INSDMV

Description

INSDMV converts the displacement values generated from a stack of coregistered interferograms into temporally ordered and non-overlapping, line of sight (LOS) displacements in meters after removing the estimated atmospheric effects from the overlapping interferograms. The estimated topographic error is given in the last layer.

Parameters

insdmv(mfile, dbic, defomodel, flsz, niters, regufact, filo)

Name	Type	Caption	Length	Value range
MFILE*	str	Input file, folder, or text file	1 -
DBIC	List[int]	Database input channel list	0 - 1
DEFOMODEL	str	deformation model	0 -	See Parameter Details. Default: POLY
FLSZ	List[int]	Kernel size of the box filter.	0 -
NITERS	List[int]	Number of iterations	0 - 1	Default: 1
REGUFACT	List[float]	The regularization factor	0 - 1	0 - Default: 0
FILO*	str	Database output file name	1 -

* Required parameter

Parameter descriptions

MFILE

The name of a folder or text file containing the data sets to be processed. For more information regarding MFILE usage, including the requirements for a valid file, see Using an MFILE with a CATALYST Professional algorithm.

DBIC

The input file channel containing the displacement values. The specified channel contains floating-point values representing terrain displacement along the radar line of sight. The displacement values are written in meters with positive values representing motion toward the radar (i.e. uplift).

DEFOMODEL

FLSZ

This parameter specifies the size of the averaging window (in pixels and lines) to be used during the estimation of the atmospheric component.

If this parameter is not specified, the window will cover an area of 2000m x 2000m based upon the image sample sizes extracted from the metadata.

NITERS

Specifies the number of iterations applied to remove the atmospheric components from the displacement.

REGUFACT

This regularization parameter weights the residual norm against the solution norm. Its role is to find a balance between solutions overfit to the noisy measurements and solutions that are constrained too much.

If not specified, the default factor value of 0 reduces to the unregularized solution.

FILO

The name of the output PCIDSK (.pix) file which will contain the displacement estimates corresponding to the time intervals bracketed by temporally ordered acquisition dates. Note the time intervals are not necessarily evenly spaced. The final channel contains the estimated topographic error.

The displacements are measured in the direction of the SAR-sensor line of sight. Positive values represent the movement towards the sensor; that is, nominally up. The displacements and the topographic error are given in meters.

The specified output file must not already exist.

Details

INSDMV creates a stack of non-overlapping line of sight (LOS) displacements and estimates the topographic error. The input displacement layers are generated from a stack of temporally overlapping interferograms. The output displacement estimates are solved for each acquisition interval using a least squares technique. The images in the input stack must be coregistered with identical sample sizes. The displacement layers in the stack are checked to ensure that each layer has the same number of lines and pixels, projection, extent, and sample sizes (range and azimuth).

INSDMV processes the input stack under the assumption that each layer is collected by compatible sensors (band, polarization, and resolution) and with compatible viewing geometries (orbit, look direction, with similar incidence angles).

The input layers must contain floating-point deformation in meters where positive values correspond to uplift. A single deformation channel from each input file is extracted and processed.

The output file contains a stack of floating-point displacement estimates at each pixel including both linear and non-linear displacements. The displacement estimates are obtained by removing the atmospheric contribution at PSC locations from the input layers.

Each layer of output corresponds to an acquisition interval. The displacement estimates are written in meters. The last layer contains the estimated topographic error in meters.

Example

The following example is based on the premise that you have a folder of several coregistered interferograms containing real-valued subsidence maps (in meters). The output channels will represent displacement in meters for the acquisition interval specified by the layer metadata tags, and the topographic channel will represent elevation errors in meters.

from pci.insdmv import insdmv

mfile  =  r"D:\Datasets\Vancouver_Stack_GG/caldefo*.pix"
dbic   =  [2]
defomodel = "POLY ORDER=1"
flsz = []
niters = [1]
regufact = []
filo   =  r"D:\Datasets\Vancouver_Stack_GG/results/Atmospherically_Corrected_displacement_topo.pix"

insdmv(mfile, dbic, defomodel, flsz, niters, regufact, filo)
        

Algorithm

During verification, INSDMV reads the nominal acquisition times associated with each interferogram. The SAR acquisition times are sorted chronologically in ascending order, and the output is generated in the sorted order.

The input displacement values are time-sorted in chronological order. Each input pixel contains a stack of floating-point displacement values each associated with known time intervals.

Each displacement layer is then decomposed into non-overlapping intervals covering the time period between the first and last acquisitions. The polynomial of user specified order is used to determine the initial velocity estimate. The displacement due to the velocity estimate is removed leaving the unmodelled displacement, atmospheric effect and uncorrelated noise. A triangular, high pass temporal filter (with a width of the minimum of 300 days or the temporal period covered by the stack) is applied to estimate the unmodelled displacement. This is followed by a large area, low pass spatial filter to estimate and remove the atmospheric noise. This process is repeated until the required number of iterations is reached leaving only the unmodeled displacement. The modeled displacement is then added back to the remaining unmodeled displacement. The final layer contains the estimated topographic error. The non-overlapping displacements are solved via a Least Square best fit algorithm.