Land Cover and Permafrost Change Mapping Using Dense Time Stacks of Landsat and Quickbird Imagery

Abstract:

Climate change is especially pronounced in the Arctic, and regions on permafrost are at the frontier of these changes. Increasing air temperatures affect the extent, type, and characteristics of permafrost which is critical to many natural phenomena and northern infrastructure. In areas of discontinuous permafrost certain land cover types are indicative of permafrost conditions making satellite imagery an important tool for assessing environmental change in these remote areas. In arctic environments remote sensing can be particularly challenging due to consistently high cloud cover, data gaps, and landscape heterogeneity. However, there has been success at dealing with such challenges in lower latitude regions using the emerging dense time stack methodology. In place of using an anniversary date for land cover comparisons from different years, this methodology includes scenes from all seasons in addition to imagery normally rejected due to data gaps and high amounts of cloud cover. The incorporation of all available data creates a “dense time stack” which provides both a more complete dataset and more nuanced spectral signatures for classification. This work applied the dense time stack method to mapping five drainage basins in the close vicinity of the city of Igarka, Russia using both Landsat and Quickbird satellite imagery. The resulting map series proved this method to be effective within the Arctic for multiscalar mapping both temporally (annual and seasonal) and spatially (at the resolutions of Landsat and Quickbird). The time series of observed land cover changes produced allowed areas of permafrost degradation to be identified. These maps will be applied in the future to ongoing hydrological research in the region investigating the sources of increased run off and its relation to permafrost degradation.