EtnaSenA44

mintpy/pic

geo_velocity.png

geo_temporalCoherence.png

geo_maskTempCoh.png

temporalCoherence.png

maskTempCoh.png

geo_avgSpatialCoh.png

avgSpatialCoh.png

maskConnComp.png

network.png

coherenceHistory.png

coherenceMatrix.png

rms_timeseriesResidual_ramp.png

numTriNonzeroIntAmbiguity.png

numInvIfgram.png

velocity.png

geometryRadar.png

coherence_1.png

coherence_2.png

coherence_3.png

coherence_4.png

coherence_5.png

coherence_6.png

coherence_7.png

coherence_8.png

coherence_9.png

coherence_10.png

coherence_11.png

coherence_12.png

coherence_13.png

unwrapPhase_wrap_1.png

unwrapPhase_wrap_2.png

unwrapPhase_wrap_3.png

unwrapPhase_wrap_4.png

unwrapPhase_wrap_5.png

unwrapPhase_wrap_6.png

unwrapPhase_wrap_7.png

unwrapPhase_wrap_8.png

unwrapPhase_wrap_9.png

unwrapPhase_wrap_10.png

unwrapPhase_wrap_11.png

unwrapPhase_wrap_12.png

unwrapPhase_wrap_13.png

unwrapPhase_1.png

unwrapPhase_2.png

unwrapPhase_3.png

unwrapPhase_4.png

unwrapPhase_5.png

unwrapPhase_6.png

unwrapPhase_7.png

unwrapPhase_8.png

unwrapPhase_9.png

unwrapPhase_10.png

unwrapPhase_11.png

unwrapPhase_12.png

unwrapPhase_13.png

connectComponent_1.png

connectComponent_2.png

connectComponent_3.png

connectComponent_4.png

connectComponent_5.png

connectComponent_6.png

connectComponent_7.png

connectComponent_8.png

connectComponent_9.png

connectComponent_10.png

connectComponent_11.png

connectComponent_12.png

connectComponent_13.png

timeseries_ERA5_demErr_wrap10_1.png

timeseries_ERA5_demErr_wrap10_2.png

timeseries_ERA5_demErr_wrap10_3.png

timeseries_ERA5_demErr_wrap10_4.png

timeseries_ERA5_wrap10_1.png

timeseries_ERA5_wrap10_2.png

timeseries_ERA5_wrap10_3.png

timeseries_ERA5_wrap10_4.png

geo_timeseries_ERA5_demErr_wrap10_1.png

geo_timeseries_ERA5_demErr_wrap10_2.png

geo_timeseries_ERA5_demErr_wrap10_3.png

geo_timeseries_ERA5_demErr_wrap10_4.png

avgPhaseVelocity.png

pbaseHistory.png

timeseries_wrap10_1.png

timeseries_wrap10_2.png

timeseries_wrap10_3.png

timeseries_wrap10_4.png

velocityERA5.png

reference_date.txt

20240206

geo_velocity.kmz

EtnaSenA44.template

######################################################
ssaraopt.platform                  = SENTINEL-1  # [Sentinel-1 / ALOS2 / RADARSAT2 / TerraSAR-X / COSMO-Skymed]
ssaraopt.relativeOrbit             = 44
ssaraopt.startDate                 = 20140701  # YYYYMMDD
######################################################
topsStack.subswath                 = 1 2 3 # '1 2'
topsStack.numConnections           = 4    # comment
topsStack.azimuthLooks             = 5    # comment
topsStack.rangeLooks               = 20   # comment
topsStack.filtStrength             = 0.2  # comment
topsStack.unwMethod                = snaphu  # comment
topsStack.coregistration           = auto  # [NESD geometry], auto for NESD
#topsStack.excludeDates            =  20240926
######################################################
mintpy.load.autoPath               = yes
mintpy.compute.cluster             = local #[local / slurm / pbs / lsf / none], auto for none, cluster type
mintpy.compute.numWorker           = 40 #[int > 1 / all], auto for 4 (local) or 40 (non-local), num of workers
mintpy.plot.maxMemory              = 180  #[float], auto for 4, max memory used by one call of view.py for plotting.
mintpy.networkInversion.parallel   = yes  #[yes / no], auto for no, parallel processing using dask
mintpy.save.hdfEos5                = yes   #[yes / update / no], auto for no, save timeseries to UNAVCO InSAR Archive format
mintpy.save.hdfEos5.update         = yes   #[yes / no], auto for no, put XXXXXXXX as endDate in output filename
mintpy.save.hdfEos5.subset         = yes   #[yes / no], auto for no, put subset range info in output filename
mintpy.save.kmz                    = yes   #[yes / no], auto for yes, save geocoded velocity to Google Earth KMZ file
mintpy.reference.minCoherence      = auto      #[0.0-1.0], auto for 0.85, minimum coherence for auto method
mintpy.troposphericDelay.method    = auto   # pyaps  #[pyaps / height_correlation / base_trop_cor / no], auto for pyaps
mintpy.networkInversion.minTempCoh = 0.6 #[0.0-1.0], auto for 0.7, min temporal coherence for mask
######################################################
miaplpy.load.processor               = isce
miaplpy.multiprocessing.numProcessor = 40
miaplpy.inversion.rangeWindow        = 24   # range window size for searching SHPs, auto for 15
miaplpy.inversion.azimuthWindow      = 7    # azimuth window size for searching SHPs, auto for 15
miaplpy.timeseries.tempCohType       = full     # [full, average], auto for full.
miaplpy.interferograms.networkType   = delaunay # network
miaplpy.unwrap.snaphu.tileNumPixels  = 10000000000     # number of pixels in a tile, auto for 10000000
######################################################
minsar.miaplpyDir.addition           = date  #[name / lalo / no] auto for no (miaply_$name_startDate_endDate))
mintpy.subset.lalo                   = 37.489:37.905,14.747:15.266    #[S:N,W:E / no], auto for no
miaplpy.subset.lalo                  = 37.525:37.825,15.050:15.210    #[S:N,W:E / no], auto for no
miaplpy.load.startDate               = auto  # 20200101
miaplpy.load.endDate                 = auto
mintpy.geocode.laloStep              = 0.0008,0.0008
#mintpy.geocode.laloStep              = 0.00013474667624865252,0.00014
miaplpy.timeseries.minTempCoh        = 0.75      # auto for 0.5
mintpy.networkInversion.minTempCoh   = 0.75
######################################################
minsar.insarmaps_flag                = True
minsar.upload_flag                   = True
minsar.insarmaps_dataset             = filt*DS