GIS Concepts

Vector Analysis
1) Buffer analyses were performed in order to define both areas where management should not occur (such as stream and riparian zone protection) and where management should occur (such as areas that are within 100 feet of a trail).
2) Clip analyses were used primarily for reducing the amount of data that needs to be processed.  For example, it is much easier to draw and run analyses on roads for only the Uncompahgre National Forest instead of the entire Grand Mesa, Uncompahgre and Gunnison National Forest the original data came from.  However, clip can also be used to extract buffer treatment areas along roads, trails and recreation buffer zones.
3) Erase analyses was used to exclude areas where management should not occur such as areas within 100 feet of a stream on within a roadless or wilderness area.
4) Union is another tool that is useful for simplifying layers and reducing the quantity of data that needs to be processed.  Instead of performing all the necessary analysis steps on the aerial detection survey for each year from 2005 to 2009 they can be combined into one layer.
5) Dissolve was often used in conjunction with merge in order to eliminate multiple lines within a polygon.  An important step to remember when running this process is to not allow multipart features.
6) Zonal Statistics using raster grids is the only raster analysis required in this process.  A grid displaying percent slope is used in order to perform zonal statistics on individual aspen stands.  From this analysis we get a table that shows the mean slope of an individual aspen stand.
7) The attribute table for the SAD impacted stands is joined with the zonal statistics table, using the common field object_id.  From the new attribute table, a treatment strategy can then be given to each individual stand based on mean slope.
8) Queries using select by attributes and select by location are used to identify stands that have specific characteristics that are important for determining the appropriate management action.  These actions are defined in the management action matrix.  The results from the queries can then be edited by either manually entering attributes into individual fields that are selected or by creating new layers from the selection.

Raster Analysis
1) Raster calculator was used for many steps in the raster analysis. Raster calculator functions used in this project include simple arithmetic operations as well as conditional statements.
2) Distance to analyses were executed from the spatial analyst toolbar for determining straight line distances to pixels from recreation points, trails, and roads.
3) Viewshed analyses were performed from the spatial analyst toolbar to determine the aesthetic value component of management value. The viewshed is the portion of the landscape that can be seen from a given point, line, or area feature. When using multiple points, lines, or polygons the output includes the number of input features that the pixel can be seen from. The raster surface used was the ASTER DEM and the input features were recreation points as well as classes of roads and trails.
4) Resample was used to process additional raster layers so that they all are aligned to the ASTER DEM and have the same spatial resolution. Resample is found under Data Management -> Raster -> Raster Processing.
5) Slope was calculated using the surface analysis menu in the spatial analyst toolbar. The input raster surface was the ASTER DEM and the output used was percent slope.
6) Zonal Statistics was used to summarize management value, management cost, and management value-cost difference rasters at the level of the stand. It was also used for selecting stands on the basis of whether they are closer to roads or trails. 
7) Queries using select by attributes were used for selecting stand on the basis of proximity to roads and trails.
8) Clip raster was utilized to select those pixels that fall within SAD affected stands both for creating mosaics of the final cost layers as well as for pixel-based prioritization analyses.
9) Mosaic outputs to new raster was used for joining together rasters with values for portions of the landscape coming from different sources, such as for cost surfaces based on either proximity to roads or trails.