Design and Implementation of LRS

Design and Implementation of LRS - A Case Study

State, UT, District, Division-1, Division-2, Reference-Point Other entities can be revised to give them generalized form as Plot, Owner, Land-Inspector, Tenant, Irrigation-Source, Revenue-Paid The term Land-Inspector and Tenant are used for Collector and Cultivator to give them general sense. (attribute level description of these entities is given in Appendix 3)

ER diagram for nationwide LRS can be given as shown in Fig.4.

Fig.2 Geographic hierarchy using conventional terminology

Fig.3 Geographic hierarchy using proposed terminology
The schema proposed for nationwide LRS can be extended further to include information about basic amenities available in the town / village / district in a single database. The basic amenities can be education, health, entertainment, drinking water, bank, electricity, road, post office, telephone, highway connectivity etc. The other useful information like population, sex ratio, literacy, per man income, rain fall, crop etc. can also be included. This extended system will help district administration to have a close watch on balance development of the whole district and to convey latest data to state or central govt. for further processing. The state and central governments will use these data for macro level planning and to decide appropriate funds for various development activities. The exact structure of information for nationwide system can be decided only after consultation the requirements with district, state and central govt. level concerned officials. The entities in nationwide LRS can be extended to include new attributes required for nationwide information system, however few new entities will also be required to consider. The extension of entities to include new attributes will be as under: -

Plot Plot-Code , LandType, Area, Shape, Map, P-Location, Crop, DrinkingWater, ElectricityConnection, OtherData1, OtherData2,…,OtherDataN

Division-2 D2-Code , D2-Name, D2-Area, D2-Population, D2-SexRatio, D2-PerManIncome,
D2-HighwayConnectivity, D2-PrimaryHospital, D2-Theatre, D2-School,
D2-College, D2-BusStand, D2-Bank, D2-Postoffice, D2-telephone, D2-CropProduction,
D2-RainFell, OtherData1, OtherData2,…,OtherDataN

Division-1 D1-Code , D1-Name, D1-Area, D1-Population, D1-SexRatio, D1-PerManIncome,
D1-Hospital, D1-NumberOftheatre, D1-NumberOfSchool, D1-CropProduction,
D1-RainFall, OtherData1, OtherData2, …,OtherDataN

District D-Code, D-Name, OtherData1, OtherData2,…,OtherDataN
State State-Code ,S-Name, OtherData1, OtherData2,…,OtherDataN
UT UT-Code , UT-Name, OtherData1, OtherData2,…,OtherDataN

New entities of interest may be:
Bus Stand, Primary School, Primary Hospital, District Hospital, Regional Hospital, College, Bank, Post Office, Theatre etc.

If we need to know details about entities like Hospital, Bank, College etc. then there is need to define these entities separately. If we need only the number of these basic amenities in a particular division or district then the extended entities are sufficient by providing additional attributes as yes/no values and the same ER diagram as described for nationwide LRS will also work for nationwide information system.

Query Classification
Ten useful queries have been identified in the case study. All queries have been implemented successfully and are listed in Appendix 4.The queries asked for an LRS will be subset of queries possible in nationwide LRS. The queries required for nationwide information system will further enlarge the list of queries. The possible classification of queries for nationwide system will be as under:

plot specific queries
owner specific queries
tenant specific queries
basic amenities related queries
division specific queries
district specific queries
queries useful for state govt.

Fig. 4 Proposed ER diagram for nationwide LRS

queries useful for central govt.
queries form planning and development point of view

One interesting and most important query may be "Find all plots owned by a particular person in the whole country". The answer of this query will expose the people having disproportionate land in favour of their names. To implement the query the owner should be identifiable at national level just like a vehicle or voter card number. Few queries for nationwide system are listed in Appendix 5.

Implementation
The case study made of LRS for district Hamirpur (HP) is implemented using Access 2000 RDBMS [24]. There are seven entity tables, three relationship tables (for many-to-many relationships) and ten queries in the implementation. One -to-one and one-to-many relationships are implemented using the concept of foreign key. OLE data type is used to represent map of a plot as an image. Forms are used for displaying results. Queries implemented are listed in Appendix 4. Welcome screen and results of few queries are shown in Appendix 6. Detail steps of implementation of database using Access are discussed in [20].

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