A Walkability Survey in Hong Kong by Clean Air Initiative for Asian Cities

2010 WALKABILITY IN ASIAN CITIES

A Walkability Survey in Hong Kong

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CONTENTS Page Summary

Acknowledgements

1.0

Introduction

2.0

Objectives of the Study

3.0

Methodology

3.1

Field Walkability Survey

3.2

Selection of field walkability survey areas

3.3

Pedestrian Interview Survey

4.0

Data Collection and Analysis

5.0

Results and Discussion

6.0

Conclusion

7.0

References

8.0

ANNEXURES i.

Field Walkability Survey Form

ii.

Field Survey Data Collection Guidelines

iii.

Field Walkability Survey Area Maps

iv.

Pedestrian Preference Survey Forms (English & Chinese)

Results of the Pedestrian Preference Survey -Mean Test (by Social economic profile) Results of the Pedestrian Preference Survey- ANOVA by Groups Results of the Pedestrian Preference Survey- Traffic Mode Count Frequency Results of the Pedestrian Preference Survey- Single mode of transport (walking) Results of the Pedestrian Preference Survey- Frequency Analysis by Age Groups Results of the Pedestrian Preference Survey- Frequency Analysis by Household Income

vi. vii. viii. ix. x.

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113 141 180 190 200

SUMMARY

A walkability survey was conducted in Hong Kong as a first step towards helping city planners understand scope and extent of existing pedestrian conditions and to identify specific pedestrianrelated shortcomings. The methodology for the survey was taken from The Global Walkability Index (GWI) and Asian Development Bank/ Clean Air for Asian Cities (CAI-Asia) and improved slightly to suit the local situation in Hong Kong. It is found that very few elderly (>60 year old) walk from home for their daily travel and not willing to walk long distance to access a transport. More than fifty percentage of people are satisfied with the existing pedestrian facilities in the city and those who are not happy feel the need of improvements in street lighting; clean, weather proof and wider foot paths; reducing road traffic and speed; removal of obstacles along the walking paths and more crossing points. Elderly prefers to have more ground level crossings as they do not prefer to walk either subways or elevated walkways and are not willing to walk long distance to access the crossing points. They further prefer to have less vehicle traffic on the roads that makes them feel safer and easier to cross the road. Among the nine variables that were evaluated in the field observational survey, walkways in Commercial areas have the best infrastructures and level of service, including provision of facilities for disables. Apart from commercial areas, all other surveyed areas scored very low in the provision of facilities for disables. There are plenty rooms for improvements in this aspect in majority areas of Hong Kong.

ACKNOWLEDGEMENTS

This study is supported by the Hong Kong Polytechnic University under Clean Air and Blue Skies Project- Phase II, Clean Air Initiatives for Asian Cities (CAI-Asia). We would like to extend our sincere gratitude to Christine Lee for her immense support from the very beginning of the study to the end. We also like to appreciate Bert Fabian, Glynda Bathan and all the members from Clean Air Initiatives for Asian Cities (CAI-Asia). Lastly, a special thanks to the students of Polytechnic University for conducting the surveys.

1.0 INTRODUCTION In the conventional transportation planning practices suggest that personal motor vehicle travel is far more important than walking, representing about fifty times as many person-miles as nonmotorized travel. From a conventional planning perspective, walking (the activity) is a minor mode of travel, and walkability deserves only modest public support. However with the rapid urban air pollution, in modern sustainable mobility management strategies walking is becoming a major green transportation mode among all the developed and developing countries. The many research studies, found that Social and physical environmental factors are influence and correlates with walking behaviors of the people. Walking is the physical activity behavior that is currently the main focus of environmental and policy initiatives in public health (Owen et al, 2004). Different agencies and personnel have developed several methodologies to assess walkability in locations and cities during past decades. But due to lack of relevant data, those indexes did not able to capture the issues related to pedestrian infrastructures (Eva, et al, 2007). This GWI was developed by Holly Krambeck, a Master‟s Degree Candidate, of Massachusetts Institute of Technology and sponsored by the World Bank. The CAI ASIA Center, Philippines initiated this assessment of GWI among the Asian cities during last few years. So far, this GWI has been conducted as a pilot studies in the Asian cities of Karachchi, Bangkok, Manila, etc. A pilot study was carried out prior to the actual surveys, and we made some improvements in the original survey methodologies in order to suit the local situation and with the objective of future cross country comparisons. In this end we selected the GWI methodology to assess walkability related issues in the major cities of Hong Kong. The GWI methodology comprises mainly three components, namely the Field Walkability Survey, the Pedestrian Interview Survey and the Government/Stakeholder Survey. However only the Field Walkability Survey and the Government/Stakeholder Survey results will use to calculate GWI and Pedestrian Interview Survey is conducted to find out the overall perception of Hong Kong pedestrian facilities, travel behaviors with socio economic backgrounds and their opinions and expectations about the development of existing pedestrian facilities. The „walkability‟ of a community may be conceptualized as the extent to which characteristics of the built environment and land use may or may not be conducive to residents in the area walking for either leisure, exercise or recreation, to access services, or to travel to work (Eva et al, 2007). There are many definitions and ways to consider “walkability”. It can be simply define as the overall support for pedestrian travel in an area. But, although a significant number of trips are made by foot in developing cities, pedestrian infrastructure, amenities, and services are often neglected in municipal planning and budgets (Fang 2005). Because the most developing countries cities do not make pedestrian planning a priority and there are few incentives for them to do so. Therefore the major rationale behind the walkability is assessment of the quality of the walking facilities available in the cities. In this regard the Walkability Index comprises of three components: safety and security, convenience, and degree of policy support. The expectations from these components are to determine the relative safety and security of the walking environment, to reflect the relative convenience and attractiveness of the pedestrian network and to find out the degree to which the municipal government or policy supports improvements in pedestrian infrastructure and related services accordingly. 4|Page

2.0 OBJECTIVES OF THE STUDY The main objective of the conducting the walkability index survey in Hong Kong is to identify specific pedestrian-related shortcomings, and recommendations for next steps to improve pedestrian conditions and provide city officials with an incentive to address walkability issues. The Global Walkability Index (GWI) is a comparative study which to rank cities across the world based on the safety, security, and convenience of their pedestrian environments that helping city planners understand the scope and extent of local pedestrian conditions relative to other cities. Therefore this would be a positive step towards improving the quality of the pedestrian environment. Specifically, the study aims to: 1. Generate awareness of walkability as an important issue in developing cities; 2. Help city planners understand scope and extent of local pedestrian conditions, relative to other cities. 3. Understand pedestrian opinion on existing pedestrian facilities in the city.

3.0 METHODOLOGY 3.1 Field Walkability Survey After studying of the Global Walkability Index (GWI) development report of Holly Krambeck, CAI ASIA/ADB and World Bank guidelines on walkability surveys we conducted 5-6 pilot field surveys in selected stretches (Whampoa Garden, Nathan Street, etc). The main objective of this survey was got familiarized and to do field testing of the ratings system provided by CAI ASIA/ADB and World Bank for different levels of services (LOS) in pedestrian walkways (Annex1) prior to the actual survey began. According to the actual field observations and experience obtained through the pilot surveys it was decided to change the field survey rating descriptions and examples to well suit with the local condition in Hong Kong. The Hong Kong field walkability survey rating description was developed considering both of the CAIASIA/ADB and World Bank rating description and no any significant changes were made and used same field walkability suvey form for the data collection (Annex 1 & 2).

3.2 Selection of field walkability survey areas According to the GWI guidelines the field observational surveys are to be carried out in the areas such as commercial, residential, educational, public transport terminals etc. However, in Hong Kong has mixed land use types and difficult to demarcate as commercial, residential, educational center. Therefore to have a good representation ten (10) biggest centers of attraction in six types of land use mixes in urban areas like housing state, educational center, public transport terminals were 5|Page

identified and the most popular commuting pedestrian routes at each of these ten locations were selected. At least two routes at each location were surveyed. The centers and the survey routes were then traced out using Google map for reference (Annex 2). The pilot field survey was conducted in the selected areas prior to the real survey to find out if the routes selected from the map represent the actual situation. After the pilot survey, some routes which were not often used by the pedestrian were discarded and selected another most commuting route for the survey. Similar changes were done for the other areas as well. The students from Polytechnic University conducted survey in ten areas which were later categorized into six different area types. The following table 1 shows the name of the top ten centers of attraction and the area type.

Table 1: Field observational surveys areas S.N.

Name of the Area

Area Type

Whampoa Garden

Residential Area

Parc Oasis

Hong Kong cultural center

Hong Kong Convention and Exhibition Center

Kwung Tong

Industrial Area

Ladiesâ&#x20AC;&#x;s Street

Shopping Area

Fa Yuen Street

Temple Street

Hong Kong Central Library

Commercial Educational Area

Baptist University

Residential Educational Area

Commercial Area

3.3 Pedestrian Interview Survey Interviewer administrative questionnaire survey was carried out with random sampling for 1029 students/workers at selected busy streets to identify the pedestrian preference in Hong Kong. A questionnaire was designed to find out the overall perception of Hong Kong pedestrian facilities and travel habit. Demographic information was also ascertained for statistical analysis purposes. A pilot study was carried out in the Polytechnic University premises using CAI ASIA/ADB questionnaire prior to the actual survey, and necessary changes in the questionnaire were made accordingly to suite to the local situation. The questionnaire was first written in English and later translated to Chinese (Annex 3). Interviewers distributed the questionnaires and conducted face to face interviews for two weeks from 16th to 30th January 2010 at selected location. The following table 2 shows the work schedule and venue of the pedestrian interview survey. 6|Page

Table 2: Pedestrian interview work schedule

Day

Location

Day

Location

Sun Yuen Long Centre

Tai Po Uptown Plaza

Sun Yuen Long Centre

Sha Tin Town Centre

Hung Hom Railway Station

Causeway Bay

Tsim Sha Tsui

Causeway Bay

Mong Kok

Central

Mong Kok

Central

Mong Kok

Central

Sha Tin Town Centre

4.0

DATA COLLECTION AND ANALYSIS

The pedestrian interview survey involves designing a questionnaire to find out the people‟s perception of pedestrian facilities. The survey, was targeted the workers and students as potential interviewees. By reference to the statistical report (Hong Kong Census and Statistics Department annual reports 2009), there were 3, 497, 000 active workers and 478, 173 students. We decided to use simple random sampling method for the survey. In pilot study, 48 samples were obtained and the maximum variance of questions in the questionnaire was 1.2642. After calculation, around 1030 samples were needed for estimating the population mean with a bound on the error of estimation equals to 0.07. The calculation of sample size can be reference to the following equation. n

 2N B2 ( N  1)  2 4

Where n = sample size = the variance of question in questionnaire N = the population size B = bound on the error of estimation 1029 pedestrians (students/workers) at selected busy streets were interviewed. Data were then entered into statistical software SPSS for analysis. Normality and logical test were applied for initial testing. The details of the analyzed results are shown in Annex 4. 7|Page

The field walkability survey is an observational survey which involves the assessment on the availability and quality of pedestrian infrastructure along selected pedestrian routes. Observers are required to rank nine different variables from 1 to 5. These variables are briefly explained in the table 3 below.

Table 3: Levels of Services for Pedestrians Variables

Description

Walking Path Modal Conflict Availability of Walking Paths( Maintenance and Cleanliness)

Pedestrians mix with other modes, such as bicycles, motorcycles, or cars. with

Clean, pleasant and convenient paths are important for pedestrians.

Availability of crossings

Ideally, crossing opportunities should be at least every 300 meters to be considered acceptable otherwise when there are no opportunities provided for crossing streets, pedestrians tend to jaywalk, increasing their risk of injury or harm.

Grade Crossing Safety

Exposure to other modes, Exposure time, and the degree to which sufficient time is allocated for pedestrians to cross at signalized intersections are three important factors to consider when evaluating how safe it is to cross the street.

Motorist Behavior

The degree to which cities can manage motorist behavior will largely impact the safety of the pedestrian environment.

Amenities

Pedestrian amenities, such as benches, street lights, public toilets, and trees greatly enhance the attractiveness and convenience of the pedestrian environment, and in turn, the city itself.

Disability Infrastructure

Disability Infrastructure typically services all pedestrians, not just those who are disabled. For wheelchair access, effective walking path width should be, at a minimum, 1 meter wide.

Obstruction

Permanent obstructions (e.g., telephone poles or tress placed in the center of the walking path), are typically the results of insufficient or ineffective urban design guidelines. All obstructions, to some degree, impact effective width and thus should be regulated.

Security from crime

This parameter is important in assessing to what degree are the walking paths, pedestrian bridges, and pedestrian subways perceived to be secure from crime (pick-pocketing, mugging, unprovoked attack, etc)

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5.0

RESULTS AND DISCUSSION A. Pedestrian Preference Survey Results

We found that almost 39 percent of daily trips are made entirely on foot, and of the almost 61 percent of the commuters who use different modes of public transport, a large percentage walk some or large part of their daily commute. (Figure1)

Figure 1: Percentage of people walking and using other transport modes

The willingness of people to walk is largely dependent on travel distance and time. When the travel distance and time is greater most people are less willing to walk and they tend to take other convenient modes of transportation. It is evident that more than 60 percent are willing to walk for a shorter distance and time. (Table 4) Hong Kong has a comparatively larger proportion of population willing to walk comparing to other cities. In Karachi about 21 percent of the people walk daily despite inadequate pedestrian facilities (Karachi, 2009) and only about 18.1 percent walk in Kathmandu (Kathmandu Valley Mapping Program (KVMP), 2001). Average Travel Distance

Frequency

Percent

Average Travel Time

Frequency

Percent

< 6 km

60.3

< = 30 min

62.7

6-9 km

6.3

31-45 min

23.8

9-12 km

7.1

46-60 min

7.9

12-15 km

4.8

61-75 min

1.6

> 15 km

21.4

76-90 min

1.6

> 90 min

2.4

Total

126

100.0

Total

126

100.0

Table 4: Willingness of people to walk

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However, the recent study conducted by the Clean Energy Nepal (CEN)/Clean Air Network Nepal (CANN) to 305 pedestrians in Kathmandu showed that 88.9 percent of commutersâ&#x20AC;&#x; daily trips are made entirely on foot. About 45.8 percent of the pedestrians in Kathmandu feel that the situation of existing pedestriansâ&#x20AC;&#x; facilities in the city is in its worst condition (Cabrido Charina, 2010). Mumbai has 55% of its population walking regularly. The study of 30 Indian cities shows that on an average, almost 40% of all trips in urban India still do not involve motorized vehicles. (Pandit A, Bhasin R & Suri M, 2009). Also according to the walkability survey completed in Colombo in March 2010 by the University of Moratuwa, 21% of the pedestrian feel that the pedestrian facilities in Colombo is in fair while 16% think the facilities are good. Only 16% of the respondents feel that the existing facilities are not good and only 4% feel that the facilities in the city is in its worst condition. However 44% of the survey respondents are willing to shift from walking to other mode of transports. Table 4 illustrates that many people would like to see improvements in walkways, i.e., to remove obstacles, have wider and leveled footpath; have easy access for disables and reduced vehicle traffic. In fact, the survey results show that 30 percent have a stronger desire to shift from walking to other transport modes if no improvement is made to the pedestrian facilities.

Figure 2: Willingness of people to shift from walking to other modes

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Rank

Easy access

Improved street lighting

Wider footpaths

Level footpaths

Clean sidewalks

Reduced traffic

Reduced speed

Remove obstacles

More crossing pt

Weather proof

113

162

243

152

161

142

170

224

140

104

141

325

396

305

367

312

336

435

357

324

304

297

204

338

312

298

287

200

305

349

270

175

194

129

232

174

198

207

211

Table 5: Pedestrians major preferences of walking facility improvements; Rank 1= Least Wanted; Rank 5= Most wanted

Majority of people who are travelling on MTR and Bus are travelling for more than 15 km but their average travel time is less than 30 minutes. This somehow reflects that people who travel on a more expensive mode like MTR/Car/Taxi/Bus have shorter travelling than walking. (Figure 3 and 4)

Figure 3: Travel distance of people with respect to traffic modes

Beyond travel distance, travel time & pedestrian facilities, other factors like household income & transport cost is also important in determining why people walk. Economically and socially disadvantaged people tend to rely heavily on walking for transport (Victoria Transport Policy Institute). In developing cities walking is often considered in terms of providing mobility for the poorest residents. But a different scenario is observed in the case of Hong Kong. From the survey result a same number of both low and high income people walk. However, a larger population of high income group is found to be travelling in a car/taxi than the low income people. (Figure 4)

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Figure 4: People choice of transport mode with respect to their household income

Cross Relationship Walking and travelling in MTR is a major combination of daily commute for majority of Hong Kong people. The decision to selection of transport modes are mainly based on the socio economic factors in the society. The availability of facilities and conditions of walkways, travel distance and travel time also influence on those decisions making process of the pedestrians. The analysis of the single mode of transport shows walking is the major mode of transport for poor and middle income groups in Hong Kong (Figure 5). And majority of the respondents (about 66%) do not own any kind of vehicle while 15% own a car and this gives a reflection of peoplesâ&#x20AC;&#x; willingness to walk. Saelens et al. (2003), also argue that the choices to use motorized or nonmotorized transport are based on the proximity (distance) and connectivity (directions of travel) between trip origin and destination. Walking has to compete with other modes of travel and may be a particularly disadvantaged choice with respect to travel distance. The relative utility of walking relative to other modes of travel drops off quickly as distances between destinations increase (Frank, 2004). Figure 5: Major transport mode of the income categories Figure 6: Type of vehicle own by the survey respondents

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Figure 7: Major mode of transport by age Groups

The travel behaviors change according to the gender, age, socio-economic status and other environmental factors. It is unclear whether the relationship between the built environment and physical activity varies by socio-demographic profile. The physical activities of the women and men also correlate with other environmental factors, neighborhood factors and safety, (Foster et al. (2004); Bengoechea G., et al. (2005); Suminski et al. (2005)). As per the results from the single transport mode, walking is a major mode of transport for almost all age groups except for the age group between 16 to 30 years (Figure 7). More male respondents walk in comparison to females and no significant preference in walking is found between them. However there is a significant mean difference occurs in their choice of transport modes, male prefers to travel by bus while female prefers to travel by two-wheelers. From the chi-square co-relation between gender and willing to walk to access crossing, male respondents are willing to walk for shorter distance than females (Table 6 & 7). Also the majority of the people (no different in gender) believe that they are most exposed to the air pollution while waiting for the transportation and walking. The result is significant at .05 levels. Tan et al. (2007) also points out that pedestrian comfort may reduce because of the pollution produced by the vehicles. However, when vehicle traffic volume is little or the speed is low, pedestrian may feel that the vehicles are not minatory and the road environment can be comfortable. Table 6 &7:- Gender willingness to walk to access crossing Value

Asymp. Sig. (2sided)

Pearson Chi-Square

19.464

.003

Likelihood Ratio

20.017

.003

Linear-by-Linear Association

0.020

.887

N of Valid Cases

1019

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Willing to walk to access crossing 101150 m

<=50 m

51-100 m

151200 m

201250 m

Male

258

161

Female

180

162

Total

438

323

123

The majority of the people are willing to walk if the average travel time is less than 45 minutes or the average travel distance is less than 3km. Also it is interesting to see that the young people of age category between 16-30 years old are significantly demarcated from other age groups in their willingness to walk; and they want less traffic on the road to improve walkability. The major transport mode of the low and middle household income groups in Hong Kong is walking and their average travel distance is more than 15 km. However there are a considerable percentage of high income people who also walk in their day to day activities. Ross et. al (2000) found that residents of socially disadvantaged neighborhoods, both men and women, walked more than those in advantaged neighborhoods, despite feeling less safe from crime. It is found that there is a stronger co-relationship between income and the major mode of transport. With the increase of household income the major mode of transport changes from walking to non walking mode. The major mode of transport of poor people (<4000HK$) is walking and shift to two wheelers with the increase of income to HK$4000-HK$15999. The major modes of transport of higher income groups with HK$28,000-HK$39,999 and >HK$40,000 are minibus and car/taxi. Based on the mean test analysis (Annex 4), all age groups prefer to have more crossing points. Elderly people (>60 years) and the age groups between 31-45 years old are not willing to walk for greater distance for crossings in comparison to other age groups of 46-60 years. Majority of the respondents, i.e., more than 73% prefer ground crossings. One of the key factors affecting walkability in Hong Kong is the design of pedestrian crossings and thus crossing time. In general the road crossings in Hong Kong are located conveniently in comparison to other countries. But due to some inconvenience in crossing, pedestrians tend to jay-walk. The study results show that the likelihood of a pedestrian using ground crossing is affected by two factors: high traffic flow and traffic speed on the road. The footbridges over busy streets are to keep pedestrians from interfering with motor vehicles rather than to create convenience for pedestrians. The timing of traffic lights also appears to facilitate the movements of vehicles more than for people (Lai Poh et al, 2009). The result also illustrates that there is a significant relationship between the level of pedestrian facilities in the city (good/bad) and willingness to walk to access crossings. According to the socio-economic data the middle and lower income people are willing to walk greater distance to access the crossings points. According to the Post Hoc test results of ANOVA there is a significant effect of 10 major road improvements on improving walkability in the city at p<0.05 level for three conditions [F(9, 10213) = 48.94, p = 0.000]. A further analysis of the means of the significant variables with post-hoc tests is conducted to determine the nature of the effect of different variables on walkability. According to the results the wider foot paths, clean sidewalks, removal of obstacles and more crossing points are the most desirables to improve walkability in terms of mean improvement. The weather proof, reduced traffic, leveled foot paths and easy access for disables are also significantly correlated with the wider foot paths.

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Figure 08: Major pedestrian improvements need in Hong Kong

B. Field Survey Results The field survey conducted in ten centers of attraction are categorized into six different land use types covering 24 road stretches and a total length of 11.9 kilometers (Figure 09). The pedestrian density is calculated using pedestrian count per hour and per meter width of the pedestrian walkways. The survey result shows that Shopping areas (Fa Yuen Street, Ladies Street and Temple Street) have the highest pedestrian density (around 1300) in comparison to other areas. Residential areas (Whampoa Garden and Parc Oasis) on the other hand have comparatively low (around 150) pedestrian density. (Figure 10)

Figure 09: Length on surveyed road stretch in Kilometers

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Figure 10: Pedestrian density in different surveyed areas

Among the six surveyed types of areas, the presence of amenities is high in Commercial and Residential areas. The areas are less secure from crime due to high pedestrian flow. In terms of walking path model conflict, it is seen that some conflicts in the Shopping and Industrial areas that make walking possible but not convenient. The grade crossing safety in Industrial area (Kwun Tong), Shopping areas (Ladiesâ&#x20AC;&#x;s Street, Fa Yuen Street, Temple Street), Commercial Educational area (Hong Kong Central Library) and Residential Educational areas (Baptist University) gain low scores. The grade crossing safety is dependent on three important factors such as exposure to other modes, exposure time, and whether sufficient time is allocated for pedestrians to cross the road. In Hong Kong, time allocated for the pedestrians to cross at signalized intersections seems to be less sufficient for the elderly persons and persons with disabilities. The results also show that obstructions occur most frequently in the Shopping and Industrial areas. The obstruction in the walking paths often create cumbersome mainly for the elderly persons and persons with disabilities. Permanent obstructions (e.g., telephone poles or trees placed in the center of the walking path), are typically the results of insufficient or ineffective urban design guidelines. Unwelcome temporary obstructions (e.g., parked cars) are often the results of insufficient or ineffective public space policy. Welcome temporary obstructions (e.g., vendors, sidewalk cafes) should be allocated space such that they both enhance the pedestrian environment without restricting the effective width of walking paths. The survey results also indicate that disability infrastructure typically services all pedestrians, not just those persons with disabilities. For example, curb ramps are convenient not just for wheel chair access, but also for persons with baby pushchairs, shopping carts, or luggage.

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Old people and persons with disabilities are most vulnerable to crimes (pick-pocketing, mugging, unprovoked attack, etc). The results from the field survey show that Shopping areas and Industrial areas are less secure from crime as the area are often crowded. These areas need improvement in the effective walking width so that they are less crowded and feel more secure and safe. Figure 11: Scores of six areas by variables

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6.0 CONCLUSION Based on the pedestrian interview survey results, almost 39 percent of daily trips are made entirely on foot in Hong Kong. 70 percent of the people are willing to walk with the existing pedestrian facilities; however 30 percent have a stronger desire to shift from walking to other transport modes if no improvements made in the pedestrian facilities. They want city to improve street lighting, clean and wider foot paths, reduce traffic and speed; removal of obstacles from walkways, more crossing points and weather proof sidewalk. These factors are very important in determining pedestriansâ&#x20AC;&#x; decision to shift from walking to other modes if no improvements are done. MTR is their first choice of other transport mode if they shift from walking. About 66 percent of the respondents do not own any kind of vehicle and the major transport mode for most people are walking, MTR and Bus. Walking is the major transport mode for low and middle income groups but there are a considerable percentage of high income people who also walk in their daily commute. Male respondents are found to be walking more in comparison to females and middle aged people between 16-30 years old are significantly demarcated from other age groups in their willingness to walk. Many people believe that they are most exposed to the air pollution while waiting for the transportation and walking. From the field survey results, Commercial areas gain high scores in terms of the most variables that were evaluated and Industrial area gain low scores. Residential, Residential Educational, Commercial and Commercial Educational areas gain high scores in availability of walking paths, positive motorist behavior, less obstructions and security from crime but these variables gain low scores in Industrial area. Shopping areas though have the highest pedestrian density; these areas obtain low scores in grade crossing safety, motorist behavior, obstructions and security from crime. Also, infrastructures for disables are given less priority in Shopping, Industrial and Residential Educational areas but are given high attention in Commercial areas.

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7.0 REFERENCES 1. Litmen, T.A, (2009), Economic Value of Walkability, Victoria Transport Policy Institute, USA 2. Saelens BE, Sallis JF, Frank LD (2003) Environmental correlates of walking and cycling: Findings from the transportation, urban design, and planning literatures. Annals of Behavioral Medicine 25(2):80-91 3. Sallis JF, Frank LD, Saelens BE, Kraft MK (2004) Active transportation and physical activity: opportunities for collaboration on transportation and public health. Transportation Research Part A, 38:249-268 4. Eva Lesliea, Ester Cerinb, Lorinne duToitc, Neville Owenc and Adrian Baumand (2007), Objectively Assessing ‘Walkability’ of Local Communities: Using GIS to Identify the Relevant Environmental Attributes, 5. Billie Giles-Corti, and Robert J. Donovan, (2003), Relative Influences of Individual, Social Environmental, and Physical Environmental Correlates of Walking, Vol 93, No. 9, American Journal of Public Health 1583-1589 6. Holly Krambeck, THE GLOBAL WALKABILITY INDEX:TALK THE WALK AND WALK THE TALK 1, Master‟s Degree Candidate (February 2006) Massachusetts Institute of Technology Dept. of Civil and Environmental Engineering & Dept. Urban Studies and Planning, Cambridge, Massachusetts, USA. 7. Karachi (2009), A Preliminary survey of Pedestrian Infrastructure in four areas of Karachi / http://www.cleanairnet.org/caiasia/1412/articles-60499_Arif.pdf) 8. Cabrido Charina, (2010), Walkability in Asian Cities: Assessment of Pedestrian Infrastructures and Services in Four Areas of Kathmandu City. 9. Pandit A, Bhasin R, Suri M (2009)/ http://timesofindia.indiatimes.com/city/ahmedabad/Ahmedabad-2nd-in-walkabilityindex/articleshow/5058499.cms 10. McFadden, D.L., (1978), Quantitative methods for analyzing travel behaviour of individuals: some recent developments. In: D. Hensher and P. Stopher, eds. Behavioural travel modelling. London: Croom Helm, pp: 279–318. 11. Frank, L.D., (2004), Economic determinants of urban form: resulting trade-offs between active and sedentary forms of travel. Am. J. Prev. Med. 27 (3S), pp: 146–153. 12. Ross, R., Freeman, J.A., et al., (2000), Exercise alone is an effective strategy for reducing obesity and related comorbidities. Exerc. Sport Sci. Rev. 28 (4), pp: 165–170. 13. Foster, C., Hillsdon, M., et al., (2004), Environmental perceptions and walking in English adults. J. Epidemiol. Community Health 58 (11), pp: 924–928. 14. Bengoechea, G., Spence, E., et al., (2005), Gender differences in perceived environmental correlates of physical activity. Int. J. Behav. Nutr. Phys. Act. 2, 12. 15. Suminski, R.R., Poston, W.S., et al., (2005), Features of the neighborhood environment and walking by U.S. adults. Am. J. Prev. Med. 28 (2), pp 149–155. 16. Lai, P.C., Wong, M., Chan, M.H., Wong, W.C., Low, C.T., (2009), An ecological study of physical environmental risk factors for elderly falls in an urban setting of Hong Kong, Science of the Total Environment, 407, pp 6157–6165 17. Parker, M.J., Twemlow, T.R., Pryor, G.A., (1996), Environmental hazards and hip fractures., Age Ageing, 25(4), pp: 322–325.

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18. Southworth, M., (2005), Designing the walkability city. J Urban Planning Development, 131(4), pp: 246â&#x20AC;&#x201C;257. 19. Ayres, T.J., Kelkar, R., (2006), Sidewalk potential trip points: a method for characterizing walkways. Int J Ind Ergon, 36, pp: 1031â&#x20AC;&#x201C;1035. 20. TAN, D., WANG, W., LU, J., BIAN, Y., (2007), Research on Methods of Assessing Pedestrian Level of Service for Sidewalk, Journal of Transportation Systems Engineering and Information Technology, Volume 7, Issue 5

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ANNEX 1 WALKABILITY IN ASIAN CITIES

FIELD SURVEY City:

Survey Area Name

Direction (L/R)

Area Type

Peak Hour

Yes

Survey Team Names

Surveyed Road Stretch 1.

Walking Path Modal Conflict

Availability Of Walking Paths (with Maintenance and Cleanliness)

Availability Of Crossings

Grade Crossing Safety

Motorist Behavior

Amenities

Disability Infrastructure

Obstructions

Security from Crime

10. Pedestrian count 11. Length of surveyed stretch (Km) General Description of Area

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Rough Sketch

ANNEX 2 Field Survey Data Collection Guidelines (Hong Kong) 1. Walking Path Modal Conflict Rating Description 1. Significant conflict walking impossible

Example that

makes

Significant conflicts that makes walking possible, but dangerous and inconvenient.

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Some conflict â&#x20AC;&#x201C; walking is possible, but not convenient

Minimal conflict, mostly between pedestrians and non-motorized vehicles

No conflict between pedestrians and other modes

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2. Availability of Walking Paths (with maintenance and cleanliness) Rating 1

Description Pedestrian walkways required but not available

2 Pedestrians Walkways available but highly congested , badly maintained and not clean

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Example

Pedestrians Walkways available but congested , needs better maintenance and cleanliness

Pedestrians Walkways available which are sometimes congested and are clean and well maintained

Pedestrian Walkways not required as people can safely walk on roads

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3. Availability of Crossings (Count the number of crossings available per stretch) Rating Description 1. Average distance of controlled crossings/subway/sky walk way is greater than 500m and average speed is high

Average distance of controlled crossings/ subway/ sky walk way is between 500-300m and average speed is around 40 Kmph

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Example

Average distance of controlled crossings/subway/sky walk way is between 200-300m and average speed is 20-40 Kmph

Average distance of controlled crossings/subway/sky walk way is between 100-200m and average speed is 20-40 Kmph

There is no need of controlled crossings/subway/sky walk way as pedestrians are safe to cross wherever they like and vehicles and pedestrians coexist

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4. Grade Crossing Safety ( Exposure to Other Modes and Exposure Time, available and required - If the other modes donâ&#x20AC;&#x2122;t stop to allow you to walk or they keep moving as you run etc...) Rating Description Example 1 There are significant risk of accidents due to no pedestrians has sufficient time to cross, tend to jay walk extremely long waiting periodmore than 60 seconds, crossing time less than 20 seconds

Dangerous-Relatively long waiting time and pedestrians faces some risk of being hurt by other modes and barely enough time for most people, insufficient for elderly

Difficult to ascertain dangers posed to pedestrians, sufficient time for most pedestrians to cross, not quite enough time for elderly crossing time between 20-30 seconds

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Safe- pedestrian is mostly safe from accident with other modes, reasonable waiting period 10-20 seconds and enough time for elderly to cross- crossing time more than 20 seconds

Very Safe- Other modes present no danger to pedestrian

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5. Motorist Behavior Rating Description 1 High traffic Pedestrians

Example disrespect

Traffic disrespect and rarely pedestrians get priority

Motorists sometimes yield

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Motorists usually obey traffic laws and sometimes yield to pedestrians

Motorists obey traffic laws and almost always yield to pedestrians

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6. Amenities (lighting, rain proof, cover/shade, hawker exclusive zones, resting place/benches etc.) Rating Description 1 No Amenities

Little amenities at some locations

Limited number of provisions for pedestrians

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Example

Pedestrians provided some good amenities for major length

Pedestrians have excellent amenities such as lighting, cover from sun and rain making walking a pleasant experience

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7. Disability Infrastructure (Footpath should be at least 1m Wide, facilities available for smooth & convenient movement, directions for disability facilities, etc) Rating Description Example 1 No infrastructure for disabled people is available

A limited infrastructure for disabled persons is available for major length and significant inconvenience due to poor construction.

Infrastructure for disabled persons is present but no directions and also it is too far from the existing walking paths

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Infrastructure for disabled persons is present in good condition, but poorly constructed and mild difficult to use.

Infrastructure for disabled persons is present, in good condition, and well placed.

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8. Obstructions Rating 1

Description Pedestrian infrastructure is completely blocked by permanent obstructions

Pedestrians are significantly inconvenienced. Effective width <1m.

Pedestrian traffic is mildly inconvenienced; effective width is < or = 1 meter.

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Example

Obstacle presents minor inconvenience. Effective width is > 1m

There are no obstructions

9. Security from Crime Rating Security when walking – do you feel safe from external elements? Rating

Description

1 2 3 4 5

Environment feels very dangerous – pedestrians are highly susceptible to crime Environment feels dangerous – pedestrians are at some risk of crime Difficult to ascertain perceived degree of security for pedestrians Environment feels secure – pedestrians at minimal crime risk Environment feels very secure – pedestrians at virtually no risk of crime

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ANNEX 3- Field Walkability Survey Area Maps 1. Whampoa Garden Section 1: Whampoa Garden Site 3 Blk 8 to Hung Hom MTR station exit B1 0.8 km â&#x20AC;&#x201C; 10 mins

http://maps.google.com.hk/maps?f=d&source=s_d&saddr=%E4%B8%8D%E7%9F%A5%E5%90%8D%E7%9A%84%E9%81%93%E 8%B7%AF&daddr=22.304135,114.183097&hl=zhTW&geocode=FQRVVAEdXlvOBg%3B&mra=dme&mrcr=0&mrsp=1&sz=17&dirflg=w&sll=22.304661,114.186015&sspn=0.004725,0. 009602&brcurrent=h3,0x340400ddfd685b6f:0xa2dcb7a8a243b328,,0x340400d4376c85e1:0xcab6faa04b58a8a7&ie=UTF8&z=17

Section 2: Whampoa Garden Site 3 Blk 8 to Whampoa Garden Bus Terminal 0.5 km -7 mins

http://maps.google.com.hk/maps?f=d&source=s_d&saddr=%E4%B8%8D%E7%9F%A5%E5%90%8D%E7%9A%84%E9%81%93%E 8%B7%AF&daddr=22.304632,114.190564&hl=zhTW&geocode=FQRVVAEdXlvOBg%3B&mra=dme&mrcr=0&mrsp=1&sz=17&dirflg=w&sll=22.304661,114.186015&sspn=0.004725,0. 009602&brcurrent=3,0x340400ddfd685b6f:0xa2dcb7a8a243b328,0,0x340400d4376c85e1:0xcab6faa04b58a8a7&ie=UTF8&ll=22.30 4572,114.190553&spn=0.004725,0.009602&z=17 39 | P a g e

Section 3: Whampoa Garden Site 3 Blk 8 to Hung Hom Complex 0.5 km â&#x20AC;&#x201C; 6 mins

http://maps.google.com.hk/maps?f=d&source=s_d&saddr=%E4%B8%8D%E7%9F%A5%E5%90%8D%E7%9A%84%E9%81%93%E 8%B7%AF&daddr=%E5%B7%AE%E9%A4%A8%E9%87%8C&hl=zhTW&geocode=FQRVVAEdXlvOBg%3BFQZhVAEdaFvOBg&mra=dme&mrcr=0&mrsp=1&sz=18&dirflg=w&sll=22.306572,114.18787 7&sspn=0.002362,0.004801&brcurrent=3,0x340400ddfd685b6f:0xa2dcb7a8a243b328,0,0x340400d4376c85e1:0xcab6faa04b58a8a 7&ie=UTF8&ll=22.305594,114.189459&spn=0.004725,0.009602&z=17 40 | P a g e

Section 4: Whampoa Garden Site 3 Blk 8 to Ferry Pier 0.5km â&#x20AC;&#x201C; 6 mins

http://maps.google.com.hk/maps?f=d&source=s_d&saddr=22.304036,114.186895&daddr=%E4%B8%8D%E7%9F%A5%E5%90%8D%E7%9A%84 %E9%81%93%E8%B7%AF&hl=zhTW&geocode=%3BFfZKVAEdL2bOBg&mra=dme&mrcr=0&mrsp=0&sz=17&dirflg=w&sll=22.302944,114.189137&sspn=0.004725,0.009602&brcu rrent=3,0x340400ddfd685b6f:0xa2dcb7a8a243b328,0,0x340400d4376c85e1:0xcab6faa04b58a8a7&ie=UTF8&ll=22.302934,114.189749&spn=0. 004725,0.009602&z=17 41 | P a g e

2. Hong Kong Cultural Centre/ Hong Kong Space Museum Section 1: Hong Kong Cultural Centre/ Hong Kong Space Museum to Tsim Sha Tsui MTR station exit F 0.3 km â&#x20AC;&#x201C; 4 mins

http://maps.google.com.hk/maps?f=d&source=s_d&saddr=%E6%A2%B3%E5%A3%AB%E5%B7%B4%E5%88%A9%E9%81%93&d addr=22.295728,114.172186&geocode=FSMwVAEdsxrOBg%3B&hl=zhTW&mra=dme&mrcr=0&mrsp=1&sz=17&dirflg=w&sll=22.294963,114.172293&sspn=0.004725,0.009602&brcurrent=3,0x340400edc 87d41dd:0xa00c39682627ff0,0,0x3404009533f68457:0x7af391a82a888312&ie=UTF8&z=17 42 | P a g e

Section 2: Hong Kong Cultural Centre/ Hong Kong Space Museum to East Tsim Sha Tsui MTR station exit J 0.4 km â&#x20AC;&#x201C; 5 mins

http://maps.google.com.hk/maps?f=d&source=s_d&saddr=%E6%A2%B3%E5%A3%AB%E5%B7%B4%E5%88%A9%E9%81%93&d addr=22.294586,114.173902&geocode=FSMwVAEdsxrOBg%3B&hl=zhTW&mra=dme&mrcr=0&mrsp=1&sz=17&dirflg=w&sll=22.294705,114.173012&sspn=0.004725,0.009602&brcurrent=3,0x340400edc 87d41dd:0xa00c39682627ff0,0,0x3404009533f68457:0x7af391a82a888312&ie=UTF8&ll=22.294626,114.173269&spn=0.004725,0. 009602&z=17 43 | P a g e

Section 3: Hong Kong Cultural Centre/ Hong Kong Space Museum to Star Ferry Pier 0.2 km â&#x20AC;&#x201C; 2 mins

http://maps.google.com.hk/maps?f=d&source=s_d&saddr=%E6%A2%B3%E5%A3%AB%E5%B7%B4%E5%88%A9%E9%81%93&d addr=%E4%B8%8D%E7%9F%A5%E5%90%8D%E7%9A%84%E9%81%93%E8%B7%AF&geocode=FSMwVAEdsxrOBg%3BFe4tV AEdxRPOBg&hl=zhTW&mra=dme&mrcr=0&mrsp=1&sz=16&dirflg=w&sll=22.295569,114.17357&sspn=0.00945,0.019205&brcurrent=3,0x340400edc87 d41dd:0xa00c39682627ff0,0,0x3404009533f68457:0x7af391a82a888312&ie=UTF8&ll=22.29469,114.170448&spn=0.004725,0.009 602&z=17 44 | P a g e

3. Ladies’ Street Section 1: Ladies’ Street to Mong Kok MTR station exit D3 0.3 km – 4 mins

http://maps.google.com.hk/maps?f=d&source=s_d&saddr=%E9%80%9A%E8%8F%9C%E8%A1%97&daddr=%E4%BA%9E%E7%9A%86%E8%80%8 1%E8%A1%97&hl=zhTW&geocode=FeyGVAEd0hzOBg%3BFfqQVAEd3hjOBg&mra=dme&mrcr=0&mrsp=1&sz=17&dirflg=w&sll=22.318061,114.171767&sspn=0.00472 4,0.009602&brcurrent=3,0x340400c62bc7810f:0x3ba12a5918081894,0,0x3404009533f68457:0x7af391a82a888312&ie=UTF8&ll=22.318398,11 4.171928&spn=0.004724,0.009602&z=17 45 | P a g e

Section 2: Ladies’ Street to Yau Ma Tei MTR station exit A2 0.4 km - 4 mins

http://maps.google.com.hk/maps?f=d&source=s_d&saddr=%E9%80%9A%E8%8F%9C%E8%A1%97&daddr=22.315425,114.17053 5+to:%E7%A2%A7%E8%A1%97&hl=zhTW&geocode=FeyGVAEd0hzOBg%3BFaGBVAEdpxrOBilfeS8nxwAENDGz5qRNOK3_cw%3BFch7VAEdcBvOBg&mra=dme&mrcr= 0&mrsp=1&sz=17&dirflg=w&sll=22.314389,114.172636&sspn=0.004724,0.009602&brcurrent=3,0x3404009533f68457:0x69f4ecff872 53282,0,0x3404009533f68457:0x7af391a82a888312&ie=UTF8&ll=22.31556,114.172196&spn=0.004724,0.009602&z=17&via=1

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4. Fa Yuen Street Section 1: Fa Yuen Street to Prince Edward MTR station exit B2 0.4 km – 4 mins

http://maps.google.com.hk/maps?f=d&source=s_d&saddr=22.32213,114.170533&daddr=%E8%8A%B1%E5%9C%92%E8%A1%97 +to:%E5%A4%AA%E5%AD%90%E9%81%93%E8%A5%BF&geocode=%3BFY6iVAEdXhnOBg%3BFTKjVAEdcBTOBg&hl=zhTW&mra=dme&mrcr=0&mrsp=0&sz=17&via=1&dirflg=w&sll=22.322249,114.171499&sspn=0.004724,0.009602&brcurrent=3,0x3404 00c62bc7810f:0x3ba12a5918081894,0,0x3404009533f68457:0x7af391a82a888312&ie=UTF8&ll=22.322964,114.171435&spn=0.00 4724,0.009602&z=17

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Section 2: Fa Yuen Street to Mong Kok MTR station exit B1 0.3 km - 4 mins

http://maps.google.com.hk/maps?f=d&source=s_d&saddr=%E8%8A%B1%E5%9C%92%E8%A1%97&daddr=%E5%BF%AB%E5%A F%8C%E8%A1%97&geocode=FdibVAEdyRrOBg%3BFaqUVAEdTRbOBg&hl=zhTW&mra=dme&mrcr=0&mrsp=1&sz=17&dirflg=w&sll=22.321981,114.171907&sspn=0.004724,0.009602&brcurrent=3,0x340400c62 bc7810f:0x3ba12a5918081894,0,0x3404009533f68457:0x7af391a82a888312&ie=UTF8&ll=22.32084,114.171295&spn=0.004724,0. 009602&z=17 48 | P a g e

Section 3: Fa Yuen Street to Mong Kok East MTR station exit B 0.7 km â&#x20AC;&#x201C; 9 mins

http://maps.google.com.hk/maps?f=d&source=s_d&saddr=%E8%8A%B1%E5%9C%92%E8%A1%97&daddr=22.321594,114.17252 9&geocode=FdibVAEdyRrOBg%3B&hl=zhTW&mra=dme&mrcr=0&mrsp=1&sz=17&dirflg=w&sll=22.321356,114.172969&sspn=0.004724,0.009602&brcurrent=h3,0x340400c6 2bc7810f:0x3ba12a5918081894,,0x3404009533f68457:0x7af391a82a888312&ie=UTF8&z=17 49 | P a g e

5. Temple Street Section 1: Temple Street to Yau Ma Tei MTR station exit C 0.6 km – 7 mins

http://maps.google.com.hk/maps?f=d&source=s_d&saddr=Temple+Street&daddr=%E5%BB%9F%E8%A1%97+to:22.31151,1 14.170673&geocode=FfphVAEdYRnOBikbWDPz6gAENDHV8DjVbs83mQ%3BFZhmVAEdlxrOBg%3B&hl=zhTW&mra=dme&mrcr=0&mrsp=2&sz=18&via=1&dirflg=w&sll=22.311768,114.171563&sspn=0.002362,0.004801&brcurrent=3,0 x3404009533f68457:0x69f4ecff87253282,0,0x3404009533f68457:0x7af391a82a888312&ie=UTF8&ll=22.309634,114.17195&spn =0.004725,0.009602&z=17 50 | P a g e

Section 2: Temple Street to Jordan MTR station exit A 0.4 km - 5 mins

http://maps.google.com.hk/maps?f=d&source=s_d&saddr=Temple+Street&daddr=22.305335,114.170365+to:%E5%BD%8C%E6%9 5%A6%E9%81%93&geocode=FfphVAEdYRnOBikbWDPz6gAENDHV8DjVbs83mQ%3BFTdaVAEd_RnOBil9UKUI6wAENDG3ZRio WIpxzQ%3BFXhaVAEdnh7OBg&hl=zhTW&mra=dme&mrcr=0&mrsp=1&sz=17&dirflg=w&sll=22.306686,114.172465&sspn=0.004725,0.009602&brcurrent=3,0x340400eba 04aacaf:0x48ca3dfe6edcb952,0,0x3404009533f68457:0x7af391a82a888312&ie=UTF8&ll=22.3062,114.1724&spn=0.004725,0.0096 02&z=17&via=1

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6. Parc Oasis Section 1: Parc Oasis Blk 10 to Kowloon Tong MTR station C2 0.4 km -5 mins

http://maps.google.com.hk/maps?f=d&source=s_d&saddr=22.336779,114.175115&daddr=%E5%8F%88%E4%B8%80%E5%B1%85 %E9%81%93&hl=zhTW&geocode=%3BFe7IVAEdPivOBg&mra=dme&mrcr=0&mrsp=0&sz=17&dirflg=w&sll=22.335141,114.177196&sspn=0.004724,0.0 09602&brcurrent=3,0x3404073153dbf8a7:0x1837330af94afb18,0,0x340400d4376c85e1:0xcab6faa04b58a8a7&ie=UTF8&ll=22.335 409,114.177496&spn=0.004724,0.009602&z=17 52 | P a g e

Section 2: Parc Oasis Blk 10 to Yau Yat Tsuen Bus Terminus 0.5 km â&#x20AC;&#x201C; 6 mins

http://maps.google.com.hk/maps?f=d&source=s_d&saddr=22.337314,114.173999&daddr=%E5%8F%88%E4%B8%80%E5%B1%85 %E9%81%93&hl=zhTW&geocode=%3BFe7IVAEdPivOBg&mra=dme&mrcr=0&mrsp=0&sz=17&dirflg=w&sll=22.335548,114.176542&sspn=0.004724,0.0 09602&brcurrent=3,0x340407335121d4d5:0xea6602cb7ee084f0,0,0x340400d4376c85e1:0xcab6faa04b58a8a7&ie=UTF8&ll=22.33 5578,114.176649&spn=0.004724,0.009602&z=17

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7. Baptist University Section 1: Baptist University to Kowloon Tong MTR station exit A2 0.7 km â&#x20AC;&#x201C; 7 mins

http://maps.google.com.hk/maps?f=d&source=s_d&saddr=%E8%81%AF%E5%90%88%E9%81%93&daddr=22.336808,114.177947 &geocode=FSjeVAEdPEjOBg%3B&hl=zhTW&mra=dme&mrcr=0&mrsp=1&sz=17&dirflg=w&sll=22.338178,114.18035&sspn=0.004724,0.009602&brcurrent=3,0x3404073153 dbf8a7:0x1837330af94afb18,0,0x340400d4376c85e1:0xcab6faa04b58a8a7&ie=UTF8&z=17 54 | P a g e

Section 2: Baptist University to Lok Fu MTR station exit B 0.7 km â&#x20AC;&#x201C; 8 mins

http://maps.google.com.hk/maps?f=d&source=s_d&saddr=%E8%81%AF%E5%90%88%E9%81%93&daddr=22.3379,114.1877&geo code=FSjeVAEdPEjOBg%3B&hl=zhTW&mra=dme&mrcr=0&mrsp=1&sz=17&dirflg=w&sll=22.338178,114.183354&sspn=0.004724,0.009602&brcurrent=3,0x34040728e 13925c5:0xa6d5e91d75f1c7de,0,0x340406c37eee9427:0xd3b9116677206d6e&ie=UTF8&ll=22.338307,114.18594&spn=0.004724,0 .009602&z=17

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8. Kwun Tong Industrial Centre Section 1: Kwun Tong Industrial Centre to Kwun Tong MTR station B1 0.4 km â&#x20AC;&#x201C; 5 mins

http://maps.google.com.hk/maps?f=d&source=s_d&saddr=22.309188,114.225208&daddr=%E9%96%8B%E6%BA%90%E9%81%93 &geocode=%3BFZFzVAEdS_TOBg&hl=zhTW&mra=dme&mrcr=0&mrsp=0&sz=17&dirflg=w&sll=22.309734,114.226044&sspn=0.004725,0.009602&brcurrent=3,0x340401488 3a04d95:0xce2b10a24961854c,0,0x3404014883a04d95:0xf7ab69df5f85d6b3&ie=UTF8&ll=22.310478,114.227117&spn=0.004725,0 .009602&z=17 56 | P a g e

Section 2: Kwun Tong Industrial Centre to Kwun Tong Ferry Bus Terminal 0.5 km â&#x20AC;&#x201C; 6 mins

http://maps.google.com.hk/maps?f=d&source=s_d&saddr=%E8%88%88%E6%A5%AD%E8%A1%97&daddr=%E4%B8%8D% E7%9F%A5%E5%90%8D%E7%9A%84%E9%81%93%E8%B7%AF&geocode=FU9pVAEdR_DOBg%3BFWxlVAEdDeLOBg&hl= zhTW&mra=dme&mrcr=0&mrsp=1&sz=17&dirflg=w&sll=22.308394,114.224929&sspn=0.004725,0.009602&brcurrent=3,0x34040 14883a04d95:0xce2b10a24961854c,0,0x3404014883a04d95:0xf7ab69df5f85d6b3&ie=UTF8&ll=22.3089,114.225186&spn=0.004 725,0.009602&z=17 57 | P a g e

9. Hong Kong Central Library Section 1: Hong Kong Central Library to Causeway Bay MTR station exit E 0.6 km â&#x20AC;&#x201C; 8 mins

http://maps.google.com.hk/maps?f=d&source=s_d&saddr=%E9%AB%98%E5%A3%AB%E5%A8%81%E9%81%93&daddr=22.2803 11,114.184996&geocode=FbL4UwEdu2POBg%3B&hl=zhTW&mra=dme&mrcr=0&mrsp=1&sz=17&dirflg=w&sll=22.280072,114.188225&sspn=0.004726,0.009602&brcurrent=3,0x34040055b 36dac7f:0x23fa8b1e7120c6a,0,0x3404004c435d4ad9:0x6e0e524894ae1a66&ie=UTF8&ll=22.279765,114.187828&spn=0.004726,0. 009602&z=17 58 | P a g e

Section 2: Hong Kong Central Library to Tin Hau MTR station exit A2 0.4 km â&#x20AC;&#x201C; 6 mins

http://maps.google.com.hk/maps?f=d&source=s_d&saddr=22.28039,114.189137&daddr=%E8%8B%B1%E7%9A%87%E9%81%93+ to:%E8%8B%B1%E7%9A%87%E9%81%93&geocode=%3BFev_UwEdo23OBg%3BFfoCVAEdrG_OBg&hl=zhTW&mra=dme&mrcr=0&mrsp=0&sz=17&via=1&dirflg=w&sll=22.281274,114.191734&sspn=0.004726,0.009602&brcurrent=3,0x3404 01acff3ac4cf:0xa3821671f88c95a,0,0x3404004c435d4ad9:0x6e0e524894ae1a66&ie=UTF8&ll=22.281621,114.191884&spn=0.0047 26,0.009602&z=17

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10. Hong Kong Convention and Exhibition Centre Section 1: Hong Kong Convention and Exhibition Centre to Wan Chai Ferry Pier 0.5 km â&#x20AC;&#x201C; 6 mins

http://maps.google.com.hk/maps?f=d&source=s_d&saddr=%E5%8D%9A%E8%A6%BD%E9%81%93&daddr=22.281879,114.17572 6&hl=zhTW&geocode=FYEFVAEd2CPOBg%3B&mra=dme&mrcr=0&mrsp=1&sz=17&dirflg=w&sll=22.282395,114.175125&sspn=0.004726, 0.009602&brcurrent=3,0x3404004bfd731ce7:0x82db136932b588ce,0,0x3404004c435d4ad9:0x6e0e524894ae1a66&ie=UTF8&ll=22 .282505,114.175243&spn=0.004726,0.009602&z=17 60 | P a g e

Section 2: Hong Kong Convention and Exhibition Centre to Wan Chai MTR station exit A1 0.9km â&#x20AC;&#x201C; 12 mins

http://maps.google.com.hk/maps?f=d&source=s_d&saddr=%E5%8D%9A%E8%A6%BD%E9%81%93&daddr=%E9%A7%B1%E5%8 5%8B%E9%81%93&hl=zhTW&geocode=FYEFVAEd2CPOBg%3BFUTwUwEdOiXOBg&mra=mi&mrsp=1&sz=17&dirflg=w&sll=22.278543,114.17564&sspn=0. 004726,0.009602&brcurrent=3,0x3404004bfd731ce7:0x82db136932b588ce,0,0x3404004c435d4ad9:0x6e0e524894ae1a66&ie=UTF 8&ll=22.27895,114.176949&spn=0.004726,0.009602&z=17 61 | P a g e

WALKABILITY IN ASIAN CITIES PEDESTRIAN PREFERENCE SURVEY

ANNEX 4 2.3 Please tick in the appropriate boxes. ( 1 = The least wanted ; 5 = The most wanted)

1. Travel Behavior How much time they spend in each mode, how much is the average travel time in one direction for a major trip say to office or school? Analysis of this would help in understanding the trip preference. It is also important to understand if they are captive or choice riders and for this reason we need to ask for availability of vehicle ownership. 1.1 Mode of transportation commonly used per day and average travel time spent on each mode (please tick) – estimates for one way can be considered 0 1- 15 16-30 31-45 46-60 61-75 76-90 > 90 Mode min min min min min min min min Walk Cycle MTR Two Wheeler Car/Taxi Mini Bus Bus Others 1.2 Average Travel Time (One Way) from residence to main destination (please tick) <=15 min 16-30 min 31-45 min 46-60 min 61-75 min 76-90 min

> 90 min

1.3 Average Travel Distance (one Way) from residence to main destination (please tick) <= 3 km 3 – 6 km 6 – 9 km 9 – 12 km 12 – 15 km > 15 km

If don’t know, please state out the district: Starting point: _____________________

Terminal point: _______________________

Easy access for people with special abilities Improved street lighting Wider footpaths A more Level footpaths Clean sidewalks Reduced the traffic on road Reduced traffic speed on road Remove obstacles/parking from footpath More crossing points Weather proof to cover the walkway

If yes, what is your choice? Cycle Bus MTR

Light bus

2. Pedestrian Preference Pedestrian preference survey is mainly to understand pedestrian needs and desire. It is also intended to understand their concerns on air pollution and other issues such as subways and skywalks. Also we need to determine if they would migrate to other modes if improvements are not made

3.2 Age ≦15 Years old

□ Ground Crossing (at-grade) 62 | P a g e

□ Skywalks (overhead crossings)

□

Two Wheeler

> 300 m

Waiting for transportation

Car/taxi

Two Wheeler

Female

16 – 30 Years old

3.3 Household Income < $4000 $4000 - $15999 (USD 510) (USD 510 -2050)

□ Subways (underground)

2.6 Do you plan to shift from walking to other mode in future if no improvement is done? □ Yes □ No

3.1 Sex Male

2.2 If you have to cross the road what do you prefer? (please tick)

2.5 When do you think are you most exposed to air pollution? Walking Cycle Bus MTR Light bus Car/taxi

3. Socio-Economic Profile(please tick)

□ Best

2.4 How far are you willing to walk to access crossings, skywalks/subways (please tick) < =50 m 51 – 100 m 101 – 150 m 151 – 200 m 201 – 250 m 251 – 300 m

1.4 What type of vehicle(s) does your family own? (please tick) Bicycle Car Two Wheeler No Vehicle Others

2.1 How do you rate the Pedestrian facilities in the city? □ Worst □ Bad □ Fair □ Good

31 – 45 Years old

46 – 60 Years old

> 60 Years old

$16000 - $27999 (USD 2050 - 3600)

$28000 - $39999 (USD 3600–5100)

> $40000 (USD 5100)

亞洲地區步行指數

2.3 你願意步行多遠使用橫過馬路的設施？(請加上 9)

行人步行習慣調查

< 50 米

51 – 100 米

101 – 150 米

2.4 請於適當位置加上9

乘坐交通工具的習慣

151 – 200 米

201 – 250 米

> 300 米

(1=最不需要改善 ; 5 = 最需要改善) 1

以下的問題旨在了解市民平均單程有多少時間用於以下各種交通工具，這研究有助了解和明白市民乘坐交通工具的習慣

251 – 300 米

增加傷殘人仕設施

□

增加街燈

□

擴寬行人路

□

步行

使行人路更平坦

□

踏單車

改善行人路的衛生情況

□

電單車

減少車輛的行駛

□

港鐵

減慢車輛的行車速度

□

私家車/的士

清除行人路上的障礙物

□

中型汽車 (小巴)

增加橫過馬路的地點

□

巴士

增加有蓋的行人路

□

1.1 以每天計算，平均會花多少時間在以下的交通工具上:（以單程計算: 上班 /上學）(請加上 9) 0 分鐘

1- 15 分鐘

16-30 分鐘

31-45 分鐘

46-60 分鐘

61-75 分鐘

76-90 分鐘

> 90 分鐘

2.5 你何時會覺得自己最暴露於受污染的空氣之中? (請加上 9)

其他

1.2 以單程計算，由居住地方至主要目的地乘坐交通工具的平均時間為: <=15 分鐘

16-30 分鐘

31-45 分鐘

46-60 分鐘

61-75 分鐘

(請加上 9) 76-90 分鐘

步行

踏單車

巴士上

港鐵上

小巴上

私家車上/的士上

電單車上

路旁候車時

> 90 分鐘 2.6 如果在未來的日子，行人路的設施没有改善，你會否由步行轉變為其他方法前往目的地？(請加上 9)

1.3 以單程計算，由居住地方至主要目的地的距離為：(請加上 9) <= 3 公里

3 – 6 公里

如不清楚，可寫下地區：

6 – 9 公里

9 – 12 公里

12 – 15 公里

出發地：_______________

□會 > 15 公里

□不會

如果會，你會轉為以下哪項？(請加上 9) 單車

終點：_____________

巴士

港鐵

小巴

私家車/的士

電單車

1.4 請問你家中所擁有的交通公具為：(請加上 9) 單車

私家車

電單車

没有

其他

3. 個人資料 3.1 性別 : (請加上 9) 男

女

2. 步行取向研究步行取向研究是主要用作了解行人的需要和要求，同時有助了解受訪者對空氣污染及其他設施（如天橋或隧道）之意見..

3.2 年齡: (請加上 9) 15 歲或以下

2.1 你認為香港的行人步行設施是下列哪一項 ? (請加上 9)

□非常差

□差

□中等

□好

□非常好

16 – 30 歲

31 – 45 歲

46 – 60 歲

大於 60 歲

3.3 家庭入息: (請加上 9)

2.2 如果你需要橫過馬路，你會選擇以下哪項？(請加上 9) 在馬路上橫過行人天橋行人隧道

少於 $4000

$4000 - $15999

$16000 - $27999

$ 28000 - $39999

多於 $40000

(USD 510)

(USD 510 -2050)

(USD 2050 - 3600)

(USD 3600–5100)

(USD 5100)

ANNEX 5 Results of the Pedestrian Preference Survey Mean Test (by Social economic profile)

By Gender ANOVA

Sum of Squares

Q1.1 Mode of transportation

Between Groups

Mean Square

6.346

Within Groups

1861.105

1026

1.814

Total

1867.451

1027

.005

Within Groups

217.757

1026

.212

Total

217.763

1027

7.599

Within Groups

3478.653

1026

3.390

Total

3486.252

1027

6.399

Within Groups

826.289

1026

.805

Total

832.688

1027

.811

Within Groups

466.667

1025

.455

Total

467.478

1026

Sig.

3.498

.062

.024

.876

2.241

.135

7.946

.005

1.781

.182

(walking)

Q1.1 Mode of transportation

Between Groups

(Cycle)

Q1.1 Mode of transportation

Between Groups

(MTR)

Q1.1 Mode of transportation (Two Between Groups Wheeler)

Q1.1 Mode of transportation

Between Groups

(Car/Taxi)

Q1.1 Mode of transportation (Mini Between Groups

1.222

Within Groups

664.276

1026

.647

Total

665.498

1027

27.954

Within Groups

2690.497

1025

2.625

Total

2718.452

1026

.389

Within Groups

254.178

1025

.248

Total

254.567

1026

1.226

Within Groups

1293.736

1023

1.265

Total

1294.962

1024

3.387

Within Groups

1138.533

1021

1.115

Total

1141.920

1022

.893

Within Groups

1143.106

1022

1.118

Total

1143.999

1023

1.887

.170

10.650

.001

1.568

.211

.969

.325

3.037

.082

.798

.372

Bus)

Q1.1 Mode of transportation (Bus) Between Groups

Q1.1 Mode of transportation

Between Groups

(Others)

Q2.3 Easy Access

Q2.3 Improved street lighting

Q2.3 Wider footpaths

65 | P a g e

Between Groups

Q2.3 Level footpaths

Q2.3 Clean sidewalks

Q2.3 Reduced traffic

Q2.3 Reduced speed

Q2.3 Remove obstacles

Q2.3 More crossing point

Q2.3 Weather proof

Between Groups

.041

Within Groups

1105.228

1021

1.082

Total

1105.269

1022

.011

Within Groups

1222.290

1021

1.197

Total

1222.301

1022

.158

Within Groups

1223.900

1018

1.202

Total

1224.058

1019

.453

Within Groups

1069.512

1020

1.049

Total

1069.965

1021

.139

Within Groups

1059.782

1022

1.037

Total

1059.921

1023

3.286

Within Groups

1070.463

1018

1.052

Total

1073.749

1019

.008

1484.188

1017

1.459

Between Groups

Within Groups

66 | P a g e

.037

.847

.009

.923

.131

.717

.432

.511

.134

.714

3.125

.077

.006

.940

Total

Average of Q2.3

Q2.4 Willing to walk to access

1484.196

1018

.006

Within Groups

160.851

465

.346

Total

160.857

466

.038

Within Groups

1931.363

1017

1.899

Total

1931.401

1018

Between Groups

crossing

Means Plots

67 | P a g e

.016

.898

.020

.888

68 | P a g e

By Age group ANOVA

Sum of Squares

Q1.1 Mode of transportation

Between Groups

Mean Square

.269

.067

Within Groups

1867.182

1023

1.825

Total

1867.451

1027

.994

.249

Within Groups

216.769

1023

.212

Total

217.763

1027

37.233

9.308

Within Groups

3449.019

1023

3.371

Total

3486.252

1027

6.965

1.741

Within Groups

825.723

1023

.807

Total

832.688

1027

4.315

1.079

Within Groups

463.163

1022

.453

Total

467.478

1026

4.026

1.007

Within Groups

661.472

1023

.647

Total

665.498

1027

Sig.

.037

.997

1.173

.321

2.761

.027

2.157

.072

2.380

.050

1.557

.184

(walking)

Q1.1 Mode of transportation

Between Groups

(Cycle)

Q1.1 Mode of transportation

Between Groups

(MTR)

Q1.1 Mode of transportation (Two Between Groups Wheeler)

Q1.1 Mode of transportation

Between Groups

(Car/Taxi)

Q1.1 Mode of transportation (Mini Between Groups Bus)

69 | P a g e

Q1.1 Mode of transportation (Bus) Between Groups

Q1.1 Mode of transportation

4.914

1.228

Within Groups

2713.538

1022

2.655

Total

2718.452

1026

1.096

.274

Within Groups

253.470

1022

.248

Total

254.567

1026

5.042

1.261

Within Groups

1289.919

1020

1.265

Total

1294.962

1024

3.601

.900

Within Groups

1138.319

1018

1.118

Total

1141.920

1022

5.117

1.279

Within Groups

1138.882

1019

1.118

Total

1143.999

1023

5.381

1.345

Within Groups

1099.888

1018

1.080

Total

1105.269

1022

1.533

.383

Within Groups

1220.769

1018

1.199

Total

1222.301

1022

Between Groups

.463

.763

1.105

.353

.997

.408

.805

.522

1.145

.334

1.245

.290

.320

.865

(Others)

Q2.3 Easy Access

Q2.3 Improved street lighting

Q2.3 Wider footpaths

Q2.3 Level footpaths

Q2.3 Clean sidewalks

70 | P a g e

Between Groups

Q2.3 Reduced traffic

Q2.3 Reduced speed

Q2.3 Remove obstacles

Q2.3 More crossing point

Q2.3 Weather proof

Average of Q2.3

Q2.4 Willing to walk to access

Between Groups

13.765

3.441

Within Groups

1210.293

1015

1.192

Total

1224.058

1019

7.560

1.890

Within Groups

1062.405

1017

1.045

Total

1069.965

1021

7.465

1.866

Within Groups

1052.456

1019

1.033

Total

1059.921

1023

11.343

2.836

Within Groups

1062.406

1015

1.047

Total

1073.749

1019

3.486

.871

Within Groups

1480.710

1014

1.460

Total

1484.196

1018

1.131

.283

Within Groups

159.726

462

.346

Total

160.857

466

18.647

4.662

Within Groups

1912.755

1014

1.886

Total

1931.401

1018

Between Groups

crossing

71 | P a g e

2.886

.022

1.809

.125

1.807

.125

2.709

.029

.597

.665

.818

.514

2.471

.043

72 | P a g e

73 | P a g e

74 | P a g e

75 | P a g e

76 | P a g e

By Household income ANOVA

Sum of Squares

Q1.1 Mode of transportation

Between Groups

Mean Square

22.077

5.519

Within Groups

1840.057

1014

1.815

Total

1862.133

1018

1.156

.289

Within Groups

215.697

1014

.213

Total

216.854

1018

9.828

2.457

Within Groups

3437.654

1014

3.390

Total

3447.482

1018

16.160

4.040

Within Groups

815.995

1014

.805

Total

832.155

1018

20.322

5.080

Within Groups

446.798

1013

.441

Total

467.120

1017

6.427

1.607

Within Groups

657.191

1014

.648

Total

663.617

1018

Sig.

3.041

.017

1.359

.246

.725

.575

5.020

.001

11.519

.000

2.479

.043

(walking)

Q1.1 Mode of transportation

Between Groups

(Cycle)

Q1.1 Mode of transportation

Between Groups

(MTR)

Q1.1 Mode of transportation (Two Between Groups Wheeler)

Q1.1 Mode of transportation

Between Groups

(Car/Taxi)

Q1.1 Mode of transportation (Mini Between Groups Bus)

77 | P a g e

Q1.1 Mode of transportation (Bus) Between Groups

Q1.1 Mode of transportation

11.764

2.941

Within Groups

2695.517

1013

2.661

Total

2707.281

1017

.494

.124

Within Groups

253.962

1013

.251

Total

254.457

1017

31.793

7.948

Within Groups

1254.255

1011

1.241

Total

1286.047

1015

9.160

2.290

Within Groups

1120.059

1009

1.110

Total

1129.219

1013

2.278

.569

Within Groups

1131.417

1010

1.120

Total

1133.695

1014

.578

.144

Within Groups

1095.881

1009

1.086

Total

1096.459

1013

3.554

.888

Within Groups

1207.059

1009

1.196

Total

1210.612

1013

Between Groups

1.105

.353

.493

.741

6.407

.000

2.063

.084

.508

.730

.133

.970

.743

.563

(Others)

Q2.3 Easy Access

Q2.3 Improved street lighting

Q2.3 Wider footpaths

Q2.3 Level footpaths

Q2.3 Clean sidewalks

78 | P a g e

Between Groups

Q2.3 Reduced traffic

Q2.3 Reduced speed

Q2.3 Remove obstacles

Q2.3 More crossing point

Q2.3 Weather proof

Average of Q2.3

Q2.4 Willing to walk to access

Between Groups

4.956

1.239

Within Groups

1208.854

1006

1.202

Total

1213.810

1010

4.008

1.002

Within Groups

1050.913

1008

1.043

Total

1054.920

1012

6.703

1.676

Within Groups

1043.035

1010

1.033

Total

1049.738

1014

17.487

4.372

Within Groups

1045.168

1006

1.039

Total

1062.655

1010

12.126

3.031

Within Groups

1464.690

1005

1.457

Total

1476.816

1009

.717

.179

Within Groups

160.139

462

.347

Total

160.857

466

5.297

1.324

Within Groups

1920.882

1005

1.911

Total

1926.179

1009

Between Groups

crossing

79 | P a g e

1.031

.390

.961

.428

1.623

.166

4.208

.002

2.080

.081

.517

.723

.693

.597

80 | P a g e

81 | P a g e

82 | P a g e

83 | P a g e

84 | P a g e

Q3.1 Gender * Q1.2 Average Travel Time Crosstab

Count

Q1.2 Average Travel Time

<=15 min

Q3.1 Gender

85 | P a g e

16-30 min

31-45 min

46-60 min

61-75 min

76-90 min

Male

107

150

135

Female

108

120

101

Total

215

270

236

103

Crosstab

Count

Q1.2 Average Travel Time

> 90 min

Q3.1 Gender

Total

Male

563

Female

465

Total

1028

Chi-Square Tests

Value

Asymp. Sig. (2-sided)

8.775a

.187

Likelihood Ratio

8.818

.184

Linear-by-Linear Association

6.381

.012

N of Valid Cases

1028

Pearson Chi-Square

a. 0 cells (.0%) have expected count less than 5. The minimum expected count is 20.81.

86 | P a g e

Q3.1 Gender * Q1.3 Average Travel Distance

Crosstab

Count

Q1.3 Average Travel Distance

<=3 km

Q3.1 Gender

3-6 km

6-9 km

Female

150

109

118

128

104

Crosstab

Count

Q1.3 Average Travel Distance

> 15 km

87 | P a g e

12-15 km

Male

Total

Q3.1 Gender

9-12 km

Total

Male

210

561

Female

205

463

Total

415

1024

Chi-Square Tests

Value

Asymp. Sig. (2-sided)

.183

Likelihood Ratio

7.564

.182

Linear-by-Linear Association

1.285

.257

N of Valid Cases

1024

Pearson Chi-Square

7.545

a. 0 cells (.0%) have expected count less than 5. The minimum expected count is 47.02.

88 | P a g e

Q3.1 Gender * Q2.2 Prefer way to cross the road

Crosstab

Count

Q2.2 Prefer way to cross the road

Ground Crossing

Q3.1 Gender

Skywalks

Subways

Total

Male

410

561

Female

345

465

Total

755

179

1026

Chi-Square Tests

Value

Asymp. Sig. (2-sided)

3.176a

.204

Likelihood Ratio

3.215

.200

Linear-by-Linear Association

1.065

.302

N of Valid Cases

1026

Pearson Chi-Square

a. 0 cells (.0%) have expected count less than 5. The minimum expected count is 41.70.

89 | P a g e

Q3.1 Gender * Q2.4 Willing to walk to access crossing Crosstab

Count

Q2.4 Willing to walk to access crossing

<=50 m

Q3.1 Gender

51-100 m

101-150 m

151-200 m

Male

258

161

Female

180

162

Total

438

323

123

Crosstab

Count

Q2.4 Willing to walk to access crossing

251-300 m

Q3.1 Gender

>300 m

Total

Male

558

Female

461

Total

1019

Chi-Square Tests

Value

Asymp. Sig. (2-sided)

19.464a

.003

20.017

.003

Linear-by-Linear Association

.020

.887

N of Valid Cases

1019

Pearson Chi-Square

Likelihood Ratio

90 | P a g e

201-250 m

Crosstab

Count

Q2.4 Willing to walk to access crossing

<=50 m

Q3.1 Gender

51-100 m

101-150 m

151-200 m

201-250 m

Male

258

161

Female

180

162

a. 2 cells (14.3%) have expected count less than 5. The minimum expected count is 2.26.

Q3.1 Gender * Q2.5 When do you think you are most exposed to air pollution Crosstab

Count

Q2.5 When do you think you are most exposed to air pollution

Walking

Q3.1 Gender

Cycle

Bus

MTR

Car/Taxi

Male

169

Female

112

Total

281

Crosstab

Count

Q2.5 When do you think you are most exposed to air pollution

Waiting for Two Wheeler

91 | P a g e

Light Bus

transportation

Total

Q3.1 Gender

Male

326

554

Female

320

462

646

1016

Total

Chi-Square Tests

Value

Asymp. Sig. (2-sided)

20.193a

.005

Likelihood Ratio

21.007

.004

Linear-by-Linear Association

10.144

.001

Pearson Chi-Square

N of Valid Cases

1016

a. 4 cells (25.0%) have expected count less than 5. The minimum expected count is 2.73.

Q3.1 Gender * Q2.6 Do you plan to change mode Crosstab

Count

Q2.6 Do you plan to change mode

Yes

Q3.1 Gender

92 | P a g e

Total

Male

155

406

561

Female

151

312

463

Total

306

718

1024

Chi-Square Tests

Value

Asymp. Sig. (2-sided)

.083

Continuity Correction

2.774

.096

Likelihood Ratio

3.001

.083

Pearson Chi-Square

3.007

Exact Sig. (2-sided)

Fisher's Exact Test

Exact Sig. (1-sided)

.087

Linear-by-Linear Association

3.004

N of Valid Cases

1024

.048

.083

a. 0 cells (.0%) have expected count less than 5. The minimum expected count is 138.36.

b. Computed only for a 2x2 table

Q3.2 Age * Q1.2 Average Travel Time Crosstab

Count

Q1.2 Average Travel Time

<=15 min

Q3.2 Age

31-45 min

46-60 min

61-75 min

<=15 Years old

16-30 Years old

107

163

139

31-45 Years old

46-60 Years old

> 60 Years old

215

270

236

103

Total

93 | P a g e

16-30 min

Crosstab

Count

Q1.2 Average Travel Time

76-90 min

Q3.2 Age

> 90 min

Total

<=15 Years old

16-30 Years old

581

31-45 Years old

196

46-60 Years old

178

> 60 Years old

1028

Total

Chi-Square Tests

Value

Asymp. Sig. (2-sided)

22.916a

.525

22.794

.532

Linear-by-Linear Association

.002

.966

N of Valid Cases

1028

Pearson Chi-Square

Likelihood Ratio

a. 8 cells (22.9%) have expected count less than 5. The minimum expected count is 1.39.

94 | P a g e

Q3.2 Age * Q1.3 Average Travel Distance Crosstab

Count

Q1.3 Average Travel Distance

<=3 km

Q3.2 Age

3-6 km

6-9 km

16-30 Years old

31-45 Years old

46-60 Years old

> 60 Years old

150

109

118

128

104

Crosstab

Count

Q1.3 Average Travel Distance

> 15 km

95 | P a g e

12-15 km

<=15 Years old

Total

Q3.2 Age

9-12 km

Total

<=15 Years old

16-30 Years old

263

580

31-45 Years old

194

46-60 Years old

177

> 60 Years old

Crosstab

Count

Q1.3 Average Travel Distance

> 15 km

Q3.2 Age

Total

<=15 Years old

16-30 Years old

263

580

31-45 Years old

194

46-60 Years old

177

> 60 Years old

415

1024

Total

Chi-Square Tests

Value

Asymp. Sig. (2-sided)

46.128a

.001

42.069

.003

Linear-by-Linear Association

.624

.429

N of Valid Cases

1024

Pearson Chi-Square

Likelihood Ratio

a. 8 cells (26.7%) have expected count less than 5. The minimum expected count is 3.15.

96 | P a g e

Q3.2 Age * Q2.2 Prefer way to cross the road Crosstab

Count

Q2.2 Prefer way to cross the road

Ground Crossing

Q3.2 Age

Skywalks

Subways

<=15 Years old

16-30 Years old

421

109

579

31-45 Years old

141

196

46-60 Years old

136

178

> 60 Years old

755

179

1026

Total

Chi-Square Tests

Value

Asymp. Sig. (2-sided)

8.353a

.400

9.788

.280

Linear-by-Linear Association

.599

.439

N of Valid Cases

1026

Pearson Chi-Square

Likelihood Ratio

a. 2 cells (13.3%) have expected count less than 5. The minimum expected count is 2.78.

97 | P a g e

Total

Q3.2 Age * Q2.4 Willing to walk to access crossing Crosstab

Count

Q2.4 Willing to walk to access crossing

<=50 m

Q3.2 Age

51-100 m

101-150 m

151-200 m

<=15 Years old

16-30 Years old

254

178

31-45 Years old

46-60 Years old

> 60 Years old

438

323

123

Total

Crosstab

Count

Q2.4 Willing to walk to access crossing

251-300 m

Q3.2 Age

98 | P a g e

201-250 m

>300 m

Total

<=15 Years old

16-30 Years old

578

31-45 Years old

194

46-60 Years old

176

> 60 Years old

Crosstab

Count

Q2.4 Willing to walk to access crossing

251-300 m

Q3.2 Age

>300 m

Total

<=15 Years old

16-30 Years old

578

31-45 Years old

194

46-60 Years old

176

> 60 Years old

Total

1019

Chi-Square Tests

Value

Asymp. Sig. (2-sided)

24.744a

.420

25.467

.381

Linear-by-Linear Association

1.169

.280

N of Valid Cases

1019

Pearson Chi-Square

Likelihood Ratio

a. 15 cells (42.9%) have expected count less than 5. The minimum expected count is .15.

99 | P a g e

Q3.2 Age * Q2.5 When do you think you are most exposed to air pollution Crosstab

Count

Q2.5 When do you think you are most exposed to air pollution

Walking

Q3.2 Age

Cycle

Bus

MTR

Light Bus

<=15 Years old

16-30 Years old

167

31-45 Years old

46-60 Years old

> 60 Years old

281

Total

Crosstab

Count

Q2.5 When do you think you are most exposed to air pollution

Waiting for Two Wheeler

Q3.2 Age

Car/Taxi

transportation

Total

<=15 Years old

16-30 Years old

353

571

31-45 Years old

122

195

46-60 Years old

117

178

100 | P a g e

> 60 Years old

Total

646

1016

Chi-Square Tests

Value

Asymp. Sig. (2-sided)

.017

48.934

.008

Linear-by-Linear Association

1.940

.164

N of Valid Cases

1016

Pearson Chi-Square

Likelihood Ratio

46.111

a. 24 cells (60.0%) have expected count less than 5. The minimum expected count is .18.

Q3.2 Age * Q2.6 Do you plan to change mode Crosstab

Count

Q2.6 Do you plan to change mode

Yes

Q3.2 Age

Total

<=15 Years old

16-30 Years old

170

410

580

31-45 Years old

139

195

46-60 Years old

122

178

> 60 Years old

306

718

1024

Total

101 | P a g e

Chi-Square Tests

Value

Asymp. Sig. (2-sided)

.818

1.500

.827

Linear-by-Linear Association

.863

.353

N of Valid Cases

1024

Pearson Chi-Square

Likelihood Ratio

1.547

a. 0 cells (.0%) have expected count less than 5. The minimum expected count is 9.26.

102 | P a g e

Q3.3 Household Income * Q1.2 Average Travel Time Crosstab

Count

Q1.2 Average Travel Time

<=15 min

Q3.3 Household Income

<$4000

16-30 min

31-45 min

46-60 min

$4000-$15999

$16000-$27999

$28000-$39999

>40000

214

267

234

Total

Crosstab

Count

Q1.2 Average Travel Time

61-75 min

Q3.3 Household Income

103 | P a g e

<$4000

76-90 min

> 90 min

Total

$4000-$15999

346

$16000-$27999

330

$28000-$39999

148

>40000

103

Crosstab

Count

Q1.2 Average Travel Time

61-75 min

Q3.3 Household Income

<$4000

76-90 min

$4000-$15999

346

$16000-$27999

330

$28000-$39999

148

>40000

103

102

1019

Chi-Square Tests

Value

Asymp. Sig. (2-sided)

13.355a

.960

12.958

.967

Linear-by-Linear Association

.278

.598

N of Valid Cases

1019

Likelihood Ratio

a. 2 cells (5.7%) have expected count less than 5. The minimum expected count is 4.15.

104 | P a g e

Total

Pearson Chi-Square

> 90 min

Q3.3 Household Income * Q1.3 Average Travel Distance Crosstab

Count

Q1.3 Average Travel Distance

<=3 km

Q3.3 Household Income

3-6 km

6-9 km

$4000-$15999

$16000-$27999

$28000-$39999

>40000

149

109

117

124

104

Crosstab

Count

Q1.3 Average Travel Distance

> 15 km

105 | P a g e

12-15 km

<$4000

Total

Q3.3 Household Income

9-12 km

<$4000

Total

$4000-$15999

133

343

$16000-$27999

142

330

$28000-$39999

147

>40000

103

Crosstab

Count

Q1.3 Average Travel Distance

> 15 km

Q3.3 Household Income

<$4000

Total

$4000-$15999

133

343

$16000-$27999

142

330

$28000-$39999

147

>40000

103

412

1015

Total

Chi-Square Tests

Value

Asymp. Sig. (2-sided)

32.765a

.036

33.069

.033

Linear-by-Linear Association

5.995

.014

N of Valid Cases

1015

Pearson Chi-Square

Likelihood Ratio

a. 0 cells (.0%) have expected count less than 5. The minimum expected count is 9.43.

106 | P a g e

Q3.3 Household Income * Q2.2 Prefer way to cross the road Crosstab

Count

Q2.2 Prefer way to cross the road

Ground Crossing

Q3.3 Household Income

<$4000

Skywalks

$4000-$15999

256

345

$16000-$27999

242

329

$28000-$39999

114

148

103

748

178

1017

Total

Chi-Square Tests

Value

Asymp. Sig. (2-sided)

5.879a

.661

5.669

.684

Linear-by-Linear Association

.336

.562

N of Valid Cases

1017

Likelihood Ratio

a. 0 cells (.0%) have expected count less than 5. The minimum expected count is 8.23.

107 | P a g e

Total

>40000

Pearson Chi-Square

Subways

Q3.3 Household Income * Q2.4 Willing to walk to access crossing Crosstab

Count

Q2.4 Willing to walk to access crossing

<=50 m

Q3.3 Household Income

<$4000

51-100 m

101-150 m

151-200 m

$4000-$15999

144

106

$16000-$27999

146

103

$28000-$39999

>40000

435

319

121

Total

Crosstab

Count

Q2.4 Willing to walk to access crossing

201-250 m

Q3.3 Household Income

108 | P a g e

251-300 m

>300 m

Total

<$4000

$4000-$15999

341

$16000-$27999

328

$28000-$39999

148

>40000

101

Crosstab

Count

Q2.4 Willing to walk to access crossing

201-250 m

Q3.3 Household Income

251-300 m

$4000-$15999

341

$16000-$27999

328

$28000-$39999

148

>40000

101

1010

Chi-Square Tests

Value

Asymp. Sig. (2-sided)

46.316a

.004

35.676

.059

Linear-by-Linear Association

.055

.814

N of Valid Cases

1010

Likelihood Ratio

a. 11 cells (31.4%) have expected count less than 5. The minimum expected count is .46.

109 | P a g e

Total

<$4000

Total

Pearson Chi-Square

>300 m

Q3.3 Household Income * Q2.5 When do you think you are most exposed to air pollution Crosstab

Count

Q2.5 When do you think you are most exposed to air pollution

Walking

Q3.3 Household Income

Cycle

Bus

MTR

Light Bus

<$4000

$4000-$15999

$16000-$27999

$28000-$39999

>40000

278

Total

Crosstab

Count

Q2.5 When do you think you are most exposed to air pollution

Waiting for Car/Taxi

Q3.3 Household Income

110 | P a g e

Two Wheeler

transportation

Total

<$4000

$4000-$15999

212

342

$16000-$27999

207

323

$28000-$39999

100

148

>40000

103

Crosstab

Count

Q2.5 When do you think you are most exposed to air pollution

Waiting for Car/Taxi

Q3.3 Household Income

Two Wheeler

$4000-$15999

212

342

$16000-$27999

207

323

$28000-$39999

100

148

>40000

103

Total

641

1007

Value

Asymp. Sig. (2-sided)

19.180a

.893

23.814

.691

Linear-by-Linear Association

.016

.900

N of Valid Cases

1007

Likelihood Ratio

a. 27 cells (67.5%) have expected count less than 5. The minimum expected count is .54.

111 | P a g e

Total

<$4000

Chi-Square Tests

Pearson Chi-Square

transportation

Q3.3 Household Income * Q2.6 Do you plan to change mode Crosstab

Count

Q2.6 Do you plan to change mode

Yes

Q3.3 Household Income

<$4000

$4000-$15999

250

344

$16000-$27999

101

228

329

$28000-$39999

105

148

>40000

103

302

713

1015

Total

Chi-Square Tests

Value

Asymp. Sig. (2-sided)

4.614a

.329

Likelihood Ratio

4.490

.344

Linear-by-Linear Association

3.063

.080

N of Valid Cases

1015

Pearson Chi-Square

a. 0 cells (.0%) have expected count less than 5. The minimum expected count is 27.08.

112 | P a g e

Total

ANNEX 6 Results of the Pedestrian Preference Survey ANOVA BY GROUPS Correlation test (Q2.1 vs Q2.4) Correlations

Q2.1 Rate the Pedestrian facilities

Pearson Correlation

Q2.1 Rate the Pedestrian

Q2.4 Willing to walk to

facilities

access crossing

Sig. (2-tailed)

Q2.4 Willing to walk to access crossing

113 | P a g e

.055

.081

1026

1016

Pearson Correlation

.055

Sig. (2-tailed)

.081

1016

1019

ANOVA within Q2.3 Descriptives

Q2.3

Mean

Std. Deviation

Std. Error

Easy access

1025

3.3493

1.12455

.03513

Improved street lighting

1023

2.8671

1.05704

.03305

Wider footpaths

1024

3.4990

1.05749

.03305

Level footpaths

1023

3.3011

1.03994

.03251

Clean sidewalks

1023

3.5376

1.09361

.03419

Reduced traffic

1020

3.3637

1.09601

.03432

Reduced speed

1022

2.9941

1.02370

.03202

Remove obstacles

1024

3.5088

1.01789

.03181

More crossing point

1020

3.5843

1.02651

.03214

Weather proof

1019

3.3651

1.20746

.03783

10223

3.3370

1.09829

.01086

Total

114 | P a g e

Descriptives

Q2.3

95% Confidence Interval for Mean

Lower Bound

Upper Bound

Minimum

Maximum

Easy access

3.2803

3.4182

1.00

5.00

Improved street lighting

2.8022

2.9319

1.00

5.00

Wider footpaths

3.4342

3.5639

1.00

5.00

Level footpaths

3.2373

3.3649

1.00

5.00

Clean sidewalks

3.4705

3.6047

1.00

5.00

Reduced traffic

3.2964

3.4311

1.00

5.00

Reduced speed

2.9313

3.0570

1.00

5.00

Remove obstacles

3.4464

3.5712

1.00

5.00

More crossing point

3.5212

3.6474

1.00

5.00

Weather proof

3.2908

3.4393

1.00

5.00

Total

3.3157

3.3583

1.00

5.00

115 | P a g e

ANOVA

Q2.3

Sum of Squares

Between Groups

Mean Square

509.746

56.638

Within Groups

11820.340

10213

1.157

Total

12330.086

10222

Sig.

48.937

.000

Post Hoc Tests Multiple Comparisons

Q2.3, LSD

95% Confidence Interval

Mean Difference (I) Variables

(J) Variables

Easy access

Improved street lighting

Std. Error

Sig.

Lower Bound

Upper Bound

.48221*

.04754

.000

.3890

.5754

Wider footpaths

-.14976*

.04753

.002

-.2429

-.0566

Level footpaths

.04819

.04754

.311

-.0450

.1414

Clean sidewalks

-.18837*

.04754

.000

-.2816

-.0952

Reduced traffic

-.01446

.04758

.761

-.1077

.0788

Reduced speed

.35514*

.04756

.000

.2619

.4484

-.15952*

.04753

.001

-.2527

-.0663

Remove obstacles

116 | P a g e

(I-J)

Improved street lighting

Wider footpaths

Level footpaths

117 | P a g e

More crossing point

-.23505

.04758

.000

-.3283

-.1418

Weather proof

-.01580

.04759

.740

-.1091

.0775

Easy access

-.48221

.04754

.000

-.5754

-.3890

Wider footpaths

-.63197

.04756

.000

-.7252

-.5387

Level footpaths

-.43402

.04757

.000

-.5273

-.3408

Clean sidewalks

-.67058

.04757

.000

-.7638

-.5773

Reduced traffic

-.49667*

.04760

.000

-.5900

-.4034

Reduced speed

-.12707*

.04758

.008

-.2203

-.0338

Remove obstacles

-.64173*

.04756

.000

-.7350

-.5485

More crossing point

-.71726*

.04760

.000

-.8106

-.6239

Weather proof

-.49801*

.04761

.000

-.5913

-.4047

Easy access

.14976

.04753

.002

.0566

.2429

Improved street lighting

.63197*

.04756

.000

.5387

.7252

Level footpaths

.19795*

.04756

.000

.1047

.2912

Clean sidewalks

-.03861

.04756

.417

-.1318

.0546

Reduced traffic

.13530*

.04759

.004

.0420

.2286

Reduced speed

.50489*

.04757

.000

.4117

.5981

Remove obstacles

-.00977

.04754

.837

-.1030

.0834

More crossing point

-.08529

.04759

.073

-.1786

.0080

Weather proof

.13396*

.04760

.005

.0406

.2273

Easy access

-.04819

.04754

.311

-.1414

.0450

Improved street lighting

Clean sidewalks

Reduced traffic

118 | P a g e

.04757

.000

.3408

.5273

.04756

.000

-.2912

-.1047

.43402

Wider footpaths

-.19795

Clean sidewalks

-.23656

.04757

.000

-.3298

-.1433

Reduced traffic

-.06265

.04760

.188

-.1560

.0307

Reduced speed

.30695

.04758

.000

.2137

.4002

Remove obstacles

-.20771

.04756

.000

-.3009

-.1145

More crossing point

-.28324*

.04760

.000

-.3765

-.1899

Weather proof

-.06399

.04761

.179

-.1573

.0293

Easy access

.18837*

.04754

.000

.0952

.2816

Improved street lighting

.67058*

.04757

.000

.5773

.7638

Wider footpaths

.03861

.04756

.417

-.0546

.1318

Level footpaths

.23656

.04757

.000

.1433

.3298

Reduced traffic

.17391*

.04760

.000

.0806

.2672

Reduced speed

.54351*

.04758

.000

.4502

.6368

Remove obstacles

.02885

.04756

.544

-.0644

.1221

More crossing point

-.04668

.04760

.327

-.1400

.0466

Weather proof

.17257*

.04761

.000

.0792

.2659

Easy access

.01446

.04758

.761

-.0788

.1077

Improved street lighting

.49667*

.04760

.000

.4034

.5900

Wider footpaths

-.13530*

.04759

.004

-.2286

-.0420

Level footpaths

.06265

.04760

.188

-.0307

.1560

Reduced speed

119 | P a g e

.04760

.000

-.2672

-.0806

.04761

.000

.2763

.4629

.04759

.002

-.2384

-.0518

-.17391

Reduced speed

.36960

Remove obstacles

-.14506

More crossing point

-.22059

.04764

.000

-.3140

-.1272

Weather proof

-.00134

.04765

.978

-.0947

.0921

Easy access

-.35514

.04756

.000

-.4484

-.2619

.12707*

.04758

.008

.0338

.2203

Wider footpaths

-.50489*

.04757

.000

-.5981

-.4117

Level footpaths

-.30695*

.04758

.000

-.4002

-.2137

Clean sidewalks

-.54351*

.04758

.000

-.6368

-.4502

Reduced traffic

-.36960*

.04761

.000

-.4629

-.2763

Remove obstacles

-.51466

.04757

.000

-.6079

-.4214

More crossing point

-.59018*

.04761

.000

-.6835

-.4969

Weather proof

-.37093*

.04763

.000

-.4643

-.2776

Easy access

.15952*

.04753

.001

.0663

.2527

Improved street lighting

.64173*

.04756

.000

.5485

.7350

Wider footpaths

.00977

.04754

.837

-.0834

.1030

Level footpaths

.20771*

.04756

.000

.1145

.3009

Clean sidewalks

-.02885

.04756

.544

-.1221

.0644

Reduced traffic

.14506*

.04759

.002

.0518

.2384

Reduced speed

.51466*

.04757

.000

.4214

.6079

Improved street lighting

Remove obstacles

Clean sidewalks

More crossing point

Weather proof

More crossing point

-.07552

.04759

.113

-.1688

.0178

Weather proof

.14373

.04760

.003

.0504

.2370

Easy access

.23505

.04758

.000

.1418

.3283

Improved street lighting

.71726

.04760

.000

.6239

.8106

Wider footpaths

.08529

.04759

.073

-.0080

.1786

Level footpaths

.28324

.04760

.000

.1899

.3765

Clean sidewalks

.04668

.04760

.327

-.0466

.1400

Reduced traffic

.22059*

.04764

.000

.1272

.3140

Reduced speed

.59018*

.04761

.000

.4969

.6835

Remove obstacles

.07552

.04759

.113

-.0178

.1688

Weather proof

.21925*

.04765

.000

.1258

.3127

Easy access

.01580

.04759

.740

-.0775

.1091

Improved street lighting

.49801*

.04761

.000

.4047

.5913

Wider footpaths

-.13396*

.04760

.005

-.2273

-.0406

Level footpaths

.06399

.04761

.179

-.0293

.1573

Clean sidewalks

-.17257*

.04761

.000

-.2659

-.0792

Reduced traffic

.00134

.04765

.978

-.0921

.0947

Reduced speed

.37093*

.04763

.000

.2776

.4643

Remove obstacles

-.14373*

.04760

.003

-.2370

-.0504

More crossing point

-.21925*

.04765

.000

-.3127

-.1258

*. The mean difference is significant at the 0.05 level.

120 | P a g e

Means Plots

121 | P a g e

T-Test (between walk and non-walk)

ANOVA

Sum of Squares

Q2.1 Rate the Pedestrian facilities

Q2.2 Prefer way to cross the road

Q2.3 Easy Access

Q2.3 Improved street lighting

Q2.3 Wider footpaths

Q2.3 Level footpaths

Between Groups

Sig

.142

Within Groups

528.065

1024

Total

528.207

1025

.021

Within Groups

418.674

1025

Total

418.695

1026

3.302

Within Groups

1291.660

1023

Total

1294.962

1024

2.113

Within Groups

1139.807

1021

Total

1141.920

1022

1.968

Within Groups

1142.031

1022

Total

1143.999

1023

1.512

1103.757

1021

Between Groups

Within Groups

122 | P a g e

0.600

0.821

0.106

.0169

0.185

0.237

Total

Q2.3 Clean sidewalks

Q2.3 Reduced traffic

Q2.3 Reduced speed

Q2.3 Remove obstacles

Q2.3 More crossing point

Q2.3 Weather proof

123 | P a g e

1105.269

1022

.069

Within Groups

1222.232

1021

Total

1222.301

1022

.663

Within Groups

1223.394

1018

Total

1224.058

1019

.117

Within Groups

1069.848

1020

Total

1069.965

1021

.263

Within Groups

1059.658

1022

Total

1059.921

1023

.905

Within Groups

1072.844

1018

Total

1073.749

1019

.309

Within Groups

1483.887

1017

Total

1484.196

1018

Between Groups

0.810

0.458

0.739

0.615

0.354

0.646

Crosstab between Q 2.2 and Q 2.4

Chi-Square Tests

Value

Asymp. Sig. (2-sided)

.054

18.587

.099

Linear-by-Linear Association

2.984

.084

N of Valid Cases

1017

Pearson Chi-Square

Likelihood Ratio

20.787

a. 6 cells (28.6%) have expected count less than 5. The minimum expected count is .45.

124 | P a g e

ANOVA (Q 2.6 and Q 2.3) ANOVA

Sum of Squares

Q2.1 Rate the Pedestrian facilities

Q2.3 Easy Access

Q2.3 Improved street lighting

Q2.3 Wider footpaths

Q2.3 Level footpaths

Q2.3 Clean sidewalks

125 | P a g e

Between Groups

Sig

1.673

Within Groups

524.488

1020

Total

526.160

1021

.163

Within Groups

1284.791

1019

Total

1284.954

1020

14.763

Within Groups

1118.352

1017

Total

1133.115

1018

5.643

Within Groups

1135.356

1018

Total

1140.999

1019

3.258

Within Groups

1100.852

1017

Total

1104.110

1018

16.154

Within Groups

1201.141

1017

Total

1217.295

1018

Between Groups

0.072

0.719

0.000

0.025

0.083

0.000

Q2.3 Reduced traffic

Q2.3 Reduced speed

Q2.3 Remove obstacles

Q2.3 More crossing point

Q2.3 Weather proof

126 | P a g e

Between Groups

4.476

Within Groups

1215.319

1014

Total

1219.795

1015

5.493

Within Groups

1058.491

1016

Total

1063.984

1017

8.958

Within Groups

1047.923

1018

Total

1056.881

1019

10.291

Within Groups

1060.598

1014

Total

1070.889

1015

12.906

Within Groups

1470.217

1013

Total

1483.123

1014

Between Groups

0.054

0.022

0.003

0.002

0.003

127 | P a g e

128 | P a g e

129 | P a g e

130 | P a g e

131 | P a g e

132 | P a g e

133 | P a g e

Chi Square test (Walking/non-walking mode vs Q2.4, Q2.5, Q2.6)

Q1.1 Walk/Traffic Mode * Q2.4 Willing to walk to access crossing Chi-Square Tests

Value

Asymp. Sig. (2-sided)

6.756a

.344

Likelihood Ratio

6.774

.342

Linear-by-Linear Association

1.156

.282

N of Valid Cases

1019

Pearson Chi-Square

a. 2 cells (14.3%) have expected count less than 5. The minimum expected count is 1.95.

Q1.1 Walk/Traffic Mode * Q2.5 When do you think you are most exposed to air pollution Chi-Square Tests

Value

Asymp. Sig. (2-sided)

3.865a

.795

3.839

.798

Linear-by-Linear Association

.012

.912

N of Valid Cases

1016

Pearson Chi-Square

Likelihood Ratio

a. 5 cells (31.3%) have expected count less than 5. The minimum expected count is 2.34.

134 | P a g e

Q1.1 Walk/Traffic Mode * Q2.6 Do you plan to change mode Chi-Square Tests

Value

Asymp. Sig. (2-sided)

.980

Continuity Correction

.000

1.000

Likelihood Ratio

.001

.980

Pearson Chi-Square

.001

Fisher's Exact Test

1.000

Linear-by-Linear Association

.001

N of Valid Cases

1025

a. 0 cells (.0%) have expected count less than 5. The minimum expected count is 118.82.

b. Computed only for a 2x2 table

135 | P a g e

Exact Sig. (2-sided)

.980

Exact Sig. (1-sided)

.517

Chi-Square test for Q2.2 vs Q2.3

Q2.2 Prefer way to cross the road * Q2.3 Easy Access Chi-Square Tests

Value

Asymp. Sig. (2-sided)

.122

14.219

.076

Linear-by-Linear Association

1.060

.303

N of Valid Cases

1023

Pearson Chi-Square

Likelihood Ratio

12.727

a. 0 cells (.0%) have expected count less than 5. The minimum expected count is 5.76.

Q2.2 Prefer way to cross the road * Q2.3 Improved street lighting Chi-Square Tests

Value

Asymp. Sig. (2-sided)

1.621a

.991

1.580

.991

Linear-by-Linear Association

.104

.748

N of Valid Cases

1021

Pearson Chi-Square

Likelihood Ratio

a. 0 cells (.0%) have expected count less than 5. The minimum expected count is 5.86.

Q2.2 Prefer way to cross the road * Q2.3 Wider footpaths Chi-Square Tests

136 | P a g e

Value

Asymp. Sig. (2-sided)

.680

5.858

.663

Linear-by-Linear Association

.162

.687

N of Valid Cases

1022

Pearson Chi-Square

Likelihood Ratio

5.710

a. 1 cells (6.7%) have expected count less than 5. The minimum expected count is 2.88.

Q2.2 Prefer way to cross the road * Q2.3 Level footpaths Chi-Square Tests

Value

Asymp. Sig. (2-sided)

7.976a

.436

Likelihood Ratio

7.958

.438

Linear-by-Linear Association

2.241

.134

N of Valid Cases

1021

Pearson Chi-Square

a. 1 cells (6.7%) have expected count less than 5. The minimum expected count is 4.55.

Q2.2 Prefer way to cross the road * Q2.3 Clean sidewalks Chi-Square Tests

Value

Asymp. Sig. (2-sided)

8.626a

.375

8.948

.347

Linear-by-Linear Association

.084

.772

N of Valid Cases

1021

Pearson Chi-Square

Likelihood Ratio

137 | P a g e

Chi-Square Tests

Value

Asymp. Sig. (2-sided)

.375

8.948

.347

Linear-by-Linear Association

.084

.772

N of Valid Cases

1021

Pearson Chi-Square

Likelihood Ratio

8.626

a. 1 cells (6.7%) have expected count less than 5. The minimum expected count is 3.24.

Q2.2 Prefer way to cross the road * Q2.3 Reduced traffic Chi-Square Tests

Value

Asymp. Sig. (2-sided)

18.456a

.018

19.678

.012

Linear-by-Linear Association

2.774

.096

N of Valid Cases

1018

Pearson Chi-Square

Likelihood Ratio

a. 1 cells (6.7%) have expected count less than 5. The minimum expected count is 4.43.

Q2.2 Prefer way to cross the road * Q2.3 Reduced speed Chi-Square Tests

Value

Asymp. Sig. (2-sided)

21.571a

.006

Likelihood Ratio

20.447

.009

Linear-by-Linear Association

11.822

.001

Pearson Chi-Square

N of Valid Cases

138 | P a g e

1020

Chi-Square Tests

Value

Asymp. Sig. (2-sided)

.006

Likelihood Ratio

20.447

.009

Linear-by-Linear Association

11.822

.001

Pearson Chi-Square

N of Valid Cases

21.571

1020

a. 0 cells (.0%) have expected count less than 5. The minimum expected count is 6.85.

Q2.2 Prefer way to cross the road * Q2.3 Remove obstacles Chi-Square Tests

Value

Asymp. Sig. (2-sided)

11.276a

.187

11.451

.177

Linear-by-Linear Association

.838

.360

N of Valid Cases

1022

Pearson Chi-Square

Likelihood Ratio

a. 2 cells (13.3%) have expected count less than 5. The minimum expected count is 1.89.

Q2.2 Prefer way to cross the road * Q2.3 More crossing point Chi-Square Tests

Value

Asymp. Sig. (2-sided)

8.365a

.399

Likelihood Ratio

8.480

.388

Linear-by-Linear Association

1.084

.298

N of Valid Cases

1018

Pearson Chi-Square

139 | P a g e

Chi-Square Tests

Value

Asymp. Sig. (2-sided)

.399

Likelihood Ratio

8.480

.388

Linear-by-Linear Association

1.084

.298

N of Valid Cases

1018

Pearson Chi-Square

8.365

a. 1 cells (6.7%) have expected count less than 5. The minimum expected count is 2.98.

Q2.2 Prefer way to cross the road * Q2.3 Weather proof Chi-Square Tests

Value

Asymp. Sig. (2-sided)

7.284a

.506

Likelihood Ratio

8.247

.410

Linear-by-Linear Association

1.236

.266

N of Valid Cases

1017

Pearson Chi-Square

a. 0 cells (.0%) have expected count less than 5. The minimum expected count is 8.05.

140 | P a g e

ANNEX 7 Results of the Pedestrian Preference Survey TRAFFIC MODE COUNT FREQUENCY Number of mode Frequency Table Q1.1 Number of mode

Frequency

Valid

Percent

Valid Percent

Cumulative Percent

1.00

126

12.2

2.00

465

45.2

57.4

3.00

247

24.0

81.4

4.00

120

11.7

93.1

5.00

4.8

97.9

6.00

1.4

99.2

7.00

99.6

8.00

100.0

Total

1029

100.0

141 | P a g e

Major Transport Mode Q1.1 Transport Mode

Frequency

Valid

walk

Percent

Valid Percent

Cumulative Percent

401

39.0

39.4

344

33.4

72.8

Two Wheeler

5.2

77.9

Car/Taxi

1.9

79.9

Mini Bus

2.0

81.9

174

16.9

98.8

1.2

100.0

1029

100.0

Cycle

MTR

Bus

Others

Total

142 | P a g e

143 | P a g e

Transport Mode (Walk/Vehicle) Q1.1 Walk/Traffic Mode

Frequency

Valid

Percent

Valid Percent

Cumulative Percent

Walk

401

39.0

Vehicle

628

61.0

100.0

1029

100.0

Total

144 | P a g e

Selected cases for worst and bad in question 2.1

Frequency Table Q2.3 Easy Access

Frequency

Valid

Valid Percent

Cumulative Percent

The least wanted

3.7

Less wanted

19.0

19.2

22.9

Fair

30.0

30.3

53.1

Wanted

28.6

28.8

81.9

The most wanted

17.9

18.1

100.0

271

99.3

100.0

273

100.0

Total

Missing

Percent

System

Total

145 | P a g e

146 | P a g e

Q2.3 Improved street lighting

Frequency

Valid

Valid Percent

Cumulative Percent

The least wanted

11.0

Less wanted

23.8

23.9

34.9

100

36.6

36.8

71.7

Wanted

21.6

21.7

93.4

The most wanted

6.6

100.0

272

99.6

100.0

273

100.0

Fair

Total

Missing

Percent

System

Total

147 | P a g e

148 | P a g e

Q2.3 Wider footpaths

Frequency

Valid

Valid Percent

Cumulative Percent

The least wanted

4.4

Less wanted

19.0

19.2

23.6

Fair

28.9

29.2

52.8

Wanted

31.5

31.7

84.5

The most wanted

15.4

15.5

100.0

271

99.3

100.0

273

100.0

Total

Missing

Percent

System

Total

149 | P a g e

150 | P a g e

Q2.3 Level footpaths

Frequency

Valid

Valid Percent

Cumulative Percent

The least wanted

7.3

7.4

Less wanted

24.9

25.0

32.4

Fair

33.3

33.5

65.8

Wanted

24.9

25.0

90.8

The most wanted

9.2

100.0

272

99.6

100.0

273

100.0

Total

Missing

Percent

System

Total

151 | P a g e

152 | P a g e

Q2.3 Clean sidewalks

Frequency

Valid

Valid Percent

Cumulative Percent

The least wanted

3.7

Less wanted

15.4

15.5

19.2

Fair

34.4

34.7

53.9

Wanted

25.6

25.8

79.7

The most wanted

20.1

20.3

100.0

271

99.3

100.0

273

100.0

Total

Missing

Percent

System

Total

153 | P a g e

154 | P a g e

Q2.3 Reduced traffic

Frequency

Valid

Valid Percent

Cumulative Percent

The least wanted

4.8

Less wanted

22.3

22.6

27.4

Fair

29.3

29.6

57.0

Wanted

25.6

25.9

83.0

The most wanted

16.8

17.0

100.0

270

98.9

100.0

1.1

273

100.0

Total

Missing

Percent

System

Total

155 | P a g e

156 | P a g e

Q2.3 Reduced speed

Frequency

Valid

Valid Percent

Cumulative Percent

The least wanted

9.9

10.0

Less wanted

27.1

27.4

37.4

109

39.9

40.4

77.8

Wanted

15.8

15.9

93.7

The most wanted

6.2

6.3

100.0

270

98.9

100.0

1.1

273

100.0

Fair

Total

Missing

Percent

System

Total

157 | P a g e

158 | P a g e

Q2.3 Remove obstacles

Frequency

Valid

The least wanted

Valid Percent

Cumulative Percent

2.6

19.4

19.6

22.2

100

36.6

37.0

59.3

Wanted

24.2

24.4

83.7

The most wanted

16.1

16.3

100.0

270

98.9

100.0

1.1

273

100.0

Less wanted

Fair

Total

Missing

Percent

System

Total

159 | P a g e

160 | P a g e

Q2.3 More crossing point

Frequency

Valid

The least wanted

Valid Percent

Cumulative Percent

3.3

Less wanted

11.4

14.8

Fair

35.5

35.8

50.6

Wanted

29.3

29.5

80.1

The most wanted

19.8

19.9

100.0

271

99.3

100.0

273

100.0

Total

Missing

Percent

System

Total

161 | P a g e

162 | P a g e

Q2.3 Weather proof

Frequency

Valid

Valid Percent

Cumulative Percent

The least wanted

11.4

11.5

Less wanted

12.8

13.0

24.4

Fair

30.8

31.1

55.6

Wanted

25.3

25.6

81.1

The most wanted

18.7

18.9

100.0

270

98.9

100.0

1.1

273

100.0

Total

Missing

Percent

System

Total

163 | P a g e

164 | P a g e

Average Travel time and travel distance for each mode Major mode = walking

Frequency Table Q1.2 Average Travel Time

Frequency

Valid

Percent

Valid Percent

Cumulative Percent

<=15 min

16.5

16-30 min

125

31.2

47.6

31-45 min

101

25.2

72.8

46-60 min

13.5

86.3

61-75 min

4.5

90.8

76-90 min

1.7

92.5

> 90 min

7.5

100.0

401

100.0

Total

Q1.3 Average Travel Distance

Frequency

Valid

Percent

Valid Percent

Cumulative Percent

<=3 km

126

31.4

31.5

3-6 km

16.2

16.3

47.8

6-9 km

12.0

59.8

9-12 km

10.5

70.3

12-15 km

7.5

77.8

165 | P a g e

> 15 km

Total

Missing

System

Total

166 | P a g e

22.2

22.3

400

99.8

100.0

401

100.0

Major mode = Cycle Q1.2 Average Travel Time

Frequency

Valid

Percent

Valid Percent

Cumulative Percent

16-30 min

50.0

31-45 min

25.0

75.0

> 90 min

25.0

100.0

Total

100.0

Q1.3 Average Travel Distance

Frequency

Valid

Percent

Valid Percent

Cumulative Percent

3-6 km

50.0

> 15 km

50.0

100.0

Total

100.0

167 | P a g e

Major mode = MTR Frequency Table Q1.2 Average Travel Time

Frequency

Valid

Percent

Valid Percent

Cumulative Percent

<=15 min

16-30 min

12.5

12.8

31-45 min

24.4

37.2

46-60 min

106

30.8

68.0

61-75 min

14.8

82.8

76-90 min

6.7

89.5

> 90 min

10.5

100.0

344

100.0

Total

Q1.3 Average Travel Distance

Frequency

Valid

Percent

Valid Percent

Cumulative Percent

<=3 km

2.0

3-6 km

6.7

8.7

6-9 km

7.3

16.0

9-12 km

15.1

15.2

31.2

12-15 km

12.8

44.0

> 15 km

192

55.8

56.0

100.0

Total

343

99.7

100.0

168 | P a g e

Missing

System

Total

169 | P a g e

344

100.0

Major mode = two wheeler Q1.2 Average Travel Time

Frequency

Valid

Percent

Valid Percent

Cumulative Percent

16-30 min

20.8

31-45 min

28.3

49.1

46-60 min

26.4

75.5

61-75 min

11.3

86.8

76-90 min

5.7

92.5

> 90 min

7.5

100.0

Total

Q1.3 Average Travel Distance

Frequency

Valid

Percent

Valid Percent

Cumulative Percent

<=3 km

9.4

3-6 km

5.7

15.1

6-9 km

18.9

34.0

9-12 km

11.3

45.3

12-15 km

9.4

54.7

> 15 km

45.3

100.0

Total

100.0

170 | P a g e

171 | P a g e

Major mode = Car/taxi

Frequency Table Q1.2 Average Travel Time

Frequency

Valid

Percent

Valid Percent

Cumulative Percent

16-30 min

30.0

31-45 min

30.0

60.0

46-60 min

20.0

80.0

61-75 min

5.0

85.0

> 90 min

15.0

100.0

Total

Q1.3 Average Travel Distance

Frequency

Valid

Percent

Valid Percent

Cumulative Percent

<=3 km

5.0

3-6 km

15.0

20.0

6-9 km

20.0

40.0

9-12 km

10.0

50.0

12-15 km

5.0

55.0

> 15 km

45.0

100.0

Total

172 | P a g e

173 | P a g e

Major mode = Mini Bus Frequency Table Q1.2 Average Travel Time

Frequency

Valid

Percent

Valid Percent

Cumulative Percent

<=15 min

4.8

16-30 min

28.6

33.3

31-45 min

47.6

81.0

46-60 min

9.5

90.5

61-75 min

4.8

95.2

> 90 min

4.8

100.0

Total

Q1.3 Average Travel Distance

Frequency

Valid

Percent

Valid Percent

Cumulative Percent

<=3 km

4.8

3-6 km

14.3

19.0

6-9 km

9.5

28.6

9-12 km

9.5

38.1

12-15 km

9.5

47.6

> 15 km

52.4

100.0

Total

100.0

174 | P a g e

175 | P a g e

Major mode = Bus

Frequency Table

Q1.2 Average Travel Time

Frequency

Valid

Percent

Valid Percent

Cumulative Percent

<=15 min

1.1

16-30 min

10.9

12.1

31-45 min

27.6

39.7

46-60 min

31.0

70.7

61-75 min

14.4

85.1

76-90 min

6.9

92.0

> 90 min

8.0

100.0

174

100.0

Total

Q1.3 Average Travel Distance

Frequency

Valid

Percent

Valid Percent

Cumulative Percent

<=3 km

5.2

3-6 km

6.3

6.4

11.6

6-9 km

14.9

15.1

26.7

9-12 km

13.2

13.4

40.1

12-15 km

11.5

11.6

51.7

176 | P a g e

> 15 km

Total

Missing

System

Total

177 | P a g e

47.7

48.3

172

98.9

100.0

1.1

174

100.0

Major mode = others Frequency Table Q1.2 Average Travel Time

Frequency

Valid

Percent

Valid Percent

Cumulative Percent

16-30 min

25.0

31-45 min

41.7

66.7

46-60 min

16.7

83.3

61-75 min

8.3

91.7

76-90 min

8.3

100.0

Total

Q1.3 Average Travel Distance

Frequency

Valid

Percent

Valid Percent

Cumulative Percent

<=3 km

8.3

6-9 km

25.0

33.3

9-12 km

8.3

41.7

12-15 km

16.7

58.3

> 15 km

41.7

100.0

Total

178 | P a g e

179 | P a g e

ANNEX 8 Results of the Pedestrian Preference Survey Single mode of transport

Frequency Table of Single walking mode

Gender Q3.1 Gender

Frequency

Valid

Valid Percent

Cumulative Percent

Male

54.0

54.4

Female

45.2

45.6

100.0

125

99.2

100.0

126

100.0

Total

Missing

Percent

System

Total

180 | P a g e

181 | P a g e

AGE Q3.2 Age

Frequency

Valid

Valid Percent

Cumulative Percent

<=15 Years old

5.6

16-30 Years old

57.9

58.4

64.0

31-45 Years old

20.6

20.8

84.8

46-60 Years old

13.5

13.6

98.4

> 60 Years old

1.6

100.0

125

99.2

100.0

126

100.0

Total

Missing

Percent

System

Total

182 | P a g e

183 | P a g e

Household Income

Frequency Table

Q3.3 Household Income

Frequency

Valid

Valid Percent

Cumulative Percent

<$4000

8.7

8.9

$4000-$15999

38.1

38.7

47.6

$16000-$27999

31.0

31.5

79.0

$28000-$39999

8.7

8.9

87.9

>40000

11.9

12.1

100.0

124

98.4

100.0

1.6

126

100.0

Total

Missing

Percent

System

Total

184 | P a g e

185 | P a g e

Average Travel Time

Frequency Table Q1.2 Average Travel Time

Frequency

Valid

Percent

Valid Percent

Cumulative Percent

<=15 min

33.3

16-30 min

29.4

62.7

31-45 min

23.8

86.5

46-60 min

7.9

94.4

61-75 min

1.6

96.0

76-90 min

1.6

97.6

> 90 min

2.4

100.0

126

100.0

Total

186 | P a g e

187 | P a g e

Average Travel Distance

Frequency Table

Q1.3 Average Travel Distance

Frequency

Valid

Percent

Valid Percent

Cumulative Percent

<=3 km

52.4

3-6 km

7.9

60.3

6-9 km

6.3

66.7

9-12 km

7.1

73.8

12-15 km

4.8

78.6

> 15 km

21.4

100.0

126

100.0

Total

Bar Chart

188 | P a g e

189 | P a g e

ANNEX 9 Results of the Pedestrian Preference Survey Frequency Analysis by Age Groups

Frequencies (For age <15)

Q1.1 Transport Mode

Frequency

Valid

Percent

Valid Percent

Cumulative Percent

walk

64.5

MTR

19.4

83.9

Mini Bus

3.2

87.1

Bus

6.5

93.5

Others

6.5

100.0

Total

190 | P a g e

191 | P a g e

Frequencies (For 16 < age <30)

Q1.1 Transport Mode

Frequency

Valid

walk

Percent

Valid Percent

Cumulative Percent

208

35.8

36.3

217

37.3

73.7

6.9

80.6

Car/Taxi

1.2

81.8

Mini Bus

82.4

17.0

99.5

100.0

581

100.0

Cycle

MTR

Two Wheeler

Bus

Others

Total

192 | P a g e

193 | P a g e

Frequencies (For 31 < age < 45)

Q1.1 Transport Mode

Frequency

Valid

Percent

Valid Percent

Cumulative Percent

walk

38.8

MTR

32.1

70.9

Two Wheeler

2.6

73.5

Car/Taxi

3.1

76.5

Mini Bus

3.6

80.1

17.9

98.0

2.0

100.0

196

100.0

Bus

Others

Total

194 | P a g e

195 | P a g e

Frequencies (For 46 < age < 60)

Q1.1 Transport Mode

Frequency

Valid

Percent

Valid Percent

Cumulative Percent

walk

42.1

Cycle

42.7

MTR

27.0

69.7

Two Wheeler

3.4

73.0

Car/Taxi

3.9

77.0

Mini Bus

3.4

80.3

18.0

98.3

1.7

100.0

178

100.0

Bus

Others

Total

196 | P a g e

197 | P a g e

Frequencies (For age > 60)

Q1.1 Transport Mode

Frequency

Valid

Percent

Valid Percent

Cumulative Percent

walk

50.0

MTR

23.8

73.8

Two Wheeler

4.8

78.6

Mini Bus

7.1

85.7

Bus

14.3

100.0

Total

100.0

198 | P a g e

199 | P a g e

ANNEX 10

Results of the Pedestrian Preference Survey Frequency Analysis by Household Income

Frequencies (Household income < $4000)

Q1.1 Transport Mode

Frequency

Valid

Percent

Valid Percent

Cumulative Percent

walk

47.8

Cycle

1.1

48.9

MTR

30.4

79.3

Two Wheeler

4.3

83.7

Car/Taxi

3.3

87.0

Bus

13.0

100.0

Total

100.0

200 | P a g e

201 | P a g e

Frequencies ($4000 < Household income < $15999)

Q1.1 Transport Mode

Frequency

Valid

walk

Cycle

MTR

Two Wheeler

Mini Bus

Bus

Others

Total

202 | P a g e

Percent

Valid Percent

Cumulative Percent

119

34.4

35.0

129

37.3

72.3

9.0

81.2

1.4

82.7

16.2

98.8

1.2

100.0

346

100.0

203 | P a g e

Frequencies ($16000 < Household income < $27999)

Q1.1 Transport Mode

Frequency

Valid

Percent

Valid Percent

Cumulative Percent

walk

140

42.4

MTR

100

30.3

72.7

3.3

76.1

Car/Taxi

1.8

77.9

Mini Bus

3.0

80.9

Bus

18.2

99.1

100.0

330

100.0

Two Wheeler

Others

Total

204 | P a g e

205 | P a g e

Frequencies ($28000 < Household income < $39999)

Q1.1 Transport Mode

Frequency

Valid

Percent

Valid Percent

Cumulative Percent

walk

39.2

MTR

34.5

73.6

Two Wheeler

4.1

77.7

Car/Taxi

78.4

Mini Bus

2.7

81.1

18.2

99.3

100.0

148

100.0

Bus

Others

Total

206 | P a g e

207 | P a g e

Frequencies (Household income > $40000)

Q1.1 Transport Mode

Frequency

Valid

Percent

Valid Percent

Cumulative Percent

walk

35.0

Cycle

1.0

35.9

MTR

29.1

65.0

1.0

66.0

Car/Taxi

9.7

75.7

Mini Bus

1.9

77.7

18.4

96.1

3.9

100.0

103

100.0

Two Wheeler

Bus

Others

Total

208 | P a g e

209 | P a g e