Margao, Mormugao ODPs to be converted into masterplans

Panaji: The town and country planning department is set to convert the existing outline development plans (ODPs) for Margao and Mormugao into comprehensive GIS-based masterplans under the Centre’s Amrut 2.0 programme. The move will see both cities digitally mapped with data-driven blueprints covering land use, infrastructure, transport, housing and employment.

The exercise is being undertaken under a sub-scheme of Amrut 2.0 specifically designed for class II towns with populations between 50,000 and 99,999. The sub-scheme is fully funded by the ministry of housing and urban affairs and targets towns that were not covered under the Amrut mission launched in 2015, which focused on metro and class I cities.

For Margao and Mormugao, the exercise will involve converting their existing notified ODPs into a GIS-based urban database covering 25 socio-economic and physical parameters, and producing a full statutory masterplan under the Goa Town and Country Planning Act, 1974.

TCP officials estimate that it will take over a year to convert the ODPs into masterplans, with the first step being the appointment of a consultant.

The masterplan for Margao will cover an area of 82sqkm, including the municipal area and peripheries of the urban area, which includes surrounding villages. For Mormugao, the TCP is considering the Vasco da Gama planning area, which covers 42.4sqkm of municipal and panchayat areas.

The masterplans will map population growth, employment, industries, commercial activity, schools, hospitals, roads, water supply, sewerage, solid waste, parks, heritage sites, agricultural land, forest cover and govt-owned vacant land. Primary surveys, including land use, traffic and transport, and household surveys, will also be conducted, the official said.

The entire process will be paperless, using an integrated mobile application developed by the ministry of housing and urban affairs in association with the Indian Institute of Remote Sensing, Dehradun, which will be used for field data collection, attribute vetting and incorporation of satellite imagery inputs.
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