Dot Pop!

This weeks class focused on creating a "dot density" map. Essentially, it's a map that has a lot of little dots that represents certain data (in our case, one dot representing many, one-to-many). We had to create a map showing population density in South Florida. Each dot represents 5,000 people. The interesting part about dot mapping with one-to-many dots that they are randomly distributed and do not correspond to geographic points. Though I tried so hard to get the dots to only appear within urban areas, ArcGIS being the ever expensive glitchy  program it is, crashed repeatedly. So I had to make do with excluding the dots from the water layer.

I created this map entirely in ArcGIS, never using AI once (I know, I know, I can't believe it either. It's such a good looking map). The first step in creating any map is figuring out the base layers and the colors to use. I went with natural colors. A blue background (the sea) and a light green for the south Florida area. You'll notice a grayed out section of Florida to the north. This is the county layers from previous modules. I decided to include this layer to create continuity instead of making south Florida look like it had been hacked off and is floating in a nebulous space.It think it's quite clear that the green area is the area we're concerned with. For the water layer, I used a layer from a previous module as opposed to the one given to us. I did this because, the water layer you see is more refined and shows major water sources. The layer given to us for Module 10 was all water and instead of taking hours to clean up that layer, I took the easy route and just clipped this layer! ( I think it was from my Intro to GIS class). For the colors, a dark blue for the lakes and a lighter blue for the streams. As for the wetlands,I went with the ESRI wetland but removed the background color and changed the foreground color to blue. By removing the background color, it allows the wetland feaure to blend into the green of the county layer map. For the urban areas, I went with the color you see. I think it's easy to see on the map while not conflicting with the colors. Essentially, it's not jarring to the eye. I then included an insert map using a US State boundary shape file I had on my computer. Next was the cities. I went with the following cities because I felt they gave the best reference points on either coast. Originally, I was using the city picture to represent the cities on the map, however, when the dots were added, the cities became covered in red dots and it was hard to see not aesthetically pleasing. Instead, I went with the circle dot and turned it blue. It's easier to see when the dots were added. The dots, I decided to go with red. Red is easy to see against blue and green. Also, the red made the dots the most prominent feature.

For the dots, I tried to have them mask by the urban layer. However, every time I attempted to mask it to be only in the urban area, Arc crashed. I tried changing the ordering of the layers. I tried deleting everything and relayer it and masking it different times in different ways. But every time I selected the urban layer and try to mask the dots to only appear there, it crashed. So I had to settle with excluding the water layer. This then inspired me to write a summary about the map (something we've done on other maps in the class and in the intro to GIS course). I wanted to make it clear that the dots are not geographic points. (Not one to one dots). Originally, I went with dots that represented 15,000 people but I felt it wasn't accurate. Instead, I went with each dot representing 5,000 people.

Dot Density map of overall population in South Florida. As the disclaimer explains above, the dots are not geographic points. The map was created entirely in ArcGIS. 

Statistics...ewww but not ewww

This week we worked with STATISTICS statics...actually, despite the use of the word statistics, we worked with a GIS tool that uses statistics to help discern if the given data is displayed or distributed correctly.We used three different scary sounding but easy to use tools (geostatistical analyst) to determine how are data related to each other. For this week, we used an ESRI course. Prior to UWF, I have done a few of the more basic (i.e. FREE) ones and they are dull. Somewhere between the monotone voice of the video and the beyond dry writing, those less than 3 hours of training, seemed like a good day's worth. ESRI makes a great software suite, but they need work in the keeping things lively department.

The primary focus of the lesson (I hope) is determining if the data we have is correct in a statistical sense. i.e. does the data relate to each other correctly. What do I mean correctly? I mean, "normally distributed". Normally distributed means data that when displayed falls along a bell curve. The data shows a logical spatial relationship with each other. In determining the bell curve, we used a histogram which displays a bar graph. If the data is mostly normally distributed, then the bars are displayed with the tallest bar in the center and the remainder creating a pyramid esque look on either side. We then learnt to use a QQ Plot which uses a plot line to show if the data falls along said line. If the data is on or near the plot, then the data is "normally distibuted". In our exercise, we determined that there were a few outliers ( i.e. data that wasn't in line with the majority.) My over all take away was that we used these tools and graphs to figure out if the data we were given is good. Outliers may be the result of bad data entry so to speak or a special phenomenon .

In the exercises, we had to use weather stations in western Europe. Of course, temperature readings in high altitude areas (the Alps) were much colder than other areas. Using the QQ plot and Histogram we found an outlier in Switzerland, Most reported temperatures where somewhere in the winter conditions where as this single station was in the 70s. So there was an obvious problem. The whole exercise was essentially learning to use statistics to figure our if our data is good or not. Bad data used can create issues down the line or at least make a GIS technician's life harder.

The map below shows the distribution of temperature across western Europe. You'll notice an X and a cross, these display the median and mean center of the stations. Then the directional distribution shows the direction in which the stations are statistically distributed. I used a color ramp to help display the temperature range better.

Thinkin' Design: Module 4 Lab GIS 3015

This week's objectives are to use Gestalt's principles in creating a map. We had to use visual hierarchy to help display information. Using VH well creates a balanced map that shows the 

end user the most important information while maintaining the needed geographical references.  

In my map, the first thing to do was to decide the colors I was going to use. I had to make sure the colors provided contrast without impeding balance. Sort of like using the right amount of seasoning

in a meal. Rosemary adds a nice flavor, but if overdone, it can ruin the meal. Again, I went with green. I don't know why but I find myself using this color a lot.  I feel I was able to create a good contrast using green. As you'll notice,  the DC area to the west and south of Ward 7 is lighter than Ward 7. If you look at it, your eyes start pushing towards Ward 7. Those DC areas provide reference without overwhelming the map. Now that your eyes are in Ward 7 (you may also notice that the white  background outside of the DC areas pushes your eyes toward Ward 7) you'll immediately notice the red icons. They jump out and you can quickly discriminate between  the different levels based on their shape. The river, I made a dark blue. Initially, the river was a lighter blue but the bridges blurred into the river and that blur was distracting. The colors were ultimately created in AI. 

Creating the map, I began in ArcGIS. I created the basics there: the symbology, the insert, the roads, etc. With the roads, I added state hwy 295. It's the only highway that cuts through Ward 7 (as far as I could tell). Adding the other highways and interstates didn't make much sense to me because they were outside ward 7 and my scale is around 1:35,000. When I turned those layers on, they would be in the left hand corner or towards the lower left hand side. The insert was easy to make. All you need to do is create a new data frame and place the layers inside that. You can even duplicate the layers (right click, copy). The extent was created by going to the properties and extent tab. I went with a red box. With the legend, I inserted it but that shows all the active layers. So I right clicked, properties and then moved all the items out except the schools. I listed the schools by level by going to the layer, right clicking and going to the symbology tab. In there I created categories based on levels (which were already in the data). I assume ES, MS and SHS were all abbreviations for the various school levels. I edited the labels, removed the heading. I then searched for a good icon. At first, I went with the little red school house icon that was used in the pdf. I decided that I didn't like because, even if you changed the sizes, it was still hard to discriminate. Instead, I went with the icons you see below. They're similar but different. I feel those icons make it easier to know what kind of school you're looking at without going back to the legend to keep checking. After all of that, I exported the mxd to AI. I changed the colors to my "better" greens and added the title. I kept the title inside the map area and created a color pattern (white with black outline) and a drop shadow that would help make it stand out and easy to read. I added a drop shadow t the ward 7 area that I think helps, but it is inconsistent. I added the border by creating a  hollow fill rectangle with a thick gray border. I'm really starting to enjoy using AI (my swearing was considerably less when manipulating layers and figuring out other things). 

The whole time, I was thinking in minimalist terms for everything including the insert map. My take away from the text was keep it simple ( albeit based on the needed information and audience)  

Side notes:

In ArcGIS I used the selection tool to select elements within Ward 7 and then exported that data as a new shape file. I then removed the previous shape file that I didn't need anymore. I did this with the schools and I even did it with the river and parks. I really enjoy using that selection feature. It really helps. 

I'm not too worried that I cut off bits of ward 7 (this is also shown with the extent box in the insert). It helped me make the area  a little bigger without taking any relevant information out. Our design starts with looking at the geography of an area.  It dictates the layout and placement of everything. (well duh right).

I'd like to take a litte time here to discuss alternate GIS programs. I was having connection issues (I need to use a VPN) and so I exported the data to Q-GIS which is already on my PC and played around with it. I found Q Gis to be faster than Arc and the maps look nice as you create them. Ultimately, I abandoned it (mostly because there's a lot to learn in Q-GIS) but this open source suite (along with others) may be worth the time to learn. It's free and seems quite powerful, at least for map making. I'm unsure of it's GIS analysis capabilities. 

Marathon Key; Typography

This week was typography or the process of, well, labeling according to cartographic principles. For this week we had to create a map of Marathon Key to exhibit our understanding of good cartographic typography as we understood it from both the lecture and chapter 11 in our text.  

The tricky part with Marathon Key is that it is not easy to label the required areas via the guidelines. So the use of leader lines was heavily employed. As for the various keys, I placed the text alongside the coast lines. I thought this would make it more apparent and easy to read. Except for Crawl Key, it's such a small feature that I used a leader line. 

I used two font styles. For the cities and keys, I used Casteller and for the title, water, and various places on the key, I used century new gothic. Both fonts are easy to read. For labeling the water features (except for Florida Bay) I went with a white font. This was to help differentiate the feature from the keys and I also enjoyed the aesthetic look of how the text seems to sink into the drop shadow. I used drop shadows to make the features easier on the eyes. Without the shadows, the key itself just bled into the blue. 

I went with a simple color scheme of blue and green. This is more intuitive for most people especially when dealing with an island. It makes it more apparent.  

Also, the island was rotated to be horizontal with the north compass also rotated to reflect the directionality. I did this for two reasons. First it made it easier to work with. I was able to label the features batter and include the basic elements (insert, legend, scale, compass) in a more linear fashion. Because I did this, I went with a north arrow that included east, west and south to make it easier to understand that the map is not true north from bottom up. I went with a simplistic compass. Second, I feel it's easier for the map reader to understand. Admittedly, I may of created too much dead space between the title and the island. 

I attempted to adhere to the principles of topography as outlined in the text and discussed in the lecture. However, I did have a hard time lining up the leader lines with the points. Also, given the lack of land I tried my best to label features such as the keys in the best way possible. I realize there is room for improvement. 

The process was simple. First, I created the map in ArcGIS. I found GIS data made by FDOT so I could include US route 1. The highway shield was created in arc as were the points for the towns. I created the insert by using Florida counties shape file and finding a good scale for it. I used the extent feature in the properties to create the small red box. The labels, legend and tile were all created in AI. 

I created the border by making a new layer that had blue (the background) with a thick grey edge.  I really developed a better sense of the layering and used that to my advantage in making the map. I was mindful of the hierarchy so to speak. 

And that's it in a nutshell. Hope you enjoy.