Module 7 - Google Earth

     This final module focused on creating Google Earth maps and tours, as well as converting ArcGIS maps to the KML format. Starting off with a surface water feature layer, I used the "Layer to KML" geoprocessing tool to convert my map into a .kmz file for use in Google Earth. I then imported my converted file as well as the other provided .kmz files into Google Earth.

        I then created a tour of South Florida using the "Record a Tour" button through placemarks I added. I had some trouble navigating Google Earth as I am used to the inverse x and y camera controls.

Module 6 - Isarithmic Mapping

    For this module we were tasked to create an isarithmic map of Washington State's precipitation. An isarithmic map is used to depict smooth, continuous data such as elevation or precipitation. We were also shown the difference between Continuous Tone and Hypsometric Tinting for shading isarithmic maps.

     This map uses Hypsometric Tinting to assist in visualizing the zones between the precipitation contour lines. This allows for better visualization of the ten classes. We would use continuous tone to depict data if we wanted to visualize more precise variations.

    We can see in this map that the eastern side of the state receives remarkably less precipitation then the rest of the state, most likely due to the rain-shadow effect of the higher elevation mountains to the west.

Module 5 - Choropleth Mapping

     This week's module had us create a choropleth map of population density as well as a proportional symbol map of wine consumption by capita. For this map, I chose a purple color scheme because it is associated with luxury (wine) and it can also represent wine and grapes itself. The wine symbols are graduated symbols with 5 classes. 

     This module was challenging as I had issues finding a vector I liked for the wine consumption symbology. I ended up creating my own wine glass vectors using a phone app. I also struggled with lag in the ArcGIS Pro program, especially when I needed to adjust the symbology of layers or when I needed to adjust the country labels. 

    To create the Balkan countries' outline I selected the countries and exported them as a new feature. Then I used the 'Merge Tool' to merge them into a singular polygon. I chose the Natural Breaks classification method as I found that the data was naturally clustered and contained outliers. 

Module 4 - Data Classification

     This module had us create four map frames using ArcGIS, each with a different data classification type. The objective was for us to learn the differences between the Equal Interval, Quantile, Standard Deviation and Natural Break classification methods. 

    The Equal Interval classification method makes sure that the classes are split into equal ranges by using equal intervals. This method’s equal intervals allows for easier relative comparisons. The drawback is that the number of observations in each range will differ depending on the dataset, making it sensitive to outliers, which could be misleading.

    The Quantile classification method distributes the number of observations into ranges containing an equal number of each. This allows for each range to be equally represented on the map. This method is good at displaying ordinal data and it is less sensitive to outliers. The drawback of this method is that observations with widely different values could be placed into the same range.

     The Standard Deviation classification method is centered around the mean of the dataset, helping display data values that are close or far from the mean. This method is good at displaying variation and identifying outliers. The drawback of this method is that if the data is not nominal, it may not be as effective. 

    The Natural Break classification method helps to minimize the differences between observations and maximizes differences between ranges. This method is good for data with outliers since it considers how observations are clustered. The drawback of this method is that if the data is quite evenly distributed, then it may not represent it accurately.      

 

        

Module 3 - Cartographic Design

     This week's module involved the creation of a map that followed Gestalt's principles. I created a map of Washington D.C.'s Ward 7 public schools using ArcGIS. After adding all of the layers, I had to use the "Clip Tool" to create a layer that only included the D.C. schools located in Ward 7.

    As mentioned above, the objective of this module was for us to understand Gestalt's principles of Visual Hierarchy, Contrast, Figure Ground, and Balance. To establish Visual Hierarchy, I ranked schools based off of their type (High > Middle > Elementary) from large to small points. I also made my data source text size smaller so attention is not drawn away from the main map features.

    To achieve adequate contrast, I made sure to use a contrasting gradient for my point features. I chose bright colors that would stand out against the grays of the map. I made sure that the main roads (interstates, highways, etc.) were a darker gray than the local roads. I also made the background a darker shade than the map.

    To establish Figure-ground I made the Ward 7 area, the main area of interest, a lighter shade than the greater Washington D.C. area. And finally, I incorporated balance by making sure Ward 7 was sized as large as possible. Then I arranged the essential map elements (legend, scale, north arrow, sources) within the empty space in the bottom right corner.

Module 2 - Typography

     This week's module was centered around the typographic guidelines when making a map. The main objectives of this module were to properly label all of the map features in order for them to be distinguishable. We were tasked to depict some of Florida's natural features as well as some of it's county seats. I learned the proper uses of italic font types, as well as how to create annotations from labels in ArcGIS.

    In order to label the "Swamp or Marsh" features I had to change the symbology to "Unique", then used the "Create label classes from symbology..." tool in order to create separate label classes, otherwise the "Lake" and "Stream" features would have been labeled as well. 

    For my customizations I removed all the non-required city points to de-clutter the map (specifically to de-clutter South Florida). I reduced the halo size of the city labels to reduce the contrast of the labels to the base map. I made the “Swamp or Marsh” labels using the “Water – Large” label format and changed the colors to be a brighter green. I made sure that every font used was the same font, Arial, to maintain consistency throughout the map. I made the Tallahassee a red star to highlight its significance as the State Capital.

Module 1 - Map Critique

     For the course's first module, we were tasked to identify good and bad map design principles from example maps provided to us. I chose a largest ancestry by county map as the good map, and a Gulf of Mexico pin map as the poor map to critique. 

    The good map displayed the largest ancestry populations on the county level and by state (via an inset map) qualitatively. The non-contiguous states’ inset maps are placed in a way that makes sense geographically. One-county ancestries are not colored separately, but are instead grouped together in an “other” label so as to not clutter the map with too many colors. The largest ancestry by state inset map helps to illustrate the proportionality of county vs state, which can be seen in Alaska and New York, where a large number of counties of one ancestry does not equate to the largest ancestry population by their states. The title of this map could be more descriptive, “Largest Ancestry by U.S. County” could work better. 

 

    I liked the color choices, the inset maps and the general layout of the legend. The “Other” category in Hawaii requires some distinction as the entire state is labeled the same, but contains different ancestries by county.

    The bad map is a cluttered pin map. There are too many pins displayed, and there is no indication as to what this map is supposed to depict. The only information we have is that it is a map of the northeastern Gulf of Mexico. This map needs a title and the essential map elements such as a legend and scale. They could use different symbology to depict the data, perhaps using polygons and displaying them quantitatively using a color gradient instead of using pins would help to de-clutter this map. If polygons do not suit the data type, then dividing the map into multiple maps by pin type could work better.

 

GIS5007: Computer Cartography Introductory Post

My name is Keanu, I was born and raised in Suriname and I am a Dutch-English bilingual. I have a Bachelor's degree in Biological Science, obtained from Florida State University in Tallahassee. I am currently employed full time with the Florida DEP's Division of Environmental Assessment and Restoration as an Environmental Specialist I, where I assist in monitoring the state's water quality.

I joined the GIS Graduate Program because I wanted to tie in the experience I have gained in the environmental field along with my computer skills. I hope to achieve a graduate certificate in GIS, or perhaps further my studies to obtain a Master's degree.

 Please find a link to my story map here: https://arcg.is/1LDnvC