Hyderabad, April 07: With the government deciding to put a stop to land sharks in the city who take over open government lands and later claim ownership over it, revenue officials have prepared a data of house numbers which will help the department of Stamps and Registerations prevent the registeration of government lands by private parties. The system will be in place and will be effective by May.
Unlike other districts, registrations in Hyderabad are done based on house numbers. But land grabbers have been taking advantage of this by creating fictitious house numbers, getting electricity connections for them and using the power bills to project themselves as the rightful owners of the land.
Officials say that with this modus operandi, large chunks of government-owned lands in the city have been resold by the land sharks to private parties who in turn sold it to other parties thereby executing multiple registrations over several decades.
“We had suggested that the stamps and registration department include survey numbers as mandatory for the execution of registration and give survey numbers for the government land in the city. But the department officials said it was not possible and instead asked us to give the house numbers of the existing government lands so that registration for them will not be done,” a district official said.
In 2009-10 the officials of Greater Hyderabad Municipal Corporation (GHMC) collected house numbers across the city using Geo-referencing system.
“This data has helped in identifying the house numbers of the all the government lands by superimposing the survey number data which we already had. This data of house numbers will be given to the stamps and registration department who will bar the registration of government lands to private parties. The buyers of the land will also be warned of the attempt to cheat him,” an official added.
The preparation of data is completed in revenue mandals like Ameerpet and Golconda and district officials are conducting field inspection to verify the collected data.
–Agencies