Wednesday, December 6, 2017

GIS Portfolio

I kept my portfolio fairly simple... 1) because that is my style and 2) because its very hard for me to highlight or talk about myself.  There were 3 main things I wanted to provide anyone who visits my site with:  a link to my blog, a link to my resume, and a link to the story map that I created for the Fish and Wildlife Service Story Map.  The website made the creation very easy and painless.  It was actually a fun project and hopefully an informative one as well.

Please visit my portfolio here.

Wednesday, November 15, 2017


Since I've been interning with the US Fish and Wildlife in Daphne, AL, I wanted to include them in celebrating GIS Day.  So I created a story map for many of their projects that the Alabama field office has been working on over the past year.  What they do is so critical and important, I just wanted to give them a Kudos for all their hard work via a map!

Check out all that they have been working on here!

Since I couldn't really get a picture of me sharing a link with the office, I've included a picture of my coworker and me helping at the Paint Rock fish assessment (I'm in the black hat... and yes, we definitely needed the waders!)

Sunday, November 12, 2017

Module 10 - Supervised Classification

Our goal was to assign eight, different land use classes to an image of Germantown, Maryland.  To assign these classes, we preformed a supervised classification which involved creating areas of interest that would typify one of the eight classes, looking at signature mean plots, and recoding spectral signatures.  Below is the final product.

Sunday, November 5, 2017

Module 9 - Unsupervised Classification

In ERDAS Imagine, we conducted an unsupervised classification on an aerial image.   We produced 50 classes, reclassified/renamed all 50 into 5 different land types, and then recoded/merged them into their appropriate classes.

Saturday, October 28, 2017

Module 8: Thermal and Multispectral Analysis

Using the composite_2011045 image, I identified the airport at 30.352798 ,-87.319821.  I used the RGB composite Red 3, Green 2, Blue 1.   Regardless of wavelength used, the main runways of the airport appeared as hot stripes with the entire airport appearing only slightly cooler compared to the surrounding area.  The encircling vegetated area and water are a much darker color and cooler.  The linear lines and “x” shape of the airport also helped to identify the airport.

Sunday, October 22, 2017

Module 7: Multspectral Analysis

This week we explored the metadata and spectral characteristics for images in ERDAS and ArcMap.  Through the use of color bands, histograms, and the Inquire tool, I was able to identify 3 separate features from the image tm_00.img

Tuesday, October 17, 2017

Module 6:

Module 6 highlighted the spatial enhancement features of both ERDAS Imagine and ArcMap.  We began by minimizing the striping produced in Landsat 7 images with Fourier Transformation.  Then with spatial effects and focal statistics, refined the image.