MontserratSenD54
miaplpy_202301_202401/network_single_reference/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

numInvIfgram.png

velocity.png

geometryRadar.png

avgPhaseVelocity.png

coherence.png

connectComponent.png

geo_timeseries_ERA5_demErr_wrap10.png

pbaseHistory.png

timeseries_ERA5_demErr_wrap10.png

timeseries_ERA5_wrap10.png

timeseries_wrap10.png

unwrapPhase.png

unwrapPhase_wrap.png

velocityERA5.png

reference_date.txt
20230916
geo_velocity.kmz
Download file.
MontserratSenD54.template
ssaraopt.platform = SENTINEL-1A,SENTINEL-1B
ssaraopt.startDate = 20170101
ssaraopt.relativeOrbit = 54
####################
topsStack.subswath = 2 3 # '1 2'
topsStack.numConnections = 2 # comment
topsStack.azimuthLooks = 4 # comment
topsStack.rangeLooks = 16 # comment
topsStack.filtStrength = 0.4 # comment
topsStack.unwMethod = snaphu # comment
topsStack.coregistration = auto # [NESD geometry], auto for NESD
####################
mintpy.load.autoPath = yes
mintpy.troposphericDelay.method = auto #[pyaps / height_correlation / base_trop_cor / no], auto for pyaps
mintpy.networkInversion.parallel = no #[yes / no], auto for no, parallel processing
mintpy.save.hdfEos5 = yes # [yes / update / no], auto for no, save timeseries to UNAVCO InSAR Archive format
mintpy.save.hdfEos5.subset = yes #[yes / no], auto for no, put subset range info in output filenam
mintpy.save.hdfEos5.update = no # [yes / no], auto for no, put XXXXXXXX as endDate in output filename
mintpy.save.kml = yes # [yes / no], auto for yes, save geocoded velocity to Google Earth KMZ file
mintpy.compute.cluster = local
mintpy.compute.numWorker = 32
mintpy.geocode.laloStep = 0.0002,0.0002 # auto # 0.0008 #[-0.000555556,0.000555556 / None], auto for None, output resolution in degree
mintpy.networkInversion.minTempCoh = auto
####################
minsar.miaplpyDir.addition = date #[name / lalo / no ] auto for no (miaply_$name_startDate_endDate))
miaplpy.load.startDate = 20230101 # 20200101
miaplpy.load.endDate = 20240101 # 20200101
mintpy.subset.lalo = 16.67:16.767,-62.233:-62.136 #[S:N,W:E / no], auto for no
miaplpy.subset.lalo = 16.67:16.767,-62.233:-62.136 #[S:N,W:E / no], auto for no
mintpy.geocode.laloStep = 0.0002,0.0002
miaplpy.interferograms.delaunayTempThresh = 90 # [days] temporal threshold for delaunay triangles, auto for 60
miaplpy.interferograms.networkType = delaunay # network
miaplpy.interferograms.networkType = single_reference # network
#############################################
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.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 = filtDS # [PS,DS,PSDS,geo,all], miaplpy dataset to ingest (Default: geo) (MintPy is always geo)