BaekduSenAT54
network: delaunay
geo_velocity.png

geo_temporalCoherence.png

geo_maskTempCoh.png

geo_avgSpatialCoh.png

temporalCoherence_lowpass_gaussian.png

maskTempCoh_lowpass_gaussian.png

network.png

coherenceHistory.png

coherenceMatrix.png

rms_timeseriesResidual_ramp.png

temporalCoherence.png

maskTempCoh.png

avgSpatialCoh.png

maskConnComp.png

numTriNonzeroIntAmbiguity.png

numInvIfgram.png

velocity.png

geometryRadar.png

avgPhaseVelocity.png

coherence.png

connectComponent.png

geo_timeseries_demErr_wrap10.png

pbaseHistory.png

timeseries_demErr_wrap10.png

timeseries_wrap10.png

unwrapPhase.png

unwrapPhase_wrap.png

reference_date.txt
20141102
geo_velocity.kmz
Download file.
BaekduSenAT54.template
ssaraopt.platform = SENTINEL-1A,SENTINEL-1B
#ssaraopt.startDate = 20160101
#ssaraopt.endDate = 20201211
ssaraopt.relativeOrbit = 54
####################
topsStack.boundingBox = 41.7 42.2 126.5 129.6
topsStack.subswath = 2 3 # '1 2'
topsStack.numConnections = 2 # comment
topsStack.azimuthLooks = 10 # comment
topsStack.rangeLooks = 30 # comment
topsStack.filtStrength = 0.4 # comment
topsStack.unwMethod = snaphu # comment
topsStack.coregistration = auto # [NESD geometry], auto for NESD
####################
mintpy.load.autoPath = yes
mintpy.compute.cluster = local
mintpy.compute.numWorker = 32
mintpy.plot.maxMemory = 32 # [float], auto for 4, max memory used by one call of view.py for plotting
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.troposphericDelay.method = no # [pyaps / height_correlation / base_trop_cor / no], auto for pyaps
mintpy.networkInversion.minTempCoh = auto
####################
minsar.miaplpyDir.addition = date #[name / lalo / no ] auto for no (miaply_$name_startDate_endDate))
mintpy.subset.lalo = 41.95:42.06,127.97:128.174 #[S:N,W:E / no], auto for no
miaplpy.subset.lalo = 41.95:42.06,127.97:128.174 #[S:N,W:E / no], auto for no
#mintpy.subset.lalo = 41.943:42.074,127.957:128.125 #[S:N,W:E / no], auto for no
#miaplpy.subset.lalo = 41.943:42.074,127.957:128.125 #[S:N,W:E / no], auto for no
miaplpy.start.endDate = auto
miaplpy.load.endDate = auto
mintpy.geocode.laloStep = 0.0002,0.0002
#mintpy.reference.minCoherence = 0.3 #[0.0-1.0], auto for 0.85, minimum coherence for auto method
#miaplpy.interferograms.delaunayTempThresh = 90 # [days] temporal threshold for delaunay triangles, auto for 60
miaplpy.interferograms.networkType = single_reference # network
miaplpy.interferograms.networkType = delaunay # 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 = 0.65 # auto for 0.5
mintpy.networkInversion.minTempCoh = 0.65
#############################################
minsar.insarmaps_dataset = DS # [PS,DS,PSDS,geo,all], miaplpy dataset to ingest (Default: geo) (MintPy is always geo)
insarmaps_flag = True