GIS4035 - Remote Sensing and Photo Interpretation - Module 10

This supervised land classification map was made mostly in Erdas. It began as a false color image of Germantown, MD. Then the land classification was diminished to 8 different categories. The .img file was then exported to ArcMap, where the finishing touches were applied.

(The color band used was R: 6, G: 4, B: 5, as shown in the bottom right corner.)

GIS4035 - Remote Sensing and Photo Interpretation - Module 9

This map was made in ArcGis. It is an aerial photograph of the Pensacola campus of the University of West Florida. The original aerial was in true color, but was converted to the image above in ERDAS Imagine. After dividing all areas on the map into five separate categories, I calculated their areas in ArcGis, and calculated the percent coverage of each of them manually. 

GIS4035 - Remote Sensing and Photo Interpretation - Module 8

I began this exercise by contemplating the image that would be used for the final section of the project. I decided to use the previously created ETMcomposite image, due to its easy to see variation in land. I right-clicked on the layer in the table of contents, and selected “Properties.” There, I clicked on the Stretched tab and projected the image using a green-red spectrum. This gave me a clear vision of the most energy-radiating features on the map by highlighting them in red, where the deep green color would represent vegetation and low-energy areas.

 I took notice of a red area to the south-west of the main downtown area (at the center of the above image.) Judging by the amount of radiance projected by this area, it seems to be man-made. The surrounding deep-green area could be a hill-side. I went back into the properties and decided to view the image through the near infrared lens by setting the color bands to Red: 4, Green: 2 and Blue: 6. This projection told me pretty much the same thing; the surrounding red area would be natural vegetation, and area to the south would be farm fields. The feature in question, however remains the same high-radiance color of the downtown (blue.)

Once more I went back into properties and selected the following combo: red – 6, green – 4, blue – 7. This made the vegetation appear bright green, and heat bumps in red. It did not really tell me anything new. I decided (for the purpose of aesthetics) to select the Stretched tab and go with the initial spectrum-style color scheme. I selected layer 3 instead of 1, and the contrast between red and green became sharper.

To finalize the project, I went into map view and added the essential map elements. I also added a description and location of my feature, and created a grid. I exported my image as a .jpg, and exited arcmap.