An effort towards understanding the dynamics of urban sprawl and its influence on land cover: A case study of East Sikkim, India

East Sikkim is one of the most emerging districts of all the four districts in the state of Sikkim, India. The district, since its very inception, has been the prime hub of administrative, educational, cultural, commercial, and industrial establishments, providing tremendous opportunities for economic prosperity and quality livelihood. The very organization of the state’s business affairs has been centric to the East District. These critical attributes have been the driving force behind the unprecedented inflow of population from the surrounding regions and rampant unorganized concretization of low-density residential and commercial provision to cater to the ever-growing needs, consequently resulting in rapid depletion of greenery and forest cover. These irreversible anthropological changes have not only impacted the land use and land cover; consequently, it has also left an indelible mark on the local ecology, bio-diversity, demography, pollution, traffic, and essential resource management such as water and power supply, thereby adversely affecting the quality of life. The rapid increase in the sprawl and unplanned encroachment of open spaces have disturbed the balance between preservation and development crucial to a healthy and sustainable urban lifestyle. Motivated by the specified pertinent problem, this research initiative aims at temporal analysis of Landsat satellite data sets of East Sikkim over an interval of 23 years to determine the rate of depletion of natural vegetation and augmentation in urban sprawl along with identification of inherent patterns and relevant causes. In pursuit of the research objectives, supervised image classification has been performed to identify various land cover classes such as urban spaces, forest, vegetative, and barren-land. The results obtained from the classification have revealed that dense forest, and barren land have decreased from by approximately 12.48 km² and 17.27 km² respectively whereas vegetation, and urban spaces has increased by approximately .93 km² and 36.04 km² respectively. The result was obtained with an average classification accuracy of 91.85% and Kappa of .8581.