GIS 5007 Module 5 - Choropleth and Proportional/Graduated Symbol Mapping

This week's module focused on choropleth and proportional/graduated symbol mapping; choropleth mapping is a mapping technique that uses a graduated shading scheme across predefined enumeration units [typically political boundaries, such as counties, states, or countries in this case]. Proportional/Graduated symbol mapping is a mapping technique that places dots at geographic locations where occurrences take place, and uses progressively bigger symbols to portray differences between classes; also, these dots can be placed at either true or conceptual points during the mapping process. For this exercise, we used the choropleth method to map the population density of many major European countries and we used the proportional/graduated symbol method to map how much wine is consumed in each of these same countries. 

Overall, this assignment was a great introduction to these two mapping schemes, and many challenges were met throughout the entirety of this assignment. ArcGIS has been the software platform used for each module's assignment, and has never presented any issues while running over a virtual desktop environment - until Module 5. For extra credit, we were allowed to use pictorial symbols for our "dots" on this map, and I found a fun little clip art file at Freepik. Once this little .SVG file was introduced to the ArcGIS project file, every action taken to create this map was slowed by an incredible amount.

The process in classifying the data was relatively simple; I chose the natural breaks method, but needed to include a fifth class so detail was not lost having only four classes. However, to create the inset maps, data had to be excluded from the main map. This regenerated new class values, so I ended up selecting the manual intervals option where I could input the original class values. 

Finally, converting all labels to annotations and converting the wine consumption feature class to a point [it was originally a polygonal feature class] also proved to be quite burdensome while working over a virtual desktop. Slowly, I was able to get each label and grape cluster positioned in a manner that was easy to read and understand.

I am very happy with the quality of this map, and I feel that this exercise proved to quite helpful in grasping an understanding of these mapping methods.

GIS 5007 Module 4 - Data Classification

This week's assignment was based on Data Classification Systems, and how each system can be used to convey information differently. We were tasked with creating two maps of the 2010 Census Tracts [United States Census Bureau] of Miami-Dade County, Florida and graphically portraying 1.) the percentage of Senior Citizens residing in each tract, and 2.) the number of Senior Citizens per square mile in each tract. For each of these maps, we were to display the data utilizing four different data classification methods and displaying the results using graduating color schemes. After final data analysis, we had to decide which map portrayed the information in the most accurate manner. As shown above, I decided that the number of Senior Citizens per square mile was the most accurate depiction, and I will discuss the reasons why toward the end of this post.

The four classification systems that we focused on were Equal Interval, Natural Breaks, Quantile, and Standard Deviation. Below is a brief synopsis of each:

Equal Interval: this data classification system takes the range of values for each feature [or observation] and creates classes that have equal value ranges. For example, if the values ranged from 0 to 100, there would be four classes with a range of 25 or five classes with a range of 20.

Natural Breaks: this data classification system takes the range of values for the entire data set, and creates class ranges that are based on any gaps that occur within the data set. For example, if there is a cluster of observations that range in value from 0 to 10 and the next observation has a value of 14, the computer would create a class that maxes out at 10. The next class would end at the next break that occurs [naturally] in data values, and this would continue until the desired number of classes are created. 

Quantile: this data classification system takes the total number of features [or observations], and creates classes that have approximately equal number of observations. For example, Miami-Dade County includes 521 census tracts [as of 2010]; this equates to four classes of 104 tracts and one class with 105 census tracts. The class ranges are dictated by the values of the 104th, 208th, 312th, and 416th data values.

Standard Deviation: this data classification system takes the entire data set, calculates the statistical mean, and creates classes that are higher and classes that are lower than the mean. There are multiple classes on each side of the mean, and graduated colors are used to visually express how far the values deviate from the calculated average.

After analyzing the data, it was apparent that Standard Deviation and Natural Breaks depicted the values more accurately than the Equal Interval and Quantile methods. The biggest issue with Equal Interval was that the data set was highly skewed to the lower end, so many values were clustered into a single class that should have been divided further. The result was a major loss in detail across the map. Similarly, the Quantile map was also misleading because of the data skew. The major issue with this classification method was that many features with very similar values were placed into different classes, and the fifth class had a range that was far greater than the preceding classes. This creates ambiguity within the map and is potentially misleading to the map viewer; this is the reason that Quantile Data Classification is appropriate for data sets that follow a linear fashion, as opposed to a data set that is highly skewed such as this one.

Finally, after careful consideration between the two maps, it was evident that the number of Senior Citizens per square mile provided a more accurate depiction of census tracts with higher densities of people over the age of 65. To illustrate, a census tract with 95 people over the age of 65 with a total population of 120 yields 79% of Senior Citizens. Conversely, a census tract with 2372 people over the age of 65 with a total population of 9593 yields 24.7% of Senior Citizens. Therefore, it is imperative that the data be normalized against a standard unit of measure to avoid any obscurities. This is why the number of Senior Citizens per square mile depicts higher density levels of Senior Citizens more accurately than mapping percentages of Senior Citizens alone. 

Overall, this lab assignment was an excellent opportunity to dive into different data classification methods and closely analyze how each differs from the others; this assignment allowed us to start making connections on which data classification method is appropriate to use for which kind of scenario. For comparison, I have attached the map containing percentages of Senior Citizens residing in each census tract below.

GIS 5007 Module 3 - Cartographic Design

 Module 3 of Cartography was based on cartographic design; essentially, this consisted of applying the information we have learned in Modules 1 and 2, and applying additional cartographic theories to create an effective map that is aesthetically pleasing and visually harmonious. The principles discussed in this module were as follows: creating a visual hierarchy, contrast, a proper figure-ground relationship, and balance. To demonstrate our understanding of these concepts, we were tasked with creating a map of Washington D.C. that illustrates the location of schools throughout Ward 7, specifically. 

To create this map, shapefiles were provided that included many elements of Washington D.C., including interstates, highways, roads, neighborhoods, parks, rivers, Ward 7, and school locations located in Washington D.C. After these were imported into ArcGIS, discretion could be used to decide which elements were necessary, which were not, and what information was needed to effectively convey the required information. 

The first decision that was made was to incorporate all map elements on a landscape page  orientation. I created a layout in portrait and one in landscape to see which map could utilize a larger scale, but there was no significant difference. I chose landscape because I thought it would create an opportunity for a more interesting final product. After this decision had been made, I began playing with color schemes that would begin to establish a visual hierarchy on the page.  For this project, I decided to color the base map with various shades of grey and use a few additional hues to accentuate certain landmarks that exist within the city. For these landmarks, I chose hues of red, blue, and green to identify major highways [roads were left white in color], rivers, and parks that lie within Ward 7 of Washington D.C. While these colors are conventional cartographic standards for these particular types of landmarks, I deliberately chose to incorporate unsaturated values of these colors to avoid confusion within the visual hierarchy I was trying to establish. Next, I chose a dark, burnt red color for the school icons that exist throughout the map. This dark red created a strong presence on the map, telling the reader that school locations were the story being told. Finally, a black san serif font type was used in the title, and the burnt red was used on other map elements to also add to the visual hierarchy on the page.

The color choices incorporated were also chosen to create an appropriate amount of contrast on the map. The greys and other hues used in the base map create a vast amount of contrast with the white space that lies on the outside edges of the layout, while the burnt red color of the icons and legend creates a high contrast with the base map they lie on top of.  Without, this high volume of contrast, the map reader's eyes would not be drawn directly to the school icons and the title block subsequently; this would create visual confusion while looking at the map and the essential information would be lost in translation. This is the reason that contrast plays such an integral role in the cartographic process. 

According to the text we were given, a proper figure-ground relationship is established within areal features by filling the focal area with lighter tones, and using darker tones on the surrounding areas. Conversely, to employ a figure-ground relationship with points that lie on the map, darker colors give the thematic icons a heavier presence, increasing their visual weight on the page. This is also illustrated by the color scheme used throughout the map. The focal point of the map [Ward 7] was filled with a lighter grey [10%], while the remaining Washington D.C. area was filled with a darker shade of grey [20%]. Additionally, the school icons were given the burnt red shade to establish prominence on the map. Not only do these color schemes aid in establishing a visual hierarchy, but they also form a proper figure-ground relationship that accentuates the importance of the schools within Ward 7 to the map viewer. 

Finally, I decided to utilize the angles of the Washington D.C. municipal boundary to create harmony between the map and the outlying map elements. To accomplish this, I arranged to title, subtitle, scale bar, legend, and North arrow in an angular fashion that loosely follows the northeasterly boundary of Washington D.C. For the inset map, I chose to create a polygonal shape that replicated the angle of the southeasterly border. To tie it all in, I chose to align the top edge of the inset map with the major arterial road that dissects Ward 7. With the alignment of all these lines and angles, a visual harmony was created on a page that consists of a very asymmetrical layout. 

This exercise was a great opportunity to expand our knowledge of this complex software platform, and I learned many things while creating this map. The greatest challenge I encountered was finding an efficient way to create the interstate labels. While the shield icons are included in the ArcGIS icon gallery, there was no field in the attribute table for the interstate feature class that included only the interstate number; all fields included the word "interstate". To properly label the shield icons with only the number, I created a new field in the attribute table, executed the 'calculate field' function, and found an Arcade function that extracted the text following a delimiter [a space in this particular case]. This created a field that included ONLY the interstate number, which I used to create labels for these roadways. The other customization that I had to make was to add the word "neighborhood" after the neighborhoods that were being labeled. Without the word 'neighborhood', the labels seemed arbitrary and confusing to anyone who is not from the D.C. area. To remedy this, I added a simple VBscript code to the label properties window that added a line break and the desired text; this added code read as follows: VBcrlf & "Neighborhood".

Overall, I am extremely pleased with the final product of Module 3, and I feel confident that my map exemplifies my understanding of the principles outlined in the text. 

GIS 5007 Module 2 - Typography

 

Module 2 of GIS 5007 [Cartography] revolved around the proper use of typography to create a map that is informative to the user, while retaining its visual appeal after labeling has been placed. The map that was created in this module was of the state of Florida with some specific features [such as cities, swamps, and rivers] being labeled according to standards outlined in the text [Field, Kenneth. (2018). Cartography. Esri Press.] To accomplish this, data sets were provided from the University of West Florida that could be imported into ArcGIS. Once these shapefiles were imported, a copy of each was saved into the project geodatabase and the data was manipulated to single out features that needed to be labeled. The 'Select by Attributes' function proved to be a very valuable tool that would isolate these specific features and the remaining geospatial data could be deleted from the newly created feature class; the labeling tool could then be used to place labels onto the map. Finally, for the rivers layer, the text was converted to an annotation feature class to gain more control over the appearance of the curvilinear labels. Once the labels were properly placed, full discretion was given to the student to create an aesthetically pleasing deliverable. 

Some of the customizations that were made to this particular map are discussed below:

The first modification to the map was to choose an appropriate sans serif font that was visually attractive, and Microsoft Sans Serif was utilized due to personal preference; this font was also used in the labels for cities [sans serif fonts are standard for manmade landmarks], and also reused in all the marginalia to tie in the necessary map elements with the map itself. The second modification made to this map was to choose an earth-toned color scheme that was not too bright or vivid but was also not too dull and boring. To prevent the text and map elements from becoming too distracting to the viewer, no black was used in this map at all. This allowed the earthy color scheme to draw in the user’s attention and also prevent any peripheral elements from muting the information being conveyed by the map. The final customization made to the map was to choose an appropriate background that would accessorize the map itself and mute out any unnecessary white space. For this background, a textured blue was chosen because it is not too bright that it distracts the user’s eyes, but it also loosely resembles the appearance of water, which is fitting since the map is a representation of the state of Florida. Without these customizations, this map would be informative, but would not draw in the map viewer’s attention as it does now.

GIS 5007 Module 1 - Map Critique

The first module of GIS 5007 - Cartography was to examine various maps, pick an example of a well-designed map and an example of a poorly-designed map, and give each one a critique on what makes that map successful or unsuccessful. While I traversed the internet looking at maps of various styles and purposes, I was particularly drawn to two maps that were provided on the school's server. 

The first map that drew my attention was the map shown below, which is the "Pictorial Wildlife and Game Map of the United States" [Moss, 1956]. 

[Source: Moss, Ira. Pictorial Wildlife and Game Map of the United States. Scale unknown. New York: Shorewood Press, Inc., 1956]

This map immediately sparked my curiosity because of its busy nature [and also because its subject matter is wildlife]. The greatest success of this map, in my opinion, is the manner in which Moss compiles so much information over a vast amount of the surface area but executes it in a way that is unobtrusive to the user's eyes. Edward Tufte and the British Cartography Design Group both have cartographic design principles that emphasize the importance of "Less is More" [or Tufte's Erase Non-Data Ink principle]; both state unnecessary information should be omitted from the map. If you look closely, any omission from this map would result in a costly sacrifice of its informational purpose and overall quality. Another successful design aspect was the colors used throughout. Earthy tones are used to reflect the animal's actual colors on the thumbnail images and across the Unites States landmass, but a bright blue was used for the oceanic bodies and a bright yellow was used for the color of the title block. This decision accomplished two things: the bright yellow immediately draws the user's eyes to the title block of the map and the bright blue creates a high contrast with the landmass of the United States, which allows the user to immediately grasp, visually, the shape of the United States that is otherwise covered by the multitude of images representing species found throughout the country. Lastly, the animals shown throughout the map are referenced to a legend that creates a quasi-border around the edge of the map. This legend gives additional information, specifically a miniature vicinity map of the United States which precisely displays where the referenced species can be found. This was a very successful elemental design decision because it provides the user with additional relative information, while framing in the asymmetrical map with a graphical legend that is very aesthetically pleasing to the eye. This map is very successful, and it is evident that Moss was very deliberate and intentional throughout the creation of this work of art.

The second map that I chose to critique was the map of unknown origin shown below.

[Source: Unknown. Provided by the University of West Florida]

At first glance, it is impossible to decipher the intention of this map. Bold colors are used throughout for roadways, icons, rivers, and the dashed pathways that intersect the map. After studying it, one can infer that this map's intended audience is most likely for bikers / hikers that may venture throughout this eastern European landscape. This assumption was created by the use of icons showing a bicycle over one of the dashed pathways as well as other icons that portray the locations of restaurants, hotels / hostels, and possibly information centers [icons with the "i"]. The problems with this map are quite substantial, beginning with the substantive & affective objectives. If the map is aimed for bikers / hikers wishing to adventure through the dashed pathways that cover the map, then the colors of the major roadways should be muted to avoid creating this visual confusion. On the other hand, if this map's objective is to guide tourists through the roadway systems of this countryside, then the dashed pathways serve no purpose and should be omitted from the map. Secondly, if the dashed pathways are the focal point of the map, the map's scale is off because we only see a vignette of these pathways with not distinctive beginning or ending. Thirdly, map elements seem to be haphazardly thrown onto the map, where one can only assume the gigantic arrow is a north arrow, and the scale bar is, in fact, a scale bar [units also need to be given for this bar to be effective]. Some white space should be created where the scale bar, the north arrow, and an appropriate title could be placed. Lastly, there is no contextual information that provides the user where on the globe this map is referencing. I had to utilize Google to determine that these towns are located in the eastern European country, Latvia. A location map, or vicinity map, showing where, on Earth, this map is referencing would be highly beneficial to the user. All of these inept design choices contribute to this poorly created map that only creates confusion without providing any useful information to the user. 

While these two maps represent both ends of the cartographic spectrum, this exercise proved to be an excellent opportunity to dive into cartography, inspect a wide variety of maps, and begin to make individualized decisions on what works and what doesn't when creating a map. Since cartography is as much of an art as it is a science, every person who creates a map will have their individualized tendencies which form their belief system on what constitutes a successful map. This exercise allotted us the time to create a foundation on what cartographic styles we wish to embody throughout the remainder of this semester, and quite possibly, the remainder of our careers.

GIS 5007 - Orientation Story Map

 Hello, everyone! My name is Marc Wright and I am currently in my second semester of the M.S. in GIS Administration program. Outside of school, I love to travel, spend time with my family, work out at the gym, read, draw, and work on the lawn / landscaping. My wife and I are also very active in our local church [Oklahoma City Community Church] and have recently committed to service opportunities that revolve around feeding the homeless within our community. Professionally, I work full time as a Network Designer / GIS Technician / Mapping Technician for a fiber optics company based out of Norman, Oklahoma. I am thankful that I get to utilize some of the knowledge that I am obtaining from the coursework here at UWF, but I am also very excited to make the jump into some sort of GIS Analyst position. Academically, I received my B.S. in Environmental Design through the College of Architecture at the University of Oklahoma, but ultimately decided against obtaining my Master's degree in Architecture. My goal upon completion of this program is to go where the best opportunity arises [I would love to find myself in the environmental sector, something like species or land conservation], and just go with the flow from there! There are not too many GIS jobs located in Oklahoma City currently, so moving out of state after graduation is probably a very realistic option.

Some adjectives that would describe me are tenacious, determined, optimistic, and comical [I think I am hilarious, but my three teenage step-daughters do not seem to agree]. Good luck to you all this semester, and I look forward to working with you!

Here is the link to my story map: Wright Family Travel Log but I have also embedded it into this blog post below [the formatting is a little off, due to the constraints of the blog frame].

GIS 5027 Final Project - Mapping Eastern Redcedar Encroachment in Western Oklahoma...

My research project for Remote Sensing and Photo Interpretation was modeled after a case study named "Mapping the Dynamics of Eastern Redcedar Encroachment into Grasslands During 1984-2010 Through PALSAR and Time Series Landsat Images" which argues that the invasion of the Eastern Redcedar throughout Oklahoma can be map / analyzed using remote sensing technology. While the scope of this case study was well beyond the scope of this introductory course, I modeled my paper after this research project and attempted to create encroachment maps using introductory fundamentals of remote sensing that were presented throughout this course. The entire paper can be read below [the picture layout cannot be viewed correctly from a mobile device].