ENVISpectralAngleMapperClassificationTask

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 ENVITrainingClassificationStatisticsTask to compute the mean spectra from vector layers.

Example

This example uses ENVITrainingClassificationStatisticsTask 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 ENVITrainingClassificationStatisticsTask 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 of the associated OUTPUT_RASTER. If you do not specify this property, or set it to an exclamation symbol (!), a temporary file will be created.

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. The files used in this example are available on the ENVI Resource DVD in the hyperspectral folder or from our website. Download the files CupriteAVIRISSubset.dat and CupriteMineralROIs.xml to a directory on your system.

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()

  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(CupriteRaster)

  roiLayers = !NULL

  FOREACH roi, rois DO $

  roiLayers = [roiLayers, Layer.AddRoi(roi)]

  Layer3 = View.CreateLayer(Task.OUTPUT_RASTER)

END

Version History

ENVI 5.2

Introduced

API Version

3.3