GIS I Lab 4: Final Project

Introduction:

The goal of this final project is to find suitable locations for new campgrounds in Bayfield County, Wisconsin. This was inspired by the unique and beautiful forested and lakeshore environments that lend themselves to recreational camping and tourism, and are underutilized in the opinion of this author. This project will use multiple tools, including buffer, intersect, erase, select and union tool, displaying proficiency with ArcMap. 

The intended audience for this project is either an individual, company, or government organization looking to establish a new campground in Bayfield County. This information would prove useful in deciding a location for said campground. 

Research Question: What locations in Bayfield County, WI are most suitable for use as a campground?

Data Sources:

The data required for this project includes maps of the county including bodies of water, major roads, and forested land from the Wisconsin Department of Natural Resources (WDNR) and U.S. Census data that was acquired from the UW - Eau Claire Geography Department server (located at geogsql.uwec.edu via a virtual private network, instructions located here), coordinates for established campgrounds from the Chequamegon-Nicolet National Forest website, and also the Bayfield County website.

One concern regarding the data is that not all coordinates for privately owned campgrounds were readily available online, and thus are not represented in this project. This is an acknowledged oversight, but deemed acceptable considering the scope of the project (the assigned "simple question" to be answered). Secondly, the use of state data on bodies of water was so thorough that it includes many bodies of water that are not realistically practical as sites for campgrounds, however this can be compensated for. 

Methods:

In order to answer to answer this research question, multiple geospatial analytic techniques were used. 

Queries were used to narrow down the scope of the data being analyzed, and the state-wide datasets were clipped down to include only the target county. Buffers were used to account for desired proximity to resources like major roads and lakes, while buffers combined with the erase tool ensured there was an appropriate distance from other, already established campsites. 

First, the county boundaries were queried to just Bayfield county, and that was used to clip the National Forest and Major Roads layers to the county in question. The Bayfield County Forests were connected to the National Forest layer using a union to account for all of the forested land in the county. The Water Bodies layer was narrowed to Perennial Lakes and Ponds using a the select tool, and then a query was used to select just the lakes. Then buffers were applied to the Bayfield County Major Roads, Lakes, and Established Campgrounds at distances of 5 miles, 2 miles, and 2 miles, respectively. The intersect tool was used to identify land that is within the buffers of major roads and bodies of water and lies on forested land. Then the erase tool was used to remove any land within the buffer of previously established campgrounds, giving the result of land for potential new campgrounds. 

The data flow chart above shows the procedure undertaken to determine the locations most appropriate for campgrounds that are not yet in use as campgrounds. 

Figure 2. Map showing all of the buffers, major roads, National and County Forests, and lakes within the County.

Results:

Below is Figure 3, which shows the final product of this project: an aesthetically pleasing and useful map that shows the locations for new campgrounds. It is likely that there are two especially good locations for campgrounds: the northernmost plot of land is close in proximity to the lakeshore as well as bring within the forested land, and the southwestern sections of land are far enough from competing camps that it could be a very successful location. 

Figure 3. The final product showing the possible locations for campgrounds. 

Evaluation:

I believe that this project, while challenging in its own right, is possibly the most useful because each student can find their own value. I think that it was intimidating to begin, because there was less direction than other labs, but once started, I found it more easy to actually complete.

If I were to repeat the project, I would have incorporated the lakeshore as a body of water to keep proximity to. Even though the forests do not come close to the lakeshore, it is a beautiful location on its own. I would go about this by including Lake Superior as a separate layer and having two resulting land types: potential forest camping sites, and shoreline camping sites.

The greatest challenge that I faced was getting the geographical coordinates for the campsites that already exist. I had to enter the x, y coordinates and then create a new feature class and edit it to add the points because there was not a table that I could easily import into ArcMap.

GIS I Lab 3: Vector Analysis with GIS

Background and Goal:

The goal of this lab was to effectively use multiple geoprocessing tools and vector analysis to find a suitable habitat for bears in Marquette County, Michigan using data retrieved from the Michigan Gis Open Data. This will involve evaluating factors such as land type, proximity to water, and proximity to urban areas. In addition to this, practice with Python coding will be a secondary goal.

Methods

Objective 1: Map a GPS Excel file of black bear locations in Marquette County, Michigan

the bear_locations_geog$ data table was added to ArcMap as an event theme. This displayed X, Y data in ArcMap. It was saved within an individual Lab 3 folder.

Objective 2: Determine the forest types where black bears are found in the study based on GPS locations of black bears

All features in the bear_management_area feature dataset were added to the map. The landcover layer's symbol was changed to display unique colors based on the minor_type field. An intersect was performed between the bear_locations and landcover layers using a simple inside spatial join to create the new bear_cover layer. A summary of the "minor_type" field within the attribute table showed that the Mixed Forest Land, Forest Wetlands, and Evergreen Forest Land values were the most common locations for bear sightings.

Objective 3: Determine if black bears are found near streams

To determine if proximity to water is a requirement for bear habitats, the buffer tool was used on the streams layer. The buffer of 500 meters created a new layer. Using the select by location tool with target of bear_locations and the source layer as streams it was revealed that significantly more than 30% of the bear sightings were within 500 meters of streams. This means that proximity to water is an important component of bear habitats. 

Objective 4: Find suitable bear habitat based on two criteria

To find the most suitable bear habitats the select by attribute function was used on the landcover layer. After selecting the Mixed Forest Land, Forest Wetlands, and Evergreen Forest Land portions of the landcover layer, this selection was made into a new layer. This new layer was intersected with the stream buffer layer to find the proper land types within the 500 meter proximity of the streams. The dissolve tool was used to produce a more aesthetically pleasing layer that is not broken into many polygons. 

Objective 5: Find all areas of suitable bear habitat within areas managed by the Michigan DNR

The dnr_mgmt feature class was added to the map and the dissolve tool was used to aggregate the many polygons. This new layer was intersected with the suitable bear habitat layer, producing a layer that shows land that meats the natural requirements for bears and is managed by the Michigan DNR. 

Objective 6: Eliminate areas near urban or built up lands
A new layer was created from a selection of the landcover layer that found only urban or build-up land. A buffer of 5 kilometers was applied to this, creating a layer that shows the areas that are not sufficiently far from urban development. The erase tool was used to remove any portion of the DNR managed bear habitat withing this proximity of the urban development. A base was put behind the map and a location map showed where the study was done.

Objective 7: Generate a digital data flow model of the workflow and cartographic output

The results from objective 6 were edited to look more cartographically pleasing, and a model of the workflow was created. Both can be seen below, in the Results section.

Objective 8: Practice using Python

Results:

Sources:

ESRI ArcMap, ESRI ArcCatalog
Information, Marquette County (2002, November 01). Michigan 1992 NLCD Shapefile by County . Retrieved December 09, 2017 from http://www.mcgi.state.mi.us/mgdl/nlcd/metadata/nlcdshp.html

Natural Resources, Michigan Department (2001, August). Michigan Department of Natural Resources Wildlife Management Unit Offices. Retrieved December 09, 2017, from http://www.dnr.state.mi.us/spatialdatalibrary/metadata/wildlife_mgmt_units.htm

Center for Shared Solutions and Technology Partnerships. (2014, June 01). Michigan Geographic Framework: Marquette County. Retrieved Decemver 08, 2017, from http://www.mcgi.state.mi.us/mgdl/framework/metadata/Marquette.html
Data downloaded from the State of Michigan Open GIS Data:

http://gis-michigan.opendata.arcgis.com/

• Landcover is from USGS NLCD: http://www.mcgi.state.mi.us/mgdl/nlcd/metadata/nlcdshp.html


• DNR management units: http://www.dnr.state.mi.us/spatialdatalibrary/metadata/wildlife_mgmt_units.htm


• Streams: http://www.mcgi.state.mi.us/mgdl/framework/metadata/Marquette.html

Banff Mountain Film Festival World Tour

On December 5th I had the opportunity to patronize the Banff Mountain Film Festival World tour. This program, created by the Banff Centre in Banff, Alberta, Canada, is a selection of short films submitted to the festival each fall.

The first film, The Space Within was a rather short introduction to get the audience in the mood. It began with a person walking along a beach. This person found some glass orbs with pictures inside. This acted as the transition between the beach, Japan, and the snowy landscape where the skiing action was filmed. While short, I thought this film was a good introduction to the types of film that one could expect.

The second film, Sky Migrations, followed some biologists who track the paths of migratory raptors through the center of the United States. This film was fascinating and important for a couple of reasons. First of all, I have never seen a Cooper's Hawk or Golden Eagle up close before, which was humbling. Secondly, the film showed how one migratory species can be indicative of the health and wellbeing of a whole swath of habitat that extends through North America. Conversely, this shows how dependent these species are on that whole extent of land, so maintaining an preserving the health and integrity of those areas are vital to ensure the survival of these magnificent birds.

The third film (Into Twin Galaxies - A Greenland Epic)was the longest of the night and tracked the incredible expedition of three people who kite skied across 1,000 kilometers across the Greenland Ice Cap to reach the northernmost river ever kayaked. The logistics of this trip stunned me, as there were so many things could (and did) go wrong. One person's back was broken after being tossed into the air by a kite while skiing. The whole trip was 45 days and the trip seemed immensely taxing both physically and mentally.

The fourth film was titled Johanna, and--I believe--encapsulates a whole segment of the activities represented in the Banff Festival. Johanna's method of relaxation is to go swimming under the ice of a frozen lake. This is a wonderful example of the kinds of amazing extreme activities that are common in this film festival.

Tsirku was the next film, in which some skiers conquered corrugated snow: steep ridges of untouched snow that require both a massive amount of technical skill and bravery to even attempt. As someone who like skiing, this short made me wish for more snow so I could go skiing.

The sixth film was titled La Casita Wip. The two women in the film worked to create their own dirt bike path. This was interesting to see, and I liked to see their dedication, but more importantly, they show young girls that they do not need to be dainty and feminine, but also that those don't define them.

Following this was Loved By All - The Story of Apa Sherpa, which was a poignant look at the less-than-glamorous life of Sherpa porters climbing Mount Everest. Everest provides a source of income for this impoverished region, but the danger is extreme. Apa Sherpa, who has summited Everest twenty-one times, has created an organization to support rural teachers and education systems so that children can have other opportunities than being porters, opportunities that are safer and well-paying.

The final film of the night was Imagination, a 5 minute short that supposes that children imagine being able to ski or snowboard across the landscape as they ride in cars. The film's whimsical transition showing professionals doing stunts off of buildings and vehicles. I thought this was a wonderful conclusion to the evening.

This event really drove home the point that geography is not an isolated thing; the environment is very closely interconnected with the humans and animals that live in and interact with it. I liked the event, and think that it was a good exposition of the films shown at Banff. I would recommend this event to everyone; it is a unique look at the interaction between humans and the environment.

GIS I Lab 2

GIS I Lab 2: Downloading GIS Data

Background and Goal:

The goal of this lab is to learn how to retrieve, perform analysis upon, and map U.S. Census Bureau Data, as well as to create an Arc GIS WebMap. The tangible products are two maps showing Wisconsin population and a variable of our choosing, respectively.

Methods

Objective 1: Download 2010 Census Bureau Data

The Fact Finder website, run by the U.S. Census Bureau was used to find the total population of the counties in Wisconsin. Utilizing the Advanced Search with conditions of "population totals" and "All Counties within Wisconsin" the data was found and downloaded as a zipped file. After extracting the data, the second row of data was deleted because it was not a record. Periods were removed from titles to adhere to naming conventions in ArcMap.

Objective 2: Download a Shapefile of the 2010 Census Boundaries

Under the "Map" tab on the Fact Finder website, and the corresponding  shapefile was downloaded as a .zip file and extracted accordingly.

Objective 3: Join the Downloaded Data to the Shapefile

The shapefile was added to the data frame, which was renamed "Population." The shapefile was joined with the standalone Excel table using the common GEO_id field.

Objective 4: Map the Data

The 0500 shapefile was changed to a graduated color symbology with four classes in a quantile classification to appropriately distribute the tiers of population.

Objective 5: Download and Map a Variable of My Choice

Using the Fact Finder website, the housing data from the 2010 census was downloaded.

Objective 6: Build a Layout with Both Maps
Both maps were adjusted to the NAD_1983_Wisconsin_TM projection to make them more accurate for this project. Both maps were given a basemap, author name, date, title, the source of the map date, a legend, and scale bar.

Objective 7: Build a WebMap with One of the Variables

A new map file was saved for the purposed of uploading to ArcGIS online, after logging on through a UWEC account. The second data frame was deleted and the standalone table was removed to avoid errors in the process. A service was created and published for this map, with pop-ups  that would show the name and population of the Counties. This was shared with the UWEC Anthropology and Geography group after the Title, summary, and tags were updated.

Results:

These maps show the population (first map) and number of housing units (second map) in the counties of Wisconsin. the population is most heavily concentrated around the Southeast corner of the state. Some counties have more housing units than would be expected based on population. I would suggest this could be explained by either a large tourist industry, as is the case in Door county, or by higher rates of homelessness.
The third map is a screen capture of the uploaded map on ArcGIS online.

Sources:

Data:
United States Census Bureau American Fact Finder. (2015). [online] Retrieved from  https://factfinder.census.gov/faces/nav/jsf/pages/searchresults.xhtml?refresh=t [Accessed: April 8, 2017].

Basemap

ESRI, HERE, DeLorme, MapmyIndia, OpenStreetMap contributors, and the GIS user community.

GIS I Lab 1: Base Data

Background and Goal:

As an intern at Clear Vision Eau Claire, an Eau Claire county initiative working to create a vision for Eau Claire, I have been asked to prepare a basic report containing relevant information and base maps for the Confluence Project. The Confluence Project is a cooperation of UW-Eau Claire and the greater Eau Claire area to create a mixed-use building that contained student housing, a community arts center, and commercial property
The purpose of this lab was to create relevant base maps of the area of the Eau Claire Confluence Project while becoming familiar with various spatial data sets used in public land management, land use, and administration positions.
Methods:  

Objective 1 - Explore various data sets for the City and County of Eau Claire and answer some basic questions about the base data.

To do this step, I connected ArcCatalog to the relevant data and looked at the contents of the 2009_07_13_EauClaire.gdb geodatabase I explored the contents of the database including the feature classes and feature datasets. I familiarized myself with the rules attached to the topology file PARCEL_FEATURES_topology. I looked at the CENSUS_FEATURES feature dataset and looked at the block groupings and tracts. Finally, I looked at the zoning feature class in the DEVELOPMENT feature dataset to familiarize myself with the area.

Objective 2 - Digitize the Site for the Proposed Confluence Project

I began by greating a new file database named EC_confluence in ArcCatalog. I imported the coordinate system from the BlockGroups feature class (the Eau Claire County Coordinate System). In this new database I added a world imagery base map, an empty feature class, and the parcel_area feature class from the City of Eau Claire geodatabase. Using the editor toolbar I digitized the proposed site for the Confluence Project.

Objective 3 - View Legal Information for the Confluence Project

I first added a new blank data frame, an imagery layer base map, the Public Land Survey System (PLSS) townships, sections, and quarter-quarter sections from the 2009-17-13 EauClaire and the City of Eau Claire geodatabases. I activated the section numbers and symbolized the sections so that I could see the patters with a streteched color filling. I used the legal descriptions (Hemstead, 2015) to identify the section that the Confluence Project sits in using quarter-quarter sections.

Objective 4 - View Legal information for the Confluence Site

I visited the City of Eau Claire mapping services (City of Eau Claire, WI, 2017) and the pdf given to me to identify the parcels in ArcMap and create a complete legal description of these parcels.

Objective 5 - Build a Map of all Relevant Base Data for the Confluence Project

To complete my final objective, I created six discrete maps showing different sets of relevant data.
The first map was of Eau Claire County civil divisions. This involved importing the data from the 2009-07-13 Eau Claire Database and assigning each division a unique value symbol.
The second map was the Census Boundaries map, which was composed of the Census tracts and Block values adjusted to show the population of people per square mile as of the year 2007. The population was adjusted to be expressed as a color gradient for aesthetic appeal.
The third map was of the parcels of downtown Eau Claire. The parcels, centerlines, and water feature classes were added to show the location of the project in relation to legal boundaries.
The fourth map was the PLSS Features map that showed the PLSS Sections and Quarter-Quarter Sections. This is useful for understanding the location as expressed in PLSS system standards.
The fifth map was of zoning assignments. The codes were grouped into broader categories to make the map and legend more simple and easily understood.
The final map was of the voting wards in Eau Claire. Rather than a legend, I used numbers within boxed backgrounds to make them easier to read and identify the individual wards.

Results

The result of this project is a set of six maps as a tangible product, but also a better understanding of the different civil, legal, voting, demographic, and PLSS information that is pertinent to the Confluence Project.