Lab 10: Image Rectification
Image rectification is the process of assigning real world coordinates to a digital image
so that it can be overlaid accurately on a map or other spatial data. Rectification is
essential for effectively using remotely sensed data in a geographic information system
(GIS) because map layers must line up with one another. For example, you may be
interested in using ArcGIS to analyze smoke plumes visible in satellite imagery in
relation to the locations of houses digitized from a paper map. To get the two datasets
to align requires that the satellite image be in the same coordinate system as the house
dataset.
Today you will rectify a Laramie TM image starting with an unrectified version called
larm1unrect.img (in the folder lab10_geom_correction). Copy this image from the
class data directory to your personal directory (H:\). You will assign map coordinates
to the image that are in the UTM map projection—UTM is one (of many) scheme for
projecting a spherical earth onto a flat map. Once you have rectified the image, you will
overlay a roads database (larmroads.shp) that is already in UTM coordinates on the
image to see how they align.
Remember to turn in the worksheet at the end before the next class meeting.
1. Open larm1unrect.img image in a Viewer (assign colors to three bands as you see
fit—You will be using the image to locate road intersections to use for Ground Control
Points [GCPs]). Note that this is a Landsat 5 image, so the bands are different than in
the Landsat 8 images you’ve been working with.
2. Choose the Multispectral tab and in the Transform and Orthocorrect area choose
Control Points. A Set Geometric Model window will open that allows you to choose a
transformation model (this is the mathematical formula that will convert the image
coordinates to real world coordinates based on your GCPs). Scroll down the model list
and choose Polynomial.
A new window will open, along with a dialog box in which you should choose to Collect
Reference Points from “Keyboard Only.”
Yet another dialog box will open. Now you will define the map projection for your
GCPs. Click the Set button and in the resulting window choose UTM for the Projection
Type, GRS 1980 for the Spheroid Name, NAD83(CONUS) for the Datum Name, 13 for
the UTM Zone, and North for the final box (North or South). All of these values are used
to define the projection (coordinate system) that we are using to make the image line
up with other spatial data. They match the projection of the roads data you will use
later. Click OK.
Then click OK to close the previous window.
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A Polynomial Model Properties window will open. For Polynomial Order, choose 1.
(Worksheet question). Then click Close. Now you are left with a tool that you can use
to enter your actual GCP’s.
3. The table below lists the UTM coordinates of ground control points that are
numbered in the image printed on the page just before the worksheet near the end of
these instructions.
Notice that I have drawn in the main roads used for the GCPs so that you can more
easily find them in your image. There are 8 GCPs, numbered 1-8. In the Erdas tool,
there are 3 subwindows that allow you to view the image at various zoom levels, or you
can just zoom into the control point locations in the big window. You can drag the box
around in the window that shows the complete image and it will appear magnified in
the upper right for GCP placement. The first GCP is at the left edge of the image,
equidistant between the two diagonal runways of the Laramie Airport. Drag the zoom
box or zoom in very tight on this feature and then click on the crosshair icon at the top
of the window (a round circle with a crosshair in it). Then carefully click on the zoomed
image at the location of the GCP. A label will appear (GCP #1). Note that you can adjust
the position by dragging the point with your mouse if necessary.
At the bottom of the screen is a table. The table now lists GCP#1 and Erdas has
automatically filled in the X and Y input coordinates. These are the raw image
coordinates (column, row). Eventually, you will type in the UTM coordinates of GCP#1
from the table below under XRef and YRef, but you can do it all at once at the end.
Now find GCP #2 in the image in these lab instructions and use the Erdas tool to place it
in the appropriate place on your image. You will need to use the zoom and pan tools to
locate it. GCP #2 should be placed at the road intersection on the NW corner of the golf
course.
Continue in this fashion until you have place all 8 GCPs.
4. When you have placed all 8 GCPs, you can enter (type in) their corresponding X Ref
and Y Ref values from the table below.
GCP #
1
2
3
4
5
6
7
UTM Easting (XRef)
443800
453486
455049
447099
447010
454025
450075
2
UTM Northing (YRef)
4573516
4574229
4570974
4578183
4568022
4568619
4571797
8
455123
4575935
5. Now you will ask Erdas to perform the transformation. Erdas will develop a
mathematical equation that will convert the raw image coordinates to their
corresponding UTM coordinates for all of the points in the image corresponding to the
GCPs.
Click on the icon at the top of the window that looks like a square with 4 little subsquares of different colors (left of the ruler tool). Provide Erdas with an output file
name for the corrected image (e.g., Laramie_correct.img). For the resample method,
choose Nearest Neighbor (Worksheet question #3). For the output cell size, choose
30.0000 for the x and 30.0000 for the y. Click OK to create a corrected image.
6. Now you will display a roads dataset (larmroads.shp) over your warped image. The
roads are in an ArcView shapefile as a “vector” dataset (lines).
If it isn’t already open, open the rectified (warped) image in a Viewer and the unrectified
image in another 2D View. Open the roads data (larmroads.shp) in the each view (You
can open vector data by clicking on the round button in the upper left corner of the
Erdas window, choosing Open and Vector Layer).
Answer the questions in the worksheet.
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Name________________________________
Lab 10: Geometric Correction
Worksheet
1. Why is a 1st order (polynomial) transform appropriate for geometrically
correcting the Laramie image that we are using?
2. If you were rectifying full TM scene centered over the Wind River mountains,
what type of transformation might you choose and why?
3. Why is the Nearest Neighbor resampling method a good choice for most
remotely sensed data?
4. Paste your rectified image below with the roads overlaid on it. How well do the
shapefile roads line up with the roads that you can see on your rectified
(corrected) TM image?? If they don’t line up, are they off by a lot or a little?
What might cause errors in alignment?
5. How well does the same roads shapefile line up with the unrectified image.
Why?
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