Upper Gunnison Basin Land Cover
The Upper Gunnison Basin is a high-elevation ecosystem in Colorado ranging in elevations from 2200 to 4300 m above sea level. Present (actual) vegetation of this 11,000 km2 basin ranges from sagebrush steppe at lower elevations, to montane and subalpine forests at mid-elevations, and alpine tundra above 3600 m. The low population density and the high percentage of federally-owned land (85% of the Basin) has helped prevent large-scale destruction except along rivers at lower elevations where riparian communities have been impacted by ranching.
Mapping of the Upper Gunnison Basin's land cover has been limited by the diverse and often incompatible needs of the federal agencies managing resources in the Basin and the lack of digital technology. Numerous large-scale maps, typically of 1:24,000 scale, have documented the spatial distribution of potential vegetation in selected areas. The only Basin-wide coverage of land cover and vegetation is a series of 1:126,720 scale maps produced by the Soil Conservation Service (USDA 1976a, 1976b, 1976c). While these maps delineate broad forest types, they combine all non-forested areas of the Basin as range. While most of the existing maps were derived through color aerial photo interpretation, considerable information is lost in the production of analog maps, and the possibility of subsequent data analysis is limited. Much more desirable are digital land cover maps developed and analyzed with geographic information systems (Coulson et al. 1991, Sample 1994, USDA 1995). Such maps layers can be compared to other spatial layers such as soil types, geologic substrates, landforms, and elevation. Development of multiple map layers, including a vegetation layer, will provide a valuable GIS database for use in ecological and geological research, land management decisions, and GIS coursework at Western.
This mapping project includes all portions of the Upper Gunnison Basin that drain into the Gunnison River above the Black Canyon of the Gunnison River (Blue Mesa Dam). This basin is delineated by the continental divide to the east and south, the Elk Mountains to the north, and the West Elk Mountains, Soap Mesa, Alpine Plateau, and the San Juan Mountains to the west. (Colorado Map -125 kb image)
Initial mapping efforts have utilized Landsat multispectral scanner (MSS) data obtained from the North American Landscape Characterization project. Two MSS images ( path 034, row 033; and path 034, row 034; 07/05/92) were concatenated. (MSS frames - 11 kb image) The outline of the Upper Gunnison Basin was then digitized and georeferenced. The resulting vector layer was converted to a polygon raster layer, which was then applied to the satellite image to eliminate areas outside the boundaries of the basin.(MSS Frames with basin -37 kb image) Cloud cover and shadows were removed through filtering and the overlaying of 1983 MSS data where needed. These corrections modified less than 5 % of the map area.
Using Idrisi software, the supervised classification methods of varying combinations of the red, green, and two infrared bands proved unsuitable in distinguishing land cover types. However an unsupervised cluster analysis, using a histogram peak technique, produced satisfactory results. An image was produced from a cluster analysis performed on the false color composite of bands 2 (red), 3 (near-infrared), and 4 (near-infrared).(Composite -19 kb image) Using a map with 15 clusters (Clusters -107 kb image) , a land cover map was derived by consolidating the clusters into six categories coniferous forest, rock/bare ground, snow, water, grasses, and aspen. Further refinement resulted when a digital elevation model (DEM) was used to distinguish among low (sagebrush steppe), mid (shrub steppe), and high (tundra) elevation vegetation.(Landcover - 133 kb image)
An error matrix analysis of random points within the Basin yielded an overall map accuracy of seventy-four percent. These points were chosen using the sample module in Idrisi.(Sample Points - 47 kb image) The points were checked using aerial photography from soil surveys, USDA aerial photos from the U.S. Forest Service, and field checking. To assist in referencing the points on the photos, roads, vegetation patterns, and global positioning system (GPS) were most often used. The road vector layers were obtained from Digital Line Graphs produced by the U.S. Department of the Interior.
The MSS data has been insufficient in spatial detail and discrete reflectances to provide land cover maps of higher discrimination. Use of Landsat thematic mapper (TM) data is expected to provide the resolution and spectral bands necessary to further refine our land cover map(USGS 1996b).
Coulson, R.N., C.N. Lovelady, R.O. Flamm, S.L. Spradling, and M.C. Saunders. 1991. Intelligent geographic information systems for natural resource management. pp 153-172. In: Quantitative methods in landscape ecology. Turner, M.G. and R.H. Gardner, eds. Springer-Verlag, New York.
North American Landscape Characterization (NALC) Http://edcww.cr.usgs.gov/glis/hyper/guide/nalc
Sample, V.A. 1994. Realizing the potential of remote sensing and GIS in ecosystem management planning, analysis, and policymaking. pp 346-352. In: Remote sensing and GIS in ecosystem management. Sample, V.A., ed. Island Press, Washington, D.C..
USDA 1976a. Land use and natural communities: Gunnison County, Colorado. United States Department of Agriculture, Soil Conservation Service, Portland, Oregon.
USDA 1976b. Land use and natural communities: Hinsdale County, Colorado. United States Department of Agriculture, Soil Conservation Service, Portland, Oregon.
USDA 1976c. Land use and natural communities: Saguache County, Colorado. United States Department of Agriculture, Soil Conservation Service, Portland, Oregon.
USDA 1995. Guidelines for the Use of Digital Imagery for Vegetation Mapping. United States Department of Agriculture, Forest Service Engineering Staff. Washington D.C..
USGS 1996a. 1-Degree USGS Digital Elevation Models. United States Geological Survey..
USGS 1996b. Thematic Mapper Landsat Data. United States Geological Survey.