Satellite image based sub pixel change detection of snow ice cover over Himalayas

Abstract

The snow cover region acts as a natural source of water for power generation, agriculture newlinegrowth, and smooth running of the hydrological cycle of the earth system. The mapping and newlinemonitoring of the snow/ice changes over different regions of the Earth surface is a challenging newlinetask due to regional rugged topography which leads towards shadow effects. Change detection newlineis one of the most common approaches to extract maximum information and generate change newlinemaps from remotely sensed imagery. Traditional change detection methods follow the perpixel allocation in which only one class is assigned to a specific pixel. For accurate snow/ice newlinemapping, there is a requirement of a sophisticated model that includes the consideration of newlineterrain features, semi or fully automatic threshold methods, and detection of the small spurious newlinechanges. On the other hand, the satellite imagery acquired over rugged topography is generally newlineaffected by the topographic effects in form of the shadow. To overcome such limitations, this newlineresearch work involves the (a) evaluation of topographically derived different classification newlinealgorithms over rugged terrain Himalayas using remote sensing data, (b) development of a newlinesubpixel-based change detection algorithm to identify and quantify the land-use and land-cover newlinevariations at the subpixel level and (c) analysis of spatial and temporal variability of snow/ice newlinecover over the Himalayas using the proposed subpixel -based change detection algorithm newline