摘要：In situ observations show increases in shrub cover in different arctic regions in recent decades and have been cited to explain the increases in arctic vegetation productivity revealed by satellite remote sensing. A widespread increase in shrub cover, particularly tall shrub cover, is likely to profoundly alter the tundra biome because of its influence on biogeochemical cycling and feedbacks to climate. To monitor changes in shrub cover, aid field studies, and inform ecosystem models, we mapped shrub cover across the North Slope of Alaska. First, images from the IKONOS and SPOT satellite sensors were used to detect tall (>1 m) and short shrub presence at high resolution (<5 m grid cells) in different parts of the domain. The resulting maps were then used to train a Random Forest regression algorithm that mapped total and tall shrub cover, expressed as a percent of the total surface area, at 30 m resolution from a mosaic of Landsat scenes. The final shrub cover maps correspond well with field measurements ( r 2 = 0.7, root mean square error = 17%, N = 24) and compared well with the existing vegetation type maps of the study area and a gridded temperature data set not used in the map generation.
