SpectralAngleMapperClassification Task

This task performs a Spectral Angle Mapper (SAM) supervised classification. SAM is a physically based spectral classification that uses an n-D angle to match pixels to reference spectra. This task requires an input vector or ROI layer from which mean spectra are computed for all of the records.

Use the TrainingClassificationStatistics task to compute the mean spectra from vector layers.

Example

This example uses the TrainingClassificationStatistics task to compute the mean spectra of each record from a polygon shapefile. It passes the mean spectra to the SAM classification task, which creates a classification image from a QuickBird scene.

; Start the application

e = ENVI()

; Open an input raster and vector

File1 = Filepath('qb_boulder_msi', Subdir=['data'], $

Root_Dir=e.Root_Dir)

Raster = e.OpenRaster(File1)

File2 = Filepath('qb_boulder_msi_vectors.shp', Subdir=['data'], $

Root_Dir=e.Root_Dir)

Vector = e.OpenVector(File2)

; Get training statistics

StatTask = ENVITask('TrainingClassificationStatistics')

StatTask.INPUT_RASTER = Raster

StatTask.INPUT_VECTOR = Vector

StatTask.Execute

; Get the task from the catalog of ENVITasks

Task = ENVITask('SpectralAngleMapperClassification')

; Define inputs

Task.INPUT_RASTER = Raster

Task.MEAN = StatTask.MEAN

; 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 for a code example that uses mean spectra from ROIs as input to SAM classification.

Syntax

Result = ENVITask('SpectralAngleMapperClassification')

Input properties (Set, Get): CLASS_COLORS, CLASS_NAMES, INPUT_RASTER, MEAN, OUTPUT_RASTER_URI, OUTPUT_RULE_RASTER_URI, THRESHOLD_ANGLE

Output properties (Get only): OUTPUT_RASTER, OUTPUT_RULE_RASTER

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

Methods

This task inherits the following methods from ENVITask:

Properties

This task inherits the following properties from ENVITask:

COMMUTE_ON_DOWNSAMPLE

CLASS_COLORS (optional)

This is an array of RGB triplets representing the class colors as defined by the input vector.

CLASS_NAMES (optional)

This is a string array of class names as defined by the input vector.

INPUT_RASTER (required)

Specify a raster on which to perform supervised classification.

MEAN (required)

Specify an array of size [number of bands, number of classes], representing the mean spectra from the input training regions. You can use the TrainingClassificationStatistics task to compute the mean spectra.

OUTPUT_RASTER

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

OUTPUT_RASTER_URI (optional)

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

If you set this property to an asterisk symbol (*), the output raster will be virtual and not written to disk.
If you do not specify this property, the associated output raster will not be created. To force the creation of a temporary file, set this parameter to an exclamation symbol (!).

OUTPUT_RULE_RASTER (optional)

This is a reference to the output rule image of filetype ENVI.

OUTPUT_RULE_RASTER_URI (optional)

Specify a string with the fully qualified filename and path of the associated OUTPUT_RASTER. If you do not specify this property, the associated OUTPUT_RASTER will not be created. To force the creation of a temporary file set the property to an exclamation symbol (!).

THRESHOLD_ANGLE (required)

Specify an array of values in radians between 0 and 1.5708 (π/2). The default value is 1.5708. You can specify a one-element array to use the same threshold value for all classes. Or, specify an n-element array (where n equals the number of classes), with separate threshold values for each class.

More Examples

The following example uses mean spectra from individual ROIs as input to SAM classification. The ROIs represent locations of known mineral types. The input image is an AVIRIS hyperspectral scene of Cuprite, Nevada, USA. files are available from our ENVI Tutorials web page. Click the Hyperspectral link to download the .zip file to your machine, then unzip the files. You will be using the files the files CupriteAVIRISSubset.dat and CupriteMineralROIs.xml.

Copy the following code into a new window of the IDL Editor and save it to a file named CupriteSAMExample.pro.
Change the input data paths to the location of the files on your system.
Compile and run the program.

PRO CupriteSAMExample

COMPILE_OPT IDL2

; Start the application

e = ENVI()

; Select input data

File = 'CupriteAVIRISSubset.dat'

CupriteRaster = e.OpenRaster(File)

ROIFile = 'CupriteMineralROIs.xml'

rois = e.OpenROI(ROIFile)

; Create a mask that includes the ROIs

MeanArray = !NULL

For i=0, N_ELEMENTS(rois)-1 DO BEGIN

ROITask = ENVITask('ROIMaskRaster')

ROITask.DATA_IGNORE_VALUE = 0

ROITask.INPUT_MASK_ROI = rois[i]

ROITask.INPUT_RASTER = CupriteRaster

ROITask.Execute

; Compute the mean from each ROI-masked image

RSTask = ENVITask('RasterStatistics')

RSTask.INPUT_RASTER = ROITask.OUTPUT_RASTER

RSTask.Execute

; Construct an array of mean values from the ROIs

MeanArray = [[MeanArray], [RSTask.MEAN]]

EndFOR

; Run SAM classification

Task = ENVITask('SpectralAngleMapperClassification')

Task.INPUT_RASTER = CupriteRaster

Task.MEAN = MeanArray

Task.OUTPUT_RASTER_URI = e.GetTemporaryFilename()