PopocatepetlSenA5
miaplpy_201901_202411/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

unwrapPhase_wrap_1.png

unwrapPhase_wrap_2.png

unwrapPhase_wrap_3.png

unwrapPhase_wrap_4.png

unwrapPhase_wrap_5.png

unwrapPhase_1.png

unwrapPhase_2.png

unwrapPhase_3.png

unwrapPhase_4.png

unwrapPhase_5.png

connectComponent_1.png

connectComponent_2.png

connectComponent_3.png

connectComponent_4.png

connectComponent_5.png

timeseries_ERA5_demErr_wrap10_1.png

timeseries_ERA5_demErr_wrap10_2.png

timeseries_ERA5_wrap10_1.png

timeseries_ERA5_wrap10_2.png

geo_timeseries_ERA5_demErr_wrap10_1.png

geo_timeseries_ERA5_demErr_wrap10_2.png

avgPhaseVelocity.png

pbaseHistory.png

timeseries_wrap10_1.png

timeseries_wrap10_2.png

velocityERA5.png

reference_date.txt
20190125
geo_velocity.kmz
Download file.
PopocatepetlSenA5.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 = 5
ssaraopt.startDate = 20190101
#ssaraopt.endDate = 20211130
hazard_products_flag = False
#insarmaps_flag = True
excludeDates = 20170722
######################################################
#topsStack.boundingBox = 18.93 19.1 -101.13 -96.13 # -1 0.15 -91.6 -90.9
topsStack.subswath = 1 # '1 2'
topsStack.numConnections = 4 # comment
topsStack.azimuthLooks = 3 # comment
topsStack.rangeLooks = 15 # 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 = 18.93:19.1,-98.75:-98.52
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 = 18.93,-98.75 # S of SN
mintpy.networkInversion.parallel = yes #[yes / no], auto for no, parallel processing using dask
mintpy.network.tempBaseMax = auto #[1-inf, no], auto for no, max temporal baseline in days
mintpy.network.perpBaseMax = auto #[1-inf, no], auto for no, max perpendicular spatial baseline in meter
mintpy.network.connNumMax = auto #[1-inf, no], auto for no, max number of neighbors for each acquisition
mintpy.network.coherenceBased = auto #[yes / no], auto for no, exclude interferograms with coherence < minCoherence
mintpy.network.aoiLALO = auto #[S:N,W:E / no], auto for no - use the whole area
mintpy.networkInversion.minTempCoh = 0.6 #[0.0-1.0], auto for 0.7, min temporal coherence for mask
mintpy.troposphericDelay.method = auto # pyaps #[pyaps / height_correlation / base_trop_cor / no], auto for pyaps
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.save.kmz = yes #[yes / no], auto for yes, save geocoded velocity to Google Earth KMZ file
####################
minsar.miaplpyDir.addition = date #[name / lalo / no ] auto for no (miaply_$name_startDate_endDate))
miaplpy.subset.lalo = 18.93:19.1,-98.75:-98.52 #[S:N,W:E / no], auto for no
miaplpy.load.startDate = auto # 20200101
miaplpy.load.endDate = auto
mintpy.geocode.laloStep = 0.0002,0.0002
mintpy.reference.minCoherence = 0.5 #[0.0-1.0], auto for 0.85, minimum coherence for auto method
miaplpy.interferograms.delaunayBaselineRatio = 4
miaplpy.interferograms.delaunayTempThresh = 120 # [days] temporal threshold for delaunay triangles, auto for 120
miaplpy.interferograms.delaunayPerpThresh = 200 # [meters] Perp baseline threshold for delaunay triangles, auto for 200
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 = 0.50 # auto for 0.5
mintpy.networkInversion.minTempCoh = 0.5
#############################################
minsar.upload_flag = False # [True / False ], upload to jetstream (Default: False)
minsar.insarmaps_flag = False
minsar.insarmaps_dataset = DSfiltDS
#############################################