RaungSenDT105

geo_velocity.png

geo_velocity.png

geo_temporalCoherence.png

geo_temporalCoherence.png

geo_maskTempCoh.png

geo_maskTempCoh.png

geo_avgSpatialCoh.png

geo_avgSpatialCoh.png

temporalCoherence.png

temporalCoherence.png

maskTempCoh.png

maskTempCoh.png

avgSpatialCoh.png

avgSpatialCoh.png

maskConnComp.png

maskConnComp.png

numTriNonzeroIntAmbiguity.png

numTriNonzeroIntAmbiguity.png

numInvIfgram.png

numInvIfgram.png

velocity.png

velocity.png

geometryRadar.png

geometryRadar.png

coherence_1.png

coherence_1.png

coherence_2.png

coherence_2.png

coherence_3.png

coherence_3.png

coherence_4.png

coherence_4.png

coherence_5.png

coherence_5.png

coherence_6.png

coherence_6.png

unwrapPhase_wrap_1.png

unwrapPhase_wrap_1.png

unwrapPhase_wrap_2.png

unwrapPhase_wrap_2.png

unwrapPhase_wrap_3.png

unwrapPhase_wrap_3.png

unwrapPhase_wrap_4.png

unwrapPhase_wrap_4.png

unwrapPhase_wrap_5.png

unwrapPhase_wrap_5.png

unwrapPhase_wrap_6.png

unwrapPhase_wrap_6.png

unwrapPhase_1.png

unwrapPhase_1.png

unwrapPhase_2.png

unwrapPhase_2.png

unwrapPhase_3.png

unwrapPhase_3.png

unwrapPhase_4.png

unwrapPhase_4.png

unwrapPhase_5.png

unwrapPhase_5.png

unwrapPhase_6.png

unwrapPhase_6.png

connectComponent_1.png

connectComponent_1.png

connectComponent_2.png

connectComponent_2.png

connectComponent_3.png

connectComponent_3.png

connectComponent_4.png

connectComponent_4.png

connectComponent_5.png

connectComponent_5.png

connectComponent_6.png

connectComponent_6.png

timeseries_ERA5_demErr_wrap10_1.png

timeseries_ERA5_demErr_wrap10_1.png

timeseries_ERA5_wrap10_1.png

timeseries_ERA5_wrap10_1.png

timeseries_ERA5_demErr_wrap10_2.png

timeseries_ERA5_demErr_wrap10_2.png

timeseries_ERA5_wrap10_2.png

timeseries_ERA5_wrap10_2.png

geo_timeseries_ERA5_demErr_wrap10_2.png

geo_timeseries_ERA5_demErr_wrap10_2.png

geo_timeseries_ERA5_demErr_wrap10_1.png

geo_timeseries_ERA5_demErr_wrap10_1.png

timeseries_wrap10_1.png

timeseries_wrap10_1.png

avgPhaseVelocity.png

avgPhaseVelocity.png

timeseries_wrap10_2.png

timeseries_wrap10_2.png

velocityERA5.png

velocityERA5.png

reference_date.txt

20190531

RaungSenDT105.template

######################################################
cleanopt                          = 0   # [ 0 / 1 / 2 / 3 / 4]   0,1: none 2: keep merged,geom_master,SLC 3: keep MINTPY 4: everything
processor                         = isce
ssaraopt.platform                 = SENTINEL-1A,SENTINEL-1B
ssaraopt.relativeOrbit            = 105
ssaraopt.startDate                = 20160101
ssaraopt.endDate                  = 20231014
hazard_products_flag              = False
insarmaps_flag                     = True

######################################################
topsStack.boundingBox             = -8.2 -8.0 113.9 114.1    # -1 0.15 -91.6 -90.9 

topsStack.subswath                = 2 # '1 2'
topsStack.numConnections          = 4    # comment
topsStack.azimuthLooks            = 6    # comment
topsStack.rangeLooks              = 24   # 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                  = -8.2:-8.0,113.9:114.1
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.reference.lalo             = -8.30,115.55     # S of SN
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             = 0.0008,0.0008                 #[-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