Week 11 - Dot Mapping

This week in GIS4043 we created dot density maps. Dot maps are great for showing the distribution of raw totals of conceptual data, such as for example income distribution or ethnicity within a city. The key here is to keep the enumeration unit small (so census tract areas would be better than a county, which would be better than a state, etc.). The map deliverable for this week shows the population density of southern Florida.

Dot map showing population density of southern Florida.

Technical Details

The dots are meant to be the main focus of the map, so the symbols for my polygon layers (the urban and water areas, and the Florida counties) are in fairly low key pastels. The water and urban area symbols are set to a 45% transparency, and the Florida counties layer is set to 10% transparency. The cities layer isn't transparent, but the symbol is 80% gray as opposed to being solid black. Incidentally the dots showing the population density and the Florida counties come from the same data layer - I just have the symbols separated out into two layers in order to be able to manipulate the map view a bit better.

The dots shown above were generated within ArcMap, under Symbology > Quantities > Dot density. Instead of keeping the default settings I opted to have the dots stay within a fixed location and applied a mask to the data. This mask stipulates that the dots will draw only within an urban area (enter the urban area layer!). Before applying the mask I had messed with the dot size vs. dot value, and eventually settled on a size of 1.87 with each dot representing 25,000 people. I had wanted to keep the dot value within increments of 5,000 and it seemed to me that 25,000 was the best fit while still allowing a reasonable dot size.

Use of the mask was fraught with all kinds of mini-dramas for my poor little laptop. The mask seems to pull on all available computer resources, and when it wasn't getting enough it caused ArcMap to crash! Repeatedly. This became an issue when I wanted to see how a different setting with the mask would look on my map, and also when I wanted to export the image. To get around this I did the following:

• Got over my need to see minor changes to the mask displayed on the whole map. It just wasn't worth it, and I found that those little boxes in the Symbol settings window were there for a reason.
• I decided to drag and drop a new population density layer onto my original map. To do this I re-created the exact original layer settings (even down to the scale) on a blank map.
• I then converted my original legend to graphics, so that I didn't have to mess with making or editing a new legend once I added my fresh population density layer (yes, ArcMap was that touchy).
• Once everything was in place and with two maps open, I then dragged and dropped the new layer onto the old map. After waiting a few minutes for it to draw I then exported it. Several more minutes later I had the .png file that you see above!

At no time during this process did I do anything else on my computer. And once my new population density layer drew correctly, I closed its source map in order to allocate even more computer resources for the map I was trying to export.

Week 11 - Vector Analysis 2

This week in GIS4043 we wrapped up a two part series on working with vector data. Our deliverable for this week is a map of potential campsites. These potential areas were located using the following modeling tools: buffer analysis, union, and erase. The final map product needed to show the result from applying the modeling tools, using these parameters:

• must be within 300 meters from a road
• must be within 150 meters from a lake or 500 meters from a river
• must not be within a conservation area

View of potential camping areas, as derived from applying various overlay tools.

 Technical Details

The potential camping area polygon is the result of several overlays. First, a buffer analysis was run on the roads and the water layers (300 meters for the roads, and between 150 meters for the lakes and 500 meters for the rivers within the water layer). Once I had my buffer zones identified, I then merged the data together using the union tool. From this I was then able to remove the conservation area locations from the union output by using the erase tool. The result of all this data processing is what you see above.

Within the lab we also ran an additional tool to separate out the polygons - specially, the multipart to singlepart tool. For analysis of each individual area it would be helpful to have the camping area polygons split up within the attribute table, but for visualization purposes I found it more useful to use the multipart polygons. I suppose I could have displayed the singlepart data, but just changed the outline of the polygon to none in order to present a seamless appearance.

The basemap above is ultimately from USGS, as provided via the ESRI basemap service. It's not the best basemap ever as it has labels I don't necessarily want, as well as its own roads and water layers - but it does show a nice hillshade effect and gives a general sense of where the forest is in relation to non-forest land. The basemap I had wanted to use from USGS came in a geo.pdf format, and at this point in time I do not know how to convert that for use within ArcMap (if such a thing is possible) - it's main selling point was that it came with contours. Perhaps for next time...

Week 9 - Flow Line Mapping

For this lab we returned to CorelDraw, as it is the easier option with which to create flow line maps.

Our goal this week was to create a map showing the flow of immigration to the United States in 2007. We we were given two options with which to present our data - either an overall worldview map showing flow into the United States, or to show disembodied continents surrounding the U.S. (still with rates of flow into the U.S.). Either way, the goal was to effectively place curved flow lines without covering up other features. Other map requirements included a choropleth map of the United States showing percentage of immigration per state, and two special stylistic effects applied to the overall map.

The flow map.

Technical Details

Let's start with the main focus of the map - the flow lines! These were created using a Bezier tool; the colors were then changed to reflect their host region, and a drop shadow effect was applied to make them stand out even further. I will admit that I let the idea of working with the Bezier tool get to me - but once I practiced with it several times I kind of got the hang of it... so much so that I incorporated the Bezier tool for my flow line legend.

The drop shadows were only one of my 'special' style effects... the other big one was the extrude effect on the United States. I had wanted my U.S. choropleth map to stand out a bit more and I ultimately decided on using the extrude function. I say ultimately because I had originally started to apply a drop shadow effect... and it didn't work out. Plus I already had drop shadows for my flow lines, so that probably would have been overkill.

To complete the extrude I had to first draw a quick outline of the United States - there was simply too much going on with my map depiction of the U.S. for the tool to even work, and going line by line trying to figure out which one represented the U.S. boundary was not a realistic option. After applying the extrude function the entire eastern seaboard was covered up by the effect. To mitigate this I placed a copy of the U.S. map in a new layer over the original extruded layer. The U.S. still isn't popping out like I'd hoped it would but I suspect I'm on the right path... one day I'll get it!

Other fairly minor effects were applied to the map: text on a path for the flow line legend, different colors for the continents, a two-toned blue circular color gradient for the map background, letter spacing and different outline color for the the region labels, etc. Basically, this map took a while to make and there are still little things I'd like to do with it... but sometimes you just have to know when to say when!

Week 8 - Isarithmic Mapping

This week's lab involved creating isarithmic maps - basically, the kind of flowing line maps that are usually seen with weather-related data. We were tasked to create two maps - each essentially the same, except one shows precipitation data using continuous tones and the other with hypsometric tints. Both maps needed to employ the hillshade effect, and one of the maps needed to show the display with contour lines. A final twist on both these maps was to employ a certain level of craftsmanship - essentially, to own our maps!

The continuous tone map.

The hypsometric map.

Technical Details

I settled on a landscape view, as I felt that would depict the data the best. An overall light gray background was used so that the really important map elements (the map itself and the legend) could further stand out with a plain white background.

The symbology presentation is what is so different about each map. To create a continuous tone map, one uses a stretched symbology, and for this map I had standardized the labels to the nearest multiple of 5 to show the beginning, center, and end of the range. After a few minutes with the legend properties (specifically, modifying the patch settings so the bar wasn't compact) I was able to get my legend to display correctly. What I couldn't do was get the values and color ramp to flip, so that the bar would read from '5' to '260'. Perhaps that's just not the done thing with these types of maps?


To create the hypsometric map I used a classified scheme. This is very similar to what I had done with the choropleth maps, except this was created using a raster file. The end result was still a color ramp being employed for the symbology. Getting the legend to display properly was a bit tricky - not only did I mess with the patch settings but I also needed to mess with how the text for the values displayed as well. This may have been a bit easier if I had a vertical legend display, but I had already set something of a style precedent with my continuous tone map... and in the end I finally got things to work without having to resort to fiddling with it in CorelDraw.

I kept the contour lines for both maps... to my mind each looked flat without it (bad pun, I know). I suppose I could have gotten away with not having contours for the hypsometric map, but after I had seen it with contours... well, why go back? Oddly enough the default color ArcMap gave me for the contours worked out, although I did some experimenting with just about every other color under the sun before realizing it. Sometimes... well, very infrequently... the default settings are good!

Week 7/8 - GIS Data Search

This lab represents our mid-term exam! For this particular project we were each assigned a specific Florida county to map in order to highlight our map creating skills learned thus far. From internet sources we were to gather data for nine required layers:

•  5 vector files (county boundary, cities, public lands, roads, and surface water)
•  2 'environmental' files (choice of either invasive plants, Strategic Habitat Conservation Areas, land cover, or wetlands)
• 2 raster datasets (just one DOQQ, and a DEM file showing our entire county).

From this data we had the option to create up to three maps, as long as the data was displayed appropriately... and all of the data needed to be in the same coordinate system (our choice of UTM or Albers). I settled on two maps, shown below.

Overview of Okeechobee County, Florida.

Conservation efforts in Okeechobee County, Florida.

The process

For me, deciding how to depict the data was the hardest part. I needed a story to put these maps together, so I created one: the maps represent areas of environmental concern in Okeechobee County, particularly around the Kissimmee Prairie Preserve State Park. To keep the flow going between the two maps I used the same types of symbolization for layers that appear on both.

The first map is an overview of Okeechobee County - basically what the county looks like, where the cities and towns are, the major roads, the surface water, where the state park is, and where the county is within the state of Florida. The second map is more of a detailed environmental map, showing the overall location of Strategic Habitat areas, and where the invasive plants are in relation to the Kissimmee Prairie Preserve State Park.

Both maps contain clipped vector data, which were clipped using the Clip (analysis) tool. I had to clip my raster files to the data frame itself (on the first map it was the DEM, and on the second map it was the Strategic Habitat areas)... I had tried to use the Clip (Data Management) tool, which says it's for raster graphic files, but ArcMap flipped out on me and I had to give it up. Oh well, maybe next time!

The labeling within the map frames are a combination of automated labels, labels converted to annotation, and labels I put on the map myself. There was no middle ground with the automatic label wizard, but not having to label everything individually was still nice. 

 My second map was the most complicated in terms of design, as it contains four data frames. In order to get items to stand out I made dropped backgrounds sort of a running theme. While creating the second map it occurred to me that maybe the first overview map was unnecessary... but trying to fit that roads layer somewhere on second map was a challenge I wasn't willing to take on.

So the big project is finished. This is the state of my map making capabilities thus far... I wonder what the final will bring!