positional arguments:¶

timeseries_file

Time series file for velocity inversion.

options:¶

-h, --help

show this help message and exit

--template TEMPLATE_FILE, -t TEMPLATE_FILE

template file with options

--ts-cov-file TS_COV_FILE

Time-series (co)variance file for velocity STD calculation

-o OUTFILE, --output OUTFILE

output file name

--update

Enable update mode, and skip estimation if: 1) output velocity file already exists, readable and newer than input file 2) all configuration parameters are the same.

--ref-lalo LAT LON

Change reference point LAT LON for estimation.

--ref-yx Y X

Change reference point Y X for estimation.

--ref-date DATE

Change reference date for estimation.

--ram MAXMEMORY, --memory MAXMEMORY

Max amount of memory in GB to use (default: 4.0). Adjust according to your computer memory.

dates of interest:¶

--start-date STARTDATE, -s STARTDATE

start date for velocity estimation

--end-date ENDDATE, -e ENDDATE

end date for velocity estimation

--exclude EXCLUDEDATE [EXCLUDEDATE ...], --ex EXCLUDEDATE [EXCLUDEDATE ...]

date(s) not included in velocity estimation, i.e.: --exclude 20040502 20060708 20090103 --exclude exclude_date.txt exclude_date.txt: 20040502 20060708 20090103

bootstrapping:¶

estimating the mean / STD of the velocity estimator

--bootstrap, --bootstrapping

Enable bootstrapping to estimate the mean and STD of the velocity estimator.

--bc BOOTSTRAPCOUNT, --bootstrap-count BOOTSTRAPCOUNT

number of iterations for bootstrapping (default: 400).

Deformation Model:¶

A suite of time functions

--poly POLYNOMIAL, --polynomial POLYNOMIAL, --poly-order POLYNOMIAL

a polynomial function with the input degree (default: 1). E.g.: --poly 1 # linear --poly 2 # quadratic --poly 3 # cubic

--periodic PERIODIC [PERIODIC ...], --period PERIODIC [PERIODIC ...], --peri PERIODIC [PERIODIC ...]

periodic function(s) with period in decimal years (default: []). E.g.: --periodic 1.0 # an annual cycle --periodic 1.0 0.5 # an annual cycle plus a semi-annual cycle

--step STEP [STEP ...]

step function(s) at YYYYMMDD (default: []). E.g.: --step 20061014 # coseismic step at 2006-10-14T00:00 --step 20110311 20120928T1733 # coseismic steps at 2011-03-11T00:00 and 2012-09-28T17:33

--exp EXP [EXP ...], --exponential EXP [EXP ...]

exponential function(s) at YYYYMMDD with characteristic time(s) tau in decimal days (default: []). E.g.: --exp 20181026 60 # exp onset at 2006-10-14T00:00 with tau=60 days --exp 20181026T1355 60 120 # exp onset at 2006-10-14T13:55 with tau=60 days overlayed by a tau=145 days --exp 20161231 80.5 --exp 20190125 100 # 1st exp onset at 2011-03-11 with tau=80.5 days and

# 2nd exp onset at 2012-09-28 with tau=100

days

--log LOG [LOG ...], --logarithmic LOG [LOG ...]

logarithmic function(s) at YYYYMMDD with characteristic time(s) tau in decimal days (default: []). E.g.: --log 20181016 90.4 # log onset at 2006-10-14T00:00 with tau=90.4 days --log 20181016T1733 90.4 240 # log onset at 2006-10-14T17:33 with tau=90.4 days overlayed by a tau=240 days --log 20161231 60 --log 20190125 180.2 # 1st log onset at 2011-03-11 with tau=60 days and

# 2nd log onset at 2012-09-28 with tau=180.2 days

Residual file:¶

Save residual displacement time-series to HDF5 file.

--save-res, --save_residual

Save the residual displacement time-series to HDF5 file.

--res-file RES_FILE, --residual-file RES_FILE

Output file name for the residual time-series file (default: timeseriesResidual.h5).

template options:¶

## Estimate linear velocity and its standard deviation from time-series ## and from tropospheric delay file if exists. ## reference: Fattahi and Amelung (2015, JGR) mintpy.velocity.excludeDate = auto #[exclude_date.txt / 20080520,20090817 / no], auto for exclude_date.txt mintpy.velocity.startDate = auto #[20070101 / no], auto for no mintpy.velocity.endDate = auto #[20101230 / no], auto for no

## Bootstrapping ## reference: Efron and Tibshirani (1986, Stat. Sci.) mintpy.velocity.bootstrap = auto #[yes / no], auto for no, use bootstrap mintpy.velocity.bootstrapCount = auto #[int>1], auto for 400, number of iterations for bootstrapping

references:¶

Fattahi, H., and F. Amelung (2015), InSAR bias and uncertainty due to the systematic and stochastic tropospheric delay, Journal of Geophysical Research: Solid Earth, 120(12), 8758-8773, doi:10.1002/2015JB012419.

Efron, B., and R. Tibshirani (1986), Bootstrap methods for standard errors, confidence intervals, and other measures of statistical accuracy, Statistical science, 54-75, doi:10.1214/ss/1177013815.

example:¶

timeseries2velocity.py

timeseries_ERA5_demErr.h5

timeseries2velocity.py

timeseries_ERA5_demErr_ramp.h5 -t KyushuT73F2980_2990AlosD.template

timeseries2velocity.py

timeseries.h5 --start-date 20080201 --end-date 20100508

timeseries2velocity.py

timeseries.h5 --exclude exclude_date.txt

timeseries2velocity.py

LS-PARAMS.h5

timeseries2velocity.py

NSBAS-PARAMS.h5

timeseries2velocity.py

TS-PARAMS.h5

# bootstrapping for STD calculation timeseries2velocity.py timeseries_ERA5_demErr.h5 --bootstrap

# complex time functions timeseries2velocity.py timeseries_ERA5_ramp_demErr.h5 --poly 3 --period 1 0.5 --step 20170910 timeseries2velocity.py timeseries_ERA5_demErr.h5 --poly 1 --exp 20170910 90 timeseries2velocity.py timeseries_ERA5_demErr.h5 --poly 1 --log 20170910 60.4 timeseries2velocity.py timeseries_ERA5_demErr.h5 --poly 1 --log 20170910 60.4 200 --log 20171026 200.7