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Spatial analysis of Indian Railways

Introduction
Country growth is seen as a direct consequence of transport development. There won’t be prosperous growth if there is the absence of a well-developed transportation system [1]. There is need for these systems to be equipped with geospatial technologies for policy making and showing rapid advancements. Railway being the biggest public sector of India and serving a large section of population is thus chosen for our analysis through emerging geospatial technologies with the use of proprietary as well as open source geospatial tools. The size of sector itself describes the amount of databases one has to handle for effective functioning of it. A seamless repository of database is necessary for its interpretation and assistance in decision making to facilitate policy making and thus resulting in growth of this sector. This is exactly where the major role of geospatial tools comes in to picture. Hence, we first create 2 kinds of open access repositories for conducting the spatial analysis. GIS is used in populating this repository. A GIS is a system for capturing, storing, managing, processing and displaying the data spatially referenced to the surface of the earth [2]. The information in GIS is stored in form of geometry elements with attributes associated to them. The paper further comes out as a mix of modeling proposals and contribution of geospatial technology affirming them suitably through thorough budget studies of an entire decade. The budget study doesn’t cover the entire country rather a portion of western, North Western and South Western and central part of country.

Data
Railway budgets [3] for financial years 2000 to 2009 have been collected to carry out the spatial analysis. Along with it, the official maps and textual documents [4] freely available serve the purpose for determining the current state of rail routes in terms of completed tasks and work in progress in the field of doubling and electrification of routes. In order to study limitations in state of Jammu and Kashmir, topographic conditions which include the height variations across various districts of the state have also been collected. The disaster occurrence patterns have been understood through collection of list of the major rail accidents over last decade and their probable reasons.

Methodology and Results
The major phases of the methodology used in the study are:

  1. Data acquisition through official textual documents.
  2. Replication of data into geometric elements through GIS.
  3. Data interpretation and analysis.
  4. Model development and derivation of assumptions from analyses.

Development of repository
Two types of repositories are mentioned in the introduction. One is structured with the use of open source GIS – OpenJump 1.4.2 and use of open source library GDAL and its OGR toolkit. The programming language used is C++. The repository is built over a district-wise geo-referenced map of India in form of Shape (.shp) files. Each district in the file is represented in form of a polygon element and the layer of point elements representing the Railway Station for districts is created by calculating the centroid of the district polygon elements using the function – int OGRGeometry::Centroid (OGRPoint * poPoint ) const [virtual]. Each connection between two railway stations is displayed with the use of line element created using the function – OGRLineString () with vertex station point elements serving as vertices using the function – Void setPoint (int, OGRPoint *). This is how the entire rail network across country is populated. . A value in the point elements shape file representing the stations in the attribute table represents the no. of trains originating from the station. The snapshots of generated network are shown in figure 1 and 2. However, there is a limitation associated with this repository, this only looks at the district level information and overlooks the sub district stations that come in the network.


Figure 1: Electrified Routes

 


Figure 2: Work in progress

The other repository is an open access Google Earth repository; the files can be imported to the local system that can be accessed offline. This repository serves the purpose of inquisitive travelers who would like to see the actual routes followed by major trains of their interest. The collection of routes of announced trains for the decade mentioned above in the selected regions along with their important stoppages and approximate track lengths has been done through Google maps. The process is described below:

  • Verification of existence of proposed train
  • Finding route of train if it exists.
  • Tagging important stoppages of the train along its route.
  • Plotting the route with the help of marked stoppages.

The limitation of this repository is that it does not follow the actual rail tracks rather the road transit system which is assumed to be parallel to the rail network and thus solving the purpose.

Inclusion of new train services and their impacts for decade 2000 to 2009:
Indian Railways hasn’t been a failure in terms of delivering the promises made in the field of introduction of trains. The connectivity of places within a state as well as across the states has been improved over the years. Few statistics affirming this remark is displayed in the figures 3 and 4.


Figure 3: Graph representing newly added trains in respective years

 


Figure 4: Graph representing introduction of bulk of trains in a single category

The arrival of several new services mentioned in above graph can be cited as one of the reason for the sudden increase in the number of introduction of trains from year 2002.

Relation of increase in no. of trains with new lines, gauge conversion and doubling It has been observed that the gradual increase or consistency in the increase in no. of trains is possible due to linear increase in length of new tracks, gauge conversion and doubling of lines. The linear increase can be understood as:


Figure 5: Graph representing completed new lines, gauge conversion and doubling works promised

As, it can easily be observed from the graph that curves shooting up in a linear fashion with consistent slope with each budget has been the driving factor to accommodate several introduced trains and avoid heavy congestion in the existing network, though there have been cases of minor congestion and accident to a certain extent (as the slope isn’t desirably high for doubling) that will be addressed in the later part of the paper.

State wise distribution of electrified network
This portion entails parameters involved in electrification progress in states and study of pattern of electrification for various states.


Figure 6: Graph showing percentage of electrified network and length of total rail network for each state

The relation between the percentage of electrified route and the length of total rail network in state are observed to be inversely proportional to each other for most of the states. The pattern can be easily realized in almost all the states marked after Tamil Nadu in the above graph. For the exceptions, the reasons are topography and availability of resources.

Predictive model based on gradual increase in length of electrified network across country for the past 85 years This study entails the analysis of patterns of route electrified over the years.


Figure 7: Graph showing length of network electrified during five year plans:

However, a fixed pattern doesn’t appear, but a conclusion can be drawn that the 5 year plan from 1980-85 brought revolution and more emphasis was being given to electric engines since then. A sudden rise in length of electrified route has been carried through and the points on the spiral almost form a circular pattern for the period 1990 to 2010 that means a constant rate has been kept to electrify the routes. The spiral web maintains a constant radius for some time and jumps suddenly; this may help in making futuristic growth assumptions and sufficient enough to derive the following predictive model for growth in the sector.

The definition of the developed model can be summarized as: the duration for which there is consistency in the length of rail route electrified is directly proportional to the length of route electrified in a year.

Topographic limitations in specific regions of India


Figure 8: Present scenario of rail network in Jammu and Kashmir

The rail route in Jammu and Kashmir could not be extended beyond that displayed in the image above. The major reason cited for this is actually large variation in heights at places situated very near to each other. In order to avert possibility of major disaster that railway has not expanded its reach there.

Following are the major possibilities of occurrence of disaster if railway network is actually established in this area decided to topographic characteristics of the location:

  • Collapse of bridges: The length of several bridges to establish rail channels in Jammu Kashmir would be more in comparison to any bridge established earlier due to high volume of waters flowing in basins and low availability of plane lands. The risk factor for any bridge increases with its length.
  • Caving in of tunnels: If compromises are to be made with construction of bridges, the other suitable arrangement for making traffic possible in Jammu and Kashmir is blasting off of mountains and hills to make tunnels. Impacts of powerful blasts and their large frequency loosen the structure and there is high probability of caving in of tunnels.
  • Derailment of trains due to high speed on slopes: As there are large variations in the heights of very closely situated regions. The slope of tracks laid there would be considerably high. This adds to risk in terms of handling high speed of trains.
  • Limitations of railways in Jammu and Kashmir due to variation of heights

Repository of Rail accidents using OpenJump 1.4.2


Figure 9: Map displaying the areas hit by rail disasters:

Areas of impact: Uttar Pradesh is observed to be an area highly prone to rail disasters. There are few cases where same place has been hit by rail disaster more than once in the span of less than 5 years, Bhagalpur being one of them.

Assumptions: The reason detected for sudden rise in number accidents occurring in year 2003 can be cited to be introduction of large number of trains in year 2002 which might have been implemented till 2003 causing heavy traffic on nearly the same length of route length.

There are few other reasons discussed later in this paper on the basis of climatic effects on Railways. This has been discussed with the help of geospatial tools.

Climatic Analysis on major accidents
From the data, it is clear that the frequency of rail disasters is more in the months of winter or monsoon. From the map digitized below it, the reason can be better understood. The main reasons cited for these accidents are usually:

  • Dense fogs in the northern parts of the country.
  • Heavy rainfall causing damage to machinery and flooding of tracks.

Conclusions
The visualisation of Indian Railways has been made very effective through the integration of geospatial technology in data storage and representation by developing repositories. These repositories definitely have advantage over the existing schematic view of Indian railways that displays just the network without any coordinates attached to the nodes and edges. The whole study led to a conclusion that the Railways have been keen on fulfilling the announcements made in the Budget sessions but has been continuously marred by mismanagement of services that led to several mishaps in last few years. An increase in load of trains without large scale increase in track lengths (through doublings, gauge conversions etc.) never averts the possibility of a disaster. Effective use of available modernized techniques may however make it possible to enhance the connectivity in Jammu and Kashmir and accidents may be reduced in high fog zones.

Discussions and future work
Until the base map database for Indian Railways with geographic coordinates is introduced by the Centre for Railway Information Systems, India [5], the repository developed as part of this work can serve as an aid to visualize railway elements, though it has got limitations. Geographic relations developed have simplified the management of geographically distributed data. An innovative idea of inculcating budgets with GIS has brought a transparency in the management and functioning of works in the sector. A simple predictive growth model can easily be derived out of such studies that can assist quick decision making. The future work includes sharing of the repository information through the development of a web portal assisted with a feedback system, and further developing small query based applications for users to fetch information of their use from the large pool of data. The essence of feedback systems is from usability perspective of the stakeholder, this feedback information may be anything – the type of data that user frequently visits, the design of elements, the query result format and what not.

References:

  • The relationship between railway and spatial development in Hong Kong, Lau, Yuen-yee, Carey and, Liu Waner, 1999
  • The concept of using GIS in the inventory of architectural and landscape units, Anna Wrocha
  • Railway Budgets, 2000-2009
  • Ministry of Railways – Annual Reports, 2000 – 2009
  • Geospatial to manage the assets and resources of the railway system, S S Mathur, 2013