Lab 7 - Photogrammetry

In this lab exercise we explored photogrammetric tasks on remotely sensed images.  The lab worked with skills in photographic scale, measurement and relief displacement.

For the first part of the lab we calculated scale on a verticle photograph.  Using a ruler, I calculated the scale of the photograph below.

I determined the scale of the photograph was 1:40,000.

. 2.70 in / 8822.47 ft  = 2.70 in / 105869.64 in = 1:39210.98 = 1:40000

 152mm / (20000ft – 796ft) = .50ft / 19235ft = 1:38470 = 1:40000

In the second part of the lab I used the same areal photograph in Erdas Imagine to measure some of the features. First, I calculated the area of the lagoon, then the perimeter, using the digitizing tool in Erdas.

Area = 38.0290 hectares

                   = 93.9716 acres

  Perimeter = 4070.87 meters

                             = 2.5295 miles

I then calculated the relief displacement:

(105.9ft x 10.3 in) / 3980ft = 105.9ft x .86ft / 3980 ft = 0.023 ft

 

In the next part of the lab I used ground control points to show a 3-dimensional perspective of Eau Claire in Erdas Imagine. I did this by generating an anaglyph of the Eau Claire area and found the following results in the output image.

The image clearly represents elevation.  It appears that the darker places in the image represent higher elevation and the lower spots represent higher elevation.  You can tell there are noticeable differences in areas that are different types of land, for example you can see that highly populated areas and areas that are unpopulated seem to stand out somewhat.  The rivers are light in color because they are lower in elevation and the hills are darker in color due to their high elevation.

These features are slightly different from reality.  You can tell that some of the areas like the more heavily populated areas and the heavily vegetated areas seem to have elevations that may not be exactly accurate.  When you zoom in you can tell that there are some specs and areas that do not look natural.  The elevation in higher and more hilly areas seems somewhat exadurated.

Factors that may have caused some difference in the anaglyph could be related to what the anaglyph pick up from the image.  The presence of man-made structures and densely populated areas may have an effect on how the elevation looks.  Also, the amount of ground cover could have an effect.  There is also a large difference in the spatial resolution between the input image and the DEM.  We also increased the vertical exaggeration before making the anaglyph.

In the next part of the lab I orthorectified an image in Erdas Imagine with the used of ground control points.  Below is a screen shot of the two orthorectified images I produced.

In terms of the spatial accuracy, the two orthorectified images match up fairly well.  When zoomed out, you can see a dark line separating the two images and they do not appear perfectly seamless, but when you zoom into the middle of the boundary on the images you can see that they fit together fairly well and the locations of the features seem to match up nicely.  The most noticeable difference at the boundaries is the difference in tone between the two images.  Some areas in the overlapped portion of the image appear darker in color, for tones of grey and dark grey, than they do on the ortho_pan.img.  At the bottom of the overlapped image there is a small gap divided by a black line of pixels that looks like it might cause some problems with spatial accuracy, like slight differences in the positions of common features.

Works Cited:

NASA Landsat Program, 2003, Landsat ETM+, SLC-Off, USGS, Sioux Falls, 2013.