FernandinaSenA106

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

unwrapPhase_wrap_1.png

unwrapPhase_wrap_2.png

unwrapPhase_wrap_3.png

unwrapPhase_wrap_4.png

unwrapPhase_1.png

unwrapPhase_2.png

unwrapPhase_3.png

unwrapPhase_4.png

connectComponent_1.png

connectComponent_2.png

connectComponent_3.png

connectComponent_4.png

avgPhaseVelocity.png

geo_timeseries_ERA5_demErr_wrap10.png

pbaseHistory.png

timeseries_ERA5_demErr_wrap10.png

timeseries_ERA5_wrap10.png

timeseries_wrap10.png

velocityERA5.png

reference_date.txt

20200917

geo_velocity.kmz

FernandinaSenA106.template

######################################################
ssaraopt.platform                 = SENTINEL-1A,SENTINEL-1B
ssaraopt.relativeOrbit            = 106
ssaraopt.startDate                = 20180901

######################################################
topsStack.subswath                = 2 3    # '1 2'
topsStack.numConnections          = 4    # comment
topsStack.azimuthLooks            = 3    # comment
topsStack.rangeLooks              = 11  # comment
topsStack.filtStrength            = 0.2  # comment
topsStack.unwMethod               = snaphu  # comment
topsStack.coregistration          = auto  # [NESD geometry], auto for NESD
#topsStack.referenceDate           = 20151220

######################################################
mintpy.load.autoPath              = yes
mintpy.subset.lalo                  = -0.515:-0.26,-91.67:-91.36
mintpy.compute.cluster            = local #[local / slurm / pbs / lsf / none], auto for none, cluster type
mintpy.compute.numWorker          = 30 #[int > 1 / all], auto for 4 (local) or 40 (non-local), num of workers
mintpy.compute.maxMemory          = 128      #[float > 0.0], auto for 4, max memory to allocate in GB
mintpy.plot.maxMemory          = 128      #[float > 0.0], auto for 4, max memory to allocate in GB
mintpy.unwrapError.method         = phase_closure  #[bridging / phase_closure / bridging+phase_closure / no], auto for no
mintpy.unwrapError.method         = bridging  #[bridging / phase_closure / bridging+phase_closure / no], auto for no
mintpy.unwrapError.method         = bridging+phase_closure  #[bridging / phase_closure / bridging+phase_closure / no], auto for no
mintpy.unwrapError.method         = auto  #[bridging / phase_closure / bridging+phase_closure / no], auto for no
mintpy.networkInversion.parallel  = yes  #[yes / no], auto for no, parallel processing using dask
mintpy.troposphericDelay.method   = auto   # pyaps  #[pyaps / height_correlation / base_trop_cor / no], auto for pyaps
mintpy.geocode.laloStep             = 0.0020,0.0020                 #[-0.000555556,0.000555556 / None], auto for None
mintpy.geocode.laloStep             = 0.0010,0.0010                 #[-0.000555556,0.000555556 / None], auto for None
mintpy.geocode.laloStep             = 0.0005,0.0005                 #[-0.000555556,0.000555556 / None], auto for None
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        = auto     #[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