The objective of the research presented in this dissertation was to better understand the factors controlling the present and potential future distribution of arctic vegetation. The analysis compares the Circumpolar Arctic Vegetation Map (CAVM) with circumpolar data sets of environmental characteristics. Geographical information system (GIS) software was used to overlay the CAVM with a satellite index of vegetation (normalized difference vegetation index, NDVI) and environmental factors that are most important in controlling the distribution of arctic vegetation, including summer temperature, landscape age, precipitation, snow cover, substrate chemistry (pH and salinity), landscape type, elevation, permafrost characteristics, and distance to sea. Boosted regression tree analysis was used to determine the relative importance of different environmental characteristics for different vegetation types and for different regions. Results of this research include maps, charts and tables that summarize and display the spatial characteristics of arctic vegetation. The data for arctic land surface temperature and landscape age are especially important new resources for researchers. These results are available electronically, not only as summary data, but also as GIS data layers with a spatial context (www.arcticatlas.org). The results emphasize the value and reliability of NDVI for studying arctic vegetation. The relationship between NDVI and summer temperatures across the circumpolar arctic was similar to the correlated increases in NDVI and temperature seen over the time period of satellite records. Summaries of arctic biomass based on NDVI match those based on extrapolation from ground samples. The boosted regression tree analysis described ecological niches of arctic vegetation types, demonstrating the importance of summer temperatures and landscape age in controlling the distribution of arctic vegetation. As the world continues to focus on the Arctic as an area undergoing accelerated warming due to global climate change, results presented here from spatially explicit analysis of existing arctic vegetation and environmental characteristics can be used to better understand plant distribution patterns, evaluate change in the vegetation, and calibrate models of arctic vegetation and animal habitat.