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| Public Schools in Ward 7 - Washington, D.C. |
This week's assignment was to use Gestalt’s Principles of perceptual organization to create a map of public schools in the Ward 7 area of Washington, D.C. Symbology needed to distinguish the different types of public schools (high, middle, and elementary). The map needed to include an inset map denoting the location of Ward 7 in relation to the larger Washington, D.C. area. It also needed to include labels for some neighborhoods located within the 7th Ward and show different pertinent roads relative to the mapped area. Data was provided through the District of Columbia Open Data site. Finally, all of the required essential map elements needed to placed appropriately on the map.
My map uses the Ward 7 data frame to display an up close view of Ward 7. There were several layers of data in this lab. Figuring out the order for the layers and which layers to display in the Ward 7 data frame were the first decisions I made. Next, I reviewed the Color Brewer site as recommended in the lab to think about color schemes. I changed the symbology color of different layers until I decided on a sequential multi-hue scheme that included a light yellow and variations of green. I thought this scheme would be visually pleasing to the end user. The color scheme also enabled me to employ Gestalt's Principles of visual hierarchy and contrast. The Washington, D.C. area was the bottom of the color scheme a light yellow. The more important area of interest, Ward 7, was the next color in the scheme (a light green). I then chose to use a slightly darker green to identify the parks layer. The surface water layer was identified with a blue color to enable those features to be seen on top of the light green Ward 7 and light yellow District of Columbia. I used the Geoprocessing Clip Tool to only display public schools located in Ward 7. At first I could not use this tool due to a script error. After a Google search I changed some of the Security settings for Internet Explorer and was able to use the tool. I liked the school house symbol shown in the lab assignment, so I chose to follow the instructions to select the school house under the Civic symbol category. Continuing to follow the lab instructions I used the Symbology tab to select the facility use values of elementary, middle, and high and changed the symbol size according to the facility use. The largest school house denoted high schools and the smallest school house denoted elementary schools.
Determining which transportation layers to display took some trial and error. I also wanted to continue to use visual hierarchy and contrast to distinguish between the different types of roads. Ward 7 streets and Major streets were displayed in different gray hues; Major streets shown in a slightly darker hue. I also made those two layers distinct by increasing the line width for Ward 7 streets from 1.5 to 2.0 for Major Streets. To distinguish the State Highways from U.S. Highways, from Interstates, I again employed the use of color and line width. State and U.S. Highways were denoted with the color red and line widths of 3 and 4 respectively. Interstates were shown with the color blue and a line width of 5. I also was able to use the Label tab to create a query for US Hwy. 50 and State Hwy. 295. I used Google Maps to identify these two roads so I would know which values to select in my Label query. I was unable to figure out how to use a field in the Interstate attribute table to identify Interstate 695.
Our lab assignment required that we identify one neighborhood from seven of the neighborhood clusters within Ward 7. This step also required some trial and error. I had originally turned off both the Neighborhoods and Neighborhood cluster layers. I turned back on the Neighborhoods layer and used the Label tab to label all the neighborhoods. I then printed off the attribute tables for both the Neighborhoods and Neighborhood Clusters layers. While looking at the Neighborhood labels on the map, I selected 7 neighborhoods that had the least overlap with the existing Public School symbols. I then turned off the Neighborhoods labels and followed the lab instructions to create a new layer from the selected neighborhoods in the attribute table. I called this new layer NeighborhoodSelection. I then used the Label tab to create labels for these neighborhoods. The Mayfair neighborhood label was overlapping a school and the Fort Davis Park label was extending beyond the Ward 7 layer, so I chose to convert the labels to annotations. I wanted to be sure to keep the annotated labels in the correct neighborhoods. I used Google Maps to identify the boundaries of the Mayfair neighborhood and moved it away from the school symbol. I also slightly relocated the annotated Fort Davis Park label.
Per lab requirements I used the Drawing Tool to label the Potomac River. I chose to use the same Type style (Lucinda Sans) throughout the map but I italicized the Potomac River label in accordance with Typography rules we learned in Module 3.
I then worked on creating and designing the essential map elements of Title, Legend, Scale, North Arrow, Author, Date, and Data Source. I tried to use the principle of Balance to properly arrange these map elements. I continued with the same Type style but made modifications to font size for the Map Title, Legend Title, Scale, and Date, Author, and Data Source. I also tried different variations of incorporating the sequential color scheme and grays to create contrast between the different neatlines in the map. In previous module assignments I had received feedback regarding my use of map space, so I tried to pay closer attention to this and created a frameline to encompass all map elements and a neatline to encompass the two data frames, legend, scale, and north arrow. Not having a graphic design background I tried different options (see Ward7Schools_MMTTest*.jpg versus the Ward7Schools_MMTFinal.jpg in my S: drive) of background colors. I needed to use Figure Ground to make some elements/features of the map appear closer to the user or to "pop". I needed to do so without introducing too many new colors and hopefully succeeded by using different levels of gray and then white for the Title and Legend.
I left the inset map to last. I removed several of the layers that were in the Ward 7 data frame in the Inset Map. They were not needed and I wanted to keep the TOC organized. As I'm writing this I realize I should have created a "transportation" group for the Ward 7 data frame's different road layers. I wanted to maintain the same color scheme used in the Ward 7 data frame in the Inset Map. I used the color selector to darken slightly the colors of the Ward 7 and WashingtonDC layers so they would appear more clearly without appearing different from the Ward 7 data frame. I kept the same color scheme for the roads shown in the inset map and also distinguished them by modifying their line width. I labeled the Inset map and identified Ward 7 with the Extent Indicator. I changed the color of the Extent Indicator to an orange hue as I had already used red in both data frames to identify State and U.S. Highways.
I saved the map and exported it to both a jpeg file and an AI file format. I looked at the map in AI just to see the number of layers it would create. I chose not to use AI to refine the map as I needed a stylizing break. There are so many more design choices in AI. You are able to really break down items within each layer on an individual basis. I noticed in my final map I may have needed to use "clip" on some layers to prevent what appeared to be "bleeding" or overlapping. AI may have helped me see some of these details more clearly and enabled me to identify layer features more distinctly especially with color saturations/hues.
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