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Creating Attribute Tables:
Attribute tables for each theme is created. Besides the inbuilt fields in the attribute table, for the 'bus stops' theme the other fields in the attribute table include the following,

• Name of the bus stop
• Passenger density in the bus stop
• Category of the bus stop (white board/yellow board stopping)
• Interval between two bus stops

Similarly for the 'land use' themes the fields created were rank of land use, which, is common for all types of land uses and the weight of that particular land use. For the theme study route (road) field like width of the road and for the theme buffer the field with weight of that particular buffer is created.

Overlaying:
The themes thus created are overlaid one above the other to get a complete picture of the study area. Now the view will contain the study route abutted with the different land uses, the location of all the bus stops and the buffer around each bus stop.

Analysis
Analysis is done basically by means of querying and drawing charts.

Querying:
Querying is done to retrieve a specific data from the attribute tables. A query request is made as per the user's need and desire. The result of a query is always accompanied with a change in the visual representation of the view in way of highlighting or change in colour of the features in the theme, which suits the query and the records correspondingly will be highlighted. Queries help in deciding on a particular issue or in decision-making and is can also form part of an analysis.

Some of the queries that can be made in the study are listed below,

• Bus stops with specified passenger density - ( [Pass_densi] >= 200 )
• Bus stops spaced lesser or more than a specified limit - ( [Dist_after] <= 400 )
• Bus stops meant for LSS - [Yellow_boa] = "Y"
• Bus stops with a specified passenger density and with a specified interval and meant for LSS, this is a typical complex query where in more than one criteria has to be satisfied. - ( [Pass_densi] >= 250) and ([Dist_after] >= 400) and ([Yellow_boa] = "Y")

Charts:
Charts are created with the inbuilt feature provided in the ArcView software. They are created to compare and arrive at findings which may be helpful for setting out the recommendations. The charts created in the study include the following,

Chart for passenger density for all the bus stops located for going towards Thiruvanmiyur and Saidapet each separately.
• Chart for inter bus-stop distance for all the bus stops located for going towards Thiruvanmiyur and Saidapet each separately.

Observations from the Analysis:
From the analysis it was found that the following bus stops need to be relocated or removed as the case may be because of the reasons attached here under, the bus stops are,

Court - because the inter bus stop distance is only 150m and the passenger density is far low (105) when compared to other bus stops.

HRS - because the passenger density is poor (89) and inter bus stop distance is low (275m).

CLRI - because the passenger density is very low (25) and the distance from the next bus stop is low (200m) and

Anna university bus stop situated in the direction-towards saidapet which is not in use may also be removed.

Conclusion
The three bus stops which has not satisfied the criteria set for rationalisation can be removed. The analysis in ArcView can be made by other means like ranking and weighting method in overlay analysis which would be more apt and will be more representational but due to time constraint that analysis was not adopted in the study. Hence by means of querying and creating charts the analysis is done and the findings and recommendation are given.

Future Scope of the Study
As mentioned in the conclusion the full use of ArcView can be realized when a ranking and weighting method is adopted as against the querying. By this, each bus stops will get a rank based on certain criteria and those bus stops below a certain rank can be regarded as the one which needs to be relocated or removed. Ranking and weighting method would be more apt when it is used for a larger study area, say for instance the entire chennai city where in the bus stops would be in hundreds and manual rationalization of bus stops would be tedious.