Europe: Men, Women, Wine

 

 

This week our task involved using what we learned last week about classification methods, then choosing an appropriate classification for each of three maps of Europe to show population density, males as a percentage of the population, and females as a percentage of the population.  We then added data on wine consumption per capita.

 

This was done in ArcMap.  After creating three data frames and adding the European Population data provided in the lab, I selected the appropriate Field Value, chose "Graduated Colors", and made layers for the assigned map topics.  Each had to be classified, and an appropriate scheme had to be chosen. 

 

Sequential color ramps in red and green classify male and female population percentages into 5 classes.  The contrasting colors work well next to each other, and 5 classes make the variation of color within the ramp easy to interpret. I chose a grey color ramp for the population density, and created 6 classes - the dark tones really stand out, which becomes even more important when the Wine Consumption symbols were added.  Proportional symbols were best suited to showing wine consumption per capita, creating an overall visual pattern that is easy to interpret.

 

Although I didn't have time to experiment with it this time, I look forward to making some customized color ramps sometime thanks to some tips from Lucas.

Lab 6: Projections Part II

This map is the result of a huge number of steps and an enormous learning curve.  We learned how to access data online, download it, import it into ArcMap, and work with it to make sure all spatial references were defined.  One of the last steps was to make sure there was a common coordinate system and projection.  Many of the layers were in a different projection (Albers), it was necessary to reproject them so that they lined up correctly. 

Another important step was undertaken in Excel, where a formula was used to convert lat./long. with degrees/min./sec.  into decimal degrees.  Then the file, which specified the location of petroleum storage tanks in a monitoring program, was imported into ArcMap and saved as a shapefile.  Again, reprojection was necessary to make the STCM sites show up correctly.

Once the main map was constructed, the process of "owning my map" began.  I added two insert maps to show the location of the two aerial quads within Escambia County, and of Escambia County within Florida.  Because of the long shape of the quad map and the lack of white space on that map, I thought I'd place several of the other map elements on the right for balance. 

This was the most difficult and time-consuming lab so far, and completing it makes me feel like I have accomplished quite a lot.

Lab 6: Four Data Classification Methods

 

 

 

This is an example of how different classification methods produce different results with the same data.  Here we see four possible ways of looking at the percentage of people over 65 in Escambia County, Florida.  While there are similarities among them all, each has its own spin on the information.

 

The Lab required that we create data frames of the same information, presented using the Natural Breaks, Equal Interval, Quantile, and Standard Deviation classification methods, then choose which one best represented the data and explain why.

 

To begin, I added the Escambia County shapefile to the first dataframe, then created 3 more dataframes and dragged the same shapefile into each one.  I renamed them according to each of the 4 classification methods.  Then I went to each layer's properties, chose the Symbology tab, and chose the Field Value PCT_65ABV to get the data about the percentage of population over 65.  Using Graduated Colors, I chose a ramp that would suit the data, ranging from light to dark.   I then selected one of the Classification types we were assigned, making sure there were 5 classes.  When the labels were created I formatted them to 2 decimal places. 

 

Once I had all the required data frames, I switched to Layout view and "owned my map" by including the usual required elements, and using the design concepts we have learned over the past few weeks.  At this point I realized the color ramp I had chosen for Standard Deviation didn't match the data - it went from light to dark, not reflecting the increased values as you move away from the mean.  I went back and chose a different one that has a light color for the mean, and darker colors at either limit.

 

After looking at all 4 classification methods, I decided the Standard Deviation method suited the data best.  The color scheme makes it clear where there is an average percentage of people over 65, and where there are far more and far fewer.  

Spatial Statistics Lab

The lab for Week 5 took us into the world of spatial statistics.  The Esri course we completed introduced topics that focused on looking at spatial relationships within a dataset, identifying patterns, and making choices about which analysis tools to use based on trends in the data.  Exploring the data is the first step.

Using a map of Europe showing weather monitoring stations, with temperature as the data to be analyzed, I looked at spatial relationships using Geostatistical Analyst tools.  I found the mean and median values, noticing if they were located close to one another.  By examining patterns in a histogram, a normal QQ plot, a Voronoi map, and a semivariogram cloud, I found outliers in the data.  However, overall there was a normal distribution of values. The last part of the process before selecting an appropriate analysis technique is to look at spatial trends.

As a result of exploring the data in these ways, the most appropriate choice for analysis seemed to be geostatistical interpolation.  This was a good fit because the data is normally distributed, stationary, autocorrelated, and has no local trends.  If a weather station needed to predict future temperatures, this technique would be useful.

This lesson probably only showed the tip of the iceberg in terms of what ArcGIS is capable of, and it has gotten me thinking about how it could be used for a particular archaeology project I'd like to do in the future.

Florida Three Ways

This week's lab was based on learning about projections, and using ArcGIS to reproject a data layer to a common Projected Coordinate System.  As the legends for each map indicate, there are slight differences in area between the three projections.

The process of actually making the map was easier this week - practice, practice, practice! My attempt at using Excel to make a chart showing the four area numbers was moderately successful, and certainly neater than using a text box, but lining everything up exactly right eluded me, even after over an hour of fine tuning the font, spacing between numbers, and text size.  The blue box wouldn't resize to exactly where I wanted it to go.  Still, the numbers do line up and the information is useful.

Week 4 Lab: Typography

      Cartography is definitely an art, and this week we focused on one aspect, typography.  With a base map of a portion of the Florida Keys centered around Marathon, we were asked to locate and label a list of geographic places, then complete the map with the usual required elements.  At the same time, we were asked to incorporate what we had learned about typography from Chapter 11 in the text, and from the lecture and tutorial material provided.
      After giving my map a horizontal orientation to match the lateral spread of the Keys, I went online and found all the required places, then made rough labels for each.  I focused on one category at a time, starting with the Keys, then cities, then the three specialized places (airport, park, and country club), and finally the bodies of water.  With each step, I tried to think of how to use font, size and positioning to make clear labels.  The airport, park and country club each got appropriate standard symbols, while the cities had traditional circle symbols.  I tried to be careful not to overlay labels on top of land.  When necessary, I used short lines to connect labels to their locations on the map.  The most challenging part of labeling was learning to get text to follow a path.  It does look nice when the water label follows the contours of the coastline.
      The last several hours were spent finding an appropriate map for the insert.  I kept on finding .gifs or  bitmaps, and all the .jpgs I found were too small so the pixels were enormous and the map was fuzzy.  Finally I got one, and once settled in the corner, it looked good, balanced against the Legend in the diagonal corner.
      I chose a dark blue background, and made the Keys stand out in a light grey-pinkish color.  Learning how to use fill was not easy at first, but I got the hang of it finally. 
      This week's lab was good practice at using CorelDraw, and at using graphic design elements to produce a basic, useful map.
      Seeing the map here, I guess I needed another border around the page.  This isn't what it looked like when I saw it in Paint.  There is room for improvement, but I'm still proud of my efforts, given my extremely limited previous experience in graphic design.

Lab 4: Map Packages

 

This week we explored ArcGIS Online and learned about Map and Tile Packages through two Esri Training Courses. 

 

First we accessed a course about the possibilities of creating and sharing maps using ArcGIS Online.  This will be useful in the future when collaborating with others on a project.

 

Following that introduction, we moved on to a course on creating and sharing map packages (MPKs), at the end of which we were required to create and share two maps, one of climbing points in Yosemite National Park, and the other of a study area for ponderosa pines in the Aguirre Springs drainage region in New Mexico.  We practiced following the standard workflow (planning-data-cartographic design- share) and optimized the Aguirre Springs map package based on who would use the map, and for what specific purposes.  We modified symbols and scale, then shared the MPKs after completing the Item Description which included adding our name to the "Tags" and "Credit" sections.  The Aguirre Springs MPK also included a text tile as an additional document describing the map.

 

 

 

 

These screenshots show the two maps I shared on ArcGIS Online.  The process was challenging, but straightforward using the directions.  As with other courses I have taken through Esri (Intro to ArcGIS and part of another course), the training videos and readings were clearly written and easy to follow, and the exercises were very useful.