GISC 7365: Remote Sensing Digital Image Processing
Instructor: Dr. Fang Qiu
Lab Three: Image Metadata, Cursor Operation and Initial Statistics
Part I: Image Metadata.
The data set we will use for this part of the exercise is:
File Name / mi-fl_10-21-88spot.img / Quick ViewLocation / Marco Island, FL /
Altitude 832 km
Sensor / SPOT XS
Spatial / 20 m x 20 m
Temporal / October 21, 1988
Spectral / Band 1 = Green (.50-.59)
Band 2 = Red (.61-.68)
Band 3 = NIR (.79-.89)
Band 4 = Panchromatic (.51-.73)
· Start ERDAS. Open the SPOT XS image of Marco Island, FL (i.e., mi-fl_10-21-88spot.img) in Viewer #1, Click on the Raster Options tab. Display as: True Color, Layers To Colors: Red-3; Green-2; Blue-1, check Clear Display, check Fit to Frame. Then click on OK. You are now looking at a false-color NIR composite of XS Bands 3, 2, 1 (R, G, B).
· In the Viewer #1 window, select Utility - Layer Info. The ImageInfo Viewer is displayed. To get layer info for different bands, you need to click up or down arrows in the ImageInfo Viewer. With each band, certain of the metadata characteristics will change.
· Navigate through the four bands of SPOT XS and answer the following questions:
Fill the following table:
Metadata / Band 1Upper Left X
Upper Left Y
Lower Right X
Lower Right Y
Pixel Size in X
Pixel Size in Y
Pixel Size Unit
Projection
Spheroid
Datum
Min
Max
Homework:
Q1: How many pixels are in one band?
· In the ImageInfo Viewer, navigate back to Band 3. Click on the Histogram tab. The image histogram for Band 3 is displayed. In the histogram, move the cursor around. See what happens and what is displayed.
Q2: Why does the histogram have a bimodal distribution?
· Change the band # in the ImageInfo Viewer to see the histogram of each band.
· Click on the Pixel Data tab, and select Band 1. You will see the individual raw digital numbers for each pixel of the image subset displayed.
Q3: What are the digital numbers for Column 149 (x), Row 165 (y), for each SPOT XS band? What might this object be?
· Click on File and then select Close to close the ImageInfo Viewer.
Part II: Viewing Pixel Values of a Landsat TM image.
Now we will look at the digital numbers (DNs) for the different bands of Landsat TM. Remember the DNs do not represent reflectance or radiance - they are just the converted digital values of the electromagnetic signal the sensor receives. The data set we are going to use in this part of the exercise is:
File Name / cola_1-15-91tm.img / Quick ViewLocation / Columbia, SC /
RGB=3,2,1
Altitude 705 km
Sensor / Landsat TM
Spatial / 30 m x 30 m
Temporal / January 15, 1991
Spectral / Band 1 = Blue (0.45-.52)
Band 2 = Green (.52-.60
Band 3 = NIR (.76-.90)
· Open the Landsat TM image of Columbia, SC (i.e., cola_1-15-91tm.img). In Viewer #1, Open Raster Layer and select cola_1-15-91tm.img. Click on the Raster Options tab. Display as: True Color, Layers To Color: Red-3; Green-2; Blue-1, check Clear Display, check Fit to Frame. Then click on OK. You are now looking at a false-color NIR composite of TM Bands 3, 2, 1 (R, G, B).
· In the Viewer #1 window, select Utility and then Inquire Cursor. Moving the crosshair cursor over the image: To move the cursor, use the lbm and drag the center of the crosshair cursor. You can also use the arrows in the Inquire Cursor dialog to move the crosshair cursor in any pixel increment by clicking on the arrows or by pressing keyboard arrows. The black circle will move the crosshair cursor to the center of the Viewer #1.
· Move the cursor over different land covers and see how the values fluctuate. You may want to get a feel for common pixel values for certain land covers. Answer the following questions.
Q: In the Inquire Cursor dialog, what does the LUT (Lookup Table) value represent?
Q: In the Inquire Cursor View, what does File Pixel represent?
Homework:
Q4: Position the crosshair cursor on a representative pixel and record the actual LUT values in each band for the following features:
Band 1 / Band 2 / Band 3Urban
Water
Forests
· When finished, close the Inquire Cursor dialog.
Part III. Histogram and Contrast Stretching
Image
File Name / murrells-inlet_cams_1997-08-02.img / Quick ViewLocation / Murrells Inlet, SC /
Altitude 1,524 m AGL
Sensor / Calibrated Airborne Multispectral
Scanner (CAMS)
Spatial / 3 x3 m
Temporal / August 2, 1997
Spectral / Band 1 = Blue (.45-.52)
Band 2 = Green (.52-.60)
Band 3 = Red (.60-.63)
Band 4 = Red (.63-.69)
Band 5 = NIR (.69-.76)
Band 6 = NIR (.76-.90)
Band 7 = NIR (1.55-1.75)
Band 8 = MIR (2.08-2.35)
Band 9 = Thermal (10.5-12.5)
Display murrells-inlet_cams_1997-08-02.img in an imagine viewer with the following CIR band selection: RGB = 6, 4, 2. Open the ImageInfo dialog through UtilityàLayer Info menu item. The ImageInfo window displays band, statistics, and map information for the selected channel as well as projection (including elevation) information if the image has been rectified and projected. Choose the band number to view each band individually. Since this image has not been rectified or projected, the Map Info is in file coordinates, not map coordinates (i.e. UTM coordinates) and the Projection Info is blank.
Find and select the button that displays the layer Histogram. The range of the x-axis consists of brightness values from 0 to 255 (corresponding to 8-bits; 0 is black and 255 is bright white). The y-axis starts at 0 and increases upwards, showing the total number of pixels that are being placed into each x-axis range from 0 to 255. You can query the histogram by moving the cursor into the window displaying the histogram. Roam around inside the graph and notice that the cursor arrow becomes a cross. The x- and y-axis values are displayed for the center cross location within the histogram. The red line down the middle represents the mean value of the histogram. Note that changing the layer in the ImageInfo dialog will change the histogram as well.
Now close the ImageInfo window and leave the CIR image displayed in the Viewer. Now click RasteràContrastàGeneral Contrast. In the Contrast Adjust window set Method selection to Standard Deviations. Notice that the default standard deviation setting to view images is 2.0. Change this number of the standard deviations to 4.0 and then click Apply in that window and then click Apply All in the Breakpoint Editor. Notice the changes that occur in the image. When you close the View Window, do NOT save your contrast (i.e. changes).
Recreate each of the histograms for band 1, 2, 4, and 6, and briefly interpret the general characteristics of each band's histogram based on your knowledge of the electromagnetic spectrum. Write down the highest frequency represented, minimum, maximum, and the mean value for each band.
Home Work:
Q5: What happens to the image when the Standard Deviation is changed to 4.0? Why?
o Hint: Page 270 (Jensen’s book) on Percentage Linear and Standard Deviation Contrast Stretching.
Now change the number for the standard deviations to 1.0 and click Apply in both menu windows.
Q6: What happens to the image when the Standard Deviation is changed to 1.0? Why?
Part IV. Introduction to Spatial Modeler
Images
cola_ikonos_2000_ms.img2000 IKONOS
MultiSpectral Data
Spatial Resolution : 4 X 4 m
Georeferenced to : UTM
Layer 1 Band 1 = Blue (.45-.52)
Layer 2 Band 2 = Green (.52-.60)
Layer 3 Band 3 = Red (.63-.69)
Layer 4 Band 4 = NIR (.76-.90)
Begin by opening the Spatial Modeler menu by selecting the Modeler icon in the Imagine icon panel. Review the function of each of the Model Maker's tools before going on.
Description of the Model Maker ToolsUse this tool to select items on the Model Maker page. Once selected, these graphics (or text) can be moved or deleted. Click and drag a selection box to select multiple elements. Multiple selected elements can be dragged to a new location as a unit. You can also use the arrow to double click on any of the graphics below to further define their contents.
Creates a raster object, which is a single or layer-set of raster data typically used to contain or manipulate data from image files.
Places a vector object, which is usually an Arc/Info coverage or an Annotation layer.
Creates a matrix object, which is a set of numbers arranged in a fixed number of rows and columns in a two-dimensional array. Matrices may be used to store numbers such as convolution kernels or neighborhood definitions.
Creates a table object, which is a series of numeric values or character strings. A table has one column and a fixed number of rows. Tables are typically used to store columns from an attribute table, or a list of values which pertain to individual layers of a raster layer-set.
Creates a scalar object, which is simply a single numeric value.
Creates a function definition, which are written and used in the Model Maker to operate on the objects. The function definition is an expression (like "a + b + c") that defines your input. You can use a variety of mathematical, statistical, Boolean, neighborhood, and other functions, plus the input objects that you set up, to write function definitions.
Use this tool to connect objects and functions together . Click and drag from one graphic to another to connect them in the order they are to be processed in the model. To delete a connection, simply click and drag in the opposite direction (from the output to the input).
Creates descriptive text to make your models readable. The Text String dialog is opened when you click on this tool.
1. Create a binary image to separate water from upland
· Now select the Model Maker button in the Spatial Modeler menu. Wait for the Model Maker dialog box and the model tools to appear. Select the raster object tool and place a raster object in the model window (towards the top of the window). It will have a question mark as a title for now, but you will assign the input raster file later. Repeat the process and place a second raster icon in the window (near the bottom center). If you make a mistake, use the Edit menu to cut the selected mistake out of the model.
· Now select the function tool and place a function symbol near the center of the model window. Use the connect tool to connect the raster object on top to the function definition symbol by selecting a point inside the top raster icon and dragging a line to the center of the function symbol. Release the mouse and a connection arrow should appear. Now connect the function symbol to the lower raster object. The resulting function should look somewhat like the model depicted below:
· Select one of the IKONOS bands that you think is the best to separate water from upland. Then select an appropriate brightness value for the separation. Now you will assign the input raster file. Double click the upper raster object, then you get a new window (Raster window) like this:
· Then select the file, cola_ikonos_2000_ms.img, and click ok. Now double click the function definition symbol (a circle), and you get a new window (Function Definition window) like this:
· The function to be used in the separation should be something similar to this:
"EITHER the value that you want to assign (e.g., 1) IF (the selected band < your selected brightness value (e.g. 20) ) OR the value that you want to assign (e.g., 0) OTHERWISE"
· This function means that the pixels with the brightness values below 20 will have value 1 and the other pixels will have value 0. Thus, you will get a binary file that consists of 0 and 1. You can select the "EITHER" function in the Conditional Functions (upper right in the window).
· Finally, you will assign the output file. Double click the lower raster object, and you get a new window like this:
· Determine the name and property of your output raster. Note that data type is set to "Unsigned 1-bit" in the above picture. You only need 2 values (0 and 1; it should be changed if you select other numbers in the function definition), and you don't want the output file of large size.
· Run your model (click run button in the process menu or just clickicon) and open your output file in a new viewer.
Homework:
Q7: Which band did you select? Why did you select this band?
Q8: What brightness value did you select for the separation?What factors might affect the selection? Print screen your result, and paste it on your word file.
Part V. Computation of Image Statistics with Spatial Modeler
Images
cola_etm_2001.imgObtained on Oct. 3, 2001
Landsat ETM+ Data
Spatial Resolution : 28.5 X 28.5 m
Georeferenced to : UTM
Layer 1 Band 1 = Blue (.450-.515)
Layer 2 Band 2 = Green (.525-.605)
Layer 3 Band 3 = Red (.630-.690)
Layer 4 Band 4 = NIR (.750-.900)
Layer 5 Band 5 = MIR (1.55-1.75)
Layer 6 Band 7 = MIR (2.08-2.35)
In Part V, you will compute several image statistics with spatial modeler.
Design the Spatial Model that computes the skewness and kurtosis of cola_etm_2001.img band 1.
· Before designing the spatial model, please read the textbook. Then, design the spatial model that compute the skewness of cola_etm_2001.img band 1. The resulting function should look somewhat like the model depicted below: