Thursday, February 20, 2020

GIS 6005 - Communicating GIS - Module 6

  

Once my layout was completed, I tweaked my symbol classes to make the job loss red circles, and job gain blue circles the same size, relative to the equivalent number on the opposite side.  Then, I added another copy of the job gain category, and changed the symbology to hollow circles with black outlines. (This was done in order to include all circles, and communicate that the number associated is symbolized by the size of the circle.)

After ungrouping the legend, I stacked the circles in order of size and labeled them with appropriate labels. Then, I created a secondary legend that explained the colors displayed on the map, and placed it above the first legend. Between the two of these legends, the colors, as well as the sizes of the circles are communicated, and the same circle size can be applied to all circles.




Color values presented are in the HSV color model. (Transparency is set to 0 for all values)

A1 – 0, 0, 96.08
A2- 171, 37.56, 80.39
A3 – 175, 99.02, 40
B1 – 42, 43.95, 87.45
B2 – 92, 11.87, 66.08
B3 – 156, 62.89, 38.04
C1 – 33, 92.86, 54.9
C2 – 45, 70.53, 41.25
C3 – 92, 43.17, 35.88

I began by generating a dividing color ramp in Color Brewer, and selected 9 classes. I chose the middle value as A1, then every other value in each direction as the next value diverging from A1. (Teal for numbers, Brown for letters)

Next, I calculated the rest of the table by adding the RGB values of opposing extant cells, and dividing the results by two, as we had done in the chloropleth module.


If a color palette is chosen well, and the values are easy to distinguish for the typical person, two distinct values can be simultaneously communicated in a single map. While three value classes may not be very thorough in communicating specifics of the degree for each value, the correlation can be communicated very well by showing areas of concentration for both variables.


Thursday, February 13, 2020

GIS 6005 - Communicating GIS - Module 5





Brief discussion of your design choices for your selected visualization technique(s).
            I began by creating the pie chart. Because I wanted to include an additional data to accompany my insufficient sleep map, I decided to select a matching color scheme. The entirety graph shows a breakdown of all U.S. counties considered in this study, and the labels reveal how much of the population within these counties reports insufficient sleep. While this may not have been the best way to label this data (it may be confusing whether the label pertains to the general variable size, or a fraction of said variable), ultimately, I found this way to be the most detailed and informative.
            The comparative line chart was generated with data obtained from a single source site, (data.worldbank.org) which cites multiple sources (The UN Population Division, and U.S. Census Bureau) itself. I looked for the change of life expectancy over time in the United States, and decided to add several other countries from all over the word to give the viewer a contrast. The countries were selected randomly, but I did want to show a somewhat worldwide distribution.

Briefly discuss what strategies you used in finalizing your layout.
            The layout was generated on a 17x22 landscape-oriented canvas. I began by creating several guides at the top, bottom, left and right of my canvas, in order to give my elements an equal amount of space from the edges of the paper. I repeated this process, and used more guides to divide the canvas into four distinct parts. I centered my map exactly how I liked it, and added it to the upper left quarter of my layout. I created the second map layout from the first, and placed it in the lower left.  
            I created a number of neatlines, and placed them around my canvas. First, a large gray canvas across the whole page, then smaller, black rectangles over which all data will be placed. Staying consistent with the theme of the project, all of the charts were exported with a dark grey-black background. The data represented on each chart was colored to match its respective map, unless the data represented showed unrelated variables, in which case they were assigned various colors.
            I tried to keep the font consistently dark-red, except for the Sleep map, for which I made it purple to match its data. The overall title was placed on the upper right, and the graphs were distributed for the best possible fit. The left-over space was used to insert citations for external data.

Friday, February 7, 2020

GIS 6005 - Communicating GIS - Module 4








Color ramp
Notes
Stepwise Intervals
Linear progression

R
G
B
·         After setting the parameters for the darkest color based on the suggestion, I attempted to make my brightest color comparable in hue.
·         The formula for the R scale progression:
255-150=105
105/5=21
·         The formula for the G scale progression:
130-0=130
130/5=26
·         The formula for the B scale progression:
225-75=150
       150/5=30

R150
R171
R192
R213
R234
R255




G000
G026
G052
G078
G104
G130




B075
B105
B135
B165
B195
B225





·          



Adjusted progression




In order to make a legible adjustment, I decided to make the 4th value in each column the half-way point between the darkest and the lightest.
For the red scale:255-150=105
105/2=52.5 (then add 52.5 to the darkest value)

For the green scale:130-000=130
130/2=65 (then add 65 to the darkest value)

For the blue scale:225-75=150
150/2=75 (then add 75 to the darkest value)

The remaining values were placed intuitively, and rounded to the nearest point. Made to equal approximately 1/3rd of the difference between 1 and 4 for the second and third value, and an approximate half way point between 4 and 6 for the fifth.


 R150
R166
R184
R202.5
R227
R255





G000
G022
G044
G065
G097
G130





B075
B100
B125
B150
B187
B225




ColorBrew




·         The values obtained from Color Brewer don’t seem to follow any easily definable pattern. While the blue and green levels seem to gradually increase on the spectrum, the red does not systematically increase. The amount of red in the 4th value drops below that of the second and third values, and spikes at the end to the highest level to create an almost-shite hue for the brightest value.
R152
R221
R223
R201
R212
R241




G000
G028
G101
G148
G185
G238




B067
B119
B176
B199
B218
B246






Brief discussion of your results. How do the linear and adjusted progression color ramps compare to the results from ColorBrewer? (Aprox. 150 words)

            When working on my linear progression, I selected a pre-determined purple color as my starting point. Then, in compliance with the lab instructions, I created my brightest color. I did so by estimating what the end of the range would look like, and attempted to keep the hue as close to my dark purple color as possible.  After completing the spectrum, I have used the same starting and ending point to create the adjusted progression ramp. Despite my attempt to broaden the spectrum around the dark end of the scale (as described above), the color ramps look very similar at a glance. Most of the values across the spectrum differ only by a few points, making it quite hard to distinguish without a close examination.
            The spectrum generated in Cold Brewer began with a very similar dark purple to the previous two. However, because I selected a multi hue spectrum, the degree of ‘redness’ across the spectrum does not increase regularly like in the first two color ramps. This makes for a much more legible color ramp, as the brighter colors are not only brighter, but also appearing more blue than those in the linear and adjusted ramps. The brightest value in the Cold Brewer ramp is also significantly closer to white than the brightest value in the previous ramps making the overall spectrum broader and easier to read.

Wednesday, January 29, 2020

GIS 6005 - Communicating GIS - Module 3



The above image shows a simplified version of a Land Cover, multi-attribute raster of the Yellowstone area. I began by combining the tree cover variables into the vegetation type, independent of their more specific classification (post-disturbance, climax). Afterwards, I selected my colors to most closely resemble vegetation, while maintaining enough of a difference in shade to make them easily distinguishable to the eye. Water was made blue, and Aspen was made dark purple to stand out. 

Next, the raster was made 60% translucent, and placed over an elevation raster, enhanced with a  multidirectional hillshade effect to show the variety of the landscape underneath. 

I initially intended to insert a pie chart to show the percentages of each category in the map above, but ArcMap Pro seemed to only give me options for a histogram and scatterplot. I found both of these graphs to be less appealing, and decided to keep the design simple.

Wednesday, January 22, 2020

GIS 6005 - Communicating GIS - Module 2

















Deliverable 11:

State your area of interest. Briefly discuss which coordinate system you selected for that area of interest and why. Express why the other options were less appropriate.

            I chose the State of Pennsylvania as my map focus, and more specifically the Philadelphia area of the State of Pennsylvania. This is the city in which I live, and most of the GIS projects I end up working on are located locally. I chose a state plane projected coordinate system, and more specifically the NAD 1983 (2011) StatePlane Pennsylvania South FIPS3702. Because Pennsylvania is fairly big (by the standards of the American Northeast), there are actually two state plane systems: north and south. Obviously, because the City of Philadelphia is situated in the very southeast of the state, I decided to select Pennsylvania south for the purpose of this project.
            The state plane projected coordinate systems tend to be very accurate when focusing on a fairly small area. The distortion of the grid is apparent within a few states, and can be seen very clearly when viewing all of the United States. The area of focus, however, lends itself well to the grid. I chose not to use a UTM based system, as the state of Pennsylvania falls at the exact center of two UTM lines. After browsing through the State Systems list, I did not see anything specific to Pennsylvania, and therefore wen with a more familiar choice.





Deliverable 8:

Provide the name and complete details of your coordinate system.
I picked the Nova Scotia province for my point of interest. Of the two Projected Coordinate Systems that appear on the list, I selected:

ESRI Projected Coordinate System: ATS 1977 MTM 4 Nova Scotia
Projection: Transverse Mercator
WKID: 2294
Authority: EPSG
Linear Unit: Meters (1.0)
False Easting: 4500000.0
False Northing: 0.0
Central Meridian: -61.5
Standard Parallel 1: (NA)
Standard Parallel 2: (NA)
Latitude of Origin: 0.0  

Geographic coordinate system: GCS ATS 1977
WKID: 4122
Authority: EPSG
Angular Unit: Degree (0.0174532925199433)
Prime Meridian: Greenwich (0.0)
Datum: D ATS 1977
Spheroid: ATS 1977
Semimajor Axis: 6378135.0
Semiminor Axis: 6356750.304921594
Inverse Flattening: 298.257

Thursday, January 16, 2020

GIS 6005 - Communicating GIS - Module 1



Deliverable 3: Briefly explain how your design choices for map elements contributed a consistent style for your map
I modified the map legend to list the polygon fields first, and in order of importance. The lines and point features were moved towards the end. I made the map title Orange, with a thick, black outline, to simply make the map look more ‘fun’ and user friendly. Because the rest of the font was small, and an outline would have made it a bit much, I kept it black. I also made a black outline around the legend, as well as the text, to make the layout appear more balanced and professional.


Deliverable 4: Briefly explain how you addressed each of the 5 map design principles
1)      Visual Contrast: I tried to make the smaller point and line features more vibrant, over the more faded background. The Travis County polygon itself is easily distinguished from the surrounding counties because of the bold line that surrounds the green color.
2)      Legibility: The legibility challenge was fairly straight forward with this map, as the overall feature amount was not too busy. The highways are the only line feature, and I made them thicker to stand out next to water, which is made up of long, slender polygons.
3)      Figure Ground Organization: I tried to incorporate bold lines wherever possible, to highlight the boundary between features.
4)      Hierarchical Organization: As stated above, the smallest features towards the top of the map. I left the labeling to the legend, to try to keep the map less busy.
5)      Balance: Map was centered on Travis County, but showed the surrounding counties to fill the negative space.




Deliverable 6: Briefly explain how you addressed each of the 5 map design principles.
I began the modification of the current map extent by addressing the five minimum criteria provided in the lab instructions first.
1)      I changed the page size by going into the layout tab, and expanding the page layout. There, I was able to chose from a pre-set page sizes, as well as put in my own parameters. I decided to go with a standard 8.5x11, using the landscape format.
2)      In the layout view, I made the layout window look more vertical, as the harvest stands C and D, and concentrated it along the lower left-hand side of the layout. This way, I will be able to put the legend, and any other relevant information along the right.
3)      In the Layers tab, I activated the map view and turned off the ‘streams’ and ‘general area’ layers in the table of contents.
4)      I changed the scale bar units to feet, and selected a more aesthetic appearance. I changed the north arrow to a simpler design, and shifted it to be in the diagonal corner of the map from the scale.
5)      The Design Principals:
a.      Visual Contrast: I placed a dotted line around the two lease polygons, and made them similar colors to look related to one another. The shading however, is different enough to clearly see the distinction.
b.      Legibility: The map is simple overall, so not much modification was needed. I left the color of the nest areas, and protected buffers as they were.
c.       Figure Ground Organization: There are really only two parts of the map that had to stand out over a white background. The dotted line was added for more contrast.
d.      Hierarchical Organization: Once again, the largest features were placed at the bottom, and the smallest at the top. Not much modification was required.

e.       Balance: I added the legend, and the map notes in their own boxes on the right-hand side, to fill a landscape page with the current map extent.




Deliverable 9: Explain in detail how you used text (type, size, placement, effects, etc.) to achieve the map design objectives of legibility, visual contrast and hierarchy. Do this for each category of text element (general, water, etc.), iterating with significant detail.

I chose a specific font for each category listed in the lab assignment, and worked my way down from the largest of the listed features, to the smallest. I approximated the size, based on how it may appear to the map reader.

I began by labeling San Francisco and Oakland with the large “City” font. Afterwards, I simply made my way down the features in size to label the neighborhoods.

I selected the standard water body font, and labeled all water features. The only label I ended up rotating, was Lake Merced, due to its tiny size.

I made the park names appear dark green, in order to make them legible on the map, but communicate that it may be associated with the outdoors, or nature.
I labeled the golden gate bridge with small, dark font.

The topographic features were labeled with the same font as larger features in the general category, but made lower case to distinguish them.






Deliverable 11: Discuss your selected label options and how they contribute to an effective map.
I imported both; the country, and the state files for Mexico. I made the outline of the country file bold, and placed it underneath the states. I imported the rivers, and made them a strong shade of blue, in order for them to stand out. I selected a slender font, and made it the same color. I tried to give it an outline, but they came out too bold. I used the curving effect to make the labels wrap around the river features.


Deliverable 13: Discuss your selected label options and how they contribute to an effective map. Specifically address the strategies employed to balance numerous labels.
I made the state labels the same shade of grey as the boundaries, and left them in the approximate center of each polygon. I attempted to select a font that is slender, in order to have the least amount of overlap as possible. For the cities, I colored the points orange, and made the labels black with an orange outline to match the points. The cities stand out on the baige background, and are easily distinguished from the water lines.