Understanding Human Walking Behaviour in relation to

Built Environment: A Mobile GIS Approach (With Special Reference to Educational Environments)

S.N Weerasinghe1, D. Dissanayake2

1School of Environment, Education and Development, University of Manchester 2School of Architecture and Built Environment, Deakin University

January 02, 2017

Summary

Whilst generally acknowledged as a critical component of urban design and planning, designing of

pedestrian-friendly urban environments is frequently overlooked in planning practice in Sri Lanka.

One of the main causes for this is the insufficient attention paid to understanding how strongly and in

what aspect human walking behaviour is influenced by the condition of the built environment. This

work comprises a novel approach to the study of human walking behaviour in relation to built

environment, whereby an existing framework is further developed to understand actual walking

behaviour of humans.

KEYWORDS: Human Walking Behaviour, Built Environment, Mobile GIS, Walkability

1. Introduction

Streets are a critical component of the built environment and are the most public of the urban spaces in

a city. In urban planning and design, a holistic understanding of the role of pedestrians is crucial to

designing user friendly environment as walking plays an important role as a mean of viable mode of

transportation. Even though, rapid growth and construction in cities have a tremendous impact on the

relationship between the pedestrians and built environment, there has thus far been no specific attempt

to translate this ideal into a built environment that encourages pedestrian travel (Rahman et al., 2015).

Walkability and pedestrian behaviour is essentially a concept that is not only difficult to define, but

also difficult to measure (Rahman et al., 2015). Until fairly recent years, the notion of walkability and

pedestrian behaviour has not even been taken into account when designing urban environments and

the idea of human walking behaviour in space has unconditionally taken a back seat to the more

overshadowing objective of facilitating the vehicle flow and accommodating automobiles.

Characterising walkability and pedestrian behaviour extends beyond pedestrian concerns, as the ability

to walk in a neighbourhood shows not just a type of mobility, but also a type of friendliness between

neighbours, which, together, influence the physical and mental health of individuals in the community

(Fotino, 2015). Marchand (1974), in his study on the effect of crowding on the pedestrian behaviour,

identifies that pedestrians tend to follow the simplest route in terms of directional changes, which, in

fact, makes it clear that movement patterns of pedestrians have transcended the effects of familiarity

with the environment, pedestrian congestion and vehicular movements.

Saelens and Handy (2008) defines built environment as a part of the physical environment which

comprises of land use patterns, space of activities and the buildings that house them, transportation

system, physical infrastructure such as roads, sidewalks, cycling paths, railway network etc. and the

service they provide and lastly the arrangement and appearance of physical elements in a community

that are constructed by human activity. A key aspect in planning and designing such environments is

to understand how different situations, conditions and facilities influence human walking behaviour.

Evaluating walkability and studying pedestrian behaviour is a priority for scholars in the field today,

as a means to alleviating the considerable stresses placed on built environment. Designing of

pedestrian-friendly environments is receiving more significance for its various benefits attached to

public health, sustainability, economy and social life. Precedent studies on human walking behaviour

and walkability clearly shows that pedestrian behaviour is related to the condition of the built

environment in which it takes place, through statistical analyses between the amount of time spent on

walking and the influential factors of built environment (Eunyoung, 2013). Although, many of the

studies on walkability and pedestrian behaviour often measure and analyse walking by the amount of

time spent on walking by individuals, there are some urban design researches that deal with pedestrian

behaviour and its relation to the built environment. Those studies mainly focus on flows and degrees

of presence, number of walkers and how such behaviour is affected by space or place and vice versa

(Ewing et al., 2006).

Nevertheless, approaches taken to study pedestrian behaviour are often observational studies which

use questionnaire surveys, one-to-one interviews and trip diaries to investigate pedestrian flows in a

given part of the built environment (Eunyoung, 2013). Whilst these studies have been able to output

different factors that influence walking behaviour, especially in terms of where people walk, they are

of limited use without incorporating the meanings of these pedestrian flows and their individual routes

(Eunyoung, 2013). Thus, as well as the attempt to identify what qualitative factors in an educational

environment determine the nature of human walking behaviour and their route choices, this work will

also comprise an attempt to further develop an existing framework that will offer a new layer to these

types of studies which will provide insights into processes and actual movements of people.

2. Methodology

University of Moratuwa in Sri Lanka (Figure 1) was selected as the study area for this research.

University of Moratuwa premises is a well-functioning place with a variety of activities taking place

within the premises. Origins of the students, academic staff, non-academic staff and others differ from

each other as some use the front entrance whilst some rear entrance. Their destinations also differ

according to their needs. Majority of the students come to the University on foot and that makes the

University purely a pedestrian environment where people take different routes each day to arrive at

their destinations within the University.

The study focused only on one particular user group i.e. the undergraduates of group 2013/2014

(Level 2 students) of the University. Sample for the study has been selected based on a few criteria:

presence of students in the University during the period of data collection, students who are still in the

process of familiarising with the University environment, students who include the road segment from

front entrance to the shrine room in their daily walking route, representation of all three faculties and

students who use smart phones with Android Operating System (OS). Using the stratified and random

sampling methods, a sample of 30 was selected for this study.

For the purpose of this study, both qualitative and quantitative data was required. Observations, survey

questionnaires, photographs, videos, voice recordings and GPS tracking were the methods of data

collection and collected data was analysed through tabular analysis in MS Excel, QGIS, ArcMap 10.0

and Sketch Up. Main method of collecting data was using the GPS in smart phones to track pedestrian

movements and they were followed by a structured questionnaire through which their preferences and

opinions on their selected route were gathered. Human movements were tracked using an Android

application called ‘My Tracks’ (Figure 2) which is freely available in the Google Play Store. This

mobile application enabled to capture routes with points of crossing, points of origin and destination,

total distance, total time taken to reach destination, moving time, average speed, maximum and

minimum elevation, time and date of the activity and the direction of movement of pedestrians.

Subjects of the sample were able to do their natural walk though they knew they were being tracked,

as they could lock their mobile phones without closing the application and carry it in their pockets as

they usually do. Subjects were tracked two times a day; in the morning hours and afternoon hours.

Tracks of subjects were emailed to the authors in the KML (Keyhole Mark-up Language) format at the

end of the day.

Figure 1: Map of University of Moratuwa premises. Produced by authors.

Further, voice clips recorded by the subjects at the time of movement were also used in order to better

understand the actual qualitative factors that influenced their walking behaviour. In addition,

photographs and videos of the subjects were taken as a part of direct observations.

Figure 2: My Tracks application for Android OS. Captured by authors from Google Play Store for

Google My Tracks on Android

Methods of Data Collection

Questionnaire Survey

GPS – Mobile Phone

Photographs

Direct Observations

Voice Recordings

Videos

GPX Tracks

Pedestrians’

perceptions

Pedestrians’

perceptions

Pedestrian behaviour

in built environment

Streetscape, serial

vision

Pedestrian behaviour

Figure 3: Data collection methods and types of data collected. Diagrammed by authors.

3. Analysis and Results

In order to achieve the pre-determined aims: to identify what factors in an educational environment

determine the nature of human walking behaviour and to further develop an existing framework to

explore and analyse actual human movements in relation to a given environment, data has been

analysed based on two criteria as follows:

Using ArcMap 10.0 and QGIS 1.8.0 applications, collected tracks were imported onto the plan of

University of Moratuwa. Thus, using these layers, pedestrian behaviour in the morning and afternoon

hours was spatially diagrammed separately taking into account the gender aspect as well. The purpose

of categorizing the tracks according to the gender and time of the day was to identify whether the

pedestrian behaviour differed extensively between these categories. Further, as the next stage, each

map was further analysed along with corresponding voice recordings, videos, serial vision

photographs, time series photographs and the data obtained from follow-up questionnaire survey.

Analysis

Spatial diagramming of

pedestrian behaviour

Tabular analysis

(Descriptive Statistics

and Formal Analysis)

Analyse counts and

percentages related to

pedestrian behaviour

Visually identify converging points or

areas and patterns of routes

Identify influencing factors

for such behaviour/pattern

Understand the

meanings of such

pedestrian behaviour

Voice recordings

Videos

Morning hours’

male pedestrian

behaviour

Morning hours’

female pedestrian

behaviour

Afternoon hours’

male pedestrian

behaviour

Afternoon hours’

female pedestrian

behaviour

Figure 4: Analysis process. Diagrammed by authors.

High

density of

pedestrian

movement

Library

Front Entrance

Sumanadasa

Building

Figure 5: Movement paths of pedestrians – spatial diagramming of collected tracks

without processing. Produced by authors.

Figure 6: Heat map of male pedestrian behavior in the morning, with the count of points in

a radius of 6 metres. Produced by authors.

Library Front

Entrance

Sumanadasa

Building High

concentration

of pedestrian

movement

Figure 7: Heat map of female pedestrian behavior in the morning, with the count of points

in a radius of 6 metres. Produced by authors.

Library Front

Entrance

Sumanadasa

Building

High

concentration of

pedestrian

movement

Figure 8: Heat map of male pedestrian behavior in the afternoon, with the count of points

in a radius of 6 metres. Produced by authors.

Library Front

Entrance

Sumanadasa

Building

High

concentration of

pedestrian

movement

Library Front

Entrance

Sumanadasa

Building

High

concentration of

pedestrian

movement

Based on the pattern of pedestrian movements in different times of day and gender, it is safe to state

that the road segment from front entrance to the beginning of Sumanadasa Building has the highest

concentration of pedestrian movement (Figures 5-9). Therefore, more concern was given to this

segment when studying the pedestrian behaviour in relation to the built environment.

Figure 10: 3D Sketch-Up model with GPS tracks. Produced by authors.

Figure 9: Heat map of female pedestrian behavior in the afternoon, with the count of

points in a radius of 6 metres. Produced by authors.

Qualitative factors influencing human walking behaviour in the university environment were

identified mainly in terms of movement pattern and speed variation of pedestrians. It was clear from

the analysis that convenience was the main factor out of many which influenced the movement

patterns of 46.67% of the sample and this was attributed by buildings and vegetation providing shade

and shelter, subjects been attracted to posters and banners displayed in the premises, subjects been

soothed by colour, texture and material of buildings and surfaces and familiarity of buildings.

4. Conclusion

Most previous approaches to the investigation of human walking behaviour in the context of a built

environment utilise conventional methodologies such as survey questionnaires, direct observations and

one-to-one interviews. The approach used in this study which incorporates Mobile GIS and voice

recording provides the facility to capture real-time and actual pedestrian movements along with their

thoughts and feelings throughout the journey of walking from one point to another, till they reach the

destination.

Looking at these three angles on the value of Mobile GIS in relation to other methods of urban

research, most important is that this knowledge provides visually accurate and combinable arguments

and as such a novel evidence base for projecting and predicting future urban developments. The strong

feature of this method is the combination of spatial-temporal data (behaviour in space and time),

spatial conditions and characteristics of the trips. Thus, such methodology can provide deeper insights

into how pedestrians react to various built environment attributes.

Further, this study has identified several aesthetic and internal (how people perceive an environment)

factors that influence pedestrian behaviour in a given environment and it also reveals that the human

walking behaviour can be better understood as a combination of conscious and unconscious decisions

taken by pedestrians in relation to the built environment.

Figure 11: Further developed framework to capture actual human walking behaviour.

Diagrammed by authors.

Spatial Diagramming

+

Accuracy

Recording of individual

qualitative aspects

+

Validation

GPS tracking + Audio recording analysis + Questionnaire survey + Video clips

5. Biography

Sandaru Weerasinghe is a full-time Master’s student in MSc. Geographical Information Science at The

University of Manchester. Her interests include utilising Mobile GIS for mobility mapping, geospatial

analysis, application of Web GIS in spatial analysis, exploring new methodologies and technologies to

apply in geospatial analysis.

Archt. Dilmini Dissanayake was a Lecturer in Urban Design within the Department of Town and

Country Planning of University of Moratuwa, Sri Lanka. She is currently teaching at the School of

Architecture and Built Environment, Waterfront Campus, Deakin University in Melbourne, Australia.

Her research interests are around lived-in historic monuments in urban areas, policies, framework and

theories in discourse to lived-in monuments and integration with urbanisation, with special reference

to reinterpretation of regional policies and regulations for place specific monuments. References

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