Remote Sensing Lab 4

When working with satellite images in remote sensing getting the perfect image can be hard to do. There are many things that interfere with the image and distort it or block the part of the image that you are most interested in. This lab is all about different ways to fix problems or process images so that they are more useful and easier to interpret. The five techniques included in this lab are creating a subset, image fusion, haze reduction, using an interpretation key and resampling.

The first technique of creating a subset is quite simple to do but can be very helpful when looking at an image. Most satellite images cover a very large area and if you are only interested in a little specific area of the image you can use this tool extract that area and get rid of the rest of the image. There are multiple ways of doing this but I am going to explain what I think is the easiest method. You open the image that you are working with and insert something called a inquire box. You can drag this box to the part of image you are interested in and make it any shape and size to contain what you want. You then go to the menu and click create subset which will take the part of the image that is in that box and save it as its own image. Below I have a whole image and the subset that I extracted from it.

Original Image with inquire box.

Subset 

Image fusion is used to enhance the quality of one image by fusing it or combining it with another image. The technique in this lab is called pan sharpen. You take a reflective image and fuse it with a panchromatic image and this will increase the detail of the reflective image. The reason this works is because the reflective image has a spatial resolution of 30 meters and the panchromatic is 15 meters, so the panchromatic has smaller pixel size and shows more detail. When you fuse the two images together the reflective image takes on the spatial resolution of the panchromatic image so it now has a spatial resolution of 15 meters instead of the original 30 and will show more detail. You can then zoom in further on the image without it becoming distorted and it will be easier to distinguish features of the image.

Pan Sharpened Image

As I mentioned above there are many of things that can get in the way of the getting a perfect image and viewing the part of an image you are trying to view. One of these things is haze. In the image it looks like clouds but in most cases it isn't. It is important to reduce the amount of haze in an image possible because it will most likely hinder your ability to interpret the image correctly. Using a tool called haze reduction you can remove most of the haze in an image so that it can be more easily interpreted. In the program ERDAS all you have to do is click a couple of things and you can see below how much of a difference using this tool can make. 

Before Haze Removal

After Haze Removal

There may be times where just looking at a satellite image isn't enough to interpret the image. Using an image interpretation key can be very helpful. In ERDAS you have the ability to link the image you are looking at with Google Earth. By doing this you can look at the remotely sensed image and the same area in Google Earth at the same time. This is very helpful, especially when it comes to zooming in on the image. In Google Earth the detail of the image is much greater because it is a high resolution image. There are also labels, road networks and many other items that can be used as reference points. The Google Earth image is also in true natural color that is seen in real life which can be helpful because many satellite images are not in true natural color.

Reflective Image of Eau Claire Area

Google Earth Image or Interpretation Key

The last technique called resampling and it used to increase or decrease pixel size in an image depending on what is needed to interpret that image. This is also a fairly simple operation. You open the image you want to work with in ERDAS and go into the spatial options of the image. You can than increase or decrease the pixel size by simply typing in what you would like it changed to. In this lab I took an image and changed the pixel size from 30x30 meters to 20x20 meters. Increasing the pixel size is called resample down and decreasing the pixel size is resample up.

Resample Up Image from 30x30 to 20x20

Sources:
http://www.google.com/earth/

Earth Resources Observation and Science Center, United States Geological Survey
ERDAS Image 2013