Remote Sensing Lab 4: Miscellaneous Image Functions 1

Goal
The goal of this Remote Sensing Laboratory Exercise was to crop out an area of interest from a larger satellite image. Also, show how spatial resolution could be optimized to improve visual interpretation usages. Next, we will be introduced to radiometric enhancement techniques in optical images. Next, we will link the satellite images we have been working with to Google Earth. Lastly, we will be introduced to numerous methods of re-sampling satellite images.

Methods
The first part of this lab exercise was to work with sub-setting and using an Inquire box. This method let you pick your area to work with just by dragging a white, or you can change the color to one more visible, box. Next we used the Subset & Chip and Create Subset Image. These tools will basically crop out everything except for the area inside the box. After saving the newly made area into our own folders, we now had a much more easily workable rectangular image.

The rectangle area of the Eau Claire Area after sub-setting original image

The second section of part one was to bring in a shapefile of both Eau Claire and Chippewa Counties. This was done in a similar way as the first section of this part.

Sub-setting of Eau Claire and Chippewa Counties shapefile.

Part two of this laboratory exercise was to work with Image Fusion. In this section we used both false coloring images and a panchromatic image. The first image, ec_cpw_2000.img had a resolution of 30 meters by 30 meters. The panchromatic image was 15 meters by 15 meters. For this part we used the Pan Sharpen tool under the Raster tool section. We then selected Resolution Merge to merge the two images into one high resolution image. The techniques used for this image were multiplicative and nearest neighbor. After the image was ready the two images were linked together to view that the new pan-sharpened image had much better resolution than the original.

Part three of this laboratory exercise was to work with simple radiometric enhancement techniques. This particular techniques worked with was Haze Reduction. Again to get to this tool we accessed the Raster tool tab, Radiometric tab, and selected Haze Reduction. After the tools finished touching up the image, again we compared the two to notice the sharper, less hazy, image.

Part four of this laboratory exercise was to work with linking the image in Erdas to Google Earth. On the tab bar there is a tab called Google Earth. After accessing the tool tab there was a tool called Connect to Google Earth, this tool opened up Google Earth and had the ability to sync the image with Google Earth to provide a new satellite images to view.

The last part of this laboratory exercise was to work with re-sampling, which changes the pixel size. For this we took a image with 30 meter by 30 meter resolution and opened the resample pixel size tool and used two different methods to increase the resolution. One method was Nearest Neighbor, and the other was Bilinear Interpolation to bring the resolution down to 20 meters by 20 meters. Both images created were viewed with the original to see how the resolution improved.

Results
The results of the lab was just a basic understanding of how to use basic remote sensing tools to further our education in the subject to be used in future labs.

Sources
Satellite Images: Earth Resources Observation and Science Center, United States Geological Survey
Shapefile Data: Price Data