Automated Spectral Normalization module

Name	Caption
Scene Folder	Input scene folder
Output Folder	Output folder
Output File Type	Output file type
Output File Options	Output file options
Save Intermediate Files	Save intermediate files
Overwrite Results	Overwrite existing results
Send Email	Email notification settings
DEM Source	DEM tile source
Prepare MODIS Data	Prepare MODIS data
MODIS Data Folder	Path of folder to downloaded MODIS data
Days Before	Download all MODIS data for this number of days before the date of the ortho image
Days After	Download all MODIS data for this number of days after the date of the ortho image
Prepared MODIS Data Folder	Path of folder to prepared MODIS data
Perform Topographic Normalization	Whether to create topographically normalized images
Calculate per-pixel angle	Calculate per-pixel solar zenith and azimuth angles and generate angle file
Angle file directory	Path and name of a directory that contains angle files
Regression Method	The regression method to use
With Spectral Classes	Whether to use spectral classes in the regression
Synthesize Blue Band For SPOT 1-5	Whether to synthesize blue band for SPOT 1-5 dataset
Create Pansharpened Images	Whether to create pansharpened images
Pansharpening Method	Pansharpening method to use
Multispectral Sharpening Channels	Multispectral sharpening channels
Multispectral Reference Channels	Multispectral reference channels
Resampling Method	Resampling method
Edge Sharpen	Amount of sharpening to image edges
AdaptRadiometry	Adapt radiometric values to input MS images

Parameter descriptions

Scene Folder

The path and name of the folder containing scenes to ingest.

Output Folder

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

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.

Save Intermediate Files

Select this check box to save any supporting files created during processing.

By keeping the files, you can use them to analyze intermediate results and, if necessary, fix any minor issues. You can then restart the job without having to regenerate all the supporting data, thereby reducing processing time.

Note: Intermediate files can consume a large quantity of disk space, thus it is a good idea to delete them when they are no longer needed.

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 single digital elevation model (DEM) file or a folder containing one or more DEM tiles.

This parameter can be specified by using any of the following:

Name of a single DEM file; for example, C:\data\DEM\dem.pix
Name of a folder containing one or more DEM tiles and an associated index.txt file; for example, C:\data\DEM
Name of an index file; for example, C:\data\DEM\index.txt

The index.txt file lists the DEM files contained in the specified folder and provides information describing each DEM tile. The information in the DEM index file supersedes other DEM parameters in the module; all other DEM-related parameters are ignored. For more information about the format of the index.txt file and specific requirements for the individual DEM tiles, see Format of the DEM index file.

When the value of DEM Source is the name of an existing folder, the module searches that folder for a file named index.txt, and a set of DEM raster tiles. The index.txt file contains a single vector channel that lists the DEM files contained in the specified folder and provides information describing each DEM tile.

If no value is specified for this parameter, the module uses the default global DEM installed with CATALYST Enterprise (gmted2010).

Prepare MODIS Data

Select this check box to prepare MODIS data based on input orthorectified images.

With this check box selected, the module downloads and prepares MODIS MCD43A2 and MCD43A4 products so that they can be used as the reference for spectrally normalizing the input orthorectified images.

MODIS Data Folder

MODIS data downloaded by this job is placed in this folder. Regardless of whether Overwrite Results is set, data is never downloaded if it already exists in this folder.

Downloading MODIS can be slow and consume a lot of bandwidth. It is recommended to use the same MODIS folder every time you run this job to prevent downloading data that has already been downloaded.

Days Before

MODIS products usually need to be composited in time to obtain sufficient number of pixels with valid MODIS data. Therefore, processing of multiple MODIS scenes for a single image is supported. Using "Days Before" and "Days After" you can select the date range of MODIS products to download for an image.

Days After

See "Days Before" for more details.

Prepared MODIS Data Folder

Only available when Prepare MODIS Data is unselected.

If the MODIS data is previously prepared and ready to use, it can be used directly after specifying the location.

Perform Topographic Normalization

Select this check box to create topographically normalized images.

With this check box selected, corrects radiometric values of images based on per-pixel incidence angles and classes.

Calculate per-pixel angle

Once checked, the job generates an angle file from the input data, and user can no longer supply their own angle file.

Angle file directory

Optionally specify a folder that contains angle files. If left empty, the job generates an angle file by running SOLVIEWZAZ. The angle files should follow CATALYST Enterprise naming convention. That is, if the input image file name is in the form of ${baseid}_${level}_${prodtype}${ext}, the original ${prodtype} should be replaced by "ANGL" to indicate it is a angle file. Otherwise the name should be appended with "_ANGL". For example:

Input file:	2014-12-29T033054_RE3_1B-NAC_18998309_270548_RAW_MS.pix
Corresponding angle file name should be:	2014-12-29T033054_RE3_1B-NAC_18998309_270548_RAW_ANGL.pix

Input file:	51194180908010853222J.pix
Corresponding angle file name should be:	51194180908010853222J_ANGL.pix

Regression Method

There are two regression methods available:

Global: all valid pixels in the corresponding image and reference bands are used jointly to derive linear regression between the two bands. If classes are used, the regression is derived separately for every class, but still over the whole area of the image. The global regression is always derived.
Local: the regression is derived for every valid image pixel, using valid pixels in a small window centered on the current pixel. If classes are used, only pixels belonging to the same class as the current pixel are used. If a local regression cannot be derived at a pixel, the parameters to use are either interpolated spatially from the adjacent derived values (when the classes are not used), or replaced by the global per-class values (if classes are used). Local regressions may run slower, and use significantly more disk space for the intermediate results, but generally produce more accurate corrections.

With Spectral Classes

Whether to use spectral classes when performing the regression. The use of classes usually improves the accuracy of results, particularly for local regressions, but may reduce the overall number of valid pixels.

Synthesize Blue Band For SPOT 1-5

Option to perform blue band synthesis for SPOT 1-5 images using the green, red and NIR bands. Only applied to SPOT 1-5 images. All other sensors ignore this option and continue processing.

Create Pansharpened Images

Select this check box to pansharpen the geometrically and spectrally corrected imagery.

With this check box selected, the module creates pansharpened images from MS and PAN pairs based on the value selected for the Pansharpening Method parameter.

Pansharpening Method

The method to use for pansharpening.

Available options are:

MRA Fusion: creates high-resolution color images by fusing black-and-white panchromatic and multispectral color images by using wavelet decomposition.
UNB Pansharp: developed by the University of New Brunswick, this method creates high-resolution color images by fusing black-and-white panchromatic and multispectral color images. The method uses an algorithm that produces sharpening results superior to other types while preserving the spectral characteristics of the original images.

With either method, both 8-bit and 16-bit data types are supported, and the images can be from the same or different sensors.

Multispectral Sharpening Channels

A comma-delimited list of the multispectral channels to sharpen.

If no value is specified for this parameter, all channels are processed by default. These channels are fused with the high-resolution, panchromatic image data.

Note: You cannot specify duplicate channels.

Multispectral Reference Channels

A comma-delimited list of the multispectral channels to use as reference for the sharpening process.

If no value is specified for this parameter, all channels are processed by default. These channels, and those of the panchromatic image, span the same range of frequency (wavelength) response.

When no reference channel is specified, the module determines the appropriate reference bands based on the available wavelength information for both the panchromatic and multispectral files.

Note: You cannot specify duplicate channels.

Resampling Method

The resampling method to use during processing.

Available resampling options are:

Cubic: cubic convolution. This method determines the gray level from the weighted average of the 16 pixels closest to the specified input coordinates and assigns that value to the output coordinates. The resulting image is slightly sharper than one produced by bilinear interpolation.
Bilinear: bilinear interpolation. This method determines the gray level from the weighted average of the four closest pixels to the specified input coordinates and assigns that value to the output coordinates. An image with a smoother appearance than nearest-neighbor interpolation is created, but the gray-level values are altered in the process, resulting in blurring or degraded image resolution.

The resampling method is only available for UNB pansharpening.

Edge Sharpen

Amount of sharpening to image edges to apply. A value of 1.0 (default) means no edge sharpening. Values greater than 1.0 apply greater sharpening. Values greater than 2.0 are not recommended.

Applying edge sharpening makes image more visually appealing but may degrade radiometric similarity with the original multispectral (MS) data.

AdaptRadiometry

Method to adapt the output spectral values to those of the input multispectral (MS) image.

Adapting the radiometry can better match to the original multispectral image. The two methods are linear regression based on a small sliding window and an estimate of the Modulation Transfer Function (MTF).

Available options are:

YES: applies both the MTF and LIN options (default)
ALL: applies both the MTF and LIN options (default)
MTF: applies MTF
LIN: applies Linear
NO: no adapting radiometery applied

Details

General job details

Preprocessing requirements

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

The DEM must be present and of the appropriate resolution
All input files must be in PCIDSK format (.pix)
The input orthorectified images must have a valid acquisition dates in the metadata
The images must have the proper radiometric transformation metadata tags
At a minimum red, green, and near infrared (NIR) bands must be available in the imagery.
That is, the available number of bands determines the levels of classification applied.
All exclusion masks, in the input orthorectified images, must be in bitmap segments.

Module details

The Automated Spectral Normalization module adjusts multispectral optical images, so that the corrected image values are converted to the radiometric quantity of Surface NBAR (Nadir BRDF-Adjusted Reflectance).

For each scene contained in the input-scenes folder, the module spawns the following child jobs:

MODIS Preparation (if selected): to download and prepare MODIS MCD43A2 and MCD43A4 products
Spectral Classification:to create a spectral classification files for topographic normalization
Topographic Normalization (if selected): to correct radiometric values based on per-pixel incidence angles and classes
Spectral Classification: to create a spectral classification files for spectral normalization
Spectral Normalization to MODIS: to adjust multispectral optical images to make them as spectrally similar as possible to the reference MODIS product MCD43A4 that is acquired at nearly the same time
Pansharpening (if selected): to merge panchromatic and multispectral image pairs to create a single, high-resolution color image

Job results

The results of the processing by this module are written to subfolders created in the specified output folder, as follows:

modisprep: contains all prepared MODIS data
speclasstoponorm: contains classification images for topographic normalization
toponorm: contains topographically normalized images
speclassspecnorm: contains classification images for spectral normalization
specnorm: contains spectrally normalized images
pansharp: contains the pansharpened images

For more information on the results of each individual module in this workflow:

Automated Spectral Normalization module

Description

Parameters

Parameter descriptions

Details