Lab 6: M 3.1 Scale & Spatial Data Aggregation

This final lab focused on the way scale and spatial data aggregation can affect the quality of data. The resolution of raster data can greatly affect the variation seen in the final results, reducing the resolution tends to smooth out data resulting in more consistent results through generalization. Altering the scale of vector data can diminish the impact of data depending on the way it's aggregated. Specific data sets that may stand out on their own may be diminished when combined with larger areas making the final impact negligible, this is most famously seen in gerrymandering when political districts are redrawn, sometimes in outlandish fashion, in order to give a specific party a political advantage. This is done by splitting up areas that may contain high density of one party into areas that contain high densities of the opposing party, essentially negating the impact of the opposing votes. The outlandishness of the districts can be quantified using the Polsby-Poplar score which compares the shape of the district to a circle and returns a score between 0 and 1. 0 being the least compact and 1 being the most compact. Below can be seen an example of a district with a low Polsby-Poplar Score.

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GIS 6005 - Module 6

Because the data provided for the above map contained positive and negative values which ArcMap does not support for proportional symbols, the data had to be modified. All states with positive values were exported to a new shapefile and the same was done with states with negative values. This was all that needed done with the positive valued states. However, for the negative valued states a new field needed added to the attribute table and it had to be populated with the absolute value of number of jobs lost to convert them to positive integers. To prepare the data for bivariate visualization classes needed to be made. To do this, three class quantification was applied to each desired variable to divide each into three relatively equal groups. Then all values in the first group of the first variable were classified with an 'A', then the second group was given a 'B', and the third was given a 'C'. the same thing was done with the second variable however 1, 2 ,...

GIS 6005 - Module 1

General: General features were given large black font with a small white halo to increase legibility and visual contrast. The font size is the largest of any font on the relevant feature. The text was placed in a central location without overlapping other labeled features or important data. Water Features: Water features were given dark blue italic serif font. The color chosen was dark enough to allow legibility and contrast with the light blue water background. For the Golden Gate and San Francisco Bay labels they are placed in a central location within the water feature at a level angle with the page. The Lake Merced label was angled to line up and be contained within the lake. Park Names: Park labels were given a dark green color with a thin white halo to allow visibility and contrast while still keeping the labels intuitive. Font size was chosen to keep the labels within the boundaries of the park. However, due to the shape of Lincoln Park the label overhangs how...

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 ▪ ...

GIS Portfolio - Michael Malone

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