This document summarizes an independent study project to create a predictive vegetation map for Alta Ski Area using GIS analysis. The methodology involved acquiring topographic and vegetation data, analyzing slope, aspect and elevation to identify attributes for each plant community type, and using spatial analysis tools to predict vegetation boundaries. The results were a predictive vegetation map and data layers. Next steps include vetting the data with ecologists and refining the vegetation type polygons. The project required more work than anticipated but provides high quality data to help guide land management.

1. Maura Olivos
Salt Lake Community College
GEOG 2900 – A. Dastrup
April 30, 2012
Alta Ski Area Vegetation Communities – A Predictive Analysis Map
Independent Study Update
This project was pursued with the intent to “help guide both the Forest Service and the ski industry in
maintaining, restoring and managing sensitive alpine environments and national forests for continued
sustainable commerce of our national lands.”1 This consisted of identifying appropriate data for analysis,
performing a series of geoprocessing tools, displaying the output in a visually appealing map, and most
importantly identifying the relevant use and additional steps to refine the data. Much of the projects steps
diverted from the original proposal, but the outcome is believed to be of higher quality than if the originally
intended data sources were used for analysis. The remainder of this update details the methodology, results,
next steps and project reflection.
Methodology
Data Acquisition: The data used for this analysis was completed with four different resources than originally
planned.
1. As mentioned in the February 15, 2012 project proposal, ASA was just starting its GIS program with
the process of georeferencing CAD files for GIS use and acquiring appropriate DEMs. From this
contracted work Alta was supplied with the slope, aspect and elevation topographic files, vector line
and polygon files, as well as a georeferenced aerial image rasters for this analysis.
2. Completed in December 2012, the original 1997 “Vegetation Communities Map” from the Final EIS –
Alta Ski Area Master Development Plan was georeferenced. The re-creation of that map’s features
was completed to act as a guideline in identifying each plant community type’s defining attributes.
3. The Town of Alta was the third party source for viable vector data, including: structures, contour
lines, roads, lifts, and mountain summits.
4. Lastly, polygon shapes were drawn to identify true locations of different plant community types
based from ASA’s Vegetation Management Plan study plot point data.
Data Analysis: This analysis of the data was the bulk of this project and took a long series of trial and errors in
determining the best geoprocessing tools for the desired and workable output. The following includes the
basic steps for each plant community type. For detailed notes please see attached “Geoprocessing Steps and
Notes.”
1. Define classification fields for slope, aspect and elevation.
2. Prepare vector data, included connecting polylines to convert to polygons
3. Identify defining attributes for each vegetation type, includes: vector similarities, slope, aspect and
elevation.
4. Perform a binary spatial analysis with geoprocessing tool “Raster Calculator” for slope, aspect and
elevation.
5. Select Binary Output “1” to create a new layer and convert “Raster to Polygon.”
1
“A Proposal for GIS Independent Study”, Maura Olivos, February 15, 2012.
M. Olivos – page 1 of 1

2. 6. “Intersect” or “Erase” new polygon layer with other appropriate polygon attributes to reach final
plant community type.
Deliverables & Results
Most of the deliverables of this project were met with the following (detailed from original proposal) and can
all be found at this site - http://olivosgisportfolio.yolasite.com. Uncompleted portions are colored in red.
1. A georeferenced version of ASA’s “Vegetation Management Plan” management boundaries in the form
a vector file, including appropriate attributes and metadata.
2. A georeferenced version of ASA’s “Vegetation Types” boundaries in the form of a vector file, including
appropriate attributes and metadata.
3. An updated version of the “Vegetation Types” map with predictive analysis providing vegetation
designations for disturbed ground within ASA to guide restoration efforts in the form of a vector file
with appropriate attributes and metadata, and an analysis outline.
4. Map and paper describing the findings and potential applications of this project.
Next Steps
The symbology of the final map for this project was manipulated to show a finished product, but to allow for
usable data for greater purposes the actual data files still need refinement. The following includes the next
appropriate steps to allow for a sharable dataset.
M. Olivos – page 2 of 2

3. 1. Share a five-layer map (aerial image, predictive output, elevation, slope and aspect) with other
certified Ecologists and Botanist for third party verification of the predictive analysis.
2. Refine Vegetation Type data layers, includes:
a. Merging or dissolving overlapping polygons of the same vegetation type.
b. Editing attribute tables
c. Permanently joining all vegetation types into a single feature class.
3. Edit anomalies within the predictive model and make note
4. Determine whether a model can be made and performed.
Once these steps are completed the project will have received appropriate verification for use and diffusion
with other ski areas or micro-management of alpine ecosystems throughout the west.
Project Reflection
This project was much more complicated than originally thought, however I believe the visual output is of high
quality and follows true to the predictive model with minor editing. In the beginning of this process the steps
were elongated due to the unknown viability of the output. Once output was confirmed, then I became more
comfortable with compiling data commands in single queries (versus a series of individual feature selection
queries). Once other ecologists confirm the data, a lot of time will additionally be needed to edit the features
so they output in a usable format with the attribute table. At first, I was very uncomfortable with not being
able to completely finish the data editing, but then I received the opportunity to hear from a guest GIS
professional “Buck” in my “Maps and Measurements” course. His comment was that the refinement of a
map’s data can take up to 10 years, considering the verification, continued field trips, and collaboration, which
is how long he and his team had been working on the maps that he shared with us. I feel much better
knowing that though geoprocessing analysis can take a relatively short amount of time, verifying the data and
editing it so that it is in a usable format can take a significant amount of collaboration and time.
M. Olivos – page 3 of 3

4. Geoprocessing Steps and Notes
1. Prepared Data
a. Vector Data for Selection
i. Trees
ii. Plant Comm 2011
iii. Wetlands
iv. Albion Wetlands
v. Land Cover
vi. AltaPavedRoads
b. Raster Data for Selection: Classified DEMs to appropriate needs
i. Slope
ii. Aspect
iii. Elevation
c. Conversions
i. Tree_Vegetation polyline to polygons (ArcToolbox > Data Management Tools > Features
> Feature to Polygon)
ii. Edited AltaPavedRoads to close polylines then converted to polygons (Alta Paved Areas)
– to be used as an erase feature
iii. Did not do the same with dirt roads because layer is not updated and falls under the
potential predictive model since they are not permanent.
2. Created Control Vegetation sites to determine criteria for each plant community type (slope, elevation,
aspect, etc.)
3. Conifer Willow
a. Attributes
i. Trees & wetlands (no intermittent wetlands) must be present
ii. Slope 0 – 30
iii. Aspect – all
iv. Elevation – all
v.
vi. Queries:
1. Performed a Binary Spatial Analyst to determine Initial criteria for slope and
aspect
M. Olivos – page 4 of 4

5. 2. Raster Calculator: input - slope_degree <= 30 / output – 1 or 30DegLess (raster)
3. Intersect: Geoprocessing > Intersect – Input: Trees and Intermittent Wetlands /
output: WetTrees
4. Convert Raster Data to Polygons: input - 30DegLess (raster) / output – 30deg
(polygons)
5. Selection by Attribute: 30deg – Gridcode = 1 > make selection into a layer
6. Intersect: Geoprocessing > Intersect – Input: WetTrees and 30deg / output:
ConiferWillow
4. Alpine Forb: General description
i. Attributes
1. No trees & wetlands
2. Present in Rock Talus & Alpine Forb
3. Slope: 10-40
4. Aspects: all but S & SW
5. Elevation: 10400 ft or more
ii. Queries
1. Rock Talus & Alpine Forb > Selected from Plant_Comm_2011 and made into a
new layer
2. Erase Analysis: Input – New Rock Talus-Alpine, Erase – Wetland and Trees
3. Elevation: Raster Calculator input >=10400 ft / output 10400ft (Binary 1)
4. Raster to Polygon: Input 10400ft / Output 10400ft
5. Selected 9800 ft and less to use for Erase feature
6. Raster Calculator: (Slope>=10) & (Slope <= 40)
7. Raster Calculator: (Aspect >= 157) & (Aspect <= 247), but worked with output 0
8. Raster to Polygon: Both Slope and Aspect outputs
9. Select appropriate Grid Codes and Intersect Slope and Aspect
10. Intersect SlopeAspect with RockTalus-AlpineForb for final AlpineForb layer
5. Short Forb: General Description
i. Attributes:
1. No trees & wetlands
2. Acceptable parameters: Rock Talus and Short Forb
3. Slope: 0-40
4. Aspects: No W, NW, N
M. Olivos – page 5 of 5

6. 5. Elevation: max 10400
ii. Queries:
1. Raster Calculator: ("slope_degree" <= 40) & ("elevation" < 10400) & ("aspect" >=
22) & ("aspect" <= 247)
2. Convert Raster to Polygon
3. Erase from new polygon: trees, wetlands, conifer willow, alpine forb
4. A lot of overlap with potential other plant community types, must come back to
later after more has been narrowed down.
5.
6. Tall Forb: This plant community type can exist with many other specific community characteristics.
Attempt will be made to identify generals then overlapping areas with other plant community will be
separated out.
i. Attributes
1. No rock/talus, no glacial polish rock
2. Acceptable overlap: Intermittent wetlands, trees, wetlands
3. Slope: 0-30
4. Aspect: No S
5. Elevation: max 10200 / True tall Forb 9800
ii. Queries:
1. Raster Calculation: ("slope_degree" <= 30) & ("elevation" <= 3109) & ("aspect"
<= 157)
2. Raster Calculator: ("slope_degree" <= 30) & ("elevation" <= 3109) & ("aspect" >=
202)
3. Raster to Polygon
4. Select output 1 and merge to “PossibleTallForb”areas (use for following)
iii. Tall Forb Variety Queries
1. Intersect: Tall Forb + Intermittent Wetlands + Trees (erase ConiferWillow) =
ConiferWillowTallForb
2. Intersect: Tall Forb + Trees = ConiferTallForb
3. Tall Forb Possible and Erase: ConiferWillowTallForb and ConiferTallForb
4. Intersect: Tall Forb + Intermittent Wetlands = Tall ForbWillow
5. Conifer/Tall Forb > Must Select out the known areas of Aspen for Aspen/Tall
Forb
6. Raster Calculator: ("elevation" >= 3109) & ("aspect" >= 202) & ("slope_degree"
>= 25) & ("slope_degree" <= 40)= ShrubTall ForbPotential
a. Convert raster to polygon
b. Select gride code = 1 and make selection into layer
c. Erase all layers that apply to narrow area occurrence
7. Conifer/Shrub
i. Attributes: Are the presence of all trees
ii. Queries
1. Trees Erase (ConiferWillow, ConiferWillowTallForb, ConiferTallForb)
8. New Data to add to ASA Geodatabase
• Tree_Vegetation2: Vector, polygon – converted polyline of Tree_Vegetation
• AltaPavedAreas: Vector, polygon – completed (closed lines) and converted polyline of paved areas
in Alta to a polygon file
M. Olivos – page 6 of 6

7. • Forest Management Zones: Vector, polygon – georeferenced 1995 hand-drawn map
• Plant Comm_1997: Vector, polygon – georeferenced 1995 hand-drawn plant community type areas
• Plant_Comm_2011: Vector, polygon – 2011 minor update of 1995 data
• Plant Community Types: Vector polygon – spatial analysis process
o Conifer Willow
o Alpine Forb
o Short Forb
o Tall Forb
o Willow-Tall Forb
o Conifer-Tall Forb
o Conifer Willow
o Conifer-Willow-Tall Forb
o Conifer – Shrub
o Shrub – Tall Frob
o Scree, Cliffs, Glacial Bedrock and Krumholz
M. Olivos – page 7 of 7