Abstract
The study on land use and land cover (LULC) changes assists in analyzing the change and regulates environment sustainability. Hence, this research analyzes the Northern TN coast, which is under both natural and anthropogenic stress. The analysis of LULC changes and LULC projections for the region between 2009-2019 and 2019-2030 was performed utilizing Google Earth Engine (GEE), TerrSet, and Geographical Information System (GIS) tools. LULC image is generated from Landsat images and classified in GEE using Random Forest (RF). LULC maps were then framed with the CA-Markov model to forecast future LULC change. It was carried out in four steps: (1) change analysis, (2) transition potential, (3) change prediction, and (4) model validation. For analyzing change statistics, the study region is divided into zone 1 and zone 2. In both zones, the water body shows a decreasing trend, and built-up areas are in increasing trend. Barren land and vegetation classes are found to be under stress, developing into built-up. The overall accuracy was above 89%, and the kappa coefficient was above 87% for all 3 years. This study can provide suggestions and a basis for urban development planning as it is highly susceptible to coastal flooding.
Highlights
The development of urbanization and industrialization led to the change in land use and land (LULC) in the last two centuries resulting in the degradation of the sustainable conditions for the future
The study area is divided into two zones: Zone 1 (Z1) and Zone 2 (Z2), five primary classifications, i.e., waterbody, built-up, vegetation, forest, and barren land
Google Earth Engine (GEE) was used to identify the Land use and land cover (LULC) because it has a cloud platform, a user-friendly interface, and an effective scripting language, and it has a high degree of adaptability and flexibility
Summary
The development of urbanization and industrialization led to the change in land use and land (LULC) in the last two centuries resulting in the degradation of the sustainable conditions for the future. This intense urbanization does not follow a linear trend (Bose & Chowdhury, 2020). Low-density built-up regions become high-density and later extremely density regions because of the increasing land demand due to changes in the desirability of the communities (Saxena & Jat, 2020). The controlling mechanism of urban development involves assessing the time-space relationship between nonlinear interactions such as culture, economy, topography, population, land use, and river systems. The controlling mechanism of urban development involves assessing the time-space relationship between nonlinear interactions such as culture, economy, topography, population, land use, and river systems. (Thapa & Murayama, 2011)
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