GIS 6005 Final Project - Data Analysis on UFO Hotspots

View the presentation for this project by clicking here.

GIS 6005 Module 6 - Proportional Symbols and Bivariate Mapping

 The sixth, and final, module of Communicating GIS explored the proportional symbols and the bivariate mapping methodologies employed  throughout the cartographic world; both parts of this assignment also provided opportunities to customize legends in a manner that gives the cartographer complete control over each element within the legend. The first two parts of this assignment used the proportional symbol method to illustrate the magnitude of a provided variable. According to Kimberling, a proportional symbol is 'used to represent an exact data value by scaling the symbol's visual variable to be directly proportional to the value it represents' [Kimberling, 2012, p. 617]. Essentially, the size of the smallest variable is set and the remaining symbols are scaled proportionally. As shown below, the first map was a map displaying cities throughout the country of India, and the magnitude of their population is conveyed by the diameter of that cities point symbol. Due to inadequacies of the human eyes and mind, people tend to visually underestimate the size of the circles as they get bigger, so an appearance compensation algorithm [Flannery] has been applied to these point symbols; more can be read on proportional symbology and the Flannery compensation technique by clicking here.

After the symbology was set, a formatted map was created, and the legend was added. ArcGIS does not currently have a nested legend option [see map above], so the legend had to be converted to graphics to successfully create this type of legend. Once the legend was converted, all elements within the legend are completely editable as graphical elements, giving the cartographer an endless amount of control over the legend's design.

 

The next portion of the lab was also based on proportional symbology, providing more opportunity to explore the capabilities and potential problems of this methodology. The map below is a map of the employment changes from 2007 through 2015 throughout the United States. The difference of data values within this dataset created problematic overlaps throughout the entire map. Once this issue was resolved, the customized legend was created by converting the legend to graphics and manipulating each element individually.

The third portion of the lab explored the bivariate mapping technique; a bivariate map 'displays two variables on a single map by combining two different sets of symbols or colors' [Kimberling, 2012, pg. 456]. The map below is a bivariate map showing the relationship between two individual variables, obesity and inactivity.

 

By examining the map, it is apparent that most U.S. counties fall within the low-low, medium-medium, and high-high classes, thus illustrating a directly proportional relationship with each other. If no correlation between the two classes existed, many of the counties would fall within the low-high or high-low classes. The main challenge of this exercise was to determine the color ramp by choosing colors that were easy to distinguish, were visually complementary, and were also progressively increasing as the values climbed. This took a lot of time and patience, but the final deliverable made the dedication worthwhile. Lastly, a customized legend was created, showing how the qualitative values of a quantitative dataset are represented on the map.

This exercise was a great opportunity to explore some customization options that will be necessary throughout the execution of the final project.

Informational sources:

Environmental Science Resource Institute (2024). Proportional Symbols. 

https://pro.arcgis.com/en/pro-app/latest/help/mapping/layer-properties/proportional-symbology.htm#:~:text=Appearance%20compensation%20uses%20an%20algorithm,and%20no%20Maximum%20size%20specified.

Kimberling, A.J. (2012). Map Use: Reading, Analysis, Interpretation (7th edition). ESRI Press Academic.

GIS 6005 Module 5 - Analytical Data

Module 5, Analytical Data was an excellent assignment; it was an opportunity to explore alternative visual elements that worked in conjunction with maps to tell a story; the goal was to create an infographic map, compiled in a manner that was clean, organized, and effectively conveyed a health related issue. For this assignment, we downloaded the 2018 county statistics from the County Health Rankings and Roadmaps website; this is a .CSV [comma separated value] file that contains health related statistics for every county in America. After exploring the dataset, we were tasked with choosing two variables and exploring any relationship between the two. The final deliverable was an infographic map, and mine is displayed below.

 As shown in the map above, the two variables I chose were smoking and fair / poor health; I began by creating two maps, one for each variable; while they are not in perfect conjunction, there are many places between the two maps that show a direct correlation. The scatterplot [top chart] emphasizes this relationship, by plotting each county as a point, using the variables as x-, y- coordinates. A brief study of this scatterplot shows us that as the percentage of smokers rises, the percentage of the population in fair to poor health also rises. The two graphs below the scatterplot are simple bar and pie charts, illustrating how the percentages of the two variables are very closely related. While other factors are definitely in play, it is hard to dispute that smoking is very detrimental to an individual's health. As an ex-smoker and ex-vaper, this information is very interesting to me; it will also be interesting to see what kind of information is available after the long-term effects of vaping are discovered. 

After the data analysis was complete, all elements were compiled onto a layout and adjusted to maintain legibility, organization, and a strong visual hierarchy. I began this assignment feeling unsure and a little underconfident, but I am definitely pleased with the outcome of this final deliverable.

GIS 6005 Module 4 - Color Concepts and Choropleth Mapping

The three color ramps displayed below show a linear progression through six different shades of brown. A sequential color ramp allows the cartographer to illustrate quantitative data, specifically on a choropleth map [generally, the darker the shade, the higher the value]. While this type of thematic mapping can be quite informative, caution must be used so the viewer can differentiate between the colors on the map. For this exercise, the RGB [Red Green Blue] value was given for the darkest shade of brown on the linear progression, the lightest shade of brown was manually chosen, and the RGB values were recorded for each. To obtain the intermediate shades, the RGB values of the lightest shade were subtracted from the RGB values of the darkest shade and divided by five. This integer was progressively added to each RGB value to obtain the next shade of brown; this is how the linear progression color ramp was calculated. The adjusted linear progression color scheme was derived from the linear progression color ramp, but the incremental values were manually adjusted so that they were bigger in the darker shades of brown and progressively reduced as the shade got lighter. This manual adjustment makes it easier for the viewer to distinguish between the darker shades of brown. The third color ramp was obtained from a free internet resource, https://colorbrewer2.org, by selecting three simple options: color scheme, RGB value, and sequential color ramp.

In my opinion, the results of the linear and adjusted progression color ramps are substantially more elegant and visually aesthetic than the ColorBrewer color ramp. The ColorBrewer color ramp utilizes very bright, bold, saturated colors while the customized linear progressions are softer and milder; they are not as visually overpowering. Additionally, the colors generated by ColorBrewer are somewhat scattered within the spectral range, employing hues such from maroon-brown to orange to yellow, while the shades of the linear and adjusted linear progression color ramps are confined within the same hue [brown in this case], only differ in saturation, and possibly lightness, values. Lastly, small modifications were easy to make throughout the construction of the adjusted linear progression ramp, so complete control is in the hands of the cartographer; ColorBrewer has approximately 20 sequential color ramp choices, so there is little room for customization. The ease and convenience of ColorBrewer is a benefit on its own accord, but time permitting, I would prefer to have complete control over the colors within the map.

After experimenting with colors and sequential color ramps, the next portion of the lab assignment was applying these fundamentals by creating a choropleth map. A choropleth map is a thematic map where 'each data collection area is given a particular color lightness, color saturation, or pattern texture depending on its magnitude' [Kimberling, 2012, p. 191]. In the map below, the percentage of Hispanic people is mapped for each county in Texas [the data collection areas] and the shade of the county is determined by the magnitude of the percentage.

To accurately portray the information, the data must be normalized, and an appropriate data classification system must be adopted. Data normalization is standardizing the data so accurate comparisons can be made between each data collection area. To illustrate, a raw count of 1,000 Hispanics residing within a rural county of 5,000 is quite different than 1,000 Hispanics living in Dallas County. Lastly, a data classification system must be employed. While data classification systems are well beyond the scope of this blog post, ESRI [the Environmental Science Research Institute] has a great introductory resource [it can be found by clicking here]. For this specific map, the natural breaks classification system was the best option. 

For the final portion of this assignment, all subjects explored throughout this module were applied in the creation of the map below.

This map is a choropleth map that shows population change between 2010 and 2014 for each county in the state of Colorado. For the diverging color ramp, I chose to employ the natural breaks classification system, slightly modified so they were divided by 0% change. Hence, a red shaded county represents negative growth while a green shaded county represents positive growth. Furthermore, the darker the shade, in either direction, the higher the magnitude of population change. Lastly, for this map, I chose to employ a custom projected coordinate system. This was an intentional decision due to the fact that there were two NAD 1983 State Plane systems [one for the north and one for the south] for the State of Colorado, but not one that encompassed the entire state. Additionally, the state of Colorado intersects UTM Zones 12N and 13N, so the use of a custom projection system minimizes the distortion that would have occurred otherwise. 

I am pleased with the subject matter of this module, and I believe that a fundamental understanding of these concepts are displayed throughout the design of these deliverables.

Sources:

Environmental Science Research Institute. [2024]. Data Classification Methods. https://pro.arcgis.com/en/pro-app/latest/help/mapping/layer-properties/data-classification-methods.htm

Kimberling, A.J. (2012). Map Use: Reading, Analysis, Interpretation (7th edition). ESRI Press Academic.

GIS 6005 Module 3 - Terrain Visualization

Module 3 of GIS 6005 - Communicating GIS was an exploration of various methods used to convey three-dimensional terrain on a two-dimensional map. The first exercise was a combination of contour lines and hypsometric tinting to illustrate how the rapidly the elevation changes throughout the mapped study area. Contour lines are 'lines of equal elevation above a datum. If a contour was actually drawn on the earth, it would trace a horizontal path that is constant in elevation [Kimberling, 2012, p. 217]. Additionally, hypsometric tinting is 'a method of "coloring between contour lines" that visually enhances the relative elevation cures for contours while maintaining the absolute portrayal of relief [Kimberling, 2012, p. 220]. A shown in the map below, the shades of the color ramp in the legend directly coincide with the elevation provided [in meters above sea level] at each contour line. For the symbology of the hypsometric tint, a green was used for the lowest elevations, which suggest a valley, and oranges / yellows for mid-elevations, and white for the highest, suggesting white capped mountains; this was the color scheme that was suggested in [Kimberling, 2012].

For the second a third portion of the lab, traditional and multi-directional hillshading effects were employed to actively display dimensionality on a printed terrain. Hillshading, or relief shading, uses a simulated light-source to provide relief on a map; however, the use of a singular light source creates overdeveloped, illuminated surfaces and dark, overbearing shadows. The solution to this problem is to utilize multiple light sources which will effectively reduce these extreme lighting characteristics found in traditional hillshading. The map below is a land classification map of a study area located in Yellowstone National Park. As shown in the legend, there are many various vegetation types that can be found on the map. To give the user a sense of depth and relief, a multi-directional hillshade effect was applied to the Digital Elevation Model and the land classification layer's transparency was set to 50%. This allows the texture of the landscape to be experienced by the viewer as they gather information on vegetation types found throughout the study area.

Part four of the lab was 'draping' a remotely sensed RaDAR imagery over a Triangulated Irregular Network Digital Terrain Model to give three-dimensionality to the orthophotos. The RaDAR imagery was gathered from a portion of Death Valley, California and can be seen in the image below.

This lab was a great opportunity to explore some techniques to give depth / relief to a two-dimensional map. A lot of material was covered in the text that we did not apply in the lab, but this assignment did provide a great foundational knowledge for future applications.

Informational sources:

Kimberling, A.J. (2012). Map Use: Reading, Analysis, Interpretation (7th edition). ESRI Press Academic.

GIS 6005 Module 2 - Coordinate Systems

 'A map projection is a geometric transformation of the earth's spherical or ellipsoidal surface onto a flat map surface' [Kimberling, 2012, p. 57]. The different map projections and their applications were the subject material covered in Module 2 of Communicating GIS. While the intensity and depth of map projections is well beyond the scope of this blog post, a great starting point on this subject is the ESRI documentation regarding coordinate systems; you can find the resource at this link:

Geographic vs Projected Coordinate Systems

Essentially, lab assignment two was applying different projected coordinate systems to various maps and examining how they affected the land masses differently. As the round surface is projected onto a flat surface [developable surface], some integrity will be lost; this will either be in distance, area, angles, or distances [Kimberling, 2012]. Each of the different projection types will preserve some of these qualities while distorting others. It is up to the cartographer to determine which projected coordinate system is appropriate for each case. 

The final part of the lab was to pick a state and determine which coordinate system was the best choice to create an accurate map. As shown in the map below, I chose to map the state of Texas. I primarily decided on Texas because a custom projection system was the best option. Two of the most popular projection systems, State Plane and UTM, were not appropriate because the state crosses numerous zones in each of these systems, which would cause major distortion to the map. Conclusively, this map was drawn using the NAD 1983 [2011] Texas Centric Mapping System Lambert projected coordinate system, which is a conformal PCS that preserves the actual geometry of the state. 

This lab was very intriguing and informative; the subject of projected coordinate systems is complex and deep, but this module was an excellent introduction to the complexity of this subject.

Informational sources:

Environmental Science Resource Institute (2024). Geographic vs Projected Coordinate System. https://www.esri.com/arcgis-blog/products/arcgis-pro/mapping/gcs_vs_pcs/#:~:text=A%20projected%20coordinate%20system%20(PCS)%20is%20a%20GCS%20that%20has,to%20know%20how%20to%20draw.

Kimberling, A.J. (2012). Map Use: Reading, Analysis, Interpretation (7th edition). ESRI Press Academic.

GIS 6005 Module 1 - Map Design and Typography

Module One of GIS 6005 - Communicating GIS revolved around cartographic design principles and typographical principles that should be followed to create effective maps. The five design principles studied were as follows:

• Visual Contrast
• Legibility
• Figure-ground organization
• Hierarchical organization 
• Balance

These principles were practiced in all five parts of the lab while typographical design, or labelling, was introduced into the last three sections of the assignment.

For part one, datasets of the Austin, Texas metropolitan area were provided and were to be compiled into a cartographic reference map for tourists coming to the city. A simple layout was provided with all required map elements, but the final map [shown below] does not incorporate any of the original layout's elements. Here is a brief synopsis of the five design principles and how they were applied to the final map:

Visual contrast 'relates to how map features differ from each other and their background' [Kimberling, 2012, p.133]. This was achieved by using bright colors for the symbology of the feature classes that are emphasized against the earthy tones of the background. Legibility is 'the degree to which something can be read and deciphered' [Kimberling, 2012, p. 132]. Careful consideration was given to the font types, size, and font colors throughout the map, ensuring they can be read at a reasonable distance. Figure-ground organization is 'a perceptual phenomenon in which our mind and eye work together to spontaneously organize what we are viewing into two contrasting impressions - the figure, on which our eye settles, and the amorphous ground below or behind it' [Kimberling, 2012, p. 136]. To achieve this aesthetical organization, a darker color was used for the focal point of the map to visually bring it to the forefront of the page. Visual hierarchy is 'the graphic structuring of the features that make up a map' [Kimberling, 2012, p. 137]. This hierarchy is simply achieved by ensuring the focal point of the map [Travis County] has the most visual weight, the title / subtitle are second to the map, and the remaining map elements hold the least amount of visual weight, not stealing unnecessary attention from the user's eyes. Finally, balance 'involves the harmonious organization of the mapped area and any marginalia on the [map]...' [Kimberling, 2012, pg. 140]. This design principle offers much more flexibility than the others, is more subjective in nature, and is achievable through many differing methods. For this map, it has a more symmetrical, or formal, balance with the map dead center and the marginalia organized on both sides at the bottom of the map. This balance is highly contrasting with the balance achieved in part two of the lab [see next map below].

Part two of this lab was creating a map for a lumber company that illustrates how much land can be harvested in two land leases, both located in the state of Alaska; all five design principles introduced in part one were to be addressed and applied in this map as well [see below], but the final product is quite different between the two maps.

Part three of this assignment still focused on the five cartographic design principles, but introduced labelling practices into the design process. There are typographical standards that provide the cartographer with general guidelines, but sacrifices sometimes need to be made to achieve the desired result. A map of San Francisco, California and some of its major landmarks was the required deliverable. Here are a couple design principles that were followed in the creation of this map: first, since the map is of San Francisco, this text was given the most weight by using a bold, larger font than the rest of the labels. A sans serif font was used in the labelling of all cities and neighborhoods because that is a cartographic standard; manmade landmarks are labelled with a sans serif font. The parks were labelled with a serif font in a green hue that is contrasting to the shade of green used in the parks themselves. Also, the spacing was increased between the letters of these labels because it spreads the labels out over a larger area, visually conveying that areal features are being labelled. Lastly, a serif font was also used for natural features in a brown hue that is contrasting to the shade of brown that was used for the land mass. Since there are roadways all over the map, they were displayed in a light shade of grey, and a halo was used on most labels that overlaid the streets to increase legibility. These decisions led to a map that is visually balanced, aesthetically pleasing, and hierarchically organized to emphasize which landmarks are most important on the map.

Finally, for part four and five, the deliverable was a map of Mexico and its significant landmarks. The same principles that were applied in step three were relevant to step four and five also, but more considerations had to be taken because the amount of labelling on this map was somewhat daunting. In step four, the only labelling that was required was the rivers. This provided an opportunity to explore the various settings to achieve a desirable result. As shown in the map below, a blue, italicized, and serif font was used for the text elements, but they were manipulated in a way that they curve along the linework of the feature class. Once these labels were added to the map and properly formatted, cities, states, and the capitol city were added to the map. Once all the labels were on the map, it was apparent that design choices, and sacrifices, were going to be required to create a legible end product. The first decision was to reduce the number of cities that were included on the map; to accomplish this, all cities that had a population less than 250,000 people were eliminated. This greatly enhanced the legibility, but it was still highly congested around the capitol city. Due to the small size of the District of Mexico, and it being a federal district [not a state], it was eliminated from the map as well. These design choices led to a final product [see below] that was substantially more legible than one displaying the label for every feature class.

Overall, this lab assignment was very fulfilling and provided numerous opportunities to get familiar with the cartographic and typographic design principles that are required to create an effective, high-quality map.

Sources:

Kimerling, A. J. (2012). Map Use: reading, analysis, interpretation (7th ed). Esri Press Academic.