Final Project

Introduction

For my final project, I chose the U.S. Department of Education scenario in which a map of the 2014 SAT scores and participation rate for each state would be created for the purpose of submitting to the Washington Post alongside an article on high school seniors and college entrance scores. I chose this option because I was curious about what regions of the U.S. were more likely to take the SAT, considering I grew up in the Central U.S. and the ACT was encouraged more than the SAT. My objectives going into the project were to: create my own tabular data, convert that data into something visibly tangible (i.e. shapefile), determine how to display each dataset thematically, choose an appropriate projection, determine how to classify the datasets, create appropriate labels, utilize inset maps, and determine how to present the most of my data without cluttering my map.

Thematic Methods

For my thematic map I chose a choropleth theme for SAT scores and graduated symbols for participation rates. I got a lot of my inspiration by looking at other standardized test score maps online, while searching for a common theme among them. The majority of them had in common the usage of graduated colors. Furthermore, the majority used a monochromatic color ramp, contrasting light and darker hues of the same color. I followed the same path and chose a blue light to dark color ramp. I chose graduated symbols because it allowed me to produce a range of symbol sizes and values close to the values on the sheet of data we were provided.

Data Classification Methods

For the SAT score data, I used graduated colors with a quantile classification of 5 classes. I used this method because most of the data was not of identical values and could be easily rank-ordered. I chose 5 classes so the viewer could easily observe the map in 20 percent fractions. I was conflicted on whether or not to include the SAT score ranges, as the College Board “strongly discourages the ranking of scores between states”. Every map I came across for my inspiration only indicated ‘high’ and ‘low’ as score ranges. However, this map was created in mind with the intention to display information, and with the quantile method I could leave out the numbers and indicate ‘high’ and ‘low’ in case concerns of state comparisons were holding back publication.  I used graduated symbols for the participation rates because it gave me more control over how to group the percentages through symbol size.

Design

 I wanted to achieve contrast, yet the map be easy on the eyes to decipher and follow. I also wanted it to be simplistic and easy to understand, considering it would reach a wide audience. I stuck with a theme of varying shades of blue with white borderlines, and labels colored appropriately to the hue. Label sizes vary with state size. ArcMap was used to produce the bare bones and data of the map, I carried out the rest of the design, typography, and neat lines in AI, where I would have better font, border, and artistic capabilities.

Google Earth

   In this lab, a previous dot map assignment was converted into a KML file in ArcMap and then used to create a Google Earth tour.

   The ArcMap conversion tools Layer to KML and Map to KML were used to create KML files for the recorded tour. One layer shows the dot map density of population for South Florida while the other shows surface water types of South Florida.  An additional unseen layer is added to provide the attribute table information. The dot map and its data were created from a previous assignment. 

3D Mapping

   In this lab, the learning objectives were to: perform techniques to visualize raster and feature data in 3D, convert 2D feature to 3D using elevation values derived from lidar data, utilize the 3D Analyst Extension in ArcMap, demonstrate proficiency in ArcScene, and export data to a KMZ file to be viwewed in Google Earth. Below is a screenshot of one of the 3D labs I completed in ESRI's virtual campus course training.

   In this part of the ESRI training, vertical exaggeration was implemented through ArcScene. It is used to give a more dynamic appearance to terrain that has small changes in elevation. Here, the terrain in Minnesota is enhanced. The other ESRI training labs demonstrated how to: set base heights for raster and feature data, set illumination and background color, and extrude features based on height or other attributes. 

   3D mapping is beneficial in many ways. It is as easy to share as 2D data and has useful applications for simulations. It can present vertical information as cant be seen in 2D and has intuitive symbology. It is easier to recognize terrain and location because of its human-centric aspects. However, it is easy to get disoriented while navigating. Map content can be hidden underneath surfaces or in building interiors. There is also the issue of performance. Since 3D mapping entails a lot of data, performance issues with computer hardware can arise. Overall, 3D mapping is a unique and immersive way to communicate data and information.

 

Dot Density Mapping

   In this lab, we made a dot density map of the population of southern Florida. Our objectives in ArcMap were to: join spatial and tabular data between an excel sheet and a shapefile, and to utilize dot density symbology by selecting a suitable dot size, unit value, and the mask function in manipulating dot placement. 

My Map

   I created this dot density map in ArcMap with the data provided in this weeks lab. In terms of alternate design, I chose to turn off the county borders in order to better see the dot placement. In this week's lab we had a bonus objective of creating the dot legend by means other than the default one provided by ArcMap's legend wizard. I decided to make my dot legend by creating three new data frames in ArcMap, dragging the dot density layer into each one, and zooming into a spot with a 'few', to 'a couple', to 'many' dots. The only issue with this is I had to turn masking on as I worked through and zoomed into a location in each data frame and then off when I went to the next data frame (To prevent bogging). Otherwise it would generate random dots when I dragged it around in layout view (Also, I had to remember to turn masking all back on before exporting). I would not recommend this if you have trouble with loading the map after turning masking back on. I waited ~3 minutes for my map to export with all the masking on in the end.

Flow Line Mapping

   In this lab, our goal was to create a flow line map in Adobe Illustrator depicting immigration to the U.S. in the year 2007. The lab objectives were to be able to: assess design issues for flow line mapping, calculate proportional line widths using excel, utilizing AI to create a global scale flow map, and produce a final map that demonstrates proper cartographic and flow map design techniques.

My Map

   This map shows the proportion of immigration by continent to the U.S. in the year 2007. The choropleth inset map shows what percentage of immigrants went to which states. Adobe Illustrator was used solely to create this map. I utilized the pen tool to create my flow lines, the text tool to create my legend and map text, the rectangle tool to make my choropleth legend continuous, the direct select tool to implement same fill color to my continents, the 3D and Bevel effect to stylize my flow lines, the transparency feature to prevent my flow lines from covering other map features, and stroke color to make my flow lines better represent the continent they come from.

Isarithmic Mapping

   In this lab, our goal was to produce an isarithmic map, with contour lines, depicting the annual rainfall coverage over the past 30 years of the state of Washington. Our learning objectives for the exercise were to be able to: understand the PRISM Interpolation Method, work with continuous raster data and implement continuous tone symbology, make map appropriate legends, utilize the Int Spatial Analyst Tool to convert raster values to integers, employ hillshade relief for both maps, manually classify data correctly, and to create contour lines using the Contour List Tool.

My Map

   This map depicts the annual precipitation over a 30 year period in the state of Washington. The data was prepared and derived using the PRISM Interpolation Method. This method utilizes elevation  data alongside precipitation data, creating stepped color zones, with contour lines, that better depict relief. 

Choropleth Mapping

   In this lab, our goal was to create a choropleth map showing overall population densities in European countries and tie in wine consumption using either graduated or proportional symbology. Our objectives were to be able to choose an appropriate color scheme, classification scheme, symbology, and legend. Additionally, we compiled our maps in accordance with cartographic design principles and polished up the end result in Adobe Illustrator.

 

My Choropleth Map

 

 

 

   The purpose of this map is to display population density in European countries and the wine consumption percentage of those countries. I started off the project in ArcMap with choosing a color scheme for my data. I chose a sequential color scheme to display the unipolar data. I used a part-spectral scheme of yellow-to-orange-to-redish-brown. Next, I chose my data classification scheme. I decided on quantile because it showed the most variation among countries while refraining from being too mono-colored. Then, I used graduated symbology to display the wine consumption data. I felt this better portrayed the percentage of wine consumption. Lastly, I touched up my map in AI. I manually labeled the countries, gave it a title, and wrote a short synopsis. 

Data Classification

Hello!

In this week's lab we learned four different methods in which to classify our data in ArcMap, which are: Natural Breaks, Equal Interval, Quantile, and Standard Deviation. Our goal was to demonstrate that we could make four maps portraying these different methods and be able to organize all four data frames onto one map deliverable. Furthermore, we were expected to appropriately symbolize our maps with a logical color ramp and implement cartographic design principles into our final product.

This lab's purpose was to compare and contrast data classification methods and presentations in order to choose which one best suited an audience scenario.

My Map

This map shows data presented by four differing methods: Natural Breaks, Equal Interval, Quantile, and Standard Deviation. The overall data presentation showcases these methods depicting the area location per square mile of individuals age 65 and older in Miami-Dade County Florida.

ESRI Spatial Statistics Training

Hello!

In this exercise we went through virtual training on ESRI's virtual campus. In this training course, we learned how to:
- Utilize the Spatial Statistics Toolbox and Geostatistical Analyst Extension.
- Recognize what questions need to be asked about your data before choosing an analysis tool.
- Calculate the Mean Center, Median Center, and Directional Distribution of a dataset.
- Examine the Spatial Distribution of your dataset and identify clusters and spatial relationships in the data.
- Bring up a Histogram and Normal QQ Plot, how to interpret them, as well as understand the properties of a normally distributed dataset.
- Find outliers in your data using a Histogram, Normal QQ Plot, Semivariogram Cloud, and Voronoi map.
- Use Trend Analysis graphs to identify patterns in your data.
- And to assess which analysis tools are appropriate to use with the given spatial distribution and values of your data.

My Map

Map Overview

This map was made through ArcMap with the data we downloaded from ESRI's virtual training course. It was our base map for the various exercises we performed throughout the training course. This particular map was made in the beginning of the training course and was made for the purpose of locating the mean center, median center, and directional distribution of weather stations in Europe. We used the Spatial Statistics tool in order to find these values. Our goal at the end was to determine which areas of Europe should be put under a freeze advisory, based off of the temperature data collected. 

Cartographic Design and Perceptual Organization

Hello!

In this lab our goal was to create a map according to end user needs by establishing a visual hierarchy to emphasize important features of our map and to effectively contrast map features in order to imply importance. We did this by implementing figure-ground, contrast, and balance, in order to create a harmonious organization and presentation of our map elements.

My Map

My Process:
 

I used the TOC in ArcMap to organize my symbols and map elements more effectively. I placed the school symbology at the top of my layer, to not overlap them with less important elements. I properly symbolized and sized them in order to stand out on the map. Next, I placed my roads in rank order: Interstate, US Highway, State Highway, Major Streets, DC Streets, and Ward 7 Streets. With decreasing rank, I decreased the width line by half a point to a point. Also, the non-major roads were given a lighter color line in order to avoid a conglomerate of bold colors. Additionally, I clipped out the non-major roads and schools that are not inclusive to the Ward 7 area. This helped to emphasize the importance of the Ward 7 area by decluttering its surroundings. Next in place was parks and surface water. Surface water was made a duller blue in order to not be too contrasting with my overall theme.  Last are the neighborhoods, neighborhood clusters, and DC boundary. I used greens in order to create a distinct figure-ground. I emphasized importance on my legend, scale bar, inset map, and map title by making them proportionately larger and putting them in empty map space. I deemphasized the source data, cartographer’s info, date, and inset map titles by making them smaller.

Last, I used Adobe Illustrator solely for typography. There, I made my map title, inset map titles, cartographer information, source information, date, and labeling for the Potomac River.

Typography

Hello!

In this lab we made a basic map of Florida, focused in on the southern tip and the Keys, in ArcMap and then exported it in an AI extension to continue the rest of the lab in Adobe Illustrator. There, we were tested on the typography guidelines we learned from reading chapter 11 in our textbook. We were to correctly label and locate certain Keys, cities, water bodies, and parks & city features. We were required to use previous knowledge and experience with AI to also add in other features, such as essential map elements, a color scheme, an inset map, and 3 personal customizations.

My Map:
This is a map that shows certain water bodies, keys, parks, city features, and cities of the Florida Keys. I used ArcMap to create the basic map, inset map, and scale bar. Then, I exported my map with an ai extension and continued my work in Adobe Illustrator. There, I added in all the required features, used unique symbology for each one, correctly labeled them, and further customized by using three different fonts and colors to distinguish them from one another. I also added the blue background to indicate the ocean surrounding the islands. I made my legend in AI with the rectangular tool and included the same symbols as used for my features. I added a simple border to give it an enclosed and finished look.

Introduction to Adobe Illustrator

Hello!

In this lab we were asked to create and export a basic map from ArcGIS to use in Adobe Illustrator. Our objectives in AI were to learn the basic tools, utilize the AI help features, change the basic map elements in AI, utilize a script in AI to improve map features, and to show our competency in the lab through a written process summary. Below is my map.

Map Backstory and Objectives: 

We were to create a map to be published (hypothetically) in a children's encyclopedia. The map should contain information on major city locations, the state capital, counties, and surface water features of the state of Florida.  The map needed to include an image or text box with only three of the following (cartographers choice): a state flag, state seal, state flower, state animal, or state nickname. It needed a subtle background color, supporting color theme, and border. Also, we had to utilize a script in order to change the symbology of the major cities and capitol on the map and on the legend. Lastly, it needed the basic map elements incorporated.

My Process:

I created the basic map of Florida in ArcGIS with the data provided from this weeks lesson module. I had to add in the surface water features that were missing on the map by going into the Categories tab, clicking unique values, and going through and selecting the Add Values items I needed. I added in Lakes, Streams, and Swamps or Marsh. I finished up the basic map by adding a North Arrow, Legend, and Scale Bar. I exported it to my S drive with an AI extension, at 200 dpi, and closed out the program.

Next, I ran the AI program and opened the AI image file I just created in ArcGIS.  I looked at my Layers Panel and reorganized the layers accordingly, to avoid future overlap. The next step on the lab guide was to change the symbology of the cities, so I un-grouped each city individually by dragging them out of their group layer to a position just above, but still in the same layer. After ungrouping, I selected a new symbol from the Symbol Library and inserted it into the desired layer panel by using the Place Symbol Instance Tool. After inserting the symbol, I highlighted all the cities and the symbol using the CTRL key. Additionally, I had to click the Click To Target function beside each item in order for the script to run. After a successful script run, I did the same process to change the symbol for the state capital and to change the symbols on my legend to match. The rest of my time was spent adding images through the copy and paste tool under the Edit tab and rearranging my layers to avoid overlap. I added the background color through the use of the Rectangle Tool, then double clicking the color wheel to add color. I used the Elliptical Tool in the same way to create my 'sun' in the top left corner of the map. I utilized red arrows from the Symbol Library and text boxes to point to the major cities I chose label. Lastly, I added a border through the Brush Definition drop-down menu and previewed border choices by dragging and dropping them onto the map.

Key tools I used: Shift to proportionately re-size images and other objects, CTRL to select items, Symbols Library, Layers Panel, Rectangle Tool, Type Tool, Fill Tool, and a lot of clicking around!

My Experience:

This was my first experience with AI and it was quite challenging. I had some previous experience with Adobe Photoshop, years ago, and that small amount of knowledge kept me sane. I see issues with my map, after the fact, that I hope to not make in future maps. This was a good learning experience, and now that I have dabbled around in it, I will be better prepared for future map making. 

Map Critique

Hello!

In this lab we were required to pick out two map examples, one of a well designed map and one of a poorly designed map. We were to give a critique to both maps with scholarly insight and assessment. Here are my map choices and my assessments.

Well-designed: 

Assessment: I like this map because it makes a hard concept easy to understand. A forecaster could say, “Expect AQI levels of 150 for today”, but without a visual guide to help the general public understand what those levels mean it would be hard for someone without knowledge in that area to comprehend the information broadcasted. A person with no previous knowledge could see the color levels and easily deduce that the red days are worse than the green days, considering this format is used in many other areas, like weather forecasting.

This map utilizes Commandment 1: Map Substantial Information, Commandment 3: Effectively Label Maps, and Commandment 4: Minimize Map Crap. 1: The information provided was not overwhelmingly scientific and is easy for someone with a high school education to read and understand. Also, there is not a lot of information crammed into the map to explain its purpose. 4: The data is kept in a simplistic, yet comprehensible format. There is not an overwhelming amount of side data included. 3: The symbols and fonts used were effective in understanding the map. The data is clear and concise and does not stray away in the design used to portray it.

This map is aesthetic to me because it is set on a neutral background, the colors of the bars stand out against the background, and the data location is easy to compare back and forth between the scales.

Poorly Designed:

Assessment:This map was probably drawn by a local (non-welcome center guide) and is hopefully not used as a directional guide. It lacks a sense of direction, scale, and data.  This map might make sense to another local, but it definitely does not meet the aim of properly directing a tourist in the right direction.

It violates Commandment 6: Evaluate your map. This map was hastily drawn, or lazily, and needs an aesthetic makeover. It violates Commandment 1: Map Substantial Information. No important information is being presented on this map. The hotel’s distance and location is unknowable. And it violates Commandment 2: The proportions are exaggerated, making the distance and locations inaccurate.

This map needs a new layout, a legend, a scale, titles, and additional information about the hotels in the area. It should be redone with an actual image of the street view of Barcelona, have the hotels appropriately highlighted with approximate distance from the start location listed in a legend, and perhaps include how many stars the hotel has received on reviews as side data.

Introduction

Hi class!

My name is Priscilla Woodrow. I recently moved to the Pensacola area from Oklahoma and am adjusting quite well, though I do miss the wide open plains sometimes. I dont have any children and am not married, but I do have four fur babies (two cats, two dogs), and they are a handful as is. Last May I graduated from the University of Oklahoma with a BA in anthropology. I focused mainly in archaeology and biological anthropology and minored in classics. Now I am a full time student here at UWF, go Argos! 

I initially learned about GIS through some self done research while writing my capstone paper and afterward became very interested in its applications in archaeology. I have always been fond of archaeology and was excited to discover this program while perusing grad school options. I feel like this program is what I needed to help me stand out in the crowd of new grads and continuing professionals. As a newbie to the topic, I am excited to hear about my fellow classmates experiences in GIS and the careers you all have chosen.

http://arcg.is/1mDznRu  <---- my story map