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The Ghaggar plain is a micro-geo-historic region of India covering Ganganagar and Hanumangarh districts of the Rajasthan State, as identified by R.L. Singh (1971) and C.D. Deshpande (1982). River Ghaggar is known as a ‘dead river’ and at present it is simply in the form of dry bed, flooded during rains. An important characteristic feature of this region is that it was humid in very ancient period, became arid afterwards and with the availability of canal water converted as an agricultural region, not only of the state but of India. Among various means of transportation, road transport plays a vital role in the transformation of the regional economy of the region.
Spatial Pattern:
The simple distribution pattern of road transportation as shown in Figure 4.12 indicates that although all the tehsils are well served by roads, yet Suratgarh, Anupgarh, Nohar and Ganganagar tehsils are having 12.9, 11.2,11.1, and 10.1 per cent of the district road length respectively. In year 1981 the road length per 100 sq. kms was 10.27 kms and per 1,000 populations was only 1.05 kms.
For intensive spatial analysis of road transportation in a micro-region like Ghaggar plain, there is a need for network analysis. Transport network, as described by Kansky (1963), is “a set of geographic locations inter-connected in a system by a number of routes”. The present analysis is based on three aspects, viz.,
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(i) Connectivity,
(ii) Accessibility, and
(iii) Traffic-flow.
i. Connectivity:
“The connectivity of a network may be defined as the degree of completeness of the links between nodes” (Robinson and Bamfrod, 1978: 74). Connectivity can be measured by beta index (β) (B = arcs/nodes), alpha index (r = a-n-1/2n – 5), gamma index (ү =arcs/3(nodes – 2)) and cyclomatic number = a – (n -1). (Where α equals the number of arcs and n the number of nodes.) We have selected, Beta and Gamma index for the analysis of spatial pattern of connectivity. Table 4.1 indicates the tehsilwise value of these two variables.
The value of beta index in the region varies from 1.22 for Karanpur tehsil to 1.62 for Padampur tehsil. In fact, there is very little variation in beta index value, thus, indicates the uniform spatial pattern of connectivity. The gamma index is a value that always lies between 0.000 and 1.00. The analysis of gamma index value also shows little variation 0.48 to 0.72 and as many as seven tehsils are having gamma index value between 0.48 and 0.53. Thus, we can conclude that connectivity in the region under study is more or less uniform with little regional variations.
ii. Accessibility:
‘One of the most important attributes of a transportation network relates to accessibility, and the geographer is particularly concerned with accessibility as a locational feature (Robinson and Bamford, 1978: 78). Several methods have been used to measure and/or represent the accessibility. The traditional one is the distance measured along routes or from centres. Thus an area adjoining to a route or centres is more accessible and inaccessibility increases with the distance from routes.
Within network, accessibility can be measured in three ways:
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(i) By shortest path matrix,
(ii) By the associated number, and
(iii) By the Shimbel Index.
For the present study shortest-path matrix method had been used. The method follows the number of arcs used in the shortest-path between all possible pairs of nodes. Table 4.2 is the shortest-path matrix between 12 important centres of the Ghaggar plain, thus indicates the accessibility at these points. When the totals of each row are added up, the lowest total indicates the node, which is most accessible, while the highest number indicates the least accessible node. It becomes clear from the table that Hanumangarh and Suratgarh are most accessible followed by Sriganganagar, while Bhadra and Nohar are having lesser accessibility.
iii. Traffic Flow:
Internal bus-traffic flow is an indicator of the movement pattern of people. The present analysis is based on daily bus-traffic flow between important centres of the region. The daily bus-traffic flow between 14 centres has been examined by arranging them in a matrix (Table 4.3). The total score of each centres represents the degree of traffic flow. Thus, Sriganganagar and Hanumangarh possess highest bus services, while Tibi, Bhadra and Nohar are having lowest score in terms of daily bus-traffic flow.
