FACILITY
HOUSING
Land Use
REGIONAL TRAIN LINES, FREIGHT TRAINS
SITE VISIT
JUSTUFIED
ISSUE
INSIGHTS!
Observe Data Analyse Data
Colect Data
DomainKnowledge
Consultants,Experts,Authorities
Info Overlap
Future Forcast
Supporting Data
Client
Field Study
Site Visit
Interview
.
.
.
.
.
.
CONCEPT PROPOSALOPINION
STATEMENT DESIGN
(Subjective) (Objective)
Industry-Others
Bronx
Queens
Brook
lyn
JerseyCity
Manhattan
Housing
Industry-Storage
OthersPublic
Com
m
ercial
New York Region
Population
Queens
Land Use Portions
NY POPULATION DISTRIBUTION, QUEENS LANDUSE
JUSTUFIED
ISSUE
INSIGHTS!
Observe Data Analyse Data
Colect Data
DomainKnowledge
Consultants,Experts,Authorities
Info Overlap
Future Forcast
Supporting Data
Client
Field Study
Site Visit
Interview
.
.
.
.
.
.
CONCEPT PROPOSALOPINION
STATEMENT DESIGN
(Subjective) (Objective)
TRAFFIC
Inbound
Outbound
TRAFFIC
Area = 597122 m²
Total warehouse space=3277280 m³
Average floor height = 5.5 Floors
1415.4696 1415.4696
Area = 283308 m²
Total warehouse space=3277280 m³
Average floor height = 11.6 Floors
--Inbound
--Outbound
--roads
Area = 396979 m²
Total warehouse space=3277280 m³
Average floor height = 8.3 Floors
less=46620 m³
A=34475m²
F=5
A=63678m²
F=6
A=67524m²
F=7
A=59980m²
F=8
A=56238m²
F=9
A=57009m²
F=10
A=49411m²
F=11
A=8663m²
F=12
A=34475m²F=5
A=34475m²F=5
A=34475m²F=5
A=34475m²F=5
A=34475m²F=5
A=34475m²F=5
A=34475m²F=5
A=34475m²F=5
Area = 396979 m²
Total warehouse space=3277280 m³
Average floor height = 8.3 Floors
Area = 378749 m²
Total warehouse space=3277280 m³
Average floor height = 8.6 Floors
PASSENGER FLOW vs ATTRACTIONS
SOCIAL HOUSING FOOTPRINT vs TIME
FLOODING OVER YEARS
EXAMPLE 2:
READING URBAN CONTEXT
TRANSIT FOR MIT KENDALLSQ.
Project by: Ren Tian, Tuan-Yee Ching, Roy Lin
TRANPORTATION TOOLS INFO MATRIX
COMMUTER RAIL
RAIL TRANSIT BUS TRANSIT
MAJOR RAIL
STATIONAIRPORT FERRY
METRO NETWORKS
LOCAL NETWORKS
RAIL TRANSIT /
400M (5MIN)RADIUS BUS TRANSIT
PROTECTED PATH
BIKE LANE ZIP CAR
EXAMPLE 3:
CITY STORY TELLING
THE CALIFORNIAREGION
Project by: Tomas Folch, Kees Lokman, Rou Lin
LANDSCAPE, ENERGY, INFRASTRUCTURES, MIGRATION, WAR, AGRICULTURE...
EXAMPLE 4:
PREDICT & SUGGEST SOLUTION
SPACE SYNTAX
Tim Stonor and
SPACE SYNTAX
HOT ZONES
HOT ZONES
EXAMPLE 5:
DEMOCRATIZE URBAN KNOWLEDGE
SOCIALEXPLOER
URBAN CONTEXT
TRADITIONAL URBAN DATA
Public Sectors, GIS, Zoning, Land, Infrastructure,
Transportation, Demographic, ...a lot of To-Be-
Opened Data!
Ashit load of everything
Private Sectors Data, User-Gnerated Data, Instant
and Dynamic Data, ...More-To-Come Big Data!
NEW URBAN DATA
Real Innovation!
Urban Context, Data, and Innovation. by Roy Lin, 2013
wearedata.watchdogs.com
senseable.mit.edu
www.honda.co.jp
URBAN CONTEXT
TRADITIONAL URBAN DATA
Public Sectors, GIS, Zoning, Land, Infrastructure,
Transportation, Demographic, ...a lot of To-Be-
Opened Data!
Ashit load of everything
Private Sectors Data, User-Gnerated Data, Instant
and Dynamic Data, ...More-To-Come Big Data!
NEW URBAN DATA
Real Innovation!
Urban Context, Data, and Innovation. by Roy Lin, 2013

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