Cognitive Map Analysis | 20.303 Urban Analysis by Clifford Mario Kosasih

20.016 Urban Analysis

COGNITIVE MAP ANALYSIS Serangoon, Yishun and Tampines Clifford Mario Kosasih (1000294) Goh Pei Xuan (1000286) Kevin Josiah Neo Jun Hao (1000133) Oor Eiffel (1000293) Sharon Ho Jia Jia (100091)

TABLE OF CONTENTS 1. INTRODUCTION

2. LITERATURE REVIEW

3. RESEARCH QUESTION

4. HYPOTHESES

5. SATELLITE IMAGE

6. SURVEY MAPS AND SAMPLE RESPONSE

7. COMPOSITE MAP

8. QUANTITATIVE TABLE

9. ANALYSIS

10. CONCLUSION

11. DESIGN RECOMMENDATIONS

12. BIBLIOGRAPHY

1. INTRODUCTION This experiment analyzes people’s familiarity on the street networks of different neighborhoods in Singapore through the use of cognitive maps. Golledge and Garling (2003) deﬁnes cognitive maps as the conceptual manifestations of place-based experience and reasoning that allow one to determine where one is at any moment and what place-related objects occur in that vicinity or in surrounding space. In this experiment, we have chosen three residential neighborhoods in Singapore: Serangoon, Yishun and Tampines to test our hypotheses on what qualities of urban design affects cognitive urban recollections more correctly.

2. LITERATURE REVIEW Cognitive maps have been utilized by various scholars in urban design as a medium to understand a city better. How much people remember an image of a city is of particular interest due to the social and political implications that it can generate. In his book Image of the City (1960), Lynch conducted interviews with regards to the image of the environment in order to test hypothesis of imageability and discover people’s image of the three cities. In his later book, City Sense and City Design (1995), Lynch ran a visual survey in a community which is directed towards identifying four visual qualities: valubale, undesirable, changing and most vulnerable. In his experiments, Lynch aimed at open community debate, to a recommended set of actions for conservation and change, including new regulations, policies, guidelines, procedures, incentives, investments, education, and public and private actions. Furthermore, in an attempt to find correlation between street properties and cognitive maps, Mohsenin and Sevtsuk (2013) discovered that continuity, street width, and pattern strongly influenced people’s memory of a city. Continuous street can be remembered easily since it involves least number of orientation changes, while wider streets allow people to have better image of the surroundings. Lastly, streets with well-defined pattern are easily remembered due to an underlying system in which the street network is designed. Other than the image of a city and street properties, Golledge and Garling (2003) are interested in how cognitive maps and travel behavior in urban environments. This study includes different transportation issues such as cognizing transportation networks, travel behaviour and trip purpose. They argued that if one has an overall anchoring structure of en-route and offroute landmarks and can determine a route through multiple networks of links and nodes, one can find his/her way between specific origins and destinations in urban environments.

3. RESEARCH QUESTION To understand how the urban design of Serangoon, Yishun and Tampines affect cognitive recollections of these residential neighborhoods.

4. HYPOTHESES Our first hypothesis was that people will remember wider streets better than narrow streets. In this experiment, street width is measured by the number of vehicular lanes passing through that street, regardless of the direction. The wider the street corresponds to higher usage frequency, hence people will better remember them. Furthermore, people have a more complete perspective of the surroundings, which will help them to visualize the street from memory more accurately (Mohsenin and Sevtsuk, 2013). Our second hypothesis was that people will remember primary junctions better than secondary junctions. In The Image of the City (1960), Lynch identifies nodes as one of the elements that people remember in a city. They are points, the strategic spots in a city into which an observer can enter, and which are the intensive foci to and from which he is traveling. In this hypothesis, we are focusing on street junctions as a subset of nodes connecting streets classified as primary and secondary. Primary junctions are defined as those connecting major streets, while secondary junctions are defined as those connecting minor streets. We argued that primary junctions are better remembered than secondary junctions because the former determines the more significant decision making process in a way-finding journey as compared to secondary junctions, hence it will be better remembered. Our last hypothesis was that people will remember streets with more bus services passing through them. As pointed out earlier in the literature review, Golledge and Garling (2003) suggested that if a particular transportation network structure is anchored in one’s mind, one can more easily navigate between destination and origin in a particular neighborhood. A higher number of bus passing through a segment indicates higher connectivity which presents people with more choices of destinations and hence increasing the frequency of possible visits. Since how well people remember roads correlates with the frequency of visit, the connectivity of street segments play a role in remembering street networks. 4

5. SATELLITE IMAGE

Braddell Heights CC

Serangoon Stadium

Lorong Chuan MRT

Serangoon Garden Market

Nanyang Junior College

Serangoon MRT

Zhonghua Secondary School

Serangoon

Serangoon NPC

Nex Shopping Mall

Northpoint

Yishun Central

Yishun Ring Road

Yishun Bus Interchange

Yishun Junior College

Yishun Pond

Nee Soon Central Coomunity Park

Yishun

Yishun MRT

Khoo Teck Puat Hospital

Tampines Bus Interchange

Tampines Regional Library

Tampines MRT

Pasir Ris Secondary School

Tampines Swimming Complex

Medical Centre Telepark

Tampines Sports Hall

Tampines

Tampines Mall

Century Mall

6. SURVEY MAPS AND SAMPLE RESPONSE This experiment’s result is highly dependent on the sites that are chosen. Therefore, we have carefully chosen our sites to better suit our research question: • Residential estate with mostly HDBs • Prominent MRT station in the vicinity • Balanced mix of roads that have bus services running through it and not We asked 10 people from each sites: Serangoon, Yishun and Tampines. With a total of 30 respondents, this experiment is done by asking them to draw the existing street networks in the blanked out space within the survey forms. After gathering data, we have devised a system to classify the two important indication of recollections of street networks based on the observation we had during the interview: • Memorability: Basic indication that a path/street is there, does not take into account the accuracy of the shape and position of the street. • Accuracy: Accurate representation of the street segment’s position in which the ends are connected to the other street segments and the angle between the adjacent street segments. Furthermore, we have decided to use numbered street segments to analyze the map. Firstly, we realized that not every roads have homogeneous street width, and bus services running through it. Therefore, by breaking it up into segments, we can better discretize the street and analyze it per segments. Secondly, segments are determined by the different junctions as well as every continuous streets that have a turn more than 20 degrees.

Y io C o ng R hu K a

Lo r C hu

Yio C hu K ang Link

Boundary Road

L or

o K io

A ve 1

U pp

go an

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a ya

L eb

ar R

oa d

S erangoon C entra

Serangoon 1:20000

hu a

S erangoon C entr

A ng M

n hua

U pp

er S

era n go o

S erangoon Ave 1

Y io C o ng R hu K a

o K io

A ve 1

go an

hu a

a ya

L eb

ar R

oa d

Statistics 73% routes remembered 70% routes drawn accurately

S erangoon Ave 1

U pp

er S

era n go o

er P

oa d

U pp

S erangoon C entra

Serangoon (blank) 1:20000

Lo r C hu

Yio C hu K ang Link

A ng M

Y is

un S Y is h

R in

t 21

Y ish

Y is hun S t 11

un A ve nu

Y is hun R ing R oad

hu n

e2 Y is

ue en

Y is hun Avenue 5

hu nA

nu e

Y is

Yishun 1:20000

Y is

hun A ve nu e 4

oa d gR

R in un Y is h

e nu

St 6

h un

un Y is h

Y is

un S Y is h

R in

t 21

Y ish

Y is hun S t 11

un A ve nu

Y is hun R ing R oad

hu n

e2 Y is

n hu

ue en

Y is hun A ve nu e 4

oa d

un Y is h

e nu

St 6

h un

nu e

R in

hu nA

Y is h

Y is

Yishun (blank) 1:20000

Y is hun Avenue 5

Statistics 97% routes remembered 83% routes drawn accurately 10

Sungei Tampines Tampines St 43

Tampines Ave 9

7 Ta m

pin es

trl

Tampines Ave 6

Tampines St 42

Tampines St 41

Tampines Ave 7

Tampines Ave 5

Tampines St 32

Tampines MRT

Tampines St 82

Ave pin es Tam

t 31

Ave

Tampines St 22

Av e 5

Tampines 1:20000

sS pine Tam

s pine Tam

s pine Ta m

Tampines St 91

Tampines

St 11

Sungei Tampines Tampines St 43

Tampines Ave 9

7 Ta m

pin es

trl

Tampines Ave 6

Tampines St 42

Tampines St 41

Tampines Ave 7

Tampines St 32 Tampines St 82

Tam

t 31

pin es

Ave

sS pine Tam

Tampines St 91

s pine Tam

s pine Ta m

2 Ave

Tampines St 22

Statistics 82% routes remembered 58% routes drawn accurately

Av e 5

Tampines (blank) 1:20000

Tampines Ave 5

Tampines

St 11

ad ng Ro hu K a Yio C

Lor Chu a

Yio Chu Kang Lin

7. COMPOSITE MAP

Boundary Road

hua

ua Ch Lo r

Serangoon 1:10000

Upp

er P aya Leb a

r Ro

Serangoon Ave 1

Upp er S e

Less than 20% 20% - 40% 40% - 60% 60% - 80% More than 80%

rang oon Roa d

Streets

rS pe p U

ad Ro

Serangoon Central

Junctions Less than 20% 20% - 40% 40% - 60% 60% - 80% More than 80%

on go n ra

Serangoon Cent ral

io Ave

C Lor

Ang M oK

Yi sh t un S Yish

n Yishu

Yishun St 11

ue Aven

Yishun Ring Road

en Av

sh Yi

Yishun Avenue 5

Yis h

Av en

u ven nA

u Yish

Junctions Less than 20% 20% - 40% 40% - 60% 60% - 80% More than 80% Streets

oad n Ri u Yish

ng R

t un S Yish

Yis h e2

Yishun 1:10000

nA ven u

Less than 20% 20% - 40% 40% - 60% 60% - 80% More than 80%

Sungei Tampines Tampines St 43

Tampines Ave 9

7 Ta

trl

Tampines Ave 6

Tampines St 42

Tampines St 41

Tampines Ave 7

Tampines Ave 5

Tampines St 32 Tampines St 82

e4 s Av Tam

pine

s St

pine

Tampines St 91

Tampines St 22

s Av

Tampines 1:10000

pine

Less than 20% 20% - 40% 40% - 60% 60% - 80% More than 80%

s Av

ine amp

Tam

Streets

Tam

Junctions Less than 20% 20% - 40% 40% - 60% 60% - 80% More than 80%

Tampines

St 11

8. QUANTITATIVE TABLE hu Yio C Kang Road

Lor Chua n

Yio Chu Kang

Link

Segment

Boundary Road uan Ch Lor S1

JS1

JS3 S3

JS4

S13

S19

JS15

JS16

S18

Ave 1

S20

Lo rC hu an

Serangoon Cen tral

Ang M o Kio

JS2

S14

S15 S7 JS14

S16

S31

S29 S21

S33 JS8 S28

JS7 S32

JS5

S27 JS6 S30 JS9S26

r pe Up

o ng ra Se

Up p er P

ad Ro

aya Leb ar

S25 JS10

S22 S24

S9 JS11

S12 S23

S10 S11

Serangoon Ave 1

Upp er

Sera ngo on

Roa d

JS12

Serangoon Central

JS13

S17

JUNCTIONS JuncƟon JS1 JS2 JS3 JS4 JS5 JS6 JS7 JS8 JS9 JS10 JS11 JS12 JS13 JS14 JS15 JS16

Type of JuncƟon 1 1 1 1 1 2 3 3 3 2 1 1 1 1 2 2

Memorability (Percentage of perceived street) 73% 36% 27% 73% 73% 0% 0% 0% 36% 18% 82% 36% 9% 55% 36% 36%

Serangoon

SEGMENTS

Accuracy (Percentage of perceived street) 36% 9% 9% 36% 64% 0% 0% 0% 36% 18% 73% 27% 0% 0% 9% 9%

Roa d

S1 S2 S3 S4 S5 S6 S7 S8 S9 S10 S11 S12 S13 S14 S15 S16 S17 S18 S19 S20 S21 S22 S23 S24 S25 S26 S27 S28 S29 S30 S31 S32 S33

ConnecƟvity (Number of bus passing through street segment) 10 7 7 6 4 4 4 6 6 8 8 6 0 0 0 2 2 0 9 9 9 9 9 14 14 14 14 0 0 0 0 0 0

Street Width (No. of Lanes)

Memorability ( percentage of perceived streets)

6 6 6 6 4 4 4 4 5 5 4 4 4 4 4 4 2 2 4 4 4 4 4 4 3 3 5 2 2 2 2 2 1

100% 55% 64% 45% 64% 64% 64% 36% 36% 36% 36% 9% 45% 36% 27% 64% 82% 27% 82% 64% 45% 73% 100% 100% 100% 100% 100% 0% 36% 36% 0% 0% 0%

Accuracy (percentage of accurate perceived streets) 82% 36% 36% 27% 18% 9% 9% 9% 18% 18% 18% 0% 18% 9% 9% 45% 55% 9% 45% 36% 27% 64% 100% 100% 100% 100% 100% 0% 0% 0% 0% 0% 0%

Yishun

SEGMENTS Yis hu n

Yishun Ring Road

Ro ad

2 nue n Ave Yishu

Yishun St 11

un St Yish

n hu Yis

JY4 Y19 JY5

Yishun Avenue 5

Rin

Y27 Y28

Y18

ue en Av

Segment

JY6

Y22 JY14 Y23

Y17

JY3 Y5 Y4 JY2 Y8

Y3 Yis hu nA

Y24

Y7 JY7

Y20

ve nu e3

Y25

Y9 Y1 JY1

Y16 JY12

Y12

Y26

Y10

JY13

JY10 Y14

JY9

Y15

Y13

n Ave

JY11

hun

Y29

Y11

Yis

Y21

JY8

ue 2

oad R ing nR Yishu

St 61

un Av en

un Yish

Yis h

JUNCTIONS JuncƟon

Type of JuncƟon

Memorability (Percentage of perceived street)

Accuracy (Percentage of perceived street)

JY1 JY2 JY3 JY4 JY5 JY6 JY7 JY8 JY9 JY10 JY11 JY12 JY13 JY14

2 2 3 2 1 1 1 1 1 1 1 1 1 2

20% 30% 0% 40% 40% 70% 60% 60% 60% 70% 70% 40% 30% 30%

10% 10% 0% 20% 30% 50% 40% 30% 30% 30% 30% 10% 10% 20%

Y1 Y2 Y3 Y4 Y5 Y6 Y7 Y8 Y9 Y10 Y11 Y12 Y13 Y14 Y15 Y16 Y17 Y18 Y19 Y20 Y21 Y22 Y23 Y24 Y25 Y26 Y27 Y28 Y29

ConnecƟvity (Number of bus passing through street segment) 1 1 1 0 0 0 0 3 3 3 3 1 3 1 3 3 2 6 9 14 14 7 7 2 1 2 0 0 1

Street Width (No. of Lanes)

Memorability ( percentage of perceived streets)

2 2 3 3 2 2 2 4 4 4 4 5 4 5 5 5 4 4 5 6 6 4 4 4 4 4 2 2 4

30% 30% 20% 20% 20% 0% 20% 90% 60% 20% 40% 50% 20% 50% 30% 30% 80% 80% 60% 50% 60% 80% 80% 50% 40% 30% 50% 100% 90%

Accuracy (percentage of accurate perceived streets) 10% 10% 10% 10% 10% 10% 0% 70% 10% 0% 70% 80% 20% 30% 30% 40% 40% 50% 50% 100% 90% 30% 10% 10% 10% 20% 30% 30% 20%

Tampines St 43

Tampines Ave 9

7 Ta m pin es

trl

Tampines Ave 6

Segment

Tampines St 42

Tampines St 41

JT14 JT10

T10

T14

JT11

JT15

Tampines Ave 5

T36

JT2

JT16 T16 JT17

T37

JT20

T38

T40 T20 JT21 T21

Tampines Ave 5

T26

T32

JT23 T43

JT24

T25

JT9

T23

T31

JT8

T24

JT25

T44

Tampines MRT T45

T27 Tampines St 32

JT26

T41

T42 JT5

JT7 T6 JT6

T28 JT27

T30 T29

JT4 T4

Ave

JT13

T13

s St pine Tam

JT3

T22 JT22

T17 JT18 T18 JT19 T19

Tampines St 82

T12

T39

T15

JT1

JT12

T11

T35

Tam

pin es

T33

T34

Tam

pines Tam

Tampines St 91

pines

Ave

Tampines St 22

Ave 5 Tampines St 11

JUNCTIONS

JuncƟon JT1 JT2 JT3 JT4 JT5 JT6 JT7 JT8 JT9 JT10 JT11 JT12 JT13 JT14 JT15 JT16 JT17 JT18 JT19 JT20 JT21 JT22 JT23 JT24 JT25 JT26 JT27

Type of JuncƟon 2 1 1 1 2 2 2 1 2 1

1 1 2 2 2 1 2 1 2 2 2 1 2 3 3 3 3

Tampines

SEGMENTS

Sungei Tampines

Memorability (Percentage of perceived street)

Accuracy (Percentage of perceived street)

50% 50% 80% 70% 50% 60% 30% 50% 30% 30% 50% 70% 10% 10% 0% 10% 10% 50% 0% 20% 0% 30% 20% 10% 10% 30% 30%

30% 40% 70% 40% 30% 20% 10% 20% 20% 30% 40% 70% 10% 0% 0% 0% 0% 20% 0% 10% 0% 20% 10% 10% 0% 20% 20%

T1 T2 T3 T4 T5 T6 T7 T8 T9 T10 T11 T12 T13 T14 T15 T16 T17 T18 T19 T20 T21 T22 T23 T24 T25 T26 T27 T28 T29 T30 T31 T32 T33 T34 T35 T36 T37 T38 T39 T40 T41 T42 T43 T44 T45

ConnecƟvity (Number of bus passing through street segment) 7 13 7 7 7 7 7 7 7 3 14 9 9 0 0 8 8 6 6 0 0 7 0 0 2 1 1 0 1 1 1 0 0 0 0 0 0 0 11 0 0 0 0 0 0

Street Width (No. of Lanes)

Memorability ( percentage of perceived streets)

80% 90% 80% 70% 70% 70% 70% 50% 60% 40% 40% 90% 80% 10% 10% 80% 80% 70% 70% 70% 70% 60% 60% 60% 20% 20% 30% 40% 40% 20% 10% 10% 60% 60% 40% 10% 60% 0% 30% 20% 20% 30% 20% 20% 30%

Accuracy (percentage of accurate perceived streets) 70% 70% 60% 60% 50% 30% 30% 20% 20% 40% 40% 60% 60% 0% 0% 10% 30% 30% 10% 20% 20% 20% 20% 10% 20% 20% 20% 20% 10% 10% 10% 0% 10% 30% 20% 0% 40% 0% 30% 20% 0% 30% 20% 0% 30%

9. ANALYSIS Wider and narrower streets Accuracy against number of lanes

120%

100%

100% RÂ˛ = 0.3397

80%

Accuracy

Memorability

Memorability against number of lanes

60% 40%

80% 60%

RÂ˛ = 0.2244

40% 20%

20%

0% 0

Number of Lanes

The scatter plot above shows the relationship between the memorability of the roads and wideness of the streets (measured by the number of lanes). From the graph, we could see that there is a positive correlation between the two, meaning that people tend to remember the street better if it is a wider street, deriving the R2 value of 0.3397. This is possibly because wider streets would also enable people to have a wider perspective of the area and hence they would be able to remember more details of the place. Wider streets are also normally the main roads and hence they would be more prominent and there would be more usage of them before they branch into secondary narrower streets which are not as frequently used by people.

Number of Lanes

The scatter plot above shows the relationship between the accuracy of the streets and wideness of the streets (measured by the number of lanes). From the graph, we could see that there is a positive correlation between the two as well, meaning that people tend to remember the street accurately (in terms of its position and shape) if it is a wider street, derving the R2 value of 0.2244. However, this R2 value is lower than that of the relationship between memorability against number of lanes. This is possibly because people only take note of the existence of the street but due to the different perspectives and perception of the area, they would form a different impression of the angle and shape of the street.

Primary and secondary junctions

Type of Junctions 1: Major-major (Primary) 2: Major-minor 3: Minor-minor (Secondary)

Junctions are an integral part of the street network and they aid in the memory of streets as well. In this analysis, we investigate the memorability and accuracy of each junction with respect to the type of junction. Primary junctions refer to intersections between major roads, while secondary junctions refer to intersections between minor roads. Major roads refer to roads with more than 3 lanes, while minor roads are those with 3 or fewer lanes. Primary junctions are the major decision making points in route choices, as the choice made between the different major streets would have a significant impact on the path taken for the rest of the journey. On the other hand, route decisions made at secondary junctions do not influence the path taken significantly as the various streets lead to the same destination. Therefore, it explains the positive correlation between the memorability and accuracy of each junction with respect to the size of the junction, with primary junctions being better remembered. Although there are positive correlations for both memorability and accuracy, there is a weaker relationship between the accuracy of the junctions with respect to the size of junction, as even though people may know that a junction exists, they may not know the exact position on the map. However, this may be a slightly biased conclusion as the number of each type of junction per site varies, having significantly more primary junctions than secondary ones. This is probably due to the position of each site being located around the MRT station, which would naturally have a larger road width to accommodate the higher traffic volume. 19

Bus routes Memorability against number of bus routes (Yishun)

120%

100%

Memorability (%)

Memorability against number of bus routes (Serangoon)

80% 60% 40% 20%

0% S13 S14 S15 S18 S28 S29 S30 S31 S32 S33 S16 S17 S5 S6 S7 S4 S8 S9 S12 S2 S3 S10 S11 S19 S20 S21 S22 S23 S1 S24 S25 S26 S27 0-4 5-9 10-14

Y27 Y28 Y4 Y5 Y6 Y7 Y1 Y12 Y14 Y2 Y25 Y29 Y3 Y17 Y24 Y26 Y10 Y11 Y13 Y15 Y16 Y8 Y9 Y18 Y22 Y23 Y19 Y20 Y21 0-4 5-9 10-14

Number of buses passing through

The connectivity of The of street street segments segmentsplay playaarole roleininrememremembering street networks. bering networks. The Theconnectivity connectivityofofa astreet streetsegment segment can be be measured measuredby by the the number number of of buses bus passing through it. it. can passing through

Memorability against number of bus routes (Tampines)

Memorability (%)

120% 100% 80% 60% 40% 20% 0% T14 T15 T20 T21 T23 T24 T28 T32 T33 T34 T35 T36 T37 T38 T40 T41 T42 T43 T44 T45 T26 T27 T29 T30 T31 T25 T10 T18 T19 T1 T3 T4 T5 T6 T7 T8 T9 T22 T16 T17 T12 T13 T39 T2 T11 0-4 5-9 10-14

Number of buses passing through

A higher highernumber number of passing bus passing through a segment A of bus through a segment indicated indicates higher connectivity which presents with higher connectivity which presents people withpeople more choices more choices and of destinations and hence increasing the of destinations hence increasing the frequency of possifrequency of possible visits. Sinceremember how well people rememble visits. Since how well people roads correlates ber roads correlates of with the the frequency of visit,of thestreet connecwith the frequency visit, connectivity segtivity of street segments play a role in remembering ments play a role in remembering street networks. street networks. As we can see from the ďŹ gures below, the Minimum and MeAs wepercentage can see fromexistence the figuresofbelow, the Minimum and Median dian the memorability of the segpercentage existence of the segments increases with the number ments increases with the number of bus routes; more people of bus routes; more remembered thebuses streetspassing with morethrough buses remembered the people streets with more passing through them. them.

Serangoon G lobal

Gobal Min Global Max Median

0% 100% 45%

0-4 bus routes

Local Min Local Max Median

0% 82% 36%

5-9 bus routes

Local Min Local Max Median

9% 100% 45%

10-14 bus routes

Local Min Local Max Median

100% 100% 100%

G lobal

Gobal Min Global Max Median

0% 100% 50%

0-4 bus routes

Local Min Local Max Median

0% 90% 40%

5-9 bus routes

Local Min Local Max Median

30% 50% 45%

10-14 bus routes

Local Min Local Max Median

90% 100% 95%

Gobal Min Global Max Median

0% 90% 50%

0-4 bus routes

Local Min Local Max Median

0% 70% 30%

5-9 bus routes

Local Min Local Max Median

50% 90% 70%

10-14 bus routes

Local Min Local Max Median

60% 75% 68%

Yishun

Tampines G lobal

As we can see from the graphs above, there is clear correlation of memorability and connectivity. On the other hand, the correlation between accuracy and connectivity is weak. While visiting an area for transport may remind the user of the particular existence of the street segment, it doe not necessarily require traveling along the segment to get there as an alternative route choice cutting through buildings may be preferred. Also, commuting on the bus would also mean that the responsibility of navigation is lifted off the user and hence the position and shape of the street may be less remembered.

10. CONCLUSION People will remember wider streets better than narrower streets There is a positive correlation between the memorability of streets and the width of streets. Furthermore, there is also a positive correlation to the number of lanes but to a smaller extent. These illustrate the extent of spatial impact of streets to the memorability of a space by an individual. People will remember primary junctions better than secondary junctions There are positive correlations for both memorability and accuracy of junctions. This being said, there is a weaker relationship between the accuracy of the junctions with respect to the size of junction. People will remember streets with more bus services passing through them There is a positive correlation between memorability and connectivity. In relation to this, it is also noted that the correlation between accuracy and connectivity is weak. Hence there are limitations to which we can determine whether the number of bus services would impact memorability.

Limitations Through the survey process we have discovered that people frequently rely on landmarks to aid cognitive mapping. As the emphasis of the mapping survey was on accuracy with respect to position and shape, landmarks were not taken into account. Therefore based on this observation, the analysis of landmarks with respect to mapped routes and mapping accuracy should be further developed. The survey process also did not take into account the different people’s usage patterns of a site. People who frequent bus routes in a neigbourhood are more likely to recall its urban layout differently from people who drive daily. The experiment might be made more specific if distilled to specific user groups to give clearer cognitive interpretation. The practice of cognitive mapping experiments also face inaccuracies in data collection. Survey processes and collected data do not accurately represent a person’s memory, but rather a person’s immediate interpretation of his memory. This highlights a fundamental flaw in the process of quantifying cognitive mapping. 22

11. DESIGN RECOMMENDATIONS Based on Shollâ&#x20AC;&#x2122;s (1996) understanding that travel requires humans to activate two process in facilitating spatial knowledge acquisition. Our design recommendations aim to improve egocentric referencing and the anchoring structure of urban networks. These design recommendations take into account that the urban networks selected for our experiment were sited in housing estates that feature key urban centres with key roads and subsidiary roads. 1. Improving local road hierarchy through street design Firstly, we recommend that a hierarchy to street design could be introduced to such urban networks to improve the imageability of streets, which might subsequently improve cognitive mapping. By implementing differentiated street design approaches to key roads and subsidiary roads, junctions could be perceived more clearly, improving the anchoring structure of the neighborhood. Such street design could include various design features of a street as well as street cross sections. Such design interventions have the potential to impact pedestrian decision-making both in priori and en-route. 1a. Differentiation of streetscape and vegetation along major and minor axes This differentiation could be executed through the implementation of a selected type of vegetation along prominent or major axes or ring roads. A contrasting or differentiated set of vegetation could be used for minor axes. This appeals subtlely to pedestrians imageability of the street through their perception of colour, canopy and shading of different streets. This might improve their spatial understanding by creating clearer transitions at junctions of primary and secondary axes. This might make the number of branches at a junction and their directionality easier to remember. This could be utilized in conjunction with a varied approach to street cross sections. This approach is applied along the East Coast Parkway in Singapore with differentiated vegetation along different lengths of the highway. This differentiation is also found along minor roads of the CBD in Tokyo. 23

1b. Differentiation by street lighting design Similarly, this differentiation can also be implemented by a hierarchy through street lighting design in relation to urban street design. This was prominently used along Yan’an Elevated Road in Shanghai which featured blue neon lights in tandem with the concrete structure to create a dramatic and vivid effect. Neighborhoods such as Serangoon which feature major roads cutting across the site could annotate heavier arteries with distinct lighting qualities. 2. Implement a standardized series of landmarks of similar characteristics across neighborhoods The standardized series of landmarks situated at key junctions or along common way finding routes through the neighborhood could be implemented to improve egocentric referencing and anchoring structure within a neighborhood. 2a. Basic visual indicators at junctions This is inspired by the usage of Obelisks in Rome which indicated prominent piazzas within the city and help to improve city way finding. Similarly, neighborhood junctions can adopt such visual indicators to improve urban configuration to aid people’s cognition. 2b. Hierarchy of commercial centers & sub centers at key junctions Alternatively, this series could also be developed by creating a hierarchy of commercial centers and sub centers within a neighborhood that provide pedestrians visual landmarks to identify with. These commercial centers could be situated at prominent junctions of the neighborhood similar to NEX in Serangoon. This design approach focuses on developing a pattern of centers that are clearly and directly linked. This approach would be strongly reinforced by the human traffic created at commercial centers, which strengthens the junctions nodal characteristics and imageability. 24

12. BIBLIOGRAPHY Cadwallader, M. T. (1976). Cognitive Distance in Intraurban Space. In G. Moore & R. Golledge (Eds.), (pp. 316–324). Strasbburg, Pa: Dowden, Hutchinson, and Ross. Golledge, R., & Garling, T. (2003). Cognitive Maps and Urban Travel. University of California Transportation Center. Lloyd, R., & Heivly, C. (1987). Systematic Distortions in Urban Cognitive Maps. Annals of the Association of American Geographers, 7(2), 191–207. Lynch, K. (1960). The image of the city (p. 194 p.). Cambridge [Mass.]: Technology Press. Mohsenin, M., & Sevtsuk, A. (2013). The impact of street properties on cognitive maps. Journal of Architecture and Urbanism, Volume 37(Issue 4), 301–309. Tampines - Google Maps. (2012, April 1). Retrieved March 29, 2015, from https://www.google.com.sg/maps/place/ Tampines/@1.3476143,103.9575054,16z/data=!4m2!3m1!1s0x31da3d043402eed1:0x8f0792a39afff4cb Yishun Ring Road - Google Maps. (2012, April 1). Retrieved March 29, 2015, from https://www.google.com.sg/maps/place/ Yishun+Ring+Rd/@1.4261791,103.8321465,17z/data=!3m1!4b1!4m2!3m1!1s0x31da146ec123d73f:0x964e8da684d4c341 Serangoon - Google Maps. (2012, April 1). Retrieved March 29, 2015, from https://www.google.com.sg/maps/place/ Serangoon/@1.3578888,103.8694351,16z/data=!4m2!3m1!1s0x31da165509ce5bb3:0x500f7acaedaa610