Release Notes GAMMA Software,

Transcription

1 Release Notes GAMMA Software, Urs Wegmüller, Charles Werner, Andreas Wiesmann, Othmar Frey, Christophe Magnard, Oliver Cartus Gamma Remote Sensing AG Worbstrasse 225, CH-3073 Gümligen 30-Jun-2017 Introduction This information is provided to users of the GAMMA software. It is also available online at This release of the Gamma software includes new programs that provide new capability, additional features to existing programs and bug fixes. Gamma Software on Linux, OSX, and Windows The Gamma software has been compiled and tested on Linux (different distributions), Apple MacOS Sierra ( ), and Windows 7, 8, and 10 (64-bit). Computationally intensive programs such as used in co-registration and resampling and geocoding have been parallelized using the OPENMP API built into the GCC compiler. Processing speed on Linux, OSX, and Windows systems is comparable. Linux Distribution: The Gamma software is developed on Ubuntu 16.4 LTS 64-bit Linux and is tested extensively with this distribution. Hence it is highly recommended to run the software on this distribution. The software has also been compiled for Ubuntu LTS and tested. Announcement: Ubuntu LTS will no longer be supported after the mid 2018 upgrade and we recommend upgrading to LTS as soon as possible. Versions of the Software will also be uploaded for RHEL6, and RHEL7 based on Centos 6, and 7. RHEL5 is no longer supported as some programs cannot be compiled due to outdated Libraries. For installation instructions for the binary LINUX distributions see the Text file INSTALL_linux.txt (provided with the distribution or found in the main directory of the distribution). Apple macos Distribution: The software in this version has been compiled using macos Sierra ( ). You will need to install libraries such as GDAL using MacPorts for your OS version. OSX El Capitan is no longer supported. For installation instructions for the binary macos distributions see the ASCII file INSTALL_macOS_Sierra.txt (provided with the distribution or found in the main directory of the distribution). 1

2 Windows Distribution: The Windows 7, 8, 10 version of the Gamma software is 64-bits and multi-threaded. The software has been compiled under Win10 and will also run on Win7, and 8. The build uses the MINGW64 GCC compiler For installation instructions for the binary Windows distributions see the ASCII file INSTALL_WIN64.txt (provided with the distribution or found in the main directory of the distribution). Documentation: The Gamma documentation browser is an html based system for viewing the web pages and pdf documents. The documentation browser includes for each module a Contents sidebar on the right side of the screen and a search functionalities. The program gamma_doc facilitates the access to the documentation related to a given module or program: gamma_doc gamma_doc DIFF gamma_doc az_proc Opens the main page of the Gamma documentation browser. Opens the DIFF&GEO documentation. Opens the reference manual web page for az_proc. Further information related to the GAMMA Software is available online: General information: gamma-rs.ch/uploads/media/gamma_software_information.pdf Technical reports, conference and journal papers: gamma-rs.ch/uploads/media/gamma_software_references.pdf Release notes / upgrade information: gamma-rs.ch/uploads/media/gamma_software_upgrade_information.pdf Hardware Recommendations Using multi-core processors (2 or more cores) will bring substantial improvement in processing speed due to parallelization of the code base. There should be at least 2 GB RAM available for each processor core with 8 to 16 GB per core recommended. Disk storage requirements for using the Gamma Software effectively depend on the amount of input data and data products that will be produced. Based on our experience we recommend to consider at least 4 TB space, especially when working with stacks of Sentinel-1 or very high resolution data (TerraSAR-X, Cosmo-Skymed) data. The current trend towards larger data products requires substantially increased storage capacities. GAMMA Software Training Courses GAMMA plans to organize in fall 2017 again training courses at GAMMA (near Bern, Switzerland) for SAR/INSAR (MSP/ISP/DIFF&GEO/LAT) and for PSI (IPTA). See also our web-site under 2

3 Significant Changes in the Gamma Software Modules since the End of Release Sentinel-1 IWS burst selection One widely recognized difficulty in S1 IWS data processing, especially when trying to automate such processing, is the identification and selection of corresponding bursts. We addressed this issue and provide now a number of related updates. We defined a new parameter, called burst number, that corresponds to the time difference between the burst sensing time and the ascending node time divided by the burst interval. For corresponding bursts acquired in different orbits of the same track this float value varies only marginally (much less than 1.0). Consequently, once determined, based on a reference scene, it can be used as a unique burst identifier. To support this strategy we added a few additional parameters to the TOPS_par file and updated par_s1_slc to write out these parameters, including for each burst the burst number and the sensor position. Furthermore, programs to determine the common bursts for a pair of acquisitions were added. S1_BURST_tab determines for a pair of S1 images the BURST_tab that can be used to extract from the second scene the bursts present in the first scene (to be used then as input to SLC_copy_S1_TOPS). S1_coreg_TOPS_burst_selection combines calculation of the BURST_tab and copying the data. S1_BURST_tab_from_zipfile indicates for a S1 zipfile for each sub-swath the burst number of the first and last bursts and it prepares for an acquisition that may include multiple zipfiles the BURST_tab files required to copy out the bursts corresponding to the indicated reference scene. Gaofen-3 Support On 10 August 2016 China launched Geofen-3 (GF3) with a multi-polarized C-band SAR. GF3 has various modes from high-resolution SAR imagery (up to 1m) to wide swaths (up to 650km). With a 3m resolution dual-polarization SLC pair we could confirm the InSAR capability of GF3. In the GAMMA Software a program was added to read GF3 SLC data. First results are very promising, indicating a high potential. GF3 Level 2 products (geocoded backscatter images) are provided as GeoTIFF and can be imported into the GAMMA Software using the program par_data_geo. GF3 differential interferogram generated based on a pair of dual-pol. SLC ( _ , B 255m). GF3 C-band HV-pol. coherence product (red: coherence, green: backscatter, blue: backscatter change) TerraSAR-X ScanSAR data A program par_tx_scansar was added to read TerraSAR-X ScanSAR SLC data. The data are kept in the same format as the S1 IWS data (with an TOPS_par per sub-swath). So far the data can be read and mosaics can be generated. 3

4 Offset estimation programs The update of the offset estimation programs (used in co-registration and offset tracking) concerns the following programs: offset_pwr, offset_pwr_tracking, offset_pwr_tracking2, offset_pwrm, offset_pwr_trackingm, offset_pwr_trackingm2, and offset_pwr_list. Modifications include revised interpolation, data filtering, iterative processing, and peak estimation. These modifications should improve the reliability of the results and minimize systematic biases introduced by finite patch size and variable overlap of the patches. The programs were tested on various datasets and are expected to perform correctly even for very small patches (tested using 8x8 patches). Note that the accuracy of the offset measurements is dependent on the patch size. General recommendations and modifications: If SLC data are available, it is preferable to perform the offset estimation on these data rather than on MLI data. Using SLC data, biases caused by an aliasing of the spectrum can be avoided, resulting in more accurate results. The reason for this is the loss of spectral information and resolution due to the multilook. The cross-correlation function oversampling factor option was removed (c_ovr command line parameter), because peak detection now uses a gradient descent algorithm that incorporates high order interpolation. For offset_pwr, offset_pwr_tracking, offset_pwrm, and offset_pwr_trackingm, a new Lanczos interpolation order option has been added (Lanczos order 5 -> 9). 5 (default) provides good interpolation quality and is relatively fast, 9 provides higher interpolation quality but is slower. While the programs work with 8x8 patches, it is recommended to use at least 64x64 patches. 128x128 patches ensure a very reliable offset detection. The patches can have differing values for width and height. In the case where there is a difference in the spatial resolution, the window dimension should in general be adjusted to give approximately square patches. In order to estimate offsets with highest accuracy and minimum bias, it is recommended to carry out an iterative offset estimation using offset_pwr_tracking2 or offset_pwr_trackingm2. Estimating offsets between SLCs: For SLC data, a 2x oversampling should be used to improve the accuracy. ScanSAR and TOPS data should be deramped prior to using the offset estimation programs. A bandwidth fraction option was added. It defines a low-pass filter applied on the complex data and might be useful when no oversampling of the SLC is applied. Its default value is 1.0 (full bandwidth). Reducing the bandwidth is not recommended for ScanSAR and TOPS data that were not previously deramped. A deramp flag option was added: the default behavior is that no deramping of the phase is applied. For most cases the Doppler centroid is close to 0, and therefore no deramping is required. In case of data with larger Doppler centroids, such as for spotlight SAR as well as for some ERS and RADARSAT data, the phase deramping flag should be set to 1. Deramping of the phase requires extra computation so the option can be specified only when required using the command line parameter. The deramping carried out in the offset estimation programs does not support ScanSAR or TOPS data deramping; for this, a dedicated program must be used. A flag was added that allows disabling the low-pass filter on the intensity data (int_filt parameter, the filtering is enabled by default). The low-pass filter is very important for avoiding biases when no oversampling is applied. In that case, it should not be disabled. Disabling the 4

5 low-pass filter may be useful for speeding up the processing when 2x oversampling and large patches are used (128 or larger). Estimating offsets between MLIs: A bandwidth fraction option was added, its default value is 0.8 (80% of the bandwidth). This option permits removing part of the aliased spectrum and thus improves the accuracy of the offset estimates (decrease of the offset bias error). As a drawback, the smaller the processing bandwidth, the greater the uncertainty in the estimated offsets (noisier results). Where greater reduction of bias error is required, reducing the bandwidth from the default value may be required. Oversampling the data provides a minimal improvement in the offset determination because once the SLC data are detected, the spectral aliasing has already occurred and cannot be significantly reduced by oversampling the detected data. If the SLC data were oversampled before detection, then further oversampling of the MLI data will also not be of significant benefit. For more detailed discussion and a detailed assessment of estimation biases and statistical quality parameters it is referred to the related GAMMA technical report available at gamma-rs.ch/uploads/media/gamma_software_references.pdf (also available in the Software Documentation). Ionosphere tools Ionospheric path delay gradients can be quite reliably and efficiently be identified in a splitbeam interferogram. The related processing, starting from the co-registered SLC is supported by the program SBI_INT. We added a program (ionosphere_check) that permits checking an individual SLC for the presence of ionospheric effects. This checking is typically less reliable than SBI, but it requires only an individual SLC (and not an interferometric pair) and consequently it also indicates which SLC includes the ionospheric effects. In the example shown below there are significant effects present in the SLC of Split-spectrum interferometry (dividing the available spectra not in the azimuth direction, but in the range direction) is supported by the new program SSI_INT radian radian SLC azimuth pixel SLC range pixel PALSAR-1 SBI phase _ PALSAR-1 SBI phase _ PALSAR-1 sub-band azi. offset ( ) PALSAR-1 sub-band r. offset ( ) 5

6 Atmosphere tools For ScanSAR and TOPS mode data a large range of look angles is included. To account for this in the modeling of the stratigraphic component we added a program atm_mod2 that includes a related mode that considers the height as well as the cosine of the incidence angle. Interpolation The spatial interpolation of data is a processing step regularly used in the software in the coregistration of data, in the geocoding, and when oversampling data. In this period we started to carefully checked and often improved the interpolators used. In some cases several operators can now be selected as different operators have different strengths and limitations. Along with this update the program interp_data was added, replacing the programs interp_cpx and interp_real; interp_data supports interpolation with Lanczos and B-spline interpolation methods, in addition to the previously available options. Besides the interpolation of fcomplex and float, the new program supports additional formats used in the software. A Technical Report on the interpolation procedures used is in preparation. When interpolating MLI images it is highly recommended to perform the interpolation on the square root of the values, to avoid aliasing issues. Geocoding for tracks different from N-S direction In this period we added support for the geocoding of SAR data acquired in tracks clearly different from the north-south or south-north directions. Such data are acquired by the satellites in regions close to the poles (e.g. in Antarctica), as well as by airborne and terrestrial sensors. The program gc_map processes the data DEM line after DEM line which is not adequate when determining the layover and shadow mask resulting in incorrect layover and shadow masks (which are then potentially also used in pixel_area which will affect the quality of the geocoding refinement and of the terrain normalization of backscatter images. For most satellite data the heading deviates by less than 15 deg. from the north-south direction and consequently the related effects can be neglected. In cases where the deviation is larger, the new program gc_map2 should be used. This program determines the layover and shadow maps in the radar look direction and provides therefore a correct result independent of the heading. The slight disadvantage of gc_map2 is that it is slower than gc_map. For this reason gc_map was kept in the software. 3D tools So far the elevation and orientation angles were used to define a direction vector (e.g. look vector, terrain gradient, flow direction etc.). Programs were now added to also do this using an orthogonal coordinate system as ENU (Easting, Northing, Up). Furthermore, a 3D vector format (3 float values per pixel) is supported as a new format to store data. The ENU look-vector components that define the direction of a line-of-sight displacement obtained using dispmap are determined using the program lk_vec_lt. Similarly, the direction of an azimuth offset component can be determined using the same program. There are programs to convert back and forth between the 3D vector format and 1D float format files (real_to_vec, vec_to_real) and a program supporting vector operations (vec_math). Furthermore, the program dispmap_enu was added to combine multiple displacement components into one combined displacement field (e.g. using several ascending and descending orbit results as well as azimuth and range offsets). Data conversion programs float2double and double2float data format conversion programs were added to the DISP package. Furthermore, the gbyte format was defined to compress radar backscatter data 6

7 from float format (4 bytes/value) to a single byte format using a logarithmic lookup table. The backscatter values (in db) between -32 and +28 db are mapped to the integers between 1 and 255 and stored as 8-bit unsigned bytes. The value 0 is used to indicate "no-data" in the gbyte format. In the backscatter values range between -20 db and -4 db the step between dn values is 0.1 db. The conversion between float and gbyte (and vice versa) is supported by the GAMMA programs float2gbyte, gbyte2float, and disgbyte The exact definition of the gbyte digital numbers used (dn) is as follows: if (dn == 1) db = -32.0; else if (dn < 17) db = 0.5*(dn - 1) ; else if (dn < 37) db = 0.2*(dn - 17) ; else if (dn < 197) db = 0.1*(dn - 37) ; else if (dn < 217) db = 0.2*(dn ) - 4.0; else if (dn < 237) db = 0.5*(dn - 217); else db = 1.0*(dn - 237) + 10; Visualization Tools Python Display Programs and Utilities were added to the DISP to complement the dis and ras programs: colormap_list.py Generate text format colormaps (*.cm) from the registered Matplotlib colormaps vis_colormap_bar.py Generate horizontal or vertical colorbar with scale from colormap file or registered colormap viscpx.py Display of complex data intensity, real, imaginary, magnitude, or phase, with linear, logarithmic, or power-law scaling visdt_pwr.py Display of float data such as displacement or unwrapped phase combined with intensity vismph_pwr.py vispwr.py visras.py Display the phase of float complex data combined with intensity Display of radar intensity, deformation, unwrapped phase, correlation or other parameter with linear, logarithmic, or power-law scaling Display raster images (BMP, PNG, JPEG, TIFF formats) Besides the advantage that very large files can be displayed, the new programs offer a wide visualization and rasterfile (quicklooks as well as rasterfiles with one pixel per data file pixel) generation functionality. Color bars can be drawn with the display and in addition to the color scales used already further color maps (as available from Matplotlib) can be selected. QGIS Plugin A plugin for the Open Source Geographic Information System QGIS ( has been developed that allows for processing synthetic aperture radar data acquired by SENTINEL-1, ERS-1/2, ENVISAT ASAR, Radarsat-1/2, ALOS PALSAR/ALOS-2, JERS, TerraSAR/Tandem-X to radiometric and terrain corrected backscatter intensity images. With the plugin, GAMMA Software functionality for data import (single look complex and ground range detected images), calibration, multi-looking, geocoding, topographic correction, and speckle filtering is made accessible through a simple python-based user interface in QGIS. The plugin can be used with QGIS installations under Windows, Mac OS, and Linux. The tool is not included in the main software release, but provided upon request. For more information please contact: gamma@gamma-rs.ch. 7

8 Gamma Software Demo examples In this period again some Gamma Software Demo examples were added/modified. Gamma Software Users with a valid license or evaluation license can download the Gamma Software Demo examples here: account: user: gamma_user password: RBS_821 Gamma Software Demo examples Demo examples which were added/modified to demonstrate the application of a range of techniques (InSAR, offset tracking, SBI, PSI for Sentinel-1) for Sentinel-1 TOPS mode data. Demo example: S1_Mexico_coreg_demo.tar.gz S1_Greenland_tracking_demo.tar.gz S1_DevonIceCap_demo.tar.gz IPTA_S1_Athens_demo.tar.gz Gamma_demo_SCH.tar.gz Gamma_demo_SBI_PALSAR_Etna.tar.gz Gamma_demo_RSAT2_multi_resolution.tar.gz Gamma_demo_vis.tar.gz Gamma_demo_S1_burst_number.tar.gz Contents Sentinel-1A Co-registration example (reading of SLC data, selection of bursts corresponding to the bursts present in the reference burst SLC (using updated version of par_s1_slc and new program S1_BURST_tab), coregistration, calculation of differential interferogram, deramping, and split-beam interferogram generation). Sentinel-1A offset tracking (co-registration, differential interferogram offset tracking, post-processing of offset field, geocoding of result). The sequence was updated to include an initial offset estimation followed by a second offset estimation using offset_pwr_tracking2 and postprocessing of the results. Sentinel-1 offset tracking example. The example also shows the identification and effects of ionospheric effects on S1 TOPS data. IPTA processing example using S1 data over a small section to the West of Athens. The site includes small areas with fast, potentially non-uniform, motion (related to the compaction of landfills). Example demonstrates IPTA processing for S1 data. Example demonstrates the combined use of single-pixel and multi-look phases. Example demonstrates the use of a multi-reference stack to map fast non-uniform motion and to optimize the spatial coverage achieved. Example demonstrates alternative approaches to separate phase related to deformation and atmospheric path delay. Data consists of stack of co-registered SLC sections. Demonstrating geocoding for orbits clearly different from N-S direction using either SCH coordinates or using the program gc_map2. Demonstrating ionosphere identification, Split-Beam InSAR (SBI), Split-Spectrum InSAR (SSI) on PALSAR-1 data. Demonstrating a multi-resolution RSAT2 DInSAR processing (using SLC with different bandwidths). Visualization and rasterfile generation using the new Python visualization and rasterfile programs vis*. Demonstrating the identification of S1 burst numbers based on the S1 SLC data zipfiles and the preparation of BURST_tabs that suited to generate consistent S1 SLC stacks (including corresponding burst). 8

9 In the following some of the results of the demo examples are shown. S1 DInSAR over Mexico City: geocoded differential interferogram (see S1_Mexico_coreg_demo). The last burst is only available in the reference, therefore the phase values are 0.0 (blue) here. S1Split-Beam Interferogram (SBI) over Mexico City (see S1_Mexico_coreg_demo). S1 IWS range offset field over site in Greenland. S1 IWS azimuth offset field over site in Greenland. S1 split-beam interferometry phase, _ , over Devon Island, indicating significant ionospheric effects. S1 azimuth offset field, _ , over Devon Island, indicating significant ionospheric effects. 9

10 MSP SWAP_io: Added B-spline and Lanczos interpolation methods. Support short, float, double and fcomplex data. Support 1D and 2D data. Include interpolation on the data values, on the log and on the sqrt. B-spline degrees of 2-9 can be used. Laczos orders 3-15 can be used. B- spline requires an initialization step. ISP SWAP_io: see MSP information. error_stat: Added program to permit calculation of the normalized mean square error between two files. This is useful for evaluation of interpolation error or for data modeling. Error can be estimated either for float or fcomplex data. offset_pwr, offset_pwr_tracking, offset_pwr_tracking2: Major update of offset estimation programs: revised interpolation, data filtering, iterative processing, and peak estimation. These modifications should improve the reliability of the results and minimize systematic biases introduced by finite patch size and variable overlap of the patches. SSI_INT: Added script to generate Range Split-Spectrum Interferogram from a co-registered interferometric SLC pair. ionosphere_check: Added script to determine azimuth spectrum sub-band range and azimuth offsets of a single SLC. Non-zero azimuth offsets between the sub-bands are an indication for the presence of ionospheric effects. offset_sub: New program to subtract offsets calculated using a polynomial from a field of offset estimates (as documented in the OFF_par file). par_s1_slc: Now calculating additional parameters to calculate matching bursts when resampling SLC image frames. Sentinel-1 IW and EW SLC image data consist of a set of overlapping bursts. These new parameters permit calculation of time offset relative to the time of the ascending node in units of the time interval between sensing of sequential bursts. The New parameters are described in the update for typedef_isp.h and ISP_io.c typedef_isp.h ISP_io: updated for new parameters to Sentinel-1 TOPS_par including: double asc_node_t0 time of the orbit ascending node (seconds of day) double burst_interval time between bursts (seconds) double sensing_pos[3] satellite position in XYZ at sensing_t0 time double asc_node_delta burst sensing_t0 - ascending_node_t0: (time past asc. node) double burst_asc_node effective burst number ( asc_node_delta/burst_interval) S1_BURST_tab: New script to calculate BURST_tab used by SLC_copy_S1_TOPS so that the SLC2 output has the same number of bursts in each swath as SLC-1 and these bursts cover the same area of the earth surface as the bursts in SLC-1. par_gf3_slc: New program to import Gaofen-3 SLC data and created SLC parameter file and SLC data file as used in GAMMA Software. 10

11 DIFF&GEO vrt2dem: Option added to add a spatial buffer at the edges. geocode_back, resamp_image, map_trans, dem_trans, rotate_image: Added further interpolation methods; SUN raster/bmp/tiff data and unsigned char data are no longer limited to nearest neighbor interpolation method; interpolation is now parallelized using OpenMP for all data types. lk_vec_dt: Added optional output of the azimuth vector for each point in the map. dispmap_enu: Added program to calculate the 3D deformation vector from input LOS or azimuth offsets and look vector or azimuth vector information calculated using lk_vec_dt. atm_mod2: New program added with wider functionality in estimating the stratigraphic atmospheric path delay component. As compared to atm_mod models better suited for very wide swaths (S1, PALSAR ScanSAR) with significant across track variation of the incidence angle were added. SLC_diff_intf: Now supports calculation of the common azimuth bandwidth if the PRFs of the two scenes differ. interp_data: This program replaces the programs interp_cpx and interp_real. interp_data supports interpolation with Lanczos and B-spline interpolation methods. It supports various data formats. offset_pwrm, offset_pwr_trackingm, offset_pwr_trackingm2, offset_pwr_list: Major update of offset estimation programs: revised interpolation, data filtering, iterative processing, and peak estimation. These modifications should improve the reliability of the results and minimize systematic biases introduced by finite patch size and variable overlap of the patches. quad_fit: Added phase model 7: a0 + a1*y. dispmap_vec2: Added mode 2: determine east-west and up-down components (north-south assumed zero). dispmap_sim: Added program to calculate LOS displacement given the displacement in East, North and Up (ENU) for every point in the geometry defined by the DEM parameter file offset_subm: New program to subtract offsets calculated using a polynomial from a field of offset estimates (as documented in the DIFF_par file). fill_gaps: Added gap filling program (inpainting). It includes 6 different methods. Uses CSparse library. gc_map2: New program similar to gc_map. Calculate lookup table and DEM related products (layover and shadow, incidence angle, local resolution, offnadir angle). Generate accurate layover and shadow map for any platform heading. S1_coreg_TOPS_burst_selection: New script to generate S1 burst SLC with bursts corresponding to a reference burst SLC. 11

12 DISP float2double, float2short, float2uchar, double2float, short2float, uchar2float: Moved the conversion tools from LAT to DISP. raspwr: supports now also double precision (8-byte) floating point data. disdt_pwr: Added display program disdt_pwr that permits display of unwrapped phase, deformation or other parameter by specifying data value per color cycle. real_to_vec: Added program to take 3 float valued files and create a file of vectors. Each vector consists of 3 float values that are the components of a vector. replace_values: Added zero_flag option to decide if 0,0 is treated as missing value or as valid value. float2gbyte, gbyte2float: Added routines flt2gb() and gb2flt() to DISPlib.c that support conversion of float data to gamma byte format (GBYTE) by applying a logarithmic mapping from backscatter to byte integer values between 0 and is no-data. The programs float2gbyte and gbyte2float support conversion from float to gbyte and back. Images in gbyte format are one quarter the size of the original float data. Added a definition for gbyte format data to display.h disgbyte, dis2gbyte: New programs to display gbyte format data. rascc, rasdt_pwr, rashgt, rashgt_shd, rasrmg, discc, disdt_pwr, dishgt, disrmg, dismph_pwr, dis2cc, dis2hgt, dis2rmg: Modified so that when no intensity file is specified, regions that are no-data are set to black. colormap_list.py, vis_colormap_bar.py, viscpx.py, visdt_pwr.py, vismph_pwr.py, vispwr, visras.py: Added Python Display Programs and Utilities (see also text above under major changes). ras8_colormap: Added program to generate 8-bit colormap (RMG, HLS, HSV, SIN) in text format and create a colorbar raster file The text format colormaps and text format with RGB values 0-> 255 in 3 columns. rasdt_cmap: Added program to generate a rasterfile of a scene using a selected colormap, with min and max limits. vec_math: Add program to perform arithmetic operations on 3D float vector data. LAT float2double, double2float: Added float to double and double to float conversion tools. float2double, float2short, float2uchar, double2float, short2float, uchar2float: Moved the conversion tools from LAT to DISP. AMI_FILTER_GEO: A new script supporting Advanced Multi Image Filtering of coregistered backscatter data stacks in map geometry. 12

13 IPTA atm_mod_pt: Added new mode to determine range phase shift with respect to slant range to support processing of GPRI2 data with IPTA. mcf_pt, def_mod_pt, multi_def_pt: Valid interferogram pixels (starting pixel) with 0.0 phase are set to 1.18e-38 (smallest float value) so that they are not flagged as "no-data". pt2geo: Modified for GPRI2 data: Now taking into account relative height of the points with respect to the position of the GPRI2. The height of the GPRI2 radar should be specified in the same datum as the DEM. Interface simplified by removal of the mode parameter, pmask_dem can be used to determine if a point is within the DEM or not. xpt_slc: Now uses gradient ascent to estimate maximum. The program was parallelized using OpenMP. The SLC is now read entirely to speed up processing. Correction of error (segmentation fault) that occured when only zeros were read within the search window. Correction of output values when no peak is found (reramp). quad_fit_pt: Added program to calculate a linear or quadratic fit (e.g. of the unwrapped phase) for all points in the point list using least-squares fit. 13