geographic information system for smart cities

Geographic information system
for smart cities



Geographic information
system for smart cities

TM Vinod Kumar
and
Associates

COPAL PUBLISHING GROUP
New Delhi


Published by Copal Publishing Group
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Preface
This is a collective effort of many authors from many countries who got
themselves associated to research and documentation on Geographic
Information System (GIS) for Smart Cities. We believe that smart cities are
cities of tomorrow, which is a great contribution of urban science to future
of civilization. The fact that smart cities have got a capability to transform
nations brought these authors together to accomplish the task. This is the first
book on smart cities from India. Again this is the first book, internationally,
that establishes the relationship of GIS with smart cities. At present GIS
usage in the professional practice of urban planning and management has
not utilized the many state-of-the-art capabilities of GIS. By the very nature
of smart cities, we require all capabilities of GIS for modeling planning,
monitoring and management of smart cities. We feel that future development
of GIS will be triggered by the challenges smart cities possess to GIS.
Transformation of nation can only be brought about by its people. The
quality of the people is related to the scope of national development one

can envisage. Smart cities are built on the primary building block of smart
people, then smart community they form and smart economy they operate.
Smart people are those having highest possible Human Development Index,
high Graduate Enrolment Ratio, adapt in the art and science of e-democracy
and e-governance, and dedicated to continuous learning process and
enjoying smart environment, smart mobility and, above all, smart living.
Therefore the primary task of any nation is to convert their population to
smart people with the attributes mentioned. Hence national development is
human development and smart city development is human development.
I would like to thank all who are directly involved in funding and
supporting this venture. We have not received or sought any grant for the
publication of this book. There are no institutions other than publisher
which directly supported the work of authors leading to the production
of book, but research work has been done in many institutions, indirectly
making it possible to publish this work. We thank all of them.
Finally I thank the spirit of BODHISATVA of MAHYANA
BUDDHISM of all authors in making this work possible.
TM Vinod Kumar



Authors
TM Vinod Kumar has more than 40 years of experience
in urban and regional planning, focusing equally to
teaching, research, and professional consultancy. He was
Dean of Studies at School of Planning and Architecture,
New Delhi, and was HOD of Urban Planning. Although
an engineer and urban planner by profession, he has
broadened his research horizon by working in various
social sciences research institutions.

M Ramachandran has a macro-level understanding of
India’s urban sector as he has been Secretary, Ministry of
Urban Development, Government of India, for about 4
years and his urban tenure is well known for the various
new initiatives including able stewardship of the mega
urban initiative titled Jawaharlal Nehru National Urban
Renewal Mission. His 38 years long career in the Indian
Administrative Service (IAS) stand out for the variety
of challenging assignments successfully handled.
Mahavir is Professor and Head of the Department of
Environmental Planning at the School of Planning
and Architecture, New Delhi. He received his PhD
jointly from ITC and the University of Utrecht, the
Netherlands. The research revolved around the concept
of ‘Continuously Built-up Areas’ with the case study of
the NCR, Delhi. He has been in the teaching, research
and practice of physical planning, remote sensing and
GIS, for about 30 years.
Prabh Bedi is a geographer, regional planner and GIS
expert. She has been practicing and teaching planning,
GIS applications and project management for the last
15 years. She is particularly interested in information
systems for planning and sustainable settlements. She
has worked on various projects in India, Vietnam and
USA. Presently, she is working towards her PhD.


viii

Geographic information system for smart cities

Priya Mendiratta is working as an urban planner for the
City and Industrial Development Corporation (CIDCO),
a fully Maharashtra government-owned company. She
is also involved in research at the Centre of Studies
in Resources Engineering (CSRE), Indian Institute of
Technology Bombay (IITB), Mumbai, India, on utility
of satellite images to trace and project the spatiotemporal urbanization trends of a metropolitan area.
Shirish Gedam is an Associate Professor with the Centre
of Studies in Resources Engineering, IIT Bombay. He
received his PhD from the Indian Institute of Technology
(IIT) Bombay, Mumbai, India, preceded by Masters of
Technology with specialization in Remote Sensing.
Dr Gedam is a Life Member of the Indian Society of
Remote Sensing and Indian Society of Geomatics. He is
also actively working in the area of precision processing
of GPS data and GPS meteorology.
Bernd Gundermann holds a Masters degree in
Architecture from the School of Fine Arts in Hamburg,
Germany. He is currently working as Principal of
Stephenson & Turner NZ Architects and Engineers
in Auckland, New Zeal. Bernd was appointed Guest
Professor at the School of Fine Arts, Hamburg, and
continues teaching as a Fellow of the University of
Auckland’s School of Architecture and Planning.
Bernd is alumnus of the German National Academic
Foundation.
Ashmita Karmakar is employed with M/S Nakheel,
Dubai as Urban Planner (Master planning and
development control, GIS) for the existing and

upcoming mega projects of Dubai. She has graduated
in Architecture from LAD College, Nagpur, India in
1998. She completed her Masters in Town and Regional
Planning from Bengal Engineering College, Howrah,
India, and PhD in Environmental Planning from School
of Planning and Architecture, New Delhi, India in 2012.




P P Anilkumar is Associate Professor at the Department
of Architecture of NIT Calicut and has been teaching for
more than 20 years. He received his PhD in Sustainable
Coastal Cities from Indian Institute of Technology
Chennai, after his Masters in City Planning from Indian
Institute of Technology Kharagpur. His active current
research interests are in sustainable cities, land-use
impacts and vernacular and green architecture.
Vijay Neekhra is an urban, regional and transport
planner, working with an international organization.
He received his PhD with ‘Best Dissertation Award’ in
urban planning from The University of Tokyo, Japan
and Master’s degree in planning from the School of
Planning and Architecture, India. Dr Neekhra has
extensive work experience in development & planning
(including urban, regional & transport planning)
involving research, policy advice & planning, analysis
and forecasting.
Bimal P holds a Masters degree in City Planning from
Indian Institute of Technology Kharagpur, and Bachelors’

degree in architecture from Kerala University. He had
been working at JUSCO, Jamshedpur, before joining
as Assistant Professor at Department of Architecture,
NIT Calicut. He is currently pursuing PhD in urban
modeling.
Naseer M A received his PhD in Transportation Planning
from Indian Institute of Technology Kharagpur India in
the year 2005 after completing his Masters degree in
City Planning. Presently, he is a faculty in Architecture
at National Institute of Technology Calicut, India. In
addition to transportation planning, his research interests
include remote sensing and GIS in urban planning.

Authorsix


x

Geographic information system for smart cities

Joaquín Borrego-Díaz is an Associate Professor in the
University of Seville’s Computer Science and Artificial
Intelligence Department, and he is a Computational Logic
Group () member. His research
focuses on computational logic and automated reasoning
and their application to Knowledge Representation on
the intersection of automated-reasoning systems and
Semantic Web.
Gonzalo A. Aranda-Corral works as an Assistant
Professor at Universidad de Huelva, Department of

Information Technologies, and he is a Computational
Logic Group member at Universidad de Sevilla.
Nowadays, his main research lines of CLG are
validation of knowledge basis for Semantic Web, social
networking, intelligent systems (mobile computing,
urban informatics, etc.) and algorithms verification.
Manuel Gomar Acosta is Master in Software
Engineering from the University of Seville. He
developed his final year project with the University of
Seville’s Computer Science and Artificial Intelligence
Department, researching in the field of natural disasters
simulation through multi-agent technology. Nowadays
he works as game developer in a multiplatform game
engine (Wave Engine).
Alejandro Blanco Escudero has completed Software
Engineering from University of Seville. He developed
his final year project with the University of Seville’s
Computer Science and Artificial Intelligence
Department, researching in the field of natural disasters
simulation through multi-agent technology.
Antonio Caperna is an Architect, and President
of the International Society of Biourbanism. He
teaches Sustainable Urban Design at the Architecture
Department of Roma Tre University (Italy). His actual
research deals with scientific issues such as fractals,
complexity theory, evolutionary biology, and artificial

intelligence, and their relation to a human-oriented
architecture.
Stefano Serafini, a philosopher and psychologist,
is Research Director and Secretary General of the
International Society of Biourbanism. He is involved
in researches about neuroergonomics, environmental
psychology, and urban studies, especially focusing on
the biological basis of the effect of space shaping on
human beings.
Walter Barberis is co-founder and promoter of the
international network “Smart Planning” and president
of the homonymous association. He works as an
independent researcher and professor in urban planning
at the School of Architecture, University of “Roma Tre”,
focusing on the themes of city form, urban fragmentation
and new technologies applied to the city (Urbótica and
smart city).
Richard Sliuzas is Associate Professor of Urban
Planning at the University of Twente’s Faculty of
Geographic Information Science and Earth Observation.
Much of his research has been focussed on monitoring
and modelling informal development and urban growth
in developing countries. His current major research
interests are urban transformations and planning in
China and Vietnam; urban growth and urban village
formation.
Mark Zuidgeest is Assistant Professor of Urban
Transport in the Faculty of Geo-Information Science
and Earth Observation of the University of Twente in
The Netherlands. He has 15 years’ experience in the

transport sector, both as an academic and as a consultant.
He is specialized in sustainable transport development,
public transport and bicycle infrastructure.

Authorsxi


xii

Geographic information system for smart cities

Shomik Mehndiratta is a Lead Transport Specialist
working in the World Bank’s Latin America and
Caribbean region based in Washington DC. He is
working on transport and climate issues across countries
in the region. He has been at the World Bank since 2002
and in the period 2007–2010 he lived and worked in
China. He is co-editor and author of an edited book on
Low Carbon Urban Development in China.
Andrew Salzberg joined the World Bank in 2009 after
completing his Master’s in Urban Planning Degree at
Harvard University. While at the Bank, Andrew has
focused on supporting due diligence evaluations of
urban transport and railway projects in Asia. Andrew’s
work focuses on how the use of data (and geospatial data
in particular) can make cities more liveable, efficient,
and sustainable.


Contents

Preface

v

Authors

vii

1. Geographic information system for smart cities

1

1.1Introduction

1



1.2

Smart urban communities

8



1.3

Smart city for social space

10



1.4

Smart city technological perspectives

11



1.5

Smart city and urban economic development

12



1.6

Concept of smart people in smart cities

13



1.7

Role of GIS for smart cities

14



1.8

GIS in building model of real world city

17

1.9Conclusion
2. GIS for smart urbanisation

26

2.1Introduction

26

2.2Urbanisation

27



2.3

Urbanisation as defined in India

28



2.4

History of India’s urbanisation

28



2.5

Challenges as resultant of urbanisation in India

29



2.6

Urbanisation policy through national plans

30



2.7

Just smart cities or smart urbanisation

32



2.8

GIS-based smart urbanisation

34

2.9Conclusion

39

3. Satellite images for sustainable urbanisation

42



42

3.1Background – role of satellite images towards
sustainable urbanisation


xiv

Geographic information system for smart cities



3.2

Sustainable urbanisation – concept and indices

46



3.3Satellite images and GIS – genesis and significance
to urban planning



3.4

Satellite image applications for sustainable development 5 6



3.5

Vision – the road ahead

49

70

4. Adaptive urbanism: Climate change, sea-level
rise and a new urban age

73



4.1

Climate change and the coastal habitat of mankind

73



4.2

Response strategies to sea-level rise

77



4.3

Available technology

81

4.4

Adaptive urbanism and the smart city

83



4.5

Conclusion

91

5. Assessment of land and land use for future development
using GIS in the community development of Dubai

94

5.1Introduction

94



95

5.2

The study

5.3Background

97



5.4

Master plan outcome

104



5.5

Use of GIS in the planning of services

106



5.6

Implementation of master plan at community level

112



5.7

Case studies

113



5.8

Implication of GIS for future development

118

5.9Conclusion

121

6. Environmentally sensitive land-use allocation for smart
coastal cities

124

6.1Introduction

124

6.2Coastal cities: why they are sensitive to urban
development?

125



6.3Is sustainability and smartness related? Isn’t a

127




Contentsxv

sustainable model smart from the futuristic
perspective?


6.4

What is CHI?



6.5Assessing land-use allocation implications on CHI:

the way forward for smart coastal cities

137



6.6

143

Broad context of application

130

6.7Epilogue

146

7. Application of GIS in categorizing and managing slum
growth in India

149



7.1

Introduction

149

7.2

Slum population in India

151



7.3

Program/policies towards slums improvement

153



7.4

Bhopal city, slums, and slum categories

159



7.5

Analysis of slums at ward level

160



7.6

Categories of ward with reference to slums

170



7.7

Categories of slums

174



7.8

Comparison of slums in 4 cities

178



7.9

Categories of slums in 4 cities

180



7.10 Conclusion

181

8. Travel management with intraday trip generation model 186
in a smart city framework
8.1Introduction

186



8.2

Activity scheduling

187



8.3

Random utility models

188



8.4

Multinomial Logit Models

189



8.5

Weighted average

190



8.6

Monte-Carlo method

190



8.7

Proposed Model

191


xvi



Geographic information system for smart cities

8.8

Activity chains

191

8.9Geography

193



8.10 The process

193

8.11 Implementation of the model

197



8.12 Study area

197



8.13Results

199



8.14 Applications in smart city

202

9. Intelligent goods transportation

205

9.1Introduction

205

9.2

Urban goods transportation

206



9.3

Intelligent goods transportation

218



9.4

Case study of Chennai Metropolitan area

220

9.5Conclusion

225

10. Exploiting digital information on the city to estimate
resilience: A multi-agent approach

226



10.1Introduction

226



10.2 Reconstruction versus resilience

228



10.3 Evaluation and validation

230



10.4 Artificial intelligence for resilience

231



10.5 Urban informational ecosystem

232



10.6 Multi-agent systems and digital information

236



10.7 A case study: Hurricane Katrina

238



10.8Results

243



10.9 Closing remarks

245

11. Biourbanism as a new framework for smart cities studies 250

11.1 Smart city initiatives – technology, economy, classes 250



11.2 What do we mean when we say “smart city”?

255




Contentsxvii



11.3 A critical analysis

258



11.4 Biourbanism to build wise cities

263



11.5 What a smart city should be

265

11.6 A case study: the Artena project to revive Italian
villages

269



11.7 A small afterword about megalopolises

277



11.8Conclusion

280

12. SMART Planning as a new way of conceiving the
city/discipline

288



12.1Introduction

288

12.2What is the context to plan? What we see and what
we can know?

290



12.3 Guiding principles of SMART Planning approach

293



12.4 Final considerations

300

13. Exploring smart city futures: Opportunities and barriers 305
to scenario-based urban planning support systems


13.1Introduction

305

13.2 Accessibility for all

307



13.3 Defining accessibility

308



13.4 Activity-based measures

309



13.5 Using GIS for modelling multi-modal accessibility

310



13.6 No smart cities without good accessibility

311

13.7Dynamic land use and contour-based accessibility in 312
Wuhan, China



13.8 Potential accessibility indicators for Ahmedabad, India 315



13.9 Discussion and conclusions

320



13.10Acknowledgements

322


xviii

Geographic information system for smart cities

14. Towards smart cities in India

325

14.1Introduction

325



14.2 Launch of flagship mission

326



14.3 Other technology programs covering urban sector

329



14.4 ICT initiatives in Indian cities

333



14.5 Smart city initiatives world wide

334

14.6 Are we ready for smart cities?

339



14.7 Way forward

341



14.8Conclusion

342

15. Implementing smart cities in India

345



15.1 Indian experience of smart cities

345



15.2Selection of settlements for smart cities development 347
in India

15.3 Smart city that is self-aware

352



15.4 Smart people for smart cities

353



15.5Towards a calibrated model for urban economic
development in smart cities

361



15.6Metropolitan planning committee and Triple Helix
institutional frame

362



15.7Innovating community interface for government

service provider in a smart city

365



15.8 Smart city technology modules

366



15.9 Smart city and e-democracy

369



15.10 From e-democracy to e-governance for smart cities

378



15.11 Conclusion

385

Index

393


1
Geographic information system for smart cities
T.M. VINOD KUMAR

Abstract: City is spatial, cultural, social, economic, political, legal, democratic and ecological
system. Spatial system can be studied from land use and urban networks and services, and
so also other systems from their components. City has capabilities to uplift any nation, and
converting cities to smart cities make smarter nations. The intervention on a city is executed
by planning, management, governance and development systems. At present, planning
system prepares master plans, zonal plans, urban land management schemes and siteplanning schemes/ urban design to achieve the goals of the spatial system which needs
a careful relook for the creation of smart cities. Management and governing systems, now
in operation, are legacy colonial with inefficient hierarchical system that is least responsive
and in real time outmoded and cumbersome for the end users. Smart city is the city of
tomorrow, which tries to identify a smarter option from legacy system for maximising the enduser satisfaction and accelerating urban socio-cultural and economic development. Smart
city is a knowledge-based city functioning on most latest and updated information and often
on automated decision making and rapid action for individuals, whether they are consumers
of urban network and services or providers of services or entrepreneurs.

State of the art of smart city is explored with a literature search and also the components
of smart cities like smart community/district, smart building, smart network and services
system. Replacement of colonial governance, management and development system is also
discussed. State of the art of GIS is explored briefly within the context of smart cities. GIS is
defined and all possible uses of GIS with increasing complexity are explained. The possibility
of representing smart city with GIS is explored, and an operational model is also described.
Key words: geographic information system, smart city, state of the art, definition, GIS as
related to smart city.

1.1Introduction
Most of us live in a city that has been planned for 40–60 years with two
or three master plans, many zonal plans, building codes, urban land
management schemes and development control regulation codes, which
guide city development. Master plan is prepared taking into account
spatial, ecological, cultural, social, economic, political, administrative and
democratic system. There is a regularity of behaviour in these systems and is
translated in to an urban land use, transportation and networks and services


2

Geographic information system for smart cities

plan. Then other social and physical infrastructures are located and planned
using spatial standards. Hence, spatial plan consists of land uses and urban
networks and services with multiple attributes. The intervention on a city is
executed by planning, management, governance and development systems.
For example, at present, constitutionally empowered planning authority
prepares city master plans, zonal plans, urban land management schemes
and site planning schemes/ urban design to achieve the specific goals and
objectives of a city. Management and governing systems that exist today
are legacy colonial systems with inefficient vertical hierarchical structure
that is least responsive for real time intervention required for rapid urban
management and development, and largely outmoded and cumbersome
for the end users. India is now legislating in many federal states to reduce
the response time of government servants, who are otherwise indifferent,
and even punishment is awarded for delayed public services delivery to
end users. In the past this legacy system has served British colonial India
very well, helped the oppressive colonial masters for collecting revenue,

retarding economic development, killing certain competitive industries to
British, and maintaining law and order; but is not particularly useful for
a modern day urban management and urban economic development. This
book indicates how these changes can be made.
Geographic information systems (GIS) are also used for planning
in most of the major cities in India and to a limited scale in urban
management and governance. However, these urban planning, governance
and management efforts have not resulted in drastic reduction in difficult
urban living. These have not helped in reducing long commutation distance,
unnecessary use of high energy and wastage of natural resources, difficult
traffic bottlenecks and congestion, retarded employment generation during
the time of economic down turns and pollution of air, water and land. Illserviced slums still do exists. There is a need to study these issues with
all the complexity in order to modify a city to a “smart city” that can
overcome these emerging urban development issues in a “smarter way”.
This book defines smart city as a knowledge-based city that develops extra
ordinary capabilities to be self-aware; functions 24 hours and 7 days a
week; communicates, selectively, knowledge in real time to citizen endusers for satisfactory way of life with easy public delivery of services,
comfortable mobility, conservation of energy, environment and other
natural resources; and creates energetic face-to-face communities and a
vibrant urban economy even at a time of national economic downturns.




Geographic information system for smart cities3

Smart city components consist of smart economy, smart people, smart
governance, smart mobility, smart environment and smart living. These
combined systems try to increase the economic competitiveness, social
and human capital, participation, transport and ICT, natural resources and

quality of life. Figure 1.1 shows smart city components.
SMART ECONOMY
(Competitiveness)

SMART PEOPLE
(Social and Human Capital)

SMART Governance
(Participation)

 Innovative spirit
Entrepreneurship
Productivity
 Flexibility of labour market
 International embeddendness
 Ability to transform

 Level of qualification
 Affinity to life long learning
 Social and ethnic plurality
Flexibility
Creativity
Cosmopolitanism/open-mindeness
Sustaniable resource
management






Participation in decision-making
Public and social services
Transparent governance
Political strategies & perspectives

SMART MOBILITY
(Transport and ICT)

SMART ENVIRONMENT
(Natural resources)

SMART LIVING
(Quality of life)

 Local accessibility
 (Inter-) national accessibility
 Availability of ICT-infrastructure

Sustainable, innovative and safe
transport systems

Attractivity of natural conditions
Pollution
 Environmental protection
Sustainable resource
management










Cultural facilities
Health conditions
Individual safety
Housing quality
Education facilities
Touristic attractivity
Social cohesion

Figure 1.1  Smart city system

GIS has got a capacity to model the real world of the city in totality. It
can incorporate millions of variables and has the capacity to geocode these
variables and simulate for planning, management and development of a
city. The hardware platform of computers is in the process of increasing
its capacity for GIS computations almost every day. This book relates GIS
with smart city urban economic development in India.
Urban development in India is assuming greater importance. In
the census year 2011, although only 31.16 percent population of India
lived in urban areas, they contributed 62% of GDP. When India aims for
9–10% GDP growth rate, urban development needs to be strengthened
further. Converting existing million-size and mega cities to smart cities
can make India develop faster to reach the GDP growth rate target. This
book investigates the role of smart cities and related development of GIS
in achieving higher GDP growth rate.

Urban population of India grew from 286 million in 2001 to 377
million in 2011. This 91 million increase in urban population is larger
than 90.5 million increase in rural population during 2001–2011. Table
1.1 shows the urban content of selected states and union territories of


4

Geographic information system for smart cities

India. In addition to union territories given in Table 1.1, there is more than
42 percent urban content in states like Gujarat, Maharashtra, Kerala and
Tamil Nadu. These states have a higher potential of contribution to GDP
in future if smart city policy is formulated and implemented there. Gujarat
is taking some steps to have smart cities, and also smart new towns are
planned along the Delhi–Mumbai High Speed Freight Corridor.
Table 1.1  States/UTs in India with higher than average urban content in 2011.
Selected states/UTs

Urban content (%)

NCT Delhi

97.49

Chandigarh

97.24

Lakshadweep

78.08

Daman & Diu

75.16

Puduchery

68.31

Goa

62.17

Mizoram

51.5

Tamil Nadu

48.44

Kerala

47.71

Maharashtra

45.24

Gujarat

42.6

Karnataka

38.57

Andhra Pradesh

33.50

Source: Census of India 2011

The scientific way of identifying smart cities is not there in many
listing of smart cities. There are many websites enumerating 10 smart
cities without giving in detail the criteria of determining the smart cities.
Identification can only be done with a good amount of research based on a
large data base of cities around the world. However there is an identification
of smart cities for award for Smart21 Committee. They have identified five
factors to consider a city as an intelligent community, which is synonymous
with smart city. They are broadband connectivity, knowledge workforce,
digital inclusion, innovation and marketing and advocacy. It is important
to stress that city needs to be marketed like any other services, and a
strong advocacy mechanism needs to be implemented. Table 1.2 describes
the list of cities in alphabetical order awarded by Intelligent Community
Organisation from 2007 to 2011.

Geographic information system for smart cities5

Table 1.2  List of smart cities during 2007–2011.
Region
Asia

Cities
Bangalore (India), Chongqing (China), Doha (Qatar), Gangnam District,
Seoul (Korea), Hong Kong, Hwaseong-Dongtan (Korea), Hyderabad
(India), Ichikawa (Japan), Jaipur Rajasthan (India), Jiading (China),
Kabul (Afghanistan), Mitaka (Japan), Shanghai (China), Seoul (Korea),
Singapore, Suwon (Korea), Taipei (Taiwan), Taoyuan County (Taiwan), Tel
Aviv (Israel), Tianjin (China), Yokosuka (Japan)

Africa

Cape Town (South Africa), Nelson Mandela Bay (South Africa)

Europe

Besancon (France), Birmingham (UK), Dundee (Scotland: UK), Eindhoven
(Netherlands), Glasgow, Scotland (UK), Hammarby Sjöstad (Sweden),
Issy-les-Moulineaux (France), Kariskrona (Sweden), Malta (Malta),
Manchester (UK), Reykjavik (Iceland), Scorpon (Hungary), Stockholm
(Sweden), Tallinn (Estonia), Sunderland (UK), Trikala (Greece)

North

US: Albany (New York), Ashland (Oregon), Arlington County (Virginia),

America

Bettendorf (Iowa), Bristol (Virginia), Chattanooga (Tennessee), Cleveland
(Ohio), Corpus Christi (Texas), Dakota County (Minnesota), Danville
(Virginia), Dublin (Ohio), Florida High Tech Corridor, LaGrange (Georgia),
Northeast

(Ohio), Loma Linda (California), Riverside (California), San

Francisco, Spokane (Washington), Westchester County (New York),
Winston-Salem (Carolina)
Canada: Burlington (Ontario), Calgary (Alberta), Edmonton (Alberta),
Fredericton

(New

Brunswick),

Kenora

(Ontario),

Moncton

(New

Brunswick), Ottawa (Ontario), Quebec City (Quebec), Stratford (Ontario),
Toronto (Ontario), Vancouver (British Columbia), Waterloo (Ontario),

Western Valley (Nova Scotia), Windsor-Essex (Ontario), Winnipeg
(Manitoba)
Middle/South

Braceloneta (Puerto Rico), Curitiba, Parana (Brazil), Pirai (Brazil), Porto

America

Alegre (Brazil)

Oceania

Ballarat (Australia), Gold Coast City (Australia), Ipswich, Queensland
(Australia), State of Victoria (Australia), Whittle sea, Victoria (Australia)

Source: />Smart21&Category=Events&link=Smart21

Bangalore, Hyderabad and Jaipur have been listed as smart cities in
India. All of these appear in the list of top 10 largest or mega cities of
India. Bangalore occupies the 5th position, Hyderabad 6th and Jaipur 10th


6

Geographic information system for smart cities

rank in the order of population. Bangalore and Hyderabad are well known
for software exports, and most of the large international firms connected
with knowledge economy have offices in Bangalore and Hyderabad. Most
surprising part was Jaipur’s ascendancy to the third smart city of India.

Population growth supports the fact that how fast it has developed during
the last decades. The smart cities are good employment multipliers, which
is one reason why the population of these cities are high. However it
may be noted that in 2011, Andhra Pradesh has another million-plus city
Vijayawada, and Rajasthan another million-plus city Jodhpur. Because
of proximity to other knowledge industries, there has been concentrated
investment in these three smart cities of India but lesser investment in
other centres. Now there is a policy change to take knowledge economy
investment to tier 2 and tier 3 cities, and in Kerala there is a policy even
to have software industry in village setting which can be the least-cost
option. So, Vijayawada and Jodhpur can get some advantage in future.
Although population growth is a function of employment growth and
inward migration, a detailed study of how smart city influenced its growth
and what innovation it implemented is yet to be documented. However,
few mega infrastructure projects like new airports and Metro rail projects
in Bangalore and Hyderabad have been implemented. Research centres
in these cities concentrate on e-governance, e-banking, e-commerce,
computer software and hardware development and so on. With several
well-known educational institutions and R&D centres located in these two
cities, knowledge economy is likely to grow faster and would contribute in
the accelerated economic development of India. Lack of systematic research
makes it difficult to understand the dynamics of smart cities in India.

1.1.1

Definition of smart cities

Smart cities were also called wired cities but the term ‘wired’ lost its
meaning in an era of wireless communication technology. Other names are
digital city, intelligent city, ubiquitous city, hybrid city and information city.

The difficulty in explaining these terms created a situation that these terms
became unpopular. People-oriented smart cities are called creative city,
learning city, humane city and knowledge city. There are also communitycentred smart cities which are discussed subsequently. All these terms
which may be considered as earlier concepts were subsequently replaced
by smart city.