URBAN SPRAWL MAPPING OF AJMER CITY (2020-2024) USING SATELLITE IMAGERY
DOI:
https://doi.org/10.48165/ngnwrq78Keywords:
Urban sprawl, Remote sensing, GIS, Supervised classification, satellite imageriesAbstract
The rate of urbanization in Indian cities, like several other developing cities around the world is increasing at an alarming rate. This unprecedented and uncontrolled urbanization may result in urban sprawl or suburban sprawl, the rapid expansion of the geographic extent of cities and towns, often characterized by low-density residential housing, single-use zoning, and increased reliance on the private automobile for transportation. Urban sprawl is caused in part by the need to accommodate a rising urban population; however, in many metropolitan areas, it results from a desire for increased living space and other residential amenities. Urbanization is the process in which the population shifts from rural to cities or urban centres for an improved standard of living due to economic growth and development. As the migration rate increases, urban cities undergo major changes in land use and land cover which trigger several negative effects such as overcrowding, water scarcity, air pollution, loss of productive agricultural lands and forest cover. Remote sensing and Geographical Information System (GIS) are used for monitoring the emerging urbanization of the cities using satellite images. The ill effects of urban sprawl in developing countries are a bit complicated compared to those of developed countries because of uncontrolled population growth and haphazard urbanization.An overview of the enormous potential of remote sensing and GIS techniques in mapping and monitoring the Spatio-temporal patterns urban sprawl is dealt with here. The spatial pattern and dynamics of the urban sprawl of Ajmer City (Rajasthan, India) during the period from 2020 to 2024 using the integrated approach of remote sensing and GIS are attempted here. Supervised classification is used for the rapid and automated extraction of built-up features from the time series satellite imageries. The extracted built-up areas of each year are then used for the quantification of urban sprawl and its associated area (in km). The results and analysis highlight the fact that there was an alarming increase in the built-up area extent from 2020 to 2024.
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