Application of time-lapse digital imagery for ground-truth verification of satellite indices in the boreal forests of Alaska

Satellite remote sensing studies of snow cover in high-latitude boreal forests require ground-truth verification based on ground observation networks. In this study, we used time-lapse digital images to precisely detect the extent of snow cover at nine locations in the boreal forests of Alaska, and to demonstrate the relationship of these ground-truth measurements to satellite indices of snow cover. Our results show that normalized difference vegetation indices (NDVIs) and normalized difference water indices (NDWIs) show significant variations at the end and beginning periods of continuous snow cover: the NDVIs on the last days of continuous snow cover ranged from 0.12 to 0.37, and those on the first days of continuous snow cover ranged from 0.16 to 0.38. The normalized difference snow indices (NDSIs) were also positive during periods of continuous snow cover and negative during periods of no snow cover. The NDWIs varied significantly from the beginning to the end of periods of continuous snow cover. This study confirms that continuous snow cover is important for accurate phenological studies using NDVIs in the region of the trans-Alaska camera network. Simple cameras can be effectively utilized in ground-based networks, functioning not only as a ground-truth verification tools for calibrating satellite indices, but also as a source of data to fill data gaps in satellite records.