GEOG 751: Digital Techniques of Remote Sensing

Exercise #11

Change Detection of Coastal Vegetation

Objectives


Images

Part I. Introduction

Change detection is the process of identifying differences in the state of a feature or phenomenon by observing it at different times. In remote sensing it is useful in land use/land cover change analysis such as monitoring deforestation or vegetation phenology. However, there are many remote sensor system and environmental parameters that must be considered whenever performing change detection. Failure to understand the impact of the various parameters on the change detection process can lead to inaccurate results. Ideally, the remotely sensed data used should be acquired by a remote sensor system that holds temporal, spatial, spectral, and radiometric resolutions constant. For example, changes in radiance values between images may be caused by a number of different factors such as a field which may have different soil moisture content and therefore appear different in two individual images.

Bring up two viewers and display the 1994 and 1996 images and compare them side-by-side in a color infrared composite (RGB=3,2,1). These images depict urban development near the headwaters of the Okatie river in Beaufort County, South Carolina. Visually examine the differences as an initial familiarization technique. It is important to have an idea of where you might expect to see changes. Answer the following questions:

Part II. Change Detection Methods

Of the many change detection methods available, we will be examining two. Ideally, it is important that the analyst has a knowledge of the cultural and biophysical characteristics of the area and preferably some ancillary data. The analyst should also be aware of the different techniques available, including the limitations and advantages of their respective algorithms.

Method 1: Image Differencing in Spatial Modeler

This involves the subtraction of two images and the addition of a constant value to the result. This results in a differenced distribution for each band (see chapter 12 in the textbook).

The Spatial Modeler function in ERDAS Imagine allows the user to graphically create a spatial model and execute it. In this simple example, we will create a change detection model which uses both suncity94.img and suncity96.img as inputs, develops an image differencing algorithm as the function, and creates a change detection image as an output.

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 Tools
Use 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.

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 left 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 and third raster icon in the window (one on the top right and one 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 objects on top to the function symbol by selecting a point inside the top left 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 upper right raster icon to the function symbol, and then the function symbol to the lower raster object. The resulting function should look somewhat like the model depicted below:

Now double click on the top left raster object. The Raster Object dialog box will open. Select suncity94.img as the input and leave all other options in their default state. When this is completed, select OK . The name of the image should now be present below the raster object. Complete the same process for the upper right raster object with suncity96.img as the input.

Next, double click on the function symbol. In the Function Definition window that appears, you will create the image differencing algorithm to be used in this model. In the list showing the available inputs, the number in parentheses corresponds to the individual raster layer. We will be using the full scene image for the calculations and NOT the individual layers. Use the dialog box calculator to create the following algorithm in the blank space in the bottom of the dialog box.

Finally, double click on the bottom raster object, which is your raster model output, and give it an output file name. Again, leave the rest of the selections in their default state. When all objects are labeled and the function definition complete, look at the top of the model window and find the Process option. Run the model by selecting Run. When the model is done processing select OK and exit the Model Maker without saving any changes. In a new viewer, display the model output image using the same RGB layers you used in the first part of the exercise.

Method 2: Multi-Date Visual Change Detection Using Write-Function Memory Insertion

This method involves the use of one band from each date of imagery. Each band is put in an image plane to create a layer stack and the composite is displayed. The corresponding colors represent change in either direction or no change.

Select the Interpreter icon in the Image icon panel and then select the Utilities option. In the menu that appears, select the Layer Stack. We will be creating a layer stack using only the NIR bands in each of the 1994 and 1996 images. When the Layer Stack dialog box appears, only select layer 3 of suncity94.img as the first input file and click Add . This should add the first input image name and path into the blank space above the Add button. Now add the 1996 NIR band to the image by selecting layer 3 of the suncity96.img in the input file space. After you have specified an output file name, leave the rest of the information in its default state and click OK. Wait until the processing is complete and then display the output image in true color mode. Assign layer 1 to red, layer 2 to green, and blue to either layer 1 or 2 (Note: 1:2:2 seems to be provide the most clearly defined change areas). After the image is displayed, go to Raster - Band Combinations and turn off the blue gun by clicking on the button next to the word Blue. This combination leaves you with just the red (1994) and green (1996) layers in the viewer window. The resulting image should have only red, green and yellow shades. Study this image and answer the following questions:

To finish this exercise, create and label a simple map composition showing the two original images (1994 and 1996) and the two change detection method images.





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Last Modified: January 16, 2006