Spectral Classification module


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Description


The Spectral Classification module converts optical data to top-of-atmosphere (TOA) reflectance, and then extracts per-pixel features and indices to create a spectral classification.
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Parameters


Name Caption
Input Scenes Input scene folder
Output Folder Output folder
Output File Type Output file type
Output File Options Output file options
Overwrite Results Overwrite existing results
Send Email Email notification settings
DEM Source DEM tile source
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Parameter descriptions

Input Scenes

The path and name of the folder containing multispectral (MS) images to process.

Output Folder

The path and name of the folder to which to write the output files.

If you do not specify a value, the output file is written to the folder specified for Input Scenes.

Output File Type

The format of the output file.

For more information on the supported file formats, see GDB-supported file formats.

Output File Options

The options to apply when creating the output file or files. The available options are specific to the file format; in each case, the default of no options is allowed.

For more information on the options available for the output file type you specify, see GDB-supported file formats.

Overwrite Results

Select this check box to overwrite the existing output files, if any exist. If this check box is left clear, and an output file exists in the relevant folder, the status of the job displays a message informing you of the existence and name of the output file. The message is also written to the event log of the job.

Send Email

If necessary, you can set up CATALYST Enterprise to send an email notification on job start and job completion.

With this check box selected, an email message is sent to each address specified in the Email Addresses box after the job starts and on completion.

You can specify one or more addresses, and each must be separated by a comma or a semi-colon. The email address of the user currently logged in displays by default.

DEM Source

The name of a file or folder containing DEM tiles.

This value may be the name of a single DEM file, the name of a folder containing DEM tiles, or the name of an index.txt file.

If the name of an existing folder is specified, the module reads the folder for a file named index.txt, and a set of DEM raster tiles. The index.txt file lists the DEM files contained in the specified folder and provides information describing each raster tile.

For more information on the format of the index.txt file and specific requirements for the individual DEM tiles, see Format of the DEM index file.

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Details

General job details

Before running this module, the following requirements must be met to ensure the job processes successfully and produces accurate results:

Module details

The algorithm used by the Spectral Classification module is applied according to specific rules to derive spectral indices and features from spectral bands. The features are calculated from several sensors and normalized to allow for cross-sensor comparison.

The spectral bands are converted on the fly to top-of-atmosphere (TOA) reflectance values by using the nominal solar-zenith angle. The values are then used to calculate indices and features including, but not limited to, the following:
  • Tasseled cap
  • Normalized difference vegetation index (NDVI)
  • Haze-optimized transformation (HOT)
  • Modified normalized difference water index (MNDWI)

At the first classification level, only basic features are derived, and a limited number of classes are extracted, such as clouds, water, shadow, vegetation, and bare ground.

At the second level, the shortwave infrared (SWIR) band is required, and basic classes are subdivided into subclasses, such as thick or thin clouds; snow; turbid, green, shallow, or deep water; various types of active and senescent vegetation, and so forth.

The last level uses a cirrus band, if available, to extract a high-cloud class.

You can use the Spectral Classification module to generate a basic quality layer to guide further radiometric and geometric processing.

The output from the Spectral Classification module can be recoded to meet the requirements of a class layer for topographic normalization, which can be achieved by running the TOPOSOLNORM algorithm.

The possible output classes are as follows:

Class Name Pixel Value
no data value 0
invalid data 1
cloud master class 10
thick clouds 12
clouds detected in the cirrus band 14
semi transparent clouds 16
master class of dark area that could be shadow or water 20
shadow introduced by cloud 24
fully shaded area introduced by topography 26
shaded areas or water not attributed to cloud or topography 28
snow master class 30
water master class with a very low SWIR signal 40
deep water 42
water with algae / aquatic vegetation 44
turbid water with suspended particles 46
shallow water wit signal from the bottom substrate 48
bare land surfaces with no vegetation master class 50
bare bright soil 52
bare red soil 54
bare dark soil 56
bare burnt area with a high SWIR signal 58
vegetation master class with weak to strong vegetation response 60
senescent vegetation master class of either dark or bright areas 70
dark senescent vegetation 72
bright senescent vegetation 74
actively growing vegetation master class 80
woody actively growing vegetation 90
conifer actively growing trees 92
broad leaved actively growing shrubs and trees 96
actively growing herbaceous vegetation 100

Job results

For each valid input scene, the Spectral Classification module creates a spectral-classification child job. Each output image contains one channel computed from the input file. The names of the output image files are based on the name of the input image file. That is, the name of the output file is appended with CLS to indicate it is a spectrally classified file; for example:

Input file: 2014-12-29T033054_RE3_1B-NAC_18998309_270548_RAW_MS.pix
Output file: 2014-12-29T033054_RE3_1B-NAC_18998309_270548_RAW_CLS.pix
 
Input file: 51194180908010853222J.pix
Output file: 51194180908010853222J_CLS.pix

You can open the processed scenes in CATALYST Professional Focus to perform quality assurance (QA).

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