Module 4 - Spatial Enhancement, Multispectral Data, and Band Indices


    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 find the pixel values. This was especially important as if you’re trying to find a certain range of data, you can look in the bands and see the spikes in their pixel values. 

    The rest of the lab before the map making part, covered changing the spectral characteristics. This was done by changing the bands of RGB to make new colored versions, like false color IR or false natural color. This then had us go on to directly compare a few images with other views. This expanded the knowledge on ERDAS more for us to undertake the map part.

    With the final part of the lab, we had to find three specific features, and to do so, we had to utilize what we had learned in the lab. 

    In the first map, the feature we had to find where layer four had a pixel value around 12-18. To do this, I used the greyscale with layer four. In doing so, I used the breakpoint editor tool to find the values I was looking for, which ended up being the river water. I chose to make it false natural color as it made the water pop out against the land.  

    In the second map, the feature we had to find was an area where layers 1-4 had a pixel value of ~200 and layers 5 and 6 with pixel values of 9-11. I had changed the image's bands to a false color IR to find this location and noted that the mountains were snowcapped. When using the inquire tool, I was able to see that layers 1-4 had values around 200 and that layers 5 and 6 were in the 9-11 range. I confirmed this by comparing with other band combinations and the breakpoint editor. With it confirmed I kept it in in false color IR as the snow contrasted with the red. 

    In the third map, the feature we had to find was an area of water where the pixel values of layers 1-3 were bright, but also layer four being semi-bright. Layers 5 and 6 were to remain unchanged. There were two locations on the map that could fulfill these criteria, and I went with the bay as it would balance out against the other maps. With the inquire tool I was able to see that layers 1-3 were bright, and that layer four was bright. I changed the bands and checked with the breakpoint editor to confirm the area. I decided to use true color bands for it, as you can clearly see the different coloration of the bay against the land.

    Overall, this lab was a good expansion on what we had learned last week in ERDAS and using it more to solve problems. I hope it is utilized more with GIS. 


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