3. India Aviation Sector : Expected Growth
India is currently considered the third
largest domestic civil aviation market
in the world.
The civil aviation industry in India has
emerged as one of the fastest growing
industries in the country during the last
three years.
India is expected to become the third
largest global aviation market by 2020
and is expected to be the largest by
2030.
3
https://www.ibef.org/industry/indian-aviation.aspx
4. Problem Definition
4
Problem Definition:
To explore India’s International Air
Connectivity.
Identify Promising International Airports
in India.
Data Source: openflights.org
Data files used:
Airlines Information
Airports Information
Routes as of 2012
Tools: R and Gephi
5. Community Detection Algorithms
5
Community Detection Algorithms (igraph package):
Walktrap:
Computing communities in large networks using random walks
Fast Greedy:
Community structure via greedy optimization of modularity
Leading Eigenvector:
Community structure detecting based on the leading eigenvector of the community matrix
Label Propagation:
Finding communities based on propagating labels/ majority voting in neighborhood
7. Key Player Detection Methods
7
Key Player Detection Methods (undirected):
Degree Centrality: Number of edges connected to a node/ direct relationships
PageRank: Highly correlated with degree based on empirical evidence. Affected by the
degrees of connected nodes
Betweenness Centrality: Attributed to probability of being located on the shortest path
between 2 distinct nodes. Nodes with high betweenness are often called gateways/ bridges
8. Key Players
8
Dubai is the most connected
followed by Beijing and
Shanghai.
Delhi and Mumbai appear in
Top 20 airports.
S.No Airport ID Betweenness PageRank Degree Airport City Airport Country
1 2188 95629.56 0.0160 187 Dubai United Arab Emirates
2 3364 65664.13 0.0128 203 Beijing China
3 3406 30287.83 0.0095 153 Shanghai China
4 3361 48487.82 0.0095 85 Sydney Australia
5 3316 47656.64 0.0091 125 Singapore Singapore
6 3930 34936.94 0.0091 133 Seoul South Korea
7 2072 33291.04 0.0089 109 Jeddah Saudi Arabia
8 3885 36124.55 0.0089 122 Bangkok Thailand
9 2241 27287.19 0.0088 118 Doha Qatar
10 3370 39513.21 0.0088 146 Guangzhou China
11 3077 41379.69 0.0087 134 Hong Kong Hong Kong
12 813 43565.02 0.0084 82 Johannesburg South Africa
13 3304 40400.71 0.0084 112 Kuala Lumpur Malaysia
14 3093 28370.96 0.0081 98 Delhi India
15 2279 24834.39 0.0079 104 Tokyo Japan
16 2397 36510.12 0.0078 78 Manila Philippines
17 1107 31551.66 0.0073 74 Addis Ababa Ethiopia
18 2997 21272.91 0.0072 85 Mumbai India
19 2359 27721.21 0.0070 73 Tokyo Japan
20 3320 26104.00 0.0070 60 Brisbane Australia
9. Key Player Visual
9
It is not very clear from the
visual which airports in India
have good connectivity with
the world.
We further drill down to only
the airports which have routes
to/ from India.
To analyse this further we
have used Gephi.
10. New Delhi: International Air Connectivity
10
Data exploration using Geo
Layout to plot nodes and
edges.
Nodes: All airports connected
to India.
Edges: Routes to New Delhi.
To identify the connectivity of
the world with New Delhi, we
considered In-degree ranking.
i.e., International Flights
serving New Delhi
11. Identify Communities Based On Modularity
11
Based on modularity score as statistics , top
four clusters were identified.
The most dense cluster contains Delhi as the
central node.
New Delhi is more connected to the world
than other airports.
As per Airports Council International’s
ranking New Delhi ranks 21st in the list of
world’s busiest airport (2016) which has
moved up from 37th rank in 2012.
12. Identify Communities Based On Modularity
12
• The 2nd most dense cluster contains Mumbai
as the central node.
• Mumbai has lower international connectivity
than New Delhi. However, we suspect this
might be misleading as there are many
missing values in the data.
As per Airports Council International’s
ranking Mumbai ranks 29th in the list of
world’s busiest airport (2016) which has
moved up from 48th rank in 2012.
13. Identify Communities Based On Modularity
13
• The 3rd cluster has
those South Indian
Airports.
• Most of these airports
lie on the West Coast
and thus have good
connectivity with the
Middle East.
• These airports can
potentially extend their
air connectivity to
Europe as well.
14. Identify Communities Based On Modularity
14
• The fourth cluster has airports
lying on the East Coast of
Southern India and thus have
good connectivity with the
South East Asia.
15. “Final Thoughts..
Load Sharing: Airports in South India can share the load of New
Delhi and Mumbai in serving European Market.
Promising Airports: Tier-2 Airports like Varanasi, Lucknow,
Mangalore, Nagpur can have more destinations on their list.
Kolkata missing from the clusters – Lost its Lustre?
