Geography 338: Remote Sensing: Lab4

Goal and Background:

This lab was designed for students to display their ability to perform multiple functions in regards to remotely sensed images. Such processes include the ability to produce an area of interest (AOI), optimization of radiometric data for the purposes of visual interpretation, radiometric enhancement techniques, ability to link images to Google Earth, resampling of satellite images, image mosaicking, and binary change detection.

Methods

The first section of the lab was designed to was to show the ability to show an area of interest or AOI. This was done in two parts; the first part was to select the area of interest by using the Inquire Box tool to draw a rectangle around an area, in this case it was the Eau Claire area. The second part of this section involved importing a shapefile of both Eau Claire and Chippewa counties. To complete this section I imported a shapefile of both Eau Claire and Chippewa counties and made them translucent so that the image could be seen underneath.

The next section of the lab was to increase the resolution of remotely sensed images. This again was done in multiple parts. The first part of this section involved pan sharpening. To do this I opened two separate viewers in Erdas Image Engine. In the first viewer, I brought in an image of the Eau Claire region and in the second view I brought in an image of the same area only this image was in the panchromatic band. Using the Pan Sharpen tool I used the Nearest Neighbor method of resampling to create a new pan sharpened image. The next section of the lab was to reduce the haze that existed in a remotely sensed image. To do this I used the Haze Reduction tool located under radiometric tools.

Following the section of the lab was to link images in Erdas Image Engine to Google Earth for the purposes of creating a selective key that could aid in image interpretation. To do this, I opened two separate viewers. I brought in an image of the Eau Claire in to the first viewer. In the second viewer, I used the Connect to Google Earth tool to link the viewer to Google Earth. Once Google Earth was brought into the second viewer I synchronized the two viewers together.

I was then tasked with resampling an image of the Eau Claire area using the methods of Nearest Neighbor and Bilinear Interpolation. To do this I used the Resample Pixel Size tool where I changed the dimension of the pixels from 30x30 meters to 15x15 meters. For the first image, I chose to use the Nearest Neighbor method and for the second image I chose the Bilinear Interpolation method creating two new images with the method of Bilinear Interpolation producing a more visually pleasing image.

Following the previous section, I was tasked with mosaicking two images. This was done by using the Mosaic Express and Mosaic Pro tools. The Mosaic Express tool produced a better image with smoother transitions between the two images than that of Mosaic Pro.

The final section of the lab was to show land use changes in the Eau Claire area between 2011 and 1991. I brought in image for each of the years into separate viewers. I then used an image differencing tool to create a new image that displayed the differences between the two images. After looking at the image metadata and histograms to detect where change had occurred in the data. I then created a model that would create a new image displaying the values form the 2011 image from the 1991 image that had changed. I then took the newly produced image and imported it into ArcMap where I overlaid it over an image of the Eau Claire area that I colored light grey to improve the contrast between the two layers.

Results

The Images below show the results of the discussed sections above.