GIS5027 Module 4: Spatial Enhancement, Multispectral Data, and Band Indices

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This week's module was on Spatial Enhancement, Multispectral Data, and Band Indices. I've never had to alter imagery when it comes to its spatial or spectral resolution, so this was very intriguing to learn but also a bit overwhelming at times trying to take it in for the first time. I'm sure in time, as I get exposed to these concepts more, I will become more confident doing these kind of image enhancements or alterations in the future.

We first began by learning how to retrieve aerial imagery. I find that this can sometimes be the hardest part of a project. Locating the data or imagery needed can truly be half the battle. I am grateful that this lab gives us those resources and walks us through how to download imagery. If we don't have the data or images needed to conduct an analysis, then accomplishing the goal or finishing a project would be impossible. I will definitely be keeping these sources in mind for future projects, including the final for this course!

Additionally, we focused on spatially enhancing imagery by passing filters on it, including low, high, and even sharpening the image. We were able to see for ourselves how each type of filter would change our ability to notice patterns or how certain features would change in the image from one filter to the next. We then learned how important it is to read imagery histograms and understanding pixel values. Certain peaks in a histogram are indicators to the user that a feature has a high-frequency of occurrence in the imagery or that its radiation is a particular bandwidth.

The map deliverable challenged us to locate 3 features that fulfilled the description requirements given to us. Utilizing our knowledge on band combinations, we also had to showcase these features in our map in a way that makes the features standout. As shown below, I selected 3 areas in Washington State that fell under the requested criteria. The first was Puget Sound, which was a dark waterbody -- I knew to look for the darkest areas of the image due to the description's pixel value landed in the lower range, indicating dark values. The second feature found was the Olympic Mountains, which were bright white -- the description asked for layers 1-4 to have higher pixel values, which told me that the visible light bands were blown out and should be lighter than the other parts of the imagery. Last was the water feature, where I selected the Port of Tacoma since it had much brighter values for layers 1-3 and somewhat in 4. Definitely switching to a near infrared band combination for the third feature helped tremendously to allow it to standout.

Screenshot of Module 4 lab's Multispectral Analysis on identifying features throughout Washington State. Based on the descriptions provided, I located the following: Puget Sound, Olympic Mountains, and the Port of Tacoma.


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