Monday, April 28, 2014

Remote Sensing Lab 7


The main goal of this lab was to develop my skills in connection with photogrammetric tasks on aerial photographs and satellite images. In particular this lab lays out and helps us understand the mathematical side of calculating photographic scales, measurement of areas and perimeters of different features, and calculating relief displacement. Another skill that is introduced and explained in this lab was stereoscopy and performing orthorectification on satellite images. By the end of the lab I was able to perform difficult and complex photogrammetric tasks.

The first thing I did in the lab was to calculate the scale of a vertical aerial photograph.
I did this buy measuring between two points on the photo with a ruler and comparing that to the real life distance between those two points. Once I know both of those distances all I had to do is take the real life distance and divide it by the distance I measured on the photo. This calculation gives you the scale of the photo. There is another method to do this as well. This method uses focal length of the camera, the altitude at which the photo was taken and the elevation of the place the image is taken. To find the scale using this method you take the photo length and divide it by the altitude minus the elevation.

We can also use aerial photos to find area and perimeters of large land features. In this case I found the area and perimeter of a large lagoon. I did this by using method called digitizing. All this is taking a tool and tracing the outside of the lagoon and the program Erdas Imagine calculates the area and perimeter for you. 

The next thing I did was to calculate relief displacement in an image from an objects height. In the lab I found the displacement of a smoke stack. In order to do this I needed to know the is the height of the tower in real life which you by taking its height in the image and multiplying that by the scale, the height from which the photo was taken, and the distance between the principle point and the top of the tower. Once you know these things you take the height of the object and multiply it time the distance from the principle point to the top of the object. You then divide that number by the height the photo was taken from and that gives you the displacement or tilt inward or outward the object has. If the displacement is a positive number you move the top of the object towards the principle point to correct and the opposite for negative values.

The second part of the lab was about stereoscopy. The main idea of this section was taking two 2D photos and combining them to create one 3D photo. The 3D photo is called an Anaglyph. 2D images only have x and y coordinates but by combining a photo with a DEM or digital elevation model you can add that z coordinate system which gives you the 3D effect.

This is the anaglyph. If you use 3D glasses you will see the different elevation features contained in the image.
The last part of the lab was about orthorectification. This process is quite time consuming but the results you get are very accurate. The whole point is to get two images to match up spatially and be spatially accurate. You do this by using ground control points just like in previous lab exercises but in this method there are way more GCPs which increases the accuracy. In previous exercises I was only correcting the x and y errors this method allows you to correct x, y and z errors. This process is quite difficult to explain so I will not go into too much detail but the basic of idea is that you use one image to correct for the x and y errors and then a second image or DEM to correct for the z errors. Below I have the before and after images of the technique. It is very obvious how well this method works in spatial correction.
These are two images before they are corrected. You can see how far off the same places in each photo are.
 
This is a slider shot of the two photos after they have been corrected you can see how well every land feature matches up.
This is the corrected image as well.

Sources:
Erdas Imagine 2013

No comments:

Post a Comment