Reese's GIS Expedition

     This week, in the fifth and final Photo Interpretation and Remote Sensing lab, it was about supervised and unsupervised classification. This lab is the last one for this course, as the next two weeks will be used for the final paper, however, the skills in this lab will be used extensively to finish the final paper.       The first part of the lab had us recode an image with unsupervised classification. This had us change the image first, so we could then manually select pixels and change them to one of five classifications. That being trees, grass, shadows, buildings or mixed. This took some time, and the lab showed us different ways to compare the image in ERDAS, as some pixels were mixed. An example of this was that some pixels on a roof were the same color as grass, these were made into mixed classification. Also, with each pixel changed, they were given an indicator for what classification they were. This was useful, as in the next step, we h...

     This week, in the fourth Photo Interpretation and Remote Sensing lab, it was about spatial enhancement, multispectral data, and band indices.      This lab was a continuation of learning to use ERDAS, but also to utilize it more and make more image maps. It first started with us finding and utilizing data from Glovis. The lab ran us through the steps to collect a specific image of Northwest Florida, using specific satellites, specific locations, and the data/year. Next, we used ERDAS to convert the file we downloaded to make it usable in ERDAS and ArcGIS.      The next part of the lab had us going more in depth with using different filters to sharpen or smooth the mapped images. This was done using lowpass, highpass, sharpen in ERDAS, as well as mean and range in ArcGIS. These filters are important as they can more broadly define or sharpen features for us to analyze. This also led to using the histogram metadata  of the image to fi...

     This week, in the third Photo Interpretation and Remote Sensing lab, was an introduction in using ERDAS imaging and Digital Data.       The first part of the lab had us learn on how to calculate wavelength, frequency, and energy of EMR. Although we do not need to calculate them for remote sensing, it is good to learn and understand it. This had us use the Maxwell’s wave theory (C = λν) and the Planck Relation (Q = hν). With the calculations brushed up on, we then opened ERDAS.      In ERDAS, we went through the steps to learn and utilize the program. These were minor things like how to zoom in and out, to fitting the layers to the window. It was expanded on when looked at our raster options for adding images, as well as navigating them and adding more windows to look at more data. This even extends to the map we made in the lab. As you can see below it is a mixture of ERDAS and ArcGIS pro. This is because ERDAS is not the best when ...