Module 4 - Image Preprocessing : Spatial & Spectral Enhancements and Band Indices

This weeks lab focused on manipulating multispectral images by adjusted which layers are displayed in order to reveal information that is otherwise omitted. The above image shows snowcaps that were identified by searching for a spike in pixel brightness in layers 1-5, a RGB combination of 3 5 4 was used to make the snowcaps contrast heavily with the surrounding area.

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Module 1 Lab: Visual Interpretations

The focus of this lab was to identify features in aerial images using various techniques. The top map used shows features that were identified using one of four methods, pattern, shape and size, association, and shadows. The bottom identified areas using texture and tone from fine to course and light to dark.

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...

GIS Portfolio - Michael Malone

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