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*click here for Cultural Overlay Final Analysis

Physical Overlay Final Analysis:

Figure 1: Index model of the Northwoods. This map was created by adding together several variables with map algebra.  The variables used were spodosol soils, frigid soils and forests, frost free days, average January temperatures, average July temperatures, and age of the bedrock.  The criteria were ranked based on their suitability for a Northwoods region, giving high values to areas that fit best with the Northwoods.  For instance, low temperatures in January resulted in a high rank.  The result is a map ranking from 1 (not Northwoods) to 22 (very Northwoods).

For the index model the following values were added together:

Spodosols
Not Spodosol = 0
Spodosol = 5
Frigid forest
Not Frigid Forest = 0
Frigid Forest = 5
Frost Free Days/Jan Temp
High FFD/High Temp = 1
Moderate FFD/Warm Temp = 2
Some FFD/ Moderate Temp = 3
Few FFD/Low Temp = 4
Very Few FFD/Very Low Temp = 5
Avg July Temp
80+ =  1
77-80 = 2
75.5-77 = 3
74-75.5 = 4
72-74 = 5
Bedrock Age
Middle Proterozoic = 5
Late Archean = 4
Archean = 3
Late Cambrian = 2
Early Proterozoic = 2
Late Ordovician = 2
Early Silurian = 1
Late Silurian = 1
Middle Devonian= 2
Late Devonian = 2

Figure 2: Northwoods Index Model with Region Delineation.  This map was created to give a boundary to the Northwoods region based on physical geography.  The highest ranking values in the index model were queried out to give a rough boundary of the region.  Some areas were left out since they branched too far off of the core region, whereas other areas were added due to them being surrounded by the Northwoods.

Figure 3: Northwoods Index Model with Core Region Delineation.  For this map, more rigorous criteria were used to query out a ‘core’ region.  The region with the highest consistent values was used to build a boundary. However, the “Arrowhead” of Minnesota was left out due to it not being contiguous with the rest of the core region.


Figure 4: Northwoods Region: Physical and Cultural. This map combines the index model of the physical region of the Northwoods, and the index model built using cultural data (with transparency).  Interestingly, the cultural region tends to shift westward from the physical region.  However, the cultural and physical regions tend complement each other quite well.

Figure 5: The Northwoods Region and Agriculture.  This map overlays the physical index model and agriculture data (crops per acre).  This gives quite an interesting result in that the higher values for agriculture are found further away from the Northwoods, especially in Minnesota.

Figure 6: The Northwoods Region and Geology.  Shown here is the physical index model overlaid with geologic fault lines and ferrous mines as points (ferrous mines produce iron and copper). Interestingly, most of the fault lines are within the Northwoods, and all of the ferrous mines are within the region.


Figure 7: The Northwoods Region and Small Game Licenses.  Shown here are the percent small game licenses (of total hunting licenses) overlaid with the physical index model.  Higher values for small game licenses are primarily found in the central Northwoods.

Figure 8: Small Game Licenses and Northwoods Counties.  Highlighted (blue) values in this graph represent counties which fall within the Northwoods region.  As you can see, many of the counties in the Northwoods are at the higher end of the spectrum, suggesting a correlation between small game licenses and being a part of the Northwoods.

Figure 9:  Fishing Licenses and Northwoods Counties.  The highlighted (blue) values in this graph represent counties that fall within the Northwoods region.  Counties in the Northwoods generally have higher values, suggesting a correlation between fishing licenses sold and the Northwoods.


Figure 10: Lutherans and Northwoods Counties.  The highlighted (blue) values in this graph represent counties that fall within the Northwoods region.  As it is shown here, Northwoods counties tend to have a higher number of Lutheran adherents, suggesting a correlation.

Figure 11: Northwoods Categorical Model.  This map represents a categorical model, using the same data used for the index model (figure 1).   The difference with this model is that each variable was given a different degree of value (tens, hundreds, thousands, etc).  This allows one to choose specific variables and locate the specific pixel that represents those variables.   For instance, 55422 represents the region that meets all of the physical criteria for the Northwoods.


Categorical Model Values:

Spodosols
Not Spodosol = 1
Spodosol = 2
Frigid forest
Not Frigid Forest = 10
Frigid Forest = 20
Frost Free Days/Jan Temp
High FFD/High Temp = 100
Moderate FFD/Warm Temp = 200
Some FFD/ Moderate Temp = 300
Few FFD/Low Temp = 400
Very Few FFD/Very Low Temp = 500
Avg July Temp
80+ =  1000
77-80 = 2000
75.5-77 = 3000
74-75.5 = 4000
72-74 = 5000
Bedrock Age
Middle Proterozoic = 50000
Late Archean = 40000
Archean = 30000
Late Cambrian = 20000
Early Proterozoic = 20000
Late Ordovician = 20000
Early Silurian = 10000
Late Silurian = 10000
Middle Devonian= 20000
Late Devonian = 20000

Cultural Overlay Final Analysis:

Introduction:

The overlay analysis aspect of the Northwoods is one of the more crucial processes in developing a definition of the Northwoods. Without combining all information gathered, this class would leave the question of where the Northwoods is located just before answering the final question of where the actual boundaries really are.  The article “Issues related to the detection of boundaries” by M. J. Fortin, discusses many of the aspects of a region that need to be considered when creating a definition of a region as it reviews the different methods associated with boundary detection (Fortin, 2000). Though this project does not include the remote sensing aspects of regions, as is listed in Fortin’s article, it does include data analysis through ArcGIS™ and statistical analysis (Fortin, 2000). The information gathered has been classified into cultural and physical groups as well as vector and raster groups.

Methods:

The flow chart (Figure 1) shows the methods used to complete the overlay analysis of the Northwoods. The process began with gathering the final maps created by the class and classifying them as cultural and physical criteria. The data chosen for the cultural map were campsites and state parks within Wisconsin, Minnesota, and Michigan, percent population over 65 years of age, hunting licenses per capita, small game licenses per capita, fishing licenses per capita, household income less than $10,000, and household income greater than $100,000. After classifying the maps as cultural, all of the data sets were classified using Jenks classification with 5 classes. The tables for these variables were then added to a final map and table. Within this final map the tables were joined and a field was added for each of the variables. Each data set was then recalculated into values 1 through 5 within its respective added field. After doing this for all criteria, another field was added for the final data.  Using field calculator all recalculated values were added together and placed in the final data field. This data was then mapped in ArcGIS™. To create the red outline of the Northwoods values 26 and above were selected, a new layer was created, and the color scheme was set to no fill with a red outline.

(Flowchart)

Figure 1: The flow chart shows the step by step process used for the overlay analysis. The rectangles show data sets and the small ovals are tools and processes.

Results:

As can be seen in Figure 2, the overlay of the criteria shows the Northwoods as being concentrated in northern Minnesota, Wisconsin, and northern Michigan. The data chosen as cultural indicators of the Northwoods were campsites and state parks within Wisconsin, Minnesota, and Michigan, percent population over 65 years of age, hunting licenses per capita, small game licenses per capita, fishing licenses per capita, household income less than $10,000, and household income greater than $100,000. When combined together these values create a distinct region in the northern areas of Minnesota, Michigan, and Wisconsin, commonly referred to as the Northwoods by many inhabitants in the Midwest.  Lower Michigan shows up as having some Northwoods criteria within it because many of the Northwoods counties are heavily forested, which can lead to an increase other variables as well.

Figure 2: Geographic Overlay of Cultural Features in the Northwoods using campsites within Wisconsin, Minnesota, and Michigan, state parks within Wisconsin, Minnesota, and Michigan, percent population over 65 years of age, hunting licenses per capita, small game licenses per capita, fishing licenses per capita, household income less than $10,000, and household income greater than $100,000.

The charts below show the relationship between the cultural variables, such as hunting and fishing license sales, in relation to the counties they are found within. For example, Figure 3 shows the number of fishing licenses per capita for all three states by county.  For all figures the highlighted columns show the counties located within the Northwoods. For many of the graphs, most of the counties within the Northwoods are found toward the higher end of the scale, thus suggesting a high correlation between the graphed variable and the Northwoods culture region.

Figure 3: Fishing licenses per capita. The blue highlighted values represent the counties which fall within the Northwoods culture region. It can be noted that most of the counties within the Northwoods are found toward the higher end of the scale, thus suggesting a high correlation between fishing licenses per capita and the Northwoods culture region.

Figure 4: Hunting licenses per capita. The blue highlighted values represent the counties which fall within the Northwoods culture region. This graph shows that many counties within the Northwoods have a high correlation with hunting licenses per capita.

Figure 5: Small game licenses per capita. The blue highlighted values represent the counties which fall within the Northwoods culture region. This suggests a high correlation between small game licenses and Northwoods cultural counties.

Figure 6: Pasty shops per capita. The blue highlighted values represent the counties which fall within the Northwoods culture region. Counties within the Northwoods have higher values, suggesting a high correlation between pasty shops and the Northwoods.

Figure 7: Percent Native American per county. The blue highlighted values represent the counties which fall within the Northwoods culture region. Counties in the Northwoods have higher values, suggesting a correlation between the percent Native Americans and the Northwoods.

Figure 8: Percent population over 65 years of age. The blue highlighted values represent the counties within the Northwoods culture region. This graph shows many of the Northwoods counties as having a high percentage of persons over 65 years of age. This suggests a correlation between persons over 65 and Northwoods counties.

Figure 9: Percent households with income less than $10,000. The blue highlighted values represent the counties within the Northwoods culture region. This graph shows many of the Northwoods counties as having a high percentage of households with incomes less than $10,000. This suggests there is a correlation between households with low income and the Northwoods counties.

Figure 10: Percent Households with Income Greater than $100,000. The blue highlighted values represent the counties within the Northwoods culture region. This graph suggests that few Northwoods counties have households with incomes greater than $100,000.

Figure 11: Final Overlay of Cultural Features and Northwoods Counties. The blue highlighted values represent the counties within the Northwoods culture region. As can be seen, with few exceptions, the areas with the most Northwoods criteria are selected as being located in the Northwoods.

Summary: 

The overlay analysis of cultural features combines the work of many classmates’ projects into one overall map of the Northwoods region. Without this final map much of what has been accomplished through this class is left just before its completion. As this research has shown, the Northwoods is a distinct cultural area in the Midwest. Combining these cultural variables with physical data such as nickel and copper mine locations, forest cover, agriculture, and soils (among many others!) it is clear the Northwoods region will be delineated as a distinct region. 

References:

Fortin. 2000. Issues Related to the Detection of Boundaries. Landscape Ecology 15, no. 5: 453-66.

Meinig, D. W. 1965. "The Mormon Culture Region: Strategies and Patterns in the Geography of the American West, 1847-1964." Annals of the Association of American Geographers 55, no. 2: 191-220.

Michigan Department of Natural Resources. 2008 Hunting and Fishing License data. (Lansing, MI) http://www.michigan.gov/dnr

Minnesota Department of Natural Resources. 2008 Hunting and Fishing License data. (St. Paul, MN) http://www.dnr.state.mn.us/index.html

US Census Bureau. www.uscensus.gov

Wisconsin Department of Natural Resources. 2008 Hunting and Fishing license data. (Madison, WI) http://www.dnr.state.wi.us/


 


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Ezra Zeitler, PhD & Joseph Hupy, PhD - Instructors