M3 Lab: Cartographic Design

The object of the lab in module 3 was to take the data provided and create a map of the schools in Washington DC's Ward 7. During the design of the map it was required that Gestalt's Principles of Cartographic Design were implemented to accurately display the data while maintaining visual hierarchy

The map above used a thumbtack symbol to represent the schools in the subject area. Both increasing size and a color gradient from least to most intense were used to symbolize that schools from elementary to high school respectively. The red color for the symbols was chosen to visually emphasize the school locations in regard to the basemap. This was an implementation of Gestalt's contrast principle. To reduce school label clutter a table was used (top left) to display the school names with their corresponding identifier. An inset map was used (bottom right) to display Ward 7's national location.

This map was created using ArcGIS Pro. Once all layers in the provided data were added to the map the clip tool was used to isolate the schools in the Ward 7 area from the rest in Washington D.C.. This was the only tool use required to aggregate the data needed however I used the clip tool multiple more times to isolate the parks and roads within Ward 7 so that I could modify them separately from the ones in the rest of D.C.. When symbolizing the roads I used the dissolve tool to remove the plethora of lines that divided the roadways to give them a cleaner look. A gradient color and size thumbtack symbol was added using the symbology pane for the layer. Once I reached my maps desired look by changing the color scheme, I was ready to start making my layout. Two map panes were added, one for the primary map, and one for the inset map (bottom right). Gradient boarders were added to the basemap, legend, inset map, and school identifier table so to enhance their figure-ground relation, improving the visual hierarchy. Finally all essential map elements were added.

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Module 5 - Unsupervised and Supervised Image Classification

This weeks module focused on classifying images using multispectral signatures. Above you can see the completed classified land cover of Germantown, Maryland. To create this image above signatures were collected that correlated to each required feature. Then bands were chosen (R:4 G:6 B:5) that contained the largest separation amongst features to minimize spectral confusion. In the above image roads and urban areas were often confused leading to a much larger area of roads than actually exist. The inset map contains a classification distance map which displays the distance each cell is (spectrally) from the sample points with brighter pixels being further than darker pixels. This indicates that brighter areas have a higher chance of error.

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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