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The CMDA administers the Chennai Metropolitan Region, spread over an area of 5,904 km 2 (2,280 sq mi) and covers the districts of Chennai, Thiruvallur, Chengalpattu, Ranipet and Kancheepuram. [1] It was set up for the purposes of planning, co-ordination, supervising, promoting and securing the planned development of the Chennai Metropolitan ...
The Chennai Metropolitan Development Authority (CMDA) is the nodal agency that handles town planning and development within the metro area. In 1974, an area encompassing 1,189 km 2 (459 sq mi) around the city was designated as the metropolitan area which was subsequently expanded to 5,904 km 2 (2,280 sq mi) in 2022.
The organisation was known as Calcutta Metropolitan Development Authority (CMDA) and retains its previous logo. KMDA is functioning under the administrative control of Department of Urban Development and Municipal Affairs of Government of West Bengal .
[2] [3] As the new airport was delayed due to land acquisition problems, [2] [4] an expansion plan was unveiled to expand the existing Chennai International Airport in 2018 to increase the terminal area to 160,000 m 2 (1,700,000 sq ft) with a capacity of 35 million passengers. [5] The existing airport is expected to reach saturation by 2035. [6]
CMDA can refer to: Christian Medical and Dental Associations , a professional medical association Chennai Metropolitan Development Authority , is the nodal planning agency within the Chennai Metropolitan Area
Land use capability maps are maps created to represent the potential uses of a "unit" of land. They are measured using various indicators, although the most common are five physical factors ( rock type , soil type , slope, erosion degree and type, and vegetation).
Community members learned how to use the computer resources, ArcView 1.0, and build a theme or land use map of the surrounding area. They were able to perform spatial queries and analyze neighborhood problems. Some of these problems included finding absentee landlords and finding code violations for the buildings on the maps. [16]
A supervised classification is a system of classification in which the user builds a series of randomly generated training datasets or spectral signatures representing different land-use and land-cover (LULC) classes and applies these datasets in machine learning models to predict and spatially classify LULC patterns and evaluate classification accuracies.