PSSARTSA

Provides Multi-Temporal metrics for a stack.


EnvironmentsPYTHON :: EASI
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Description


PSSARTSA computes multi-temporal metrics form a co-registered stack of data. Fourteen metrics based upon amplitude statistics (see details section) are computed for the stack. The input values are automatically converted to amplitude when the metadata indicates units of intensity or decibel. If the input units are not specified, no conversion occurs. The option to append amplitude layers in temporal order is also provided.
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Parameters


pssartsa(mfile, dbic, mask, maskfile, stack, flsz, filo)

Name Type Caption Length Value range
MFILE* str Input folder, or text file 1 -    
DBIC List[int] Input raster channel 0 -   Default: 1
MASK List[int] Area mask (bitmap or vector) 0 - 1  
MASKFILE str Mask file 0 -    
STACK str Stack Data 0 -   yes| no
Default: no
FLSZ List[int] Filter size (pixels, lines) ODD 0 -  
FILO* str Database output file name 1 -    

* Required parameter
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Parameter descriptions

MFILE

The name of a folder, or a text file that contains the input images to process. Only the PIX file format (*.pix) is supported.

All input files must be co-registered and have the same number of lines and columns.

When MFILE is a text file, it must contain a list of files (one per line) with their full pathname, for example: MFILE="C:/change_detection/sarimge_list.txt"

where the text file contains

C:/change_detection/sarimage_20201028.pix C:/change_detection/sarimage_20201121.pix C:/change_detection/sarimage_20201215.pix C:/change_detection/sarimage_20201009.pix C:/change_detection/sarimage_20201126.pix \u00e2\u20ac\u00a6

Alternatively, an input folder can be specified: MFILE = "C:\change_detection"

The use of wildcards (*) is recommended to refine the search within the specified folder, for example:

MFILE = "C:\InSAR_project\RAW\*.pix"

MFILE = "C:\InSAR_project\RAW\ref*.pix"

Note: For more information about using MFILE, including the requirements for a valid file, see Using an MFILE with a CATALYST Professional algorithm.

DBIC

Specifies the channel of the input files to be used for the multi-temporal calculations.
Most channel type are supported.

All input channels must be of the same size (lines, columns) and type.

Complex data are converted to amplitude before calculating the selected metrics.

MASK

The areas of the dataset to be included in the metric calculations. You can define inclusion areas using either bitmaps or polygon vectors. When a bitmap segment is specified, all pixels having a bitmap value of one define the area to mask. The bitmap segment must match the projection of the input. When a vector mask is specified, the masked pixels are those contained within the polygons.

Note: When bitmaps and vectors share the same segment number, the bitmap segment is selected in preference to a vector segment. If you do not specify a value for the MASK and MASKFILE parameters, no masking is performed. You cannot use a default value for MASK when MASKFILE is explicitly specified.

MASKFILE

The name of the file containing the mask. If you do not specify a value for the MASK and MASKFILE parameters, no masking is performed. You cannot use the default value of MASK when MASKFILE is explicitly specified. MASKFILE is expected to be in a slant range projection of input files.

STACK

When STACK = "YES", all output amplitudes are time ordered and stack in a single PIX file.

When STACK = "NO", only the selected multi-temporal metric layers are produced.

FLSZ

This parameter specifies the boxcar filter size to be applied to the data.

FILO

Specifies the name of the PIX file to be generated.

This file must not already exist.

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Details

SAR MULTI-TEMPORAL METRICS

The multi-temporal metric is based on first-order statistics were derived from SAR intensity data.

  1. Sum of Absolute changes (ASC) between adjacent temporal layers.
  2. Mean: Represents the average value for each pixel.
  3. Standard Deviation: Represents the standard deviation for each pixel.
  4. Coefficient of Variation: Represents the ratio of the standard deviation to mean.
  5. Median: Represents the median value (the central value in the ordered series) for each pixel.
  6. Maximum Value: Represents the maximum value extracted from for each pixel.
  7. Minimum Value: Represents the minimum value extracted from for each pixel.
  8. Span: Maximum Value - Minimum Value
  9. Maximum change: represents the maximum absolute change between consecutive acquisition dates.
  10. Maximum change contribution to the ASC as a percentage %.
  11. Index of Date of the Maximum change between layers.
  12. Second Largest Change: represents the second largest absolute change between consecutive acquisition dates.
  13. Second Largest Change contribution to the ASC in percentage %.
  14. Index of Date of the Second Largest Change between adjacent layers.
  15. to 14+N (optionally) temporally ordered layers.

Coregistration of the data layers must be performed by the INSCOREG module.

Pixels set as NoData values are not used in the calculations.

Required METADATA

All input files must contain the following file metadata: "Acquisition DateTime"

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Examples

Generate the metrics only, with no averagin, for a list of SAR images contained in the text file.

from pci.pssartsa import pssartsa

mfile    =  r"C:/mfile.txt"					#List of raw interferograms files
dbic	 = []								#select channel, default 1st channel
mask	 =	[]								#select mask channel (Left Blank)
maskfile =	''								#no maskfile specified
stack    =  "no"							#generate metrics only
flsz     =  []								#no filter
filo     =  r"C:/PSSARTSA_stats.pix"		#output containing the raster layers

pssartsa(mfile, dbic, mask, maskfile, stack, flsz, filo)
        

Generate the metrics only without averaging for the areas defined by the second vector segment of the MASKFILE using the files in the specified directory.

from pci.pssartsa import pssartsa

mfile    =  r"C:/mfile.txt"					#directory containing SAR data sets
dbic	 = []								#select channel, default 1st channel
mask	 = [2]								#select mask channel (Left Blank)
maskfile = "C:/MASK.pix"					#no maskfile specified
stack    =  "no"							#process default ""=no, only statistics
flsz     =  []								#no filter
filo     =  r"C:/PSSARTSA_Mask_stats.pix"	#output containing the raster layers

pssartsa(mfile, dbic, mask, maskfile, stack, flsz, filo)
        

Apply a 5x5 averaging filter before calculation the metrics..

from pci.pssartsa import pssartsa

mfile    =  r"C:/mfile.txt"					#directory containing SAR data sets
dbic	 = []								#select mask channel (Left Blank)
mask	 =	[]								#selecting mack channel (Left Blank)
maskfile =	''								#no maskfile specified
stack    =  ""								#process default "no", only statistics
flsz     =  [5]								# 5 x 5 filter
filo     =  r"C:/PSSARTSA_stats.pix"		#output containing the raster layers

pssartsa(mfile, dbic, mask, maskfile, stack, flsz, filo)
        

Using the MFILE wildcard, generate a pix file with a 5x7 filter containing the metrics channels and the time-ordered amplitude layers.

from pci.pssartsa import pssartsa

mfile    =  "C:/input/*_SLC.pix"			#wildcard identifying SAR data sets
dbic	 = []								#select channel, default 1st channel
mask	 =	[]								#select mask channel (Left Blank)
maskfile =	''								#no maskfile specified
stack    =  "yes"							#append temporally ordered layers
flsz     =  [5,7]							#rectangular 5x7 filter size
filo     =  r"C:/PSSARTSA_5x7_stats.pix"	#output containing the raster layers

pssartsa(mfile, dbic, mask, maskfile, stack, flsz, filo)
        

Generate a pix file containing the statistics channels from channel 2, could be from any valid channel.

from pci.pssartsa import pssartsa

mfile    =  r"C:/mfile.txt"					#List of raw interferograms files
dbic	 = [2]								#select channel 2, could be any valid channel
mask	 =	[]								#select mask channel (Left Blank)
maskfile =	''								#no maskfile specified
stack    =  "no"							#process default ""=no, only statistics
flsz     =  []								#no filter
filo     =  r"C:/PSSARTSA_ch_2_def.pix"		#output containing the raster layers

pssartsa(mfile, dbic, mask, maskfile, stack, flsz, filo)
        

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