Final Project - Rock Climbing Destinations in Wisconsin

Objective   
The purpose of the project was to come up with a research question and try to answer it using some of the data processing methods learned throughout the semester.  The research question for this project was: "Where could possible new climbing destinations be found in Wisconsin?".

This was chosen because rock climbing is a growing sport and more and more people are exploring for areas that could be useful for rock climbing around Wisconsin.  Though there are existing established rock climbing areas around the state already, there is still some potential for exploration of new lesser known spots.

Literature Review
Though no projects were found with the goal of finding new climbing destinations, these sources were interesting references that incorporated rock climbing into scholarly/academic work.

Aldighieri, B., et al. “3D Exploration of the San Lucano Valley: Virtual Geo-Routes for Everyone             Who Would Like to Understand the Landscape of the Dolomites.” Geoheritage, vol. 8, no. 1,               2015, pp. 77–90., doi:10.1007/s12371-015-0164-x.

Bollati, Irene, et al. “Geoheritage and Sport Climbing Activities: Using the Montestrutto Cliff                  (Austroalpine Domain, Western Alps) as an Example of Scientific and Educational                              Representativeness.” Italian Journal of Geosciences, vol. 133, no. 2, 2014, pp. 187–199.,                      doi:10.3301/ijg.2013.24.

Buchroithner, Manfred. “Creating the Virtual Eiger North Face.” ISPRS Journal of                                    Photogrammetry and Remote Sensing, vol. 57, no. 1-2, 2002, pp. 114–125.,                                          doi:10.1016/s0924-2716(02)00109-0.

García-Rodríguez, Manuel, and Enrique Fernández-Escalante. “Geo-Climbing and                              Environmental Education: the Value of La Pedriza Granite Massif in the Sierra De                                Guadarrama National Park, Spain.” Geoheritage, vol. 9, no. 2, Dec. 2016, pp. 141–151.,                      doi:10.1007/s12371-016-0187-y. 

Data Sources
-WI State Boundary and Cities were acquired through "Geospatial Data" in the Q drive.
-Major Roads are from the 2010 U.S. Census Bureau
-Depth to Bedrock is from the DNR, GCSM dataset
-10 meter elevation raster (DEM) from NED dataset on the UW - Madison GIS website

Data Analysis
First a map incorporating slope and bedrock depth was created.

-In the bedrock feature class the feature to raster tool was used to convert the shapefile to a raster with the bedrock depth value being displayed, as shown in Figure 1.  This was done so that raster overlay could be performed.  It was reclassified so that a weighted overlay could be performed.

Figure 1: The depth to bedrock feature.  

-The slope tool was then used to show slope on the landscape throughout all of Wisconsin, as shown in Figure 2.  A resample was used to make the processing faster.  This feature was then reclassified also to rank the slopes from highest being the most desirable areas to lowest slope angles being the least desirable.

Figure 2: The DEM after the slope tool was used.  

-These two features were used in a weighted sum to create a map showing areas most likely to contain areas with possible rock climbing crags.

Next a map showing accessibility of the areas with steep slope was created using the cities and major roads features.

-A buffer was created around both the cities and roads was created and combined with a union/dissolve, as shown in Figure 3. 

Figure 3: The buffer around the cities and major roads.  

Areas within these areas are the most accessible.  Feature to raster was used so that raster analysis could be performed.  Then euclidean distance was used to show the distance to areas from the roads and cities.  Reclassify was used to rank them in order, and weighted sum was used with the reclassified slope feature to create a map.

Results

Figure 4: This is the map that shows possible climbing destinations based on slope and depth to bedrock.  It can be observed that the southwestern part of the state, or the "driftless area", contains the most areas with a higher probability of possible new climbing destinations.  

Figure 5: This is the map showing the accessibility of the areas of steep slope based on distance from cities and roads.  Again the driftless area contains the most areas with potential climbing sites, and the most accessible ones are within the buffer of the cities and roads and then in rank from red to green.  

Conclusion/Future Work
The driftless area seems to have the most potential for possible new climbing destinations, with many of the areas being easily accessible to major cities in the state and by major roads.

This method could be replicated and more/other characteristics could be added in searching for climbing destinations.

One possibility for future work could be to use the locations of established climbing destinations and see how they rank in each of the maps created for this project.

Lab 3: Geodatabase Development

Introduction
The purpose of this lab was to give an opportunity to show the organization of the final project geodatabase structure and organization. 

The purpose of this project is to develop maps that could be helpful in locating places around Wisconsin that could be possible locations for rock climbing.  Local rock climbers could use this as a way to use specifically identified physical characteristics that may be useful in locating these potential sites. 

Methods
The area extent is the state of Wisconsin.  The map scale was set so that all of the state is visible.  The projection used was North_American_1983_HARN_Transverse_Mercator.  Topology was not included.  The plan for metadata was for the end product to have descriptions within the item that inform the user of the relevant information to the project. 

From the DNR GCSM the “depth to bedrock” shapefile was used for its depth attribute.  This was mapped because rock closer to the surface means more potential for exposed bedrock, which is what is used in climbing.  The NED Elevation raster was used to show elevation and slope.  Areas with a steeper slope could be potential climbing sites as well.  The major roads feature and WI cities were also used.  Areas close to roads or cities would be more accessible, so people wouldn’t have as much trouble looking through these areas when exploring for new sites.  Figure 1 shows the ranking order of the areas.  

Figure 1: The rank of the data after being reclassified.

This was the order of rank used throughout the project.  Some features/maps had more than 3 numbers of rank, but the lowest numbers had the highest potential for a climbing site.  Some of these features were added to each other using the weighted sum tool. 

Results

Figure 2: This is the folder containing the geodatabase to be used in the final project.  Some of the text on the right describes the organization of the folder/geodatabase and details some of the contents.  

Conclusion
Having a plan for geodatabase organization and structure before actually starting the project will help later down the line.  The project here looks somewhat disorganized, and would need some cleaning up if it were to be used by someone else or if the project were to be recreated. 

Lab 2: Watershed Analysis

Introduction
The purpose of this lab was to gain an introduction into watershed analysis. The data was acquired, process, and watersheds were delineated, and questions regarding the results were answered in the initial report.

The data used is shown below.

Methods
The project is broken into three steps: data collection, data processing, and watershed delineation.
 1) Data Collection
-The data was downloaded from the sources above, unzipped, and brought into ArcMap.

2) Data Processing
-A buffer was set around the park boundary at 20km.
-The hydrology was then projected to match the park boundary.
-A 30 arc-second DEM of North America was then added as a basemap, which was clipped to the size of the park buffer and projected to match the other data.
The result is shown in Figure 1, which includes the DEM, park boundary, and hydrology.

Figure 1: The result after processing the data.

3) Delineating Watersheds
-Flow direction was calculated.
-The sinks were filled with values ranging from approximately 21 - 1469.
-Flow direction was then recalculated.
-Flow accumulation was then determined.
-A source raster was then created using 50,000 as the raster threshold.
-Stream link was used next.
-Watershed tool was then used to delineate watersheds and that was clipped to the size of the park.
Figure 2 shows the result of the watershed delineation.

Figure 2: The watersheds within the park boundary. 

Results

Figure 3: The map showing the watersheds within the Adirondack park boundary.  It can be observed that the water moves from North to South, and the map shows the areas for each watershed.  The number of watersheds depends on several criteria when processing the data and other aspects of the delineation process.  

Conclusion
This method of delineating watershed analysis could be useful for modeling, locating stream sources, identifying streams, etc.  The size and number of watersheds can be determined by choosing the characteristics that pertain the specific project at hand.  Overall this was a good introduction to using the watershed tools and creating a watershed analysis.