Tuesday, May 2, 2017

GIS 3015 - Final Project


      Well, here is my final post for the Cartography Skills class. The main objective for the final was to recall the methods and techniques learned this semester to autonomously
outline and complete a cartographic analysis and design project.
     
      For the final project I had to pose as an employee of the National Center for Education Statistics at the U.S. Department of Education. My task was to create a map for the Washington Post to go along with their article on high school seniors and college entrance scores. The map has to specifically show 2014 mean composite SAT Scores and students participation rates for the entire United States, including the District of Columbia. The mean composite score is determined by adding the 3 test score sections together. Those sections being Critical Reading, Writing and Mathematics. 

       I chose a combination of choropleth mapping and graduated symbology to display the two data sets on the map. The U,S, map was obtained from the U.S. Census Bureau website and given that the data is compared by area, I chose to use the Albers Equal Area Conic projection. I transferred the data that we were given from a .pdf file to an Excel spreadsheet and added it to ArcMap. I used the Natural Breaks classification method to classify the mean composite score data into five classes.  This method provided enough data points in each break and kept similar values together. As you can see below, the Natural Breaks classification Method was also used on the graduated symbols.  

      Once all the data was classified, I utilize the Gestalt Principles to design my map in Ai. I applied contrast to create figure ground distinction used visual hierarchy to guide the user through the map. 

      Overall, I learned a lot about making maps this semester and I also really enjoyed this class. 






Wednesday, April 19, 2017

Module 12 - Google Earth



      Week 12 is here and all that's left is the Final. There were two parts to this week's lab assignment. In Part 1 of the lab, I had to use the Dot Density map that I created in Lab 10 to create a shareable web map in Google Earth. Google Earth is an interactive, 3D mapping environment that is available for us to download for free. 
      
      In order to create the interactive Dot Density map in Google Earth, I had to convert the original map from Lab 10 to a kmz file.  This was accomplished in ArcMap by utilizing the Map to Kml tool.  I also had to convert the population density layer to kmz by using the Layer to Kml tool.  Once both files were converted, I opened them in Google Earth and made the required changes per the lab instructions.  Below is my Dot Density map overlaid on the Google Earth map.    




      In Part 2 of the lab, I had to create an interactive Google Earth tour. First, I had to create placemarks of the locations that I wanted to visit. Those included: The Miami Metropolitan Area, Downtown Miami, Downtown Fort Lauderdale, Tampa Bay Area, St. Petersburg and Downtown Tampa. Once all the placemarks were created and stored in a file, it was time to start recording. I zoomed in to each location and panned around for a better look. This lab was fun to do and I believe this is definitely the future of Cartography.   

Sunday, April 9, 2017

Module 11 - 3D Mapping



    This weeks Cartography assignment was to explore 3D mapping. The data for the first part of the lab was provided by ESRI.com. The data was used for a training session also produced by ESRI. This weeks lecture consisted of a lecture from an ESRI user conference and a white paper discussing 3D mapping.

    What makes 3D data? In addition to x and y, 3D data incorporates an extra dimension, a Z value.  This value normally represents elevation values such as geological depth or height above sea level. Z-values can also represent density or quantity of a particular attribute. The z-value is typically used to reference height above or below a surface. Buildings will usually have a positive z-value referencing their height whereas wells will have a negative z-value (below ground) showing their depth. The "surface" is usually raster data or a triangulated irregular network (TIN).  


This is an image of the area around Minneapolis-St. Paul showing the Mississippi River running north to south through the terrain. Due to the difference in elevation being only 132 meters, Vertical Exaggeration was used to emphasize the small change in elevation. Vertical exaggeration is a scene property that is applied to all layers in a 3D scene.  



Sunday, April 2, 2017

Module 10 - Dot Mapping


Hi Everyone,

   
    Wow, this semester is flying by. This week's topic was Dot Mapping. That is a mapping method which uses dots representing a particular value to show the distribution of a discrete (raw data total) phenomena across a given region. The main learning objectives for this week were to identify appropriate data types for dot mapping and interpret and understand dot mapping design techniques and guidelines. 
      
    The map below is a population distribution map of Southern Florida. It was exclusively created in ArcMap and the data being mapped was supplied to us from UWF. You will notice that each dot on the map represents 20,000 people and most of the dots are located in urban locations such as the Miami area. You will also notice that the wetlands and other bodies of water serve as limiting factors, thus impeding human settlement.
     
    The first step in this week's lab was to prepare the data. I started by joining data from an Excel spreadsheet to a South Florida shapefile. The spreadsheet contained census data, including population for each county. I then used the "Dot density" symbology option to convey this data. Masking was used to restrict the dots to urban areas and also used to remove dots from any areas of open water. Lastly, I adjusted the dot size and dot value until the dots were beginning to coalesce in areas of greatest density. I hope you enjoy and find my map interesting.







Sunday, March 26, 2017

Module 9 - Flow Line Mapping



    This week we delved into the world of flow line mapping. The objectives for this week's lab were to create a flow line map using proper cartographic and flow map design techniques, calculate proportional line widths using Excel, apply stylistic effects and construct the map solely in Adobe Illustrator. 

    Flow maps are maps which are used to depict the movement of some phenomena between different geographic regions. The movement is usually symbolized using lines of different widths or tones representing the quantity of flow. The map below is a distributive flow map. A distribution map depicts the movement of commodities, people or ideas between geographic regions. In this case, we showed the immigration flow from different regions in the World to the United States in 2007. 

    Since we are showing immigration to the U.S., I chose to use the choropleth map as the main focus point. It shows the percentage of total immigrants settling into each state. The regions shown are Europe, Asia, Oceania, Africa, South America and North America. As you can see by the visual width of the flow lines, the largest flow of immigrants in 2007 came from Asia and the least came from Oceania.

   The main stylistic effect that I used was the drop shadow. I applied the drop shadow to the United States so the it could provide a figure-ground differentiation. It provides a 3D height difference between the land and water. Thus, it enhances the map by separating the United States (including Alaska and Hawaii) from the rest of the map layout. I also added it to the scale bar to show that it was associated with the U.S. choropleth map. I created the choropleth legend by using the rectangle tool and kept the legend swatches contiguous. I also added text above it and the total percentages of immigration below the swatches. Until next week, I hope you enjoy my flow map. 


 



Sunday, March 12, 2017

Module 8 - Isarithmic Mapping


This week we were introduced to Isarithmic mapping. Isarithmic maps depict smooth, continuous phenomena, such as rainfall, barometric pressure and the Earth's topography. The most common form of Isarithmic map is the contour map. The learning objectives for this week were the following:

  • Define an Isarithmic Map
  • Recognize different kinds of Isarithmic maps
  • Understand the appropriate data types for Isarithmic mapping
  • Understand the different interpolation methods
  • Recognize the different symbolization methods
  • Understand the basics of contour lines
  • Interpret basic topographic maps

    The map below represents the average precipitation compiled over a 30 year span for the State of  Washington. The data was collected from known weather stations. Where did the rest of the data originate? It was gathered through a process known as interpolation. Interpolation is the estimation of surface value at unsampled points based on known surface values of surrounding points. The interpolation method applied to the map above was designed by PRISM (Parameter-elevation Relationships on Independent Slopes Model). PRISM is an interpolation method which takes into account major terrain and like factors that influence climate patterns. This process looks at the relationship  between precipitation, elevation and landscape. Then it weighs known data measuring points against all other points and associated terrain when creating a value for these points.    

   This map was created entirely with ArcMap. The first part of the lab consisted of creating a continuous tone map. A continuous tone map does not have any clear delineation between the different shades of color. The map below however, is a hypsometrically tinted map, supplemented with contour lines. The shades of color do not gradually merge into each other, so there is a clear distinction between one band of color and another. Therefore it is easy to associate each band of color with the data class that it represents on the legend.  

   


Sunday, March 5, 2017

Module 7 - Choropleth & Proportional Symbol Mapping


This week's post is about Choropleth mapping, Graduated and Proportional symbols and one of my favorite liquids,Wine. The completed map shows Europe by population density and wine consumption per capita. All the data was provided by UWF and created in ArcMap. I tried to polish the map in Adobe Illustrator but for some reason I had computer issues and had to abort that project.

The learning objectives for this week's assignment consisted of the following;
  • Recognize when a choropleth map should be used
  • Choose an appropriate color scheme for a choropleth map
  • Create appropriate legend for classification scheme and map type
  • Compute varying standardization methods
  • Know what color schemes are appropriate for certain data types
  • Determine what data is used for a proportional symbol map
  • Evaluate what type of proportional/graduated symbol map to use

First, let's define a Choropleth map. A Choropleth map uses differences in shading or coloring within predefined areas to indicate the average values of a property or quantity in those areas.

What is a graduated symbol map? The size of the symbol is proportional to the value of the attribute it symbolizes.Graduated Symbol maps are useful for illustrating quantitative information, such as traffic volume, earthquakes of different magnitudes, and population.

What is a proportional map? Proportional symbol maps scale the size of simple symbols  proportionally to the data value found at that location. The larger the symbol, the "more" of something exists at a location.

What is wine? Wine has been described as the perfect beverage because the grapes contain all the ingredients necessary to create their transformation. 

Below is my completed map. I used a sequential color scheme (lighter to darker) for my population density. I utilized the quantile classification method for this data because it rank orders data and puts equal numbers of observations in each class. I used graduated symbols for wine consumption. They vary in size to show their relative quantitative values. 





Below is my uncompleted attempt at using AI due to technical difficulties.