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Release Notes GAMMA Software, 20131205 (Urs Wegmüller, Charles Werner, 5-Dec-2013)

Gamma Remote Sensing AG

Worbstrasse 225, CH-3073 Gümligen

http://www.gamma-rs.ch

This information is provided to users of the GAMMA software. Further distribution of this

document is restricted.

This release of the Gamma software includes new programs that provide new capability,

additional features to existing programs and bug fixes.

Linux Distribution

This Linux Gamma software distribution is based on Ubuntu 12.04 LTS 64-bits.

In installations running 64-bit Redhat RHEL 6 OS it will be necessary to request software

compiled using an older version of glibc, 2.11 from October 2009. The version of glibc is

used in Ubuntu Linux 10.04. Please contact Gamma for this version.

Windows Distribution

The Windows version of the Gamma software is now fully 64-bits! The software has been

compiled and tested under 64-bit Windows 7. The software may work with 64-bit Windows 8,

but has not been tested on this platform. The build uses the MINGW64 GCC compilers. The

installation instructions for the binary distributions has been updated for the 64-bit release.

This release requires installation of a new GAMMA_LOCAL_w64_20130917.zip file

containing updated libraries and support for the updated compiler. Support for LAPACK and

LAPACKe, gdal 1.10, and hdf 1.8.11 has been included in

GAMMA_LOCAL_w64_20130917. Using any previous versions of GAMMA_LOCAL will

not work with this release.

Mac OSX

The software in this version has been compiled again using Snow Leopard 10.6 with 64-bits.

GAMMA Software Training Courses

GAMMA plans to organize in 2013 again training courses at GAMMA (near Bern,

Switzerland) for SAR/INSAR (MSP/ISP/DIFF&GEO/LAT) and for PSI (IPTA).

The dates for the courses ( not yet fixed) will be announced on our web-site under

http://www.gamma-rs.ch/courses/training-courses.html.

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Significant Changes in the Gamma Software Modules since the mid--2013 release

Sensors

GPRI: Furthermore, improvements in the software to specifically support data in the GPRI

geometry were included.

We are looking forward to support the upcoming SAR Sensors Sentinel-1 and ALOS

PALSAR-2.

MSP

az_proc: Corrected moderate linear phase error that occurred when deskewing the output SLC

to zero-Doppler geometry. This error was only affecting interferograms of data pairs

processed with different range dependent Doppler functions. In interferograms between SLC

processed with the old version and the corrected new version will be affected by a phase

ramp. If it is necessary to correct previously processed SLCs, Gamma can provide a program

to correct the SLC phase of “old SLCs”.

pre_rc: Added capability to process subbands of the range-chirp. This permits generation of

range split-band interferograms using the upper and lower range portions of the range-chirp

bandwidth (as an alternative to band-pass filtering of the full bandwidth SLCs).

ISP

par_CS_SLC, par_CS_SLC_TIF: Changed sign on calibration gain factor (cal_gain) to be

consistent with radcal_SLC.

ptarg_cal_SLC, ptarg_cal_MLI: Enhanced point target characterization functionality:

1. Updated programs to estimate null to null main lobe width using 3 dB beamwidth

2. Change bounds for detection if the point target is centered in the data window

3. No longer attempt to subtract clutter power when sidelobes are same level or lower than

the clutter.

4. Update ptarg_cal_SLC.c to have the option to write out the clutter region data samples

in fcomplex format to a file specified by the c_image parameter.

fspf: Added mode to permit fast spatial filtering of GPRI interferograms with variable azimuth

resolution by giving the option of providing an MLI parameter file. If an MLI parameter is

provided, the number of looks in range and azimuth used to generate the intermediate 2D-

multi-look image are adjusted to have approximately equal dimension in ground-range and

azimuth. If the data are GPRI, then the azimuth pixel spacing is calculated as a function of

range. In the case of non-GPRI data, when an MLI parameter file is provided, the ground

range pixel spacing is determined from the incidence angle at the center of the swath.

par_ASAR: Corrected sensor string in parameter file for ENVISAT ASAR Wide Swath SLC

data to the form ASAR_SS1_VV to be compatible with radcal_SLC.

offset_SLC_tracking: Parallelized using OPENMP, resulting in a factor ~3 speedup with 4

threads. Using lfit1() rather than lfit() to avoid exit when search of lease-squares fit of the

peak fails.

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DIFF&GEO

SLC_diff_intf, offset_pwrm: Now using init_openmp() subroutine to initialize OPENMP.

Running the program with an user selected number of threads greater than 4 is now possible.

The number of threads in any program using openmp for parallelization is done by setting the

OMP_NUM_THREADS environment variable (e.g. export OMP_NUM_THREADS=2).

projection_params.h, create_dem_par: Added support for the Albers Equal Area Conic

AEAC for Alaska. create_dem_par Now prints out a list of possible projections if an

unknown region is entered when searching for regions with defined projection parameters.

pixel_area: Improved parallelization of pixel_area so that there is a factor of 3 speedup when

using 4 threads.

phase_sim, phase_sim_orb: Added new capability to remove a multiple of 2PI from the

simulated phase to increase the precision of the simulated phases in float format.

offset_list_fitm: Added new option to output the input coordinates using the lookup-table and

polynomial model.

dh_map_orb: New program to calculate the sensitivity of the interferometric phase to terrain

height and height difference. Especially useful for scaling unwrapped differential

interferometric phases when working with Tandem-X data.

map_trans, dem_trans: Updated to correct failure in DEM corner calculation when EQA is

selected as the output projection.

DISP

DISP_lib: Corrected memory allocation error when reading/writing BMP image lines.

float_math: Added capability to use a user-specified region as a reference. data in that area are

averaged and used to normalize the data. In the case of addition or subtraction, the average

value in the reference region is subtracted from the data. In the case of multiplication or

division, the data are divided by the average value.

cpx_math: Added program to permit simple mathematical operations on fcomplex format data

files.

data2geotiff: Added support for the Albers Equal Area Conic projection for Alaska (EPSG

3338).

LAT

mt_lee_filt_cpx: Corrected error in the mt_lee_filt_cpx program that precluded filtering the

entire complex image scene. The program used the wrong size of the data objects and

therefore calculated the incorrect number of lines of the input images.

lin_comb: Corrected error when only one file is supplied as input.

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IPTA

pt2geo: The point geocoding program now supports the GPRI polar format data geometry.

IPTA processing of GPRI data: Substantial tests were conducted to confirm that the IPTA

package is fully compatible with GPRI data.

def_mod_pt: Program has been parallelized using OPENMP. With 4 threads a speedup factor

> 3 can be achieved.

fspf_pt: Added support for GPRI data to the fast spatial filter fspf_pt. The GPRI data have

variable azimuth pixel spacing from near to far range. Data are resampled to constant azimuth

pixel spacing before filtering.

Tandem-X DEM generation

In this section a possible approach for the generation of a Digital Elevation Model (DEM)

using Tandem-X data under the assumption that a pre-existing DEM as the SRTM DEM is

available.

SRTM Preparation:

In the preparation of the SRTM DEM over the area it is recommended to modify the geoidal

heights which are provided in the SRTM tiles to WGS84 heights as this is what is specified in

the DEM parameter file as vertical Datum. The offset can be determined using a geoidal

height calculator as available under

http://www.unavco.org/community_science/science-support/geoid/geoid.html

For our example (Mount Etna) we determine for the center coordinate (center_latitude:

37.8341714 degrees, center_longitude: 15.1176991 degrees) a Geoid height of 41.547 m.

We add this value to the SRTM heights to get WGS84 heights.

Tandem-X SLC data preparation:

We determine based on the meta data if the data is acquired in bistatic mode (as in our

example) or in ping-pong mode (accordingly we have to select the corresponding phase model

later on). We also check which sensor was the master and is used as the geometric reference.

In our example this was TSX (and TDX was receive only). Accordingly TSX is our master

SLC for the interferograms.

The Tandem-X SLC pair is already co-registered, we call the two scenes and the related SLC

parameter files

20121009.TSX_HH.rslc, 20121009.TSX_HH.rslc.par

20121009.TDX_HH.rslc, 20121009.TDX_HH.rslc.par

We determine an MLI image with 4 range and 4 azimuth looks:

multi_look 20121009.TSX_HH.rslc 20121009.TSX_HH.rslc.par 20121009.TSX_HH.mli

20121009.TSX_HH.mli.par 4 4 0 - 0.000001

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and generate a rasterfile of it

raspwr 20121009.TSX_HH.mli 4282 1 0 1 1 1. .35

Geocoding heights of master using SRTM (with refinement)

Then we conduct a geocoding using the SRTM heights. This is done mainly to get the SRTM

heights (corrected for the geoid offset) into the SAR geometry of the master. For this we

prepared a DEM_parameter file in the required resolution (EQA.dem_par) and the related

heights were obtained using dem_trans. The geocoding steps done include:

gc_map 20121009.TSX_HH.mli.par - EQA.dem_par EQA.dem EQA.dem_seg_par

EQA.dem_seg 20121009.lt 1 1 EQA.20121009.sim_sar - - EQA.20121009.inc - -

EQA.20121009.ls_map

geocode 20121009.lt EQA.20121009.sim_sar 8220 20121009.sim_sar 4282 6714 0 0

create_diff_par 20121009.TSX_HH.mli.par - 20121009.diff_par 1 0

offset_pwrm 20121009.sim_sar 20121009.TSX_HH.mli 20121009.diff_par offs snr 256 256

offsets 2 64 64 7.0

offset_fitm offs snr 20121009.diff_par coffs coffsets 10 3

and we check the quality achieved considering the refinement polynomial and the offset

statistics (in the screen output of offset_fitm):

final solution: 772 offset estimates accepted out of 4096 samples

final range offset poly. coeff.: 1.60243 -3.67299e-04 2.76519e-04

final azimuth offset poly. coeff.: 0.66999 -1.31173e-05 2.77370e-05

final range offset poly. coeff. errors: 3.27437e-03 1.17686e-06 8.75214e-07

final azimuth offset poly. coeff. errors: 2.35827e-03 8.47597e-07 6.30349e-07

final model fit std. dev. (samples) range: 0.4814 azimuth: 0.3467

The refinement is applied to the lookup table::

gc_map_fine 20121009.lt 8220 20121009.diff_par 20121009.lt_fine 1

Permitting us to transform data between the map geometry and the SAR geometry

geocode 20121009.lt_fine EQA.dem_seg 8220 20121009.hgt 4282 6714 0 0

rashgt 20121009.hgt 20121009.TSX_HH.mli 4282 1 1 0 1 1 128 1. .35 1 20121009.hgt.ras

and between SAR geometry and map:

geocode_back 20121009.TSX_HH.mli 4282 20121009.lt_fine EQA.20121009.TSX_HH.mli

8220 11580 2 0

raspwr EQA.20121009.TSX_HH.mli 8220 1 0 1 1 1. .35

Generate multi-look interferogram, unwrapping, generation of relative heights

We first generate for the master and the slave a multi-look intensity image:

multi_look 20121009.TSX_HH.rslc 20121009.TSX_HH.rslc.par 20121009.TSX_HH.mli

20121009.TSX_HH.mli.par 4 4 0 - 0.000001

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multi_look 20121009.TDX_HH.rslc 20121009.TDX_HH.rslc.par 20121009.TDX_HH.mli

20121009.TDX_HH.mli.par 4 4 0 - 0.000001

then we define the offset parameter file:

create_offset ../slc/20121009.TDX_HH.rslc.par ../slc/20121009.TSX_HH.rslc.par

20121009.off 1 4 4 0

and simulate the interferometric phase. Here it is relevant that we use phase_sim_orb (not

phase_sim) and that we use the correct scene as the master and that we indicate that the data is

bistatic data (if that is the case as in our example).

phase_sim_orb 20121009.TSX_HH.rslc.par 20121009.TDX_HH.rslc.par 20121009.off

20121009.hgt 20121009.ph_sim_orb 20121009.TSX_HH.rslc.par - - 0

We use then SLC_diff_intf to calculate the differential interferogram.

SLC_diff_intf ../slc/20121009.TSX_HH.rslc ../slc/20121009.TDX_HH.rslc

../slc/20121009.TSX_HH.rslc.par ../slc/20121009.TDX_HH.slc.par 20121009.off

20121009.ph_sim_orb 20121009.diff 4 4 1 0 0.25

and display the differential interferogram:

rasmph_pwr24 20121009.diff 20121009.TDX_HH.mli 4282 1 1 6714 1 1 1. .35

The differential interferogram looks quite flat but shows local deviations related to noise (e.g.

over the sea), topographic effects related to the low resolution of the SRTM DEM e.g. to the

north of the area, and deviations related to actual changes of the topography as observed in the

Mount Etna peak region (see Figure 1).

Figure 1: Differential interferogram Figure 2: Unwrapped differential

interferogram

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The crucial step, the phase unwrapping is addressed. For this example we get a good result

when using mcf with a weighting factor based on the coherence, without application of any

spatial filtering (but maksing of coherence below 0.3):

cc_ad 20121009.diff 20121009.TDX_HH.mli 20121009.TSX_HH.mli - - 20121009.cc 4282

3 9 0

rascc_mask 20121009.cc 20121009.TSX_HH.mli 4282 1 1 6714 1 1 0.3 0.0 0.0 1.0 1. .35 1

20121009.cc.ras

mcf 20121009.diff 20121009.cc - 20121009.diff.unw 4282 0 0 0 - - 1 1 512 1880 4400 0

The result is displayed (see Figure 2

rasrmg 20121009.diff.unw 20121009.TDX_HH.mli 4282 1 1 6714 1 1 0.5 1. .35 0. 1

20121009.diff.unw.ras

and carefully checked for unwrapping errors. In the case errors appear e.g. some spatial

filtering may be used.

It is very important that the unwrapped phase are carefully checked and if errors are observed

these need to be fixed or masked as well as possible.

To convert the unwrapped phases to relative heights the new program dh_map_orb is used.

Basically, this program calculates for each pixel the phase to height sensitivity and applies it

to scale the unwrapped phases:

dh_map_orb 20121009.TSX_HH.rslc.par 20121009.TDX_HH.rslc.par 20121009.off

20121009.hgt 20121009.diff.unw 20121009.dpdh 20121009.dh 20121009.TSX_HH.rslc.par 0

To move to absolute heights we need to use a height reference and possibly also a large scale

reference to remove any tilts that may be present. For both we can well use the SRTM

heights. Our assumption is that the deviation from the SRTM should be zero at large scale and

without linear trend. We determine for this reason a plane through the relative heights and

subtract it from the relative heights to get the height corrections that we have to apply to the

SRTM heights to get an initial Tandem-X height map.

create_diff_par 20121009.TSX_HH.mli.par - 20121009.diff_par 1 0

quad_fit 20121009.dh 20121009.diff_par 16 16 20121009.cc.ras plotdata.txt 3

quad_sub 20121009.dh 20121009.diff_par 20121009.dh.shifted 0 0

SVD fit parameters: -2.8355e+01 6.5855e-04 -5.4887e-03

std. dev. of SVD phase model residuals (radians): 9.2322

This means that besides the offset a range trend of 0.66m per 1000 range pixels and an

azimuth trend of -5.4m per 1000 azimuth pixels (in MLI geometry) is corrected.

Geocoding

The relative heights are then resampled into the map geometry using the refined lookup table

calculated based on the SRTM DEM. It is clear that this is not the final solution as a lookup

table based on the Tandem-X heights should be used (see below). Besides the relative height

we also resample the coherence and the backscattering

geocode_back 20121009.dh.shifted 4282 20121009.lt_fine EQA.20121009.dhgt1 8220

11580 1 0

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geocode_back 20121009.TDX_HH.mli 4282 20121009.lt_fine

EQA.20121009.TDX_HH.mli 8220 11580 2 0

geocode_back 20121009.cc 4282 20121009.lt_fine EQA.20121009.cc 8220 11580 2 0

Generation of initial Tandem-X DEM

In the map geometry we add then relative heights to the SRTM heights:

lin_comb 2 ../DEM/EQA.dem_seg EQA.20121009.dhgt1 0.0 1. 1. EQA.20121009.hgt0 8220

1 11580 1 1 0

and do some more quality control. For this we mask low coherence areas

rascc_mask EQA.20121009.cc EQA.20121009.TDX_HH.mli 8220 1 1 11580 1 1 0.3 0.0 0.0

1.0 1. .35 1 EQA.20121009.cc.ras

mask_class EQA.20121009.cc.ras EQA.20121009.hgt0 EQA.20121009.hgt0.tmp1 0 1 1 1 0

0.0

determine a mask for outliers (= high deviation from spatially filtered value).

interp_ad EQA.20121009.hgt0 EQA.20121009.hgt.filt1 8220 4 9 25 2 2 0

lin_comb 2 EQA.20121009.hgt0 EQA.20121009.hgt.filt1 0.0 1. -1. EQA.20121009.dh1 8220

1 11580 1 1 0

single_class_mapping 1 EQA.20121009.dh1 -10. 10. EQA.20121009.dh1a.ras 8220 1 11580

1 1

and remove heights for outliers

mask_class EQA.20121009.dh1a.ras EQA.20121009.hgt0.tmp1 EQA.20121009.hgt1 0 1 1 1

0 0.0

and determine a mask containing area of non-zero data (to avoid interpolation outside this

area):

lin_comb 1 EQA.20121009.hgt1 1000.0 0. tmp1 8220 1 11580 1 1 0

rascc_mask tmp1 EQA.20121009.TDX_HH.mli 8220 1 1 11580 1 1 0.900 0.0 900.0 1100.0

1. .35 1 EQA.20121009.mask1.ras

Then we apply a slight interpolation to fill very small gaps

interp_ad EQA.20121009.hgt1 EQA.20121009.hgt2 8220 4 8 2 2 1

and apply a slight spatial filtering to reduce noise

interp_ad EQA.20121009.hgt2 EQA.20121009.hgt.interp.final1 8220 1 4 15 2 2 0

rashgt EQA.20121009.hgt.final1 EQA.20121009.TSX_HH.mli 8220 1 1 11580 1 1 200. 1.

.35

to get the final result for the first iteration.

EQA.20121009.hgt.interp.final1 (see Figure 3).

Of course this conditioning can be modified. What is done in the example is just to show

some possibilities.

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Figure 3: Tandem-X height map obtained in initial iteration using a color scale with 200m per

color cycle.

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Additional iterations

We can now do iterations to change the geocoding from using the SRTM height based lookup

table to a Tandem-X height based lookup table. Typically, 2 iterations should be sufficient..

gc_map 20121009.TSX_HH.mli.par - EQA.dem_seg_par EQA.20121009.hgt.interp.final1

EQA.dem_seg_par.tmp EQA.dem_seg.tmp 20121009.lt 1 1 EQA.20121009.sim_sar - -

EQA.20121009.inc - - EQA.20121009.ls_map

gc_map_fine 20121009.lt 8220 20121009.diff_par 20121009.lt_fine 1

geocode_back 20121009.hgt.shifted 4282 20121009.lt_fine EQA.20121009.dhgt1 8220

11580 1 0

geocode_back 20121009.TSX_HH.mli 4282 ../DEM/20121009.lt_fine

EQA.20121009.TSX_HH.mli 8220 11580 2 0

geocode_back 20121009.cc 4282 20121009.lt_fine EQA.20121009.cc 8220 11580 2 0

lin_comb 2 EQA.dem_seg EQA.20121009.dhgt1 0.0 1. 1. EQA.20121009.hgt0 8220 1 11580

1 1 0

followed again by the conditioning step to determine the solution for the first iteration:

EQA.20121009.hgt.interp.final1

Validation

No strict validation on this result was done, but a comparison of the Tandem-X DEM (using

2012 data) and the SRTM DEM (using 2000 data) is shown in Figure 4.

Figure 4 Mount Etna, Sicily. Elevation change between 2000 (SRTM) and 2012 (Tandem-X

data). The image brightness corresponds to the shaded relief of the 2012 Tandem-X

interferometric DEM. Elevation increase > 100m has been observed for some areas. Tandem-

X data courtesy INSA3397, © DLR. InSAR processing by GAMMA.

-20m 0m +20m

elevation change

-150m 0m +150m

elevation change

3.0km 0.7km