SPECL

Description

SPECL creates a spectral classification from ground-reflectance data. The algorithm is a spectral-rule classification that creates a quality layer for use with atmospheric-correction (ATCOR) products. You can also use the quality layer for mosaicking or otherwise creating composite images. For a list of supported sensors, see Supported sensors.

Parameters

Name	Type	Caption	Length	Value range
FILI*	String	Input image	1 - 192
DBIC	Integer	Input channels	0 - 6	1 -
SRCBGD	String	Source background value	0 - 192	Default: FILE
FILO*	String	Spectral classification	1 - 192
FTYPE	String	Output file type	0 - 4	Default: PIX
FOPTIONS	String	Output file options	0 - 64

* Required parameter

Parameter descriptions

FILI

The name of the input image from a supported sensor. The input must be ground-reflectance data (ATCOR output).

DBIC

The list of input channels to process. Each channel you specify must exist in the input data. By default, blue, green, red, NIR, SWIR, and, optionally, SWIR1 are processed based on the wavelength sequence in the metadata.

If the input file does not contain metadata, and the number of channels is:

Equal to the number of sensor bands, you need not specify a value for this parameter. SPECL will map the first channel to the blue band, the second to the green band, and so on. To verify the expected number of bands for each sensor, check the sensor files available in the PCIHOME\atcor\cal\ folder of your CATALYST Professional installation.
Greater than the number of bands for the selected sensor, you must specify a value for this parameter. For example, if the sensor is Landsat-7, and the input file has all the reflective bands from Landsat; that is, it has six channels containing bands 1,2,3,4,5, and 7, specify this parameter as DBIC=1,2,3,4,5,6.

If the input file contains the wavelength metadata for each channel, you need not specify a value for this parameter.

This parameter is optional.

Ranges of channels or segments can be specified with negative values. For example, {1,-4,10} is internally expanded to {1,2,3,4,10}. When you are not specifying a range in this way, only 48 numbers can be specified explicitly.

SRCBGD

The pixels in the source image to consider as background (NoData). In general, SPECL processes pixels considered NoData in a specific way.

The available options for processing NoData pixels are as follows:

FILE: Reads the NoData value from the NO_DATA_VALUE metadata of the input file. The file-level metadata tag is used as the default for each channel. Channel-level tags, when available, override the default. When metadata does not exist, all pixels of the input are considered valid.
0: Each pixel, in each channel, having a value of zero is considered NoData.
NONE: Each pixel, in each channel, is considered valid.
<value>: Each pixel, in each channel, having the specified value is considered NoData.
FILE [, <value>]: Same as FILE, but defines the NoData value for each channel when metadata does not exist.
For example, the default "FILE, 0" specifies that SPECL uses metadata. If the metadata is unavailable, pixels with a value of zero are considered NoData.

Note: You can specify multiple values by using a comma-delimited list. The first value is applied to the first channel, the second value to the second channel, and so on. If you specify fewer values than the number of input channels, the last value is repeated for all remaining channels. If you specify more values than the number of input channels, the extra values are ignored.

FILO

The name of the output file to which to write the computed spectral classification. The file name you specify must not already exist. The output file will contain one 16-bit signed (16S) channel and a pseudocolor table (PCT) layer.

FTYPE

The format of the output file. The format must be a GDB-supported type.

The following formats, among others, are supported:

PIX: PCIDSK format (default)
TIF: Tagged Image File Format
JP2: JPEG 2000 format

For a complete list of GDB-recognized file types, see GDB-supported file formats.

FOPTIONS

The options to use when creating the output file, which are specific to each format. For example, with some formats, you can select compression schemes, subtypes, and more.

This parameter is optional; that is, you need not specify any options.

For a complete list of GDB-recognized file types, including the available options for each, see GDB-supported file formats.

Details

SPECL creates a spectral classification from the bands of ground-reflectance data. By default, blue, green, red, NIR, SWIR, and, optionally, SWIR1 are processed based on the wavelength sequence in the metadata.

The SWIR band has a wavelength of 1.5\u00e2\u20ac\u201c1.8 microns. The SWIR1 band has wavelength of 2.1\u00e2\u20ac\u201c2.35 microns.

This function created spectral classified 16S image and pseudo-color segment associated with it.

Spectral classification creates the following classes based on ground-reflectance data.

Invalid	100
Snow	3,000
Cloud	1,000
Bright Soil	7,000
Dark Soil	5,000
Average Vegetation	15,000
Bright Vegetation	16,000
Dark Vegetation	14,000
Yellow Vegetation	13,000
Mix Vegetation	12,000
Dry Vegetation	10,000
Sparse Vegetation	11,000
Asphalt/Dark Sand	6,000
Sand/Bare Soil/Cloud	8,000
Bright Sand	9,000
Water Turbid	4,000
Water Clear	4,300
Water over Sand	4,700

SPECL supports imagery in any GDB-supported format. For more information about GDB-supported formats, see GDB-supported file formats.

Supported sensors

Spectral classification can be processed for the following sensors:

Landsat-4 TM
Landsat-5 TM
Landsat-8
Landsat-7 ETM+
ALI
SAC-C
Sentinel-2
WorldView-3

Example

Calculate a spectral classification based on ground-reflectance image: Landsat-8, ATCORCorrected_l8.pix

EASI>fili =	"ATCORCorrected_l8.pix"
EASI>dbic =                   ! based on metadata
EASI>srcbgd = ""
EASI>filo = "spectral_classification.pix"
EASI>ftype = ""
EASI>foption = ""

EASI>run SPECL

References

Chander, G.; Markham, B.; Helder, D. Summary of Current Radiometric Calibration Coefficients for Landsat MSS, TM, ETM+ and EO-1 ALI Sensors. Remote Sensing of Environment, 113, 893-903.

Environments	PYTHON :: EASI :: MODELER
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