2020-10-20 02:42:07 +00:00
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######################################################################################
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# Tutorial for alosStack
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# Cunren Liang, October 2020
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######################################################################################
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This is the tutorial of alosStack processor.
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###########################################
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# 0. SET ENVIRONMENT VARIABLE
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###########################################
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Set environment variable 'PATH_ALOSSTACK'
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export PATH_ALOSSTACK=CODE_DIR/contrib/stack/alosStack
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where CODE_DIR is the directory of your isce code. Note that alosStack is not installed when you install
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the software, so CODE_DIR is your code directory rather than installation directory.
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###########################################
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# 1. PREPARE DATA
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###########################################
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1. ALOS-2 data
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Currently the processor only supports the processing of a stack of data acquired in the same mode.
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To find the acquisition mode code, check the unpacked ALOS-2 product. For example, in the following
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file name
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IMG-HH-ALOS2183010685-171012-FBDR1.1__A
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^^^
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FBD (indicated by ^) is the acquisition mode code. Here is the list of acquistion modes:
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Operation Mode | Mode (AUIG2) | Mode (in file name)
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--------------------------------------------------------------
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spotlight | SPT | SBS
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--------------------------------------------------------------
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stripmap | SM1 | UBS, UBD
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| SM2 | HBS, HBD, HBQ
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| SM3 | FBS, FBD, FBQ
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--------------------------------------------------------------
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ScanSAR | WD1 | WBS, WBD, WWS, WWD
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| WD2 | VBS, VBD
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Create a folder such as 'saf_d169', and in this folder, unpack all frames of each date in an individual folder
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named YYMMDD. YYMMDD is the acquistion date, and it must be in this format. Now the data directory should look
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like
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saf_d169_data-------150225-------IMG-HH-ALOS2041062800-150225-WBDR1.1__D-F1
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|__150408 |__IMG-HH-ALOS2041062800-150225-WBDR1.1__D-F2
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|__150520 |__IMG-HH-ALOS2041062800-150225-WBDR1.1__D-F3
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|__150701 |__IMG-HH-ALOS2041062800-150225-WBDR1.1__D-F4
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|__... |__IMG-HH-ALOS2041062800-150225-WBDR1.1__D-F5
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|__IMG-HH-ALOS2041062850-150225-WBDR1.1__D-F1
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|__IMG-HH-ALOS2041062850-150225-WBDR1.1__D-F2
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|__IMG-HH-ALOS2041062850-150225-WBDR1.1__D-F3
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|__IMG-HH-ALOS2041062850-150225-WBDR1.1__D-F4
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|__IMG-HH-ALOS2041062850-150225-WBDR1.1__D-F5
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|__LED-ALOS2041062800-150225-WBDR1.1__D
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|__LED-ALOS2041062850-150225-WBDR1.1__D
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2. DEM and water body
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You MUST FIRST have an account to download DEM and water body. See
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https://github.com/isce-framework/isce2#notes-on-digital-elevation-models
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or
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https://github.com/isce-framework/isce2
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for more details.
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See input xml file alosStack.xml in this folder on how to download DEM and water body.
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###########################################
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# 2. PROCESS DATA
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###########################################
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1. Create and enter a folder for processing data, e.g.
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mkdir saf_d169_proc
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cd saf_d169_proc
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2. Input xml file alosStack.xml can be found in code directory. Copy it to current folder and simply set
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the parameters.
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cp ${PATH_ALOSSTACK}/alosStack.xml ./
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3. Create command files for processing data. Run
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${PATH_ALOSSTACK}/create_cmds.py -stack_par alosStack.xml
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4. Do most of the single date processing. Run
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./cmd_1.sh
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2020-11-09 20:43:12 +00:00
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In cmd_1.sh and other command files, note that you can split the 'for loop' in each step into a number
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of parallel runs. See command file for details.
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Higly recommended parallel processing steps in each command file.
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cmd_1.sh:
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estimate SLC offsets
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resample to a common grid (WD1 SLC size may be up to 7.2 G, so each run requires this much memory!)
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cmd_2.sh
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form interferograms (does not requires a lot of computation, more parallel runs recommended)
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mosaic interferograms (does not requires a lot of computation, more parallel runs recommended)
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cmd_3.sh
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subband interferograms (does not requires a lot of computation, more parallel runs recommended)
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cmd_4.sh
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all steps
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2020-10-20 02:42:07 +00:00
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5. InSAR processing before ionosphere correction. Run
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./cmd_2.sh
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6. Ionosphere correction (if do ionospheric phase estimation, by default True). If the following parameter of
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the input xml file is True (default)
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<!--<property name="do ionospheric phase estimation">True</property>-->
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Run
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./cmd_3.sh
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After it finishes, check the images in folder 'fig_ion' to see if ionosphere estimation is OK for each
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pair. The anomalies include dense fringes or slight phase difference between adjacent swaths in ScanSAR
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interferograms after removing ionosphere. There might also be dense fringes elsewhere. These are all anomalies
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and the associated ionosphere estimation results should not be used in the next steps.
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At the end of this command file, there is a step called 'estimate ionospheric phase for each date'. If you found
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some pairs with ionosphere estimation anomalies, specify them by adding argument '-exc_pair' to the command ion_ls.py.
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Make sure all dates are still connected after excluding these pairs, and then run ion_ls.py.
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You can plot baselines to see if the pairs are fully connected, e.g.
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${PATH_ALOSSTACK}/plot_baseline.py -baseline baseline/baseline_center.txt -pairs_dir pairs_ion -pairs_exc 150520-150701 -output baselines.pdf
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If the following parameters of the input xml file are True (default)
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<!--<property name="do ionospheric phase estimation">True</property>-->
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<!--<property name="apply ionospheric phase correction">True</property>-->
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there is a final step called 'correct ionosphere' in cmd_3.sh, uncomment the code marked by '#uncomment to run this command'
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and then run the entire step.
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7. InSAR processing after ionosphere correction. Run
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./cmd_4.sh
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If everything is OK, you may consider removing the huge slc files in folder dates_resampled. When you need them in
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the future, you can re-run the commands in the '#resample to a common grid' step in cmd_1.sh.
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Furthermore, you may consider removing the huge original data files you unpacked previously.
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###########################################
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# 3. ADDING MORE DATES
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###########################################
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Sometimes we want to add new acquistions to the already processed stack. To do this,
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1. Upack the new acquistions in data directory following #1. PREPARE DATA.
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2. Repeat the processing in #2. PROCESS DATA.
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We recommend saving previous command files in a folder before new processing. Note that even the previously processed
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pairs will be reprocessed again by cmd_4.sh if the following parameters of the input xml file are True (default)
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<!--<property name="do ionospheric phase estimation">True</property>-->
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<!--<property name="apply ionospheric phase correction">True</property>-->
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because ionospheric phase will be estimated by ion_ls.py at the end of cmd_3.sh for each date with new pairs included,
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and therefore all steps after ion_ls.py should be reprocessed.
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###########################################
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# 4. CHECK RESULTS
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###########################################
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baseline basline files
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burst_synchronization.txt burst synchronization
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dates original date of each date
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dates_ion ionospheric phase of each date
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dates_resampled resampled date of each date. Data of all other dates are coregistered to reference date.
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The parameter xml files including *.track.xml and f*_*/*.frame.xml are in reference date
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folder. These should be the files you should use in most cases, such as looking for data
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parameters, preparing for time series analysis etc.
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fig_ion figures for checking ionosphere estimation results
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pairs pairs of InSAR processing
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pairs_ion pairs for ionosphere estimation
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If you want to know more details about the files in each folder, read
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CODE_DIR/examples/input_files/alos2/alos2_tutorial.txt
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File name conventions and directory structures are mostly the same.
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###########################################
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# 5. KNOWN ISSUES
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###########################################
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1. Issues with Ionospheric Correction
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According to our experience, ionospheric correction works for most of the interferograms. Because it
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relies on coherence and phase unwrapping, it does not work in some cases. These include:
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(1) data have low coherence
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(2) the majority of the imaged area is low coherence area like lake, ocean...
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(3) the imaged area is completely divided into several isolated areas by low coherence areas, such as
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islands.
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In addition to the above issues, there are also data-mode-related issues.
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(1) ScanSAR-ScanSAR interferometry. While you can process one single subswath, it's better to process
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more than one subswath if the addistional subswath has good coherence. This is good for ionospheric
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correction.
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(2) Range distortions in JAXA product. This mostly happens in stripmap-stripmap interferometry using
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data not covering Japan. If you see very dense fringes in the corrected inteferogram, probably it is
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caused by this problem. This has been reported to JAXA and JAXA is working on debugging the focusing
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program.
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UPDATE: On November 20, 2018 (JST), JAXA updated the software for PALSAR-2 standard products. Therefore,
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if your product is ordered after this time, you don't have this problem.
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2. How do I improve ionospheric correction?
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First of all, we recommend reading through cmd_3.sh before manually improving ionosphere estimation results.
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Isolated areas lead to relative phase unwrapping errors, and therefore leads to significant errors in ionosphere
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estimation result, usually shown as dense fringes in the corrected interferograms. If your scene covers an area
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with two or more isolated areas and you are interested in one of the areas, you can mask out the other areas by
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setting "areas masked out in ionospheric phase estimation".
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Or if you have processed the data, you can also specify the argument -masked_areas in ion_filt.py in cmd_3.sh.
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Then check the updated results following step '#check ionosphere estimation results' in cmd_3.sh
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For ScanSAR, the software uses some accurate values for removing phase difference between adjacent swaths.
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This, however, does not work well sometimes as a result of the inconistencies between different JAXA products,
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especially products processed by different versions of JAXA software. As a result of this, you may see dense
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fringes in the ionospheric correction result. In this case, you can try not to use aforementioned accurate
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values by setting -snap in ion_subband.py in cmd_3.sh, and run this command and the remaining commands to see
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if ionosphere estimation results have improvement.
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Note that each time you updated ionosphere estimation results, you need to re-run the steps after
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'#estimate ionospheric phase for each date' (including this step) in cmd_3.sh, as well as cmd_4.sh
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4. ScanSAR burst synchronization
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For ScanSAR data acquired before February 8, 2015, chances of having enough burst synchronization for
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interferometry are very low. Don't include data acquired before this date in your stack processing.
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###########################################
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# 6. REFRENCES
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###########################################
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The methods and algorithms implemented can be found in the following papers.
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1. ScanSAR or multi-mode InSAR processing
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C. Liang and E. J. Fielding, "Interferometry with ALOS-2 full-aperture ScanSAR data,"
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IEEE Transactions on Geoscience and Remote Sensing, vol. 55, no. 5, pp. 2739-2750, May 2017.
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2. Ionospheric correction, burst-by-burst ScanSAR processing, and burst-mode spectral diversity (SD) or
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multi-aperture InSAR (MAI) processing
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C. Liang and E. J. Fielding, "Measuring azimuth deformation with L-band ALOS-2 ScanSAR interferometry,"
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IEEE Transactions on Geoscience and Remote Sensing, vol. 55, no. 5, pp. 2725-2738, May 2017.
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3. Ionospheric correction
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C. Liang, Z. Liu, E. J. Fielding, and R. Bürgmann, "InSAR time series analysis of L-band wide-swath SAR
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data acquired by ALOS-2,"
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IEEE Transactions on Geoscience and Remote Sensing, vol. 56, no. 8, pp. 4492-4506, Aug. 2018.
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