HawaiiKoaeSenA124
miaplpy/network_delaunay_4/pic
geo_velocity.png
geo_temporalCoherence.png
geo_temporalCoherence_lowpass_gaussian.png
geo_maskTempCoh.png
geo_maskTempCoh_lowpass_gaussian.png
geo_maskPS.png
temporalCoherence.png
temporalCoherence_lowpass_gaussian.png
maskTempCoh.png
maskTempCoh_lowpass_gaussian.png
maskPS.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
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_1.png
unwrapPhase_2.png
unwrapPhase_3.png
unwrapPhase_4.png
unwrapPhase_5.png
unwrapPhase_6.png
unwrapPhase_7.png
connectComponent_1.png
connectComponent_2.png
connectComponent_3.png
connectComponent_4.png
connectComponent_5.png
connectComponent_6.png
connectComponent_7.png
timeseries_ERA5_demErr_wrap10_1.png
timeseries_ERA5_demErr_wrap10_2.png
timeseries_ERA5_demErr_wrap10_3.png
timeseries_ERA5_wrap10_1.png
timeseries_ERA5_wrap10_2.png
timeseries_ERA5_wrap10_3.png
geo_timeseries_ERA5_demErr_wrap10_1.png
geo_timeseries_ERA5_demErr_wrap10_2.png
geo_timeseries_ERA5_demErr_wrap10_3.png
avgPhaseVelocity.png
pbaseHistory.png
timeseries_wrap10_1.png
timeseries_wrap10_2.png
timeseries_wrap10_3.png
velocityERA5.png
reference_date.txt
20210422
geo_velocity.kmz
Download file.
HawaiiKoaeSenA124.template
####################
every_day_flag = yes
processor = isce
parallel = yes
cleanopt = 0
hazard_products_flag = TRUE
ssaraopt.platform = SENTINEL-1A,SENTINEL-1B
ssaraopt.relativeOrbit = 124
####################
topsStack.boundingBox = 18.9 20.0 -156.1 -154.5 # '-1 0.15 -91.6 -90.9'
topsStack.subswath = 2 3 # '1 2'
topsStack.numConnections = 4 # comment
topsStack.azimuthLooks = 2 # comment
topsStack.rangeLooks = 8 # 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 = 20161021,20200301
####################
#mintpy.reference.lalo = 19.5059, -155.3477
mintpy.troposphericDelay.method = auto #[pyaps / height_correlation / base_trop_cor / no], auto for pyaps
#mintpy.network.startDate = 20200801 # [20090101 / no], auto for no
mintpy.geocode.laloStep = 0.0002,0.0002 #[-0.000555556,0.000555556 / None], auto for None, output resolution in degree
mintpy.geocode.laloStep = 0.0008,0.0008 #[-0.000555556,0.000555556 / None], auto for None, output resolution in degree
mintpy.load.autoPath = yes
mintpy.compute.cluster = local
mintpy.compute.numWorker = 32
mintpy.solidEarthTides = no #[yes / no], auto for no
#mintpy.timeFunc.stepDate = 20210306 #[20110311,20170908 / 20120928T1733 / no], auto for no, step function(s)
#mintpy.reference.lalo = 19.58,-155.46
#mintpy.subset.lalo = 19.38:19.53,-155.69:-155.45 #[S:N,W:E / no], auto for no
#mintpy.subset.lalo = 19.31:19.60,-155.74:-155.40 #[S:N,W:E / no], auto for no
#mintpy.subset.lalo = 19.23:19.68,-155.83:-155.31 #[S:N,W:E / no], auto for no
#mintpy.subset.lalo = 19.43:19.51,-155.65:-155.54 #[S:N,W:E / no], auto for no
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.reference.lalo = 19.52,-155.56 # 19.52,-155.56 for Asc, 19.52,-155.51 for Desc
#mintpy.subset.lalo = 19.43:19.51,-155.65:-155.54 #[S:N,W:E / no], auto for no
#mintpy.subset.lalo = 19.31:19.60,-155.74:-155.40 #[S:N,W:E / no], auto for no
#mintpy.subset.lalo = 19.23:19.68,-155.83:-155.31 #[S:N,W:E / no], auto for no
mintpy.subset.lalo = 19.28:19.4,-155.355:-155.200 #[S:N,W:E / no], auto for no
miaplpy.subset.lalo = 19.28:19.4,-155.355:-155.200 #[S:N,W:E / no], auto for no
###### Southwest Rift Zone ######
#minsar.miaplpyDir.addition = SWRZ1 #[name / lalo / no ] auto for no (miaply_$name_startDate_endDate))
#mintpy.subset.lalo = 19.337:19.349,-155.345:-155.328 #[S:N,W:E / no], auto for no
#miaplpy.subset.lalo = 19.337:19.349,-155.345:-155.328 #[S:N,W:E / no], auto for no
####################
miaplpy.interferograms.networkType = delaunay # network
miaplpy.timeseries.minTempCoh = 0.75 # auto for 0.5
mintpy.networkInversion.minTempCoh = 0.75 # auto for 0.5
minsar.insarmaps_flag = True # [PS,DS,PSDS,geo,all], miaplpy dataset to ingest (Default: geo) (MintPy is always geo)
minsar.insarmaps_dataset = filt*DS # [PS,DS,PSDS,geo,all], miaplpy dataset to ingest (Default: geo) (MintPy is always geo)