The Indian Himalayan region experiences the highest amount of snowfall. The continuous monitoring and mapping of snow over these regions plays a crucial role in gaining insights into how snow influences climate change and in enhancing the management of water resources. Satellite imagery makes it easy to track aggressive and inaccessible snow cover areas. Several remote sensing sensors are available for research, such as synthetic aperture radar (SAR), panchromatic (PAN), multispectral (MS), and hyperspectral (HS). To monitor snow cover areas, numerous classification and change detection techniques were applied. This study provides a brief summary of these techniques and explores the general framework for snow cover change detection. Key concepts, challenges, and recent advancements in snow-covered areas are comprehensively reviewed. This paper navigates through the critical components of snow cover mapping and change detection using remote sensing techniques. It begins by emphasizing the significance of monitoring snow cover in regions with substantial snowfall, such as the Indian Himalayas. The literature review synthesizes existing knowledge, and the following sections explore several approaches to classification and change detection. Findings are presented and discussed, culminating in a conclusion that summarizes key contributions and proposes potential directions for future research.