SAMImageDifference Task

This task performs a type of image change detection known as spectral angle difference. It determines the spectral similarity between the Time 1 image spectra and the Time 2 image spectra for every pixel. Each pixel spectrum is represented by a vector in space whose dimensionality is equal to the number of bands. The task calculates the angle between the two vectors. The smaller the angle, the more similar the two spectra.

Before running this task, ensure that the two input images have the same number of bands and the same spatial dimensions. Use the BANDS parameter to the SubsetRaster task to define spectral subsets, if needed. Also use the ImageIntersection task to ensure that the two images have the same dimensions, projection, and pixel size.

Example

This example performs a SAM image difference change detection on two co-registered Sentinel-2 multispectral images. The images are before and after a flood event along the Mala River in Peru in 2017. They have the same number of bands, columns, and rows; no preprocessing is necessary.

The source files are available from our ENVI Tutorials web page. Click the Sentinel link to download the .zip file to your machine, then unzip the files. The files you will use in this example are located in the S2A_MalaRiver folder of the download. Update the file references in the example with the correct locations.

; Start the application

e = ENVI()

; Open input files

File1 = 'MalaRiver_2017-02-20.dat'

Raster1 = e.OpenRaster(File1)

File2 = 'MalaRiver_2017-03-12.dat'

Raster2 = e.OpenRaster(File2)

; Get the task from the catalog of ENVITasks

Task = ENVITask('SAMImageDifference')

; Define task inputs

Task.INPUT_RASTER1 = Raster1

Task.INPUT_RASTER2 = Raster2

; Run the task

Task.Execute

; Get the collection of data objects currently

; available in the Data Manager

DataColl = e.Data

; Add the output to the data manager

DataColl.Add, Task.OUTPUT_RASTER

; Display the result

View = e.GetView()

Layer = View.CreateLayer(Task.OUTPUT_RASTER)

See More Examples below.

Syntax

Result = ENVITask('SAMImageDifference')

Input parameters (Set, Get): INPUT_RASTER1, INPUT_RASTER2, OUTPUT_RASTER_URI

Output parameters (Get only): OUTPUT_RASTER

Parameters marked as "Set" are those that you can set to specific values. You can also retrieve their current values any time. Parameters marked as "Get" are those whose values you can retrieve but not set.

Input Parameters

INPUT_RASTER1 (required)

Specify a multiband raster representing the earliest time.

INPUT_RASTER2 (required)

Specify a multiband raster representing the latest time.

OUTPUT_RASTER_URI (optional)

Specify a string with the fully qualified filename and path of the associated OUTPUT_RASTER.

If you do not specify this parameter, the associated OUTPUT raster will not be created.
If you do not specify this parameter, or set it to an exclamation symbol (!), ENVI creates a temporary file.
If you set it to the hash symbol (#), ENVI creates a file in the temporary directory, but this file will not be deleted when ENVI closes.

Output Parameters

OUTPUT_RASTER

This is a reference to the output raster of filetype ENVI.

Methods

Execute

Parameter

ParameterNames

Properties

More Examples

This example performs a SAM image difference change detection between a Landsat TM image from 1985 and a Landsat 8 image from 2020. It shows the effects of urban sprawl in Las Vegas, Nevada over a 35-year period. Because the number of bands is different between the two images, the example uses the SubsetRaster task to create a spectral subset of the Landsat 8 image. The example also uses the ImageIntersection task to ensure that the two images cover the same geographic extent and that they have the same spatial dimensions.

The source files are available from our ENVI Tutorials web page. Click the Landsat Case Studies link to download the .zip file to your machine, then unzip the files. The files you will use in this example are located in the TimeSeries folder of the download. Update the file references in the example with the correct locations.

; Start the application

e = ENVI()

; Open a Landsat TM image

File1 = 'LasVegasMay1985.dat'

Raster1 = e.OpenRaster(File1)

; Open a Landsat 8 image

File2 = 'LasVegasMay2020.dat'

Raster2 = e.OpenRaster(File2)

; Create a spectral subset of the Landsat 8 image that

; omits the coastal aerosol band, so that the bands match

; those of the Landsat TM image (Raster1)

Time2SubsetTask = ENVITask('SubsetRaster')

Time2SubsetTask.INPUT_RASTER = Raster2

Time2SubsetTask.BANDS = [1,2,3,4,5,6]

Time2SubsetTask.Execute

; Run the image intersection task so that the spatial dimensions

; are the same between the two rasters

ImageIntersectionTask = ENVITask('ImageIntersection')

ImageIntersectionTask.INPUT_RASTER1 = Raster1

ImageIntersectionTask.INPUT_RASTER2 = Time2SubsetTask.OUTPUT_RASTER

ImageIntersectionTask.Execute

; Run the SAM image difference task

Task = ENVITask('SAMImageDifference')

Task.INPUT_RASTER1 = ImageIntersectionTask.OUTPUT_RASTER1

Task.INPUT_RASTER2 = ImageIntersectionTask.OUTPUT_RASTER2

Task.OUTPUT_RASTER_URI = e.GetTemporaryFilename()

Task.Execute

; Get the collection of data objects currently

; available in the Data Manager

DataColl = e.Data

; Add the output to the data manager

DataColl.Add, Task.OUTPUT_RASTER

; Display the result

View = e.GetView()

Layer = View.CreateLayer(Task.OUTPUT_RASTER)

View.Zoom, 0.4

Version History

ENVI 5.5

Introduced