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MINTPY-UNWRAP_ERROR_PHASE_CLOSURE(1) | User Commands | MINTPY-UNWRAP_ERROR_PHASE_CLOSURE(1) |
NAME¶
mintpy-unwrap_error_phase_closure - Unwrapping Error Correction based on Phase Closure
DESCRIPTION¶
usage: unwrap_error_phase_closure.py [-h] [-c CC_MASK_FILE] [-n NUMSAMPLE]
- [-m CONNCOMPMINAREA]
- [-a {calculate,correct}] [-i DATASETNAMEIN] [-o DATASETNAMEOUT] [--water-mask WATERMASKFILE] [-t TEMPLATE_FILE] [--update] ifgram_file
Unwrapping Error Correction based on Phase Closure
- by exploiting the conservertiveness of the integer ambiguity of interferograms triplets. This method assumes: a. abundance of network: for interferogram with unwrapping error, there is
- at least of one triangular connection to form a closed circle; with more closed circles comes better constrain.
- b. majority rightness: most of interferograms have to be right (no unwrapping
- error) to correct the wrong minority. And if most of interferograms have unwrapping errors, then the minor right interferograms will turn into wrong.
positional arguments:¶
- ifgram_file
- interferograms file to be corrected
options:¶
- -h, --help
- show this help message and exit
- -c CC_MASK_FILE, --cc-mask CC_MASK_FILE
- common connected components file, required for --action correct
- -n NUMSAMPLE, --num-sample NUMSAMPLE
- Number of randomly samples/pixels for each common connected component.
- -m CONNCOMPMINAREA, --min-area CONNCOMPMINAREA
- minimum region/area size of a single connComponent.
- -a {calculate,correct}, --action {calculate,correct}
- action to take (default: correct): correct - correct phase unwrapping error calculate - calculate the number of non-zero closure phase
- -i DATASETNAMEIN, --in-dataset DATASETNAMEIN
- name of dataset to be corrected, default: unwrapPhase
- -o DATASETNAMEOUT, --out-dataset DATASETNAMEOUT
- name of dataset to be written after correction, default: {}_phaseClosure
- --update
- Enable update mode: if unwrapPhase_phaseClosure dataset exists, skip the correction.
mask:¶
- --water-mask WATERMASKFILE, --wm WATERMASKFILE
- path of water mask file.
- -t TEMPLATE_FILE, --template TEMPLATE_FILE
- template file with options for setting.
reference:¶
- Yunjun, Z., H. Fattahi, and F. Amelung (2019), Small baseline InSAR time series analysis: Unwrapping error correction and noise reduction, Computers & Geosciences, 133, 104331, doi:10.1016/j.cageo.2019.104331.
template options:¶
- ## A quick assessment of: ## 1) possible groud deformation ## using the velocity from the traditional interferogram stacking ## reference: Zebker et al. (1997, JGR) ## 2) distribution of phase unwrapping error ## from the number of interferogram triplets with non-zero integer ambiguity of closue phase ## reference: T_int in Yunjun et al. (2019, CAGEO). Related to section 3.2, equation (8-9) and Fig. 3d-e.
template options:¶
- ## connected components (mintpy.load.connCompFile) are required for this step. ## SNAPHU (Chem & Zebker,2001) is currently the only unwrapper that provides connected components as far as we know. ## reference: Yunjun et al. (2019, section 3) ## supported methods: ## a. phase_closure - suitable for highly redundant network ## b. bridging - suitable for regions separated by narrow decorrelated features, e.g. rivers, narrow water bodies ## c. bridging+phase_closure - recommended when there is a small percentage of errors left after bridging mintpy.unwrapError.method = auto #[bridging / phase_closure / bridging+phase_closure / no], auto for no mintpy.unwrapError.waterMaskFile = auto #[waterMask.h5 / no], auto for waterMask.h5 or no [if not found] mintpy.unwrapError.connCompMinArea = auto #[1-inf], auto for 2.5e3, discard regions smaller than the min size in pixels
- ## phase_closure options: ## numSample - a region-based strategy is implemented to speedup L1-norm regularized least squares inversion. ## Instead of inverting every pixel for the integer ambiguity, a common connected component mask is generated, ## for each common conn. comp., numSample pixels are radomly selected for inversion, and the median value of the results ## are used for all pixels within this common conn. comp. mintpy.unwrapError.numSample = auto #[int>1], auto for 100, number of samples to invert for common conn. comp.
- ## briding options: ## ramp - a phase ramp could be estimated based on the largest reliable region, removed from the entire interferogram ## before estimating the phase difference between reliable regions and added back after the correction. ## bridgePtsRadius - half size of the window used to calculate the median value of phase difference mintpy.unwrapError.ramp = auto #[linear / quadratic], auto for no; recommend linear for L-band data mintpy.unwrapError.bridgePtsRadius = auto #[1-inf], auto for 50, half size of the window around end points
example:¶
- # correct phase unwrapping error with phase closure unwrap_error_phase_closure.py ./inputs/ifgramStack.h5 --cc-mask maskConnComp.h5 -t smallbaselineApp.cfg --update unwrap_error_phase_closure.py ./inputs/ifgramStack.h5 --cc-mask maskConnComp.h5 --water-mask waterMask.h5 --update
- # calculate the number of non-zero closure phase unwrap_error_phase_closure.py ./inputs/ifgramStack.h5 --action calculate unwrap_error_phase_closure.py ./inputs/ifgramStack.h5 --action calculate --water-mask waterMask.h5
May 2022 | mintpy-unwrap_error_phase_closure v1.3.3 |