Cartography: Module 10 – Dot Density Mapping

     The last couple of weeks have focused on thematic mapping. Dot density mapping is yet another thematic mapping type and was explored in this week’s assignment. Dot density maps are used when the data is conceptual (raw totals) and is not uniformly distributed within the enumeration unit. The dot is then representative of a particular value and placed where that phenomenon is likely to occur. For instance, a dot can represent a given number of individuals (e.g. 1 dot = 10,000) and placed in a populated region (as opposed to an area that is unlikely to be populated).

     These maps are advantageous in that they are easy to interpret and can convey variations in large quantities of data. It is also easy for the user to recreate the original data by simply counting the dots (unless the map is dense or poorly designed). Dot maps take into account ancillary information thus ensuring dot placement in reasonable, logical areas. They are not without issue as there is a human tendency to underestimate density which may affect the map user’s ability to draw the intended conclusion.

    This week’s map is a population density map of South Florida. It was created entirely within ArcMap. The Symbology tab of the Layer Properties contains all of the options for modification of the dot size, value, and color choice. I experimented with combinations of dot size and value until I landed on I choice I felt appropriately represented the data without too many dots converging in densely populated areas. Masking, also found in the Symbology tab (by way of the Properties button once in the Dot Density option), allowed for placement of dots only within urban areas.

A map of the population density of South Florida as depicted through the use of dots.
Each dot represent 25,000. A handful of cities are included to provide reference. 

     My map displays the population density of South Florida with one dot representing 25,000 people. I colored them a bright pink so they would stand out from the other features of the map. Five cities are included to provide a geographic reference. Water features are categorized by type and urban areas are provided for added context. County boundaries are not included to reduce visual clutter and focus the user’s attention on population clusters. I particularly enjoyed this week's assignment as I got to map an area I am familiar with. I am originally from the Miami/Fort Lauderdale area which is chock-full of people (not to age myself, but a while back I went to high school with about 5,000 other students). It is not surprising that the dot map is most dense in this area. 

Intro to GIS: Week 11 – Vector Analysis

     This week’s assignment introduces modeling tools in ArcGIS. Two tools in particular, the buffer and overlay tools, were used to alter feature classes to display a select portion of data. Additionally, the lab introduces script creation in ArcPy.

     The goal of this exercise is to generate potential camping sites by combining the use of buffers and overlays. The possible campground sites must meet the following criteria simultaneously: must be within 150 meters of a lake, within 500 meters of a river, and within 300 meters of a road. They must also be located outside of conservation areas. Variable distance buffers were applied to the water feature layer to generate the specific buffer regions. Then a set buffer was applied to the roads layer. Lastly, the Union and Erase tools were used to prepare the final zones for potential camp sites. Other skills used included practicing with ArcPy to quickly apply multiple buffer distances to the same layer, the Select by Attributes tool to select features that met the zonal criteria, and converting a layer from multipart to singlepart. 

A map of prospective campground sites chosen to meet specific criteria.
An inset map is included for geographic reference.

     My map shows possible campground sites that fall within (and exclude) the previously mentioned criteria. These requirements are also noted on the map. An inset map with an extent indicator is included to provide a geographic reference. 

Cartography: Module 9 – Flow Line Mapping

     This week continues to examine thematic mapping by way of the flow line map. Flow maps illustrate the movement of phenomena between various locations. The widths of the flow lines are proportional to the value of the data they represent. Typically these maps are used to depict the flow of people or commodities (distributive flow maps) but they can also be used to map networks (network flow maps), radial phenomena (like migration – radial flow maps), continuous phenomena (continuous flow maps), and other information (like telecommunications). This map includes another thematic map type – the choropleth – as well.

     I made a distributive flow map of immigration to the United States by region (continent) from a base map provided as lab content. My map was entirely designed and edited in CorelDraw. The flow lines are of proportional widths to the data. The thicknesses were calculated using a specific formula entered into Excel. I used these calculated values to manually generate flow line width (within the Object Properties tool of Corel).

A distributive flow line map depicting immigration
from continental regions to the United States. 

Design Considerations

     The drop shadow and transparency were the main effect tools used. In tandem, these tools helped the flow lines lift off the page without obscuring geographic information. To simplify the map I placed the name of the immigration region within its flow line. Oceania and the Unknown region had such small flow lines that I opted for a placement above the flow line (whilst trying to keep typography guidelines in mind). The continents are somewhat transparent to create a figure-ground relationship with the choropleth map of the United States (one in which the choropleth becomes the central focus). 

     A contiguous legend is included for the choropleth map and the number of immigrants from each region is represented by its own legend of sorts. I used arrows of the same color as the region they represent to display the raw immigration data. The arrows are of decreasing length from the most immigration for a region (Asia) to the least immigration (Unknown). Here, the drop shadow is used to emphasize this information. 

     The maps are not to scale although attention was paid to keeping them in correct proportions (by using the Shift key while resizing). The projections of both the continents and the United States are also noted. Again, I employed the drop shadow tool for the title. As the map contains a lot of information, I did not want the title to be drowned out. The use of the drop shadow helped to make the title noticeable while not overburdening or detracting from the map.  

Cartography: Module 8 - Isarithmic Mapping

     Isarithmic maps map continuous phenomena, like precipitation. This week the assignment was to produce such a map. The aim was to map precipitation data using two different manners of symbolization, continuous tone and hypsometric tints. Contour lines were then added to a map of our choice. The exercises were carried out entirely in ArcMap. Symbolizing raster data was necessarily introduced as well as the Spatial Analyst tool, Int. My two maps are found below. The first map is the continuous tone map and the second map is the hypsometric tints map. Each map displays a short description of the interpolation method used -- PRISM. As a brief overview, PRISM (Parameter-elevation Relationships on Independent Slopes Model) is an interpolation method that incorporates elevation, other physiographic data, and proximity information when deriving a value for a given pixel (using a climate-elevation regression function). It was a method developed by Chris Daly in 1991 while a Ph.D. student at Oregon State University and serves as a way to mimic the choices climatologists made when deriving maps before digitization.  
     The first map uses continuous tones and contour lines to depict average annual rainfall over several decades for the state of Washington. This symbolization is applied by manipulating the settings in the symbology tab of the layer properties. The standard precipitation color ramp is used. Contour lines were added with the Contour List tool accessed through the Spatial Anlayst toolbox. Contours are set at predetermined values.

An isarithmic map displaying precipitation data symbolized in continuous tones.
A short description of PRISM interpolation is also included. 

      The second map uses hypsometric tinting without contour lines to depict the same precipitation information. This symbolization required an extra processing step before tinting could be applied. I used the Int (Spatial Analyst Tool) to convert the raster values from fractional to whole numbers. This helps to create distinct contours using the new whole number values. Again, from the symbology tab (layer properties) I applied a classification to assign colors to ranges of values. I used a manual classification scheme with 10 classes and the precipitation color ramp. Hillshade effects were used in both maps.

An isarithmic map displaying precipitation data symbolized in hypsometric tints.
A short description of PRISM interpolation is also included. 

Intro to GIS: Weeks 7 & 8 -- Data Search

     This assignment is the culmination of the work I produced over the past several weeks. Thus far, I have learned various skills within each lab such as cartographic design and data projection, as well as searching/downloading GIS data. These skills are put to the test in this week’s assignment through the acquisition, organization, alteration, manipulation, and presentation of GIS data for a given county in Florida.

     I generated three maps for Brevard County, Florida using ArcMap. Each map has a different subset of information portrayed to meet the data requirements of the assignment (that is, particular vector layers, environmental data, and raster data). I tried to organize them in a logical, cohesive manner. I will briefly discuss the process and design of the maps and which skills I reinforced during each preparation.

Map, the First

     I thought it reasonable to include invasive species information with conservation area data since these often coincide in environmental studies. On the left side of the map, water bodies are shown in relation to the habitat conservation areas. On the right side, the locations of various invasive plant species are shown. In the background I have included major roads for context and noted the regional hydrography. To prepare these maps I had to clip various data layers since they originally included information at the state level. Symbology for invasive plants was customized within the layer properties Symbology options. The legends were also customized to fit in limited spaces. For the conservation and hydrography map, I excluded those conservation areas that were not found within the extent of the county (that excluded two priority levels - 5 and 6). Another key process was creating new shapefiles from selections within a layer. For instance, there are a multitude of invasive species in Brevard County. From examining the attribute table and consulting outside resources (check this nifty website out), I decided to only keep ten of the most problematic plant species.       

Map of Brevard County, FL displaying major roads, hydrography,
strategic habitat conservation areas, and a selection
of invasive plant species. 

Map, the Second

     This map shows major cities in Brevard County in relation to parks and recreational facilities. Again, I made new layers from selections based off of certain criteria (excluding towns with no reported population information and parks that were essentially beach access points). For this map I included an inset map of a quarter quadrant. It is also included on the base map. I altered layer transparency in the previous map but for this map I altered the display settings of a raster (a slightly different process). I also included an extent indicator on the base map to emphasize the area from which the quarter quadrant is derived. I designed the legend to fill the majority of the empty space on the right hand side of the map. In a previous lab, Cartography Design (Week 3), we converted labels to annotation so that they could be manipulated. I did just that for this map and also included leader lines since many of the cities are along the coast.  

A map of Brevard County, FL showing various cities along
with parks and recreational areas. A quarter quadrant of the Titusville region
is displayed as an inset with the location of public parks noted.  

Map, the Last but not Least

     The final map is a topographic map of the county. The digital elevation model (DEM) has a 1-arc second resolution (assignment specification). In order to display the data properly I had to project the raster using the Project Raster tool in the Data Management portion of ArcToolbox. I used a diverging color ramp and clipped the DEM to the county boundary. I included an inset map as well as some of the surrounding counties for additional context. The units are noted in the legend. 

A topographic map of Brevard County, FL. 

     The data for this lab was gathered from Florida Geographic Data Library, the Florida Department of Environmental Protection (labins.org), and US Geological Survey. This assignment provided practice in accessing these resources and gaining familiarity with how to access GIS data. While this more time consuming than previous labs, it was fun to bring it all together.