M5 Lab: Choropleth Mapping

This weeks lab required the creation of a choropleth map visualizing the population density and wine consumption in Europe. Population density has been symbolized by using a graduated color scheme from light blue to purple, and wine consumption per capita has been symbolized using graduated symbols (small to large and light to dark green). We were tasked with choosing between graduated or proportional symbols, I chose graduate as the proportional symbols blocked many of the smaller European countries from view. To isolate the specific countries I wanted to symbolize and label, which varied between the primary and inset map, the data exclusion section of the symbology window was used and a query was written to omit unnecessary or redundant data. The graduated symbols used to represent wine consumption were sent through the Feature to Point tool which allowed my to move their individual positions. Similarly the country labels were converted to annotation so they could be positioned. Smaller countries required the addition of leader lines to their labels. After adding all essential map elements the legend was converted into a graphic so I could position each element, including the population density choropleth symbols being aligned for continuity of data. Everything was designed using ArcGIS Pro.

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M1 Lab: Map Critique

This modules lesson topic was the history of cartography and appropriate map design principles. The lab for this module involved looking through many maps to find one well-designed map and one poorly-designed maps in an effort to develop our own individual cartographic design styles that align with the design principles. My two maps and evaluation are as follows. Map Evaluation Template Well-designed map: Synopsis: This map shows the six Wildlife Management Area Game Zones in South Carolina. It can be used Wildlife management professionals or hunters. I think the data to ink ratio has been nearly maximized. The zones being numbered outside the legend is redundant but makes the map easier to read at a glance. There is nothing misleading, the data is substantial, and clutter is minimized to the essentials. For these reasons I think this is a well-designed map. Answer the following questions for the well-designed map: General ▪ ...

Lab 5: M 2.2 Interpolation

This weeks module focused on identifying the best interpolation method for modeling the air quality over Tampa Bay. Four methods were tested using the same set of sample points Thiessen, Inverse Weighted Distance (IDW), Tensioned Spline (seen above), Regularized Spline. Thiessen Interpolation assigns all cells in the raster with the value of the nearest sample point. IDW calculates the value of all cells by considered multiple sample points nearby and giving closer points a higher weight than further points. Both Spline methods create a smooth surface over the sample points but the regularized version creates a smooth curvature regardless of the range of values in the sample meaning cell values can end up both above and below the minimum and maximum values found in the sample. The tension model attempts to fix this by constricted the curvature of values to the ranges found in the sample points.

GIS 6005 - Module 4

Above is a choropleth map of the population change percentage in North Dakota counties between 2010 and 2014. The colors were chosen to intuitively indicate bad (red) for population decline and good (blue) for a population increase. The legend patches were snapped together to give them an appearance of continuous color that mimic the continuous data in the dataset.

GIS Portfolio - Michael Malone

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