Journal of Global Resources

Volume 2

January 2016 Page 153-158
ISSN: 2395-3160 (Print), 2455-2445 (Online)

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SPATIAL ANALYSIS AND ASSESSMENT OF TRANSPORT NETWORK STRUCTURE
USING GEO-INFORMATICS: A CASE STUDY OF MAHENDRAGARH DISTRICT,HARYANA
Pardeep Kumar1 and S. K. Bansal2
Research Scholar 2Professor & Head Department of Geography,
Maharshi Dayanand University, Rohtak, India
Email: pkgeography@rediffmail.com

1Abstract: It is a great challenge to provide all-weather road connectivity to all the habitations withbetter physical accessibility, quality, mileage, and safe public sustainable transport system in India. TheTransportation System is a critical component of infrastructure development and lifeline of the area aswell. It plays a key role in economic growth of the region and controls the movement of people, goods,services and the flow of resources. Network Analysis helps in identifying optimum locations for theservices to be provided. A transportation network is a flow network representing the movement ofpeople, vehicles or goods. There is urgent need to develop GIS based Road Information System (RIS).
This will be capable to quick display of large scale real world geographical conditions of various
information about the transport network structure. Geospatial technology has provided many types ofnetworks and route analysis modules in various GIS packages to improve the movement of people,
goods, services and the flow of resources. A case study approach was adopted to explore the existing
spatial structure and patterns of the transportation network system discuss through in terms of surface
gross accessibility, surface accessibility by mileage, by nodality and physical accessibility, road densityof Mahendragarh district, Haryana. Present work was carried out to adopt an integrated approach of
remote sensing and GIS. It can be more helpful to improve the movement of people, goods, services
and the flow of resources for the better utilization, conservation, and management in sustainable
manner.
Keywords: Road Information System, Accessibility, Nodality, Mileage and Topology.

Introduction
It is a great challenge to provide all-weather road connectivity to all the habitations with better quality,
mileage accessibility and safe public sustainable transport system in India. The Transportation System
is a critical component of infrastructure development and lifeline of the area (Rai, et al., 2013). It plays akey role in economic growth of the region and controls the crime, movement of people, goods, services
and the flow of resources. Network Analysis helps in identifying optimum locations for services to beprovided. A transportation network is a flow network representing the movement of people, vehicles orgoods (Bell and Iida, 1997). For any country to develop with right momentum modern and efficient
Transport as a basic infrastructure is a must. It has been seen throughout the history of any nation thata proper, extensive and efficient Road Transport has played a major role. A well linked and coordinatedsystem of transport plays an important role in the sustained economic growth of a country. Railways androads are the dominant means of transport carrying more than 95% of total traffic generated in India(http://shodhganga.inflibnet.ac.in). Connectivity and mobility are the keys to reaching out and opening
up new opportunities. With the construction of village roads, rural India is rapidly transforming. Wherever
the roads network has come up, the rural economy and quality of life has improved. There is required todevelop a comprehensive and reliable road inventory database for effective and efficient construction
and maintenance management system. It should contain detailed information about the physicalfeatures of the roads along with identification number, geometric features, present condition, annual
average daily traffic, rural market, social infrastructures (School, College, Religious places, Community
Clinic, and Health Centre), and their controlling point on the road. Geospatial technology is capable todevelop such type of comprehensive and reliable road inventory database .In recent times it has153

provided many types of network and route analysis modules in various GIS packages to improve themovement of people, goods, services and the flow of resources. Geographical Information System canbe facilitate in understanding of spatial aspects of social and economic development by relating sociosocioeconomic variables to natural resources and the physical world, providing a tool for targetinginterventions and monitoring impacts on various scales over wide areas (Rout, J. 2012). It can be more
helpful for the better utilization, conservation,conservation management and quick monitoring of natural andmanmade resources in sustainable manner.

Study Area
Mahendragarh district is constituted by eight administrative
blocks (Mahendragarh, Satnali, LKanina,Ateli, Nangal
Chaudry, Shima, Narnaul and Nizampur) located between
00027 47’ 50” and 28 28’ 00” North Latitudes and 75 54’ 00”
0and 76 22’ 11” East Longitudes (Fig. 1). It lies in Southern2part of Haryana state covering an area of 1939 km sq.km
according to Survey of India Topographical maps. It isbounded by Bhiwani district in the north, by Rewari districtin the east and by the state of Rajasthan in the southeast,
south, southwest and west (Map - 1).Physiographical thedistrict consists of flat level plain interrupted from place toplace by clusters of sand dunes, isolated hillocks and rockyrridges. The leveled plain is spread in north, along the north
northeastern boundary while the clusters of sand dunes, isolated
hillocks and rocky ridges lying area covers the south, south
central southeastern and western part of the district. In
present time the district has 347 Gram Panchyats, 367
villages and 458 habitations. All the villages are connectedwith road transport network .Their quality, wide size andhierarchical levels are fully different.

Figure 1:: Location of Study Area

Material and Methods
Open series topographical maps on 1:50,000 scales, obtained from Survey of India, Chandigarh havebeen used in the study.. Data about road network hierarchy levels, their numbers werew
obtained from
Public Works Department; Narnaul, Government of Haryana. IRS LISS III satellite data, March 2012,
Google Earth data and other related data collected from various agencies and publications were also
used in the study. A visual supervised classification technique is used for various type transport networkfeatures. All thematic layers were integrated
integrated and analyzed in a GIS environment. The overall results
demonstrate that the use of remote sensing and GIS provide potentially powerful tools to study spatial
analysis and assessment of transport network structure. This process also included collection
colleof primarydata such as site investigation and observation.

Objectives of the study
The main objectives of the study are as follows:
Spatial Analysis of connectivity pattern,
Thematic mapping of spatial structure of transport network,
Identificationn and assessment of accessibility

Results and Discussion
It has been seen throughout the field work that most of villages have linked with transport network but
not with efficient quality, wideness and monitoring system. Kanina block is leading stage followed by
Narnaul, Mahendragarh and Shima block having lowest followed by Nizampur and Satnali blocks interm of total length of all hierarchical level transport network length. With the total length point of view,
the other district road, major district road and state highway are the dominant factor in the wholetransport network system in the study area (Table - 1).

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Table 1: Block Wise Transport Network Length (in km)
Category

SatnaliNizampur

N Chaudhry

M. GarhKaninaShima

NarnaulAtelli

Total

S.H

25.28

7.88

0.00

41.64

25.13

9.74

34.29

17.99

161.95

MDR

14.97

11.18

26.67

0.00

43.87

16.90

9.16

25.08

147.81

Rail Track

18.83

13.90

0.00

16.15

16.94

0.00

14.91

17.15

97.88

HSAMB

8.39

12.91

13.28

19.09

25.04

10.83

23.76

8.35

121.65

Panchayats

0.00

0.00

0.78

6.94

2.70

1.31

0.28

3.30

15.31

PMGSY

0.00

0.00

0.00

22.90

0.00

0.00

0.00

0.00

22.90Others

58.02

81.80

106.97115.76116.6849.20

140.9056.14

725.47

Total
125.49127.67147.70222.48230.3687.97
223.29128.01
Source: Calculated from IRS LISS III Satellite Image; March, 2012. SOI, Toposheets, & P. W. D. Narnaul

1292.97

Physical Accessibility
Accessibility refers to people’s ability to reach goods, services and activities, which is the ultimate goalof most of the transport activities and therefore the time and money that people and businesses must
devote to transportation. Many factors affect accessibility, including mobility (physical movement), thequality and affordability of transport options, transport system connectivity, mobility substitutes, and land
use patterns. Generally, in transport network, physical accessibility refers to the minimum distancecovered for reaching one node to another node. In study area 33.70 areas have high accessibility (< 2km), 25.47 have moderate (2-4 km), 15.20 have low (4-6 km) and 25.20 are very low accessible areas(>6 km) shown in Table - 2. Spatial patterns of physical accessibility and gross accessibility arepresented in figure - 2.
Table 2: Area under Physical Accessibility
Sr. No.

Distance (km)Area (sq.km.)

In %

1<2639.87

33.70

22-4483.63

25.47

34-6

296.9615.64

4>6478.54

25.20

1899.00

100.00Total
Source: Calculated from IRS Satellite Image LISS III; March, 2012.

Gross Accessibility
Accessibility is a product of mobility and proximity known as an indicator of the ability to efficiently reachone place to another place. Notably, it gives attention to alternative strategies for reducing traffic
congestion and mitigating environmental problems, such as promoting efficient, resource conserving
and land-use arrangements. Rank surface gross accessibility is the gravity based accessibility
measurement indicator. Narnaul and Nizampur blocks are found as the highest accessible nodal points
and Satnali and Kanina are the lowest accessible places in term of rank surface gross accessibility(Table – 3 & Figure - 2).
Table 3: Block Wise Gross Matrix
Block Name

NodeNode Rank

Assumed Distance

MilegeTotalRank

SatnaliA

810394474

8M.GarhB

410234274

3KaninaC

210300320

6ShimaD510210260

2Atelli

E210280300

4NarnaulF

110200210

1Nizampur

G

510269319

5N. Chaudhary
H510311
Source: Calculated from IRS LISS III Satellite Image; March, 2012. SOI, Toposheets, 1: 50,000

361

7155

Figure 2: Accessibility Year - 2014
Rank Surface Gross Accessibility

Physical Accessibility by Road

Source: IRS LISS III Satellite Image; 2012. Google Earth Image, SOI, Toposheets, 1: 50,000.

Nodality
Geographically, nodality refers to the spatial arrangement and geometrical linkage of nodes in transport
network. It represents the nodal centrality and direct relation of number of nodes within network. In thestudy area node F (Narnaul) having highest linkage and place of centrality (Figure - 2) with compressionof others nodal points followed by E (Ateli), C (Kanina) and node A (Satnali) has lowest linkage
followed by node D (Shima) and G ( Nizampur). It is clear that the node F is most accessible and A is
least accessible node in the district (Table - 4).
Table 4: Node Wise Nodality Matrix
Block Name

NodeA

BCDEFGH

TOTAL

RANK

Satnali

A00123233148M.Garh

B0001212284Kanina

C1000012262Shima

D21002122105Ateli

E2101001162Narnaul

F2111000051Nizampur

G32221000105105N. Chaudhary
H32221000
Source: Calculated from IRS LISS III Satellite Image; March, 2012. SOI, Toposheets, 1: 50,000

Spatial Dimension of Mileage
In the study area node F (Narnaul) have higher accessible by mileage (Figure - 2) with compression ofothers nodal points followed by D (Shima), and B (Mahendragarh) while on the other side, node A(Satnali) has least accessible followed by node H (Nangal Chaudhry) and C (Kanina). It is clear that thenode F is most accessible and A is least accessible node in the district (Table - 5).

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Table 5: Node Wise Mileage Matrix
Block Name

B

C

DEF

G

H

TOTAL

RANK

Satnali

NodeA

A
026

44

50

75

546976394

8M.GarhB

260182445

28

4350

234

3Kanina

C

44

18030

2748

63

70

300

6ShimaD50

2430033

122734210

2Atelli

E754527330213643280

5NarnaulF

5428481221015222001Nizampur

G6943632736150162694N. Chaudhary
H765070344322160Source: Calculated from IRS LISS III Satellite Image; March, 2012. SOI, Toposheets, 1: 50,0003117Figure 2: Accessibility by Nodality & Mileage Year – 2014
Rank Surface Accessibility by Nodality

Rank Surface Accessibility by Mileage

Source: IRS LISS III Satellite Image; 2012. Google Earth Image, SOI, Toposheets, 1: 50,000.

Road Density
Road density is representing the total length of roads per square kilometer area (Figure - 3). In the study
area block Narnaul have high road density in compression to others blocks followed by Nizampur andNangal Chaudhry and on other side, the Satnali has lowest followed by Mahendragarh and Kanina.
Table 6: Block Wise Road Density Year- 2014
Block Name

Road Length (Km)Area (Sq. Km)

Density

Satnali

125.49226.53

0.55

Nizampur

127.67172.340.74

Nangal Chaudhary

147.70193.990.76

Mahendragarh

222.48366.13

0.61

Kanina230.36352.28

0.65

Shima

87.97

110.66

0.79

Narnaul

223.29279.34

0.80

Ateli

128.01

197.70

0.65

Total

1292.97

1899.00

0.68

Source: Calculated from IRS LISS III Satellite Image; March, 2012. SOI, Toposheets, 1: 50,000

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Topology
Topology refers to the spatial relationship between the links and the nodes with their physical distancefor separating two nodes in network. It specify the direction of movement of goods, peoples and otherresources. Study area topological view and road density is represented in figure - 3.
Figure 3: Road Density & Topology Year – 2014
Road Density

Topology

Source: IRS LISS III Satellite Image; 2012. Google Earth Image, SOI, Toposheets, 1: 50,000.

Conclusion
The accurate high resolution spatial information may be provides a solid foundation in selecting the area
for road building, alignment, accessibility measurement or for upgrading these. In the coming years, itwill be useful for planning and monitoring the roads for a maintenance check and a assured
environmentally sustainable transport network system. In Mahendragarh district a well linked andcoordinated system of transport playing an important role in the sustained economic growth. Narnaul
have highest accessible central place and Satnali and Kanina least accessible place in term of mileageand physical accessibility. Narnaul block have leading position and Satnali block has lowest level interm of road density. During the field checking, time it was observed that few roads have efficient quality
while rest of the roads have low levels quality in term of wideness, build-up materials and monitoring
system in all over the district. There is urgent need of large scale investments in the whole transport
network system to boost the local economic growth for assured environmentally sustainabledevelopment. It will be more helpful for rational utilization of land resources to sustain the transport
network system of the study area.

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