AsosanSenA156
mintpy/pic
geo_velocity.png

geo_temporalCoherence.png

geo_maskTempCoh.png

temporalCoherence.png

maskTempCoh.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

unwrapPhase_wrap_1.png

unwrapPhase_wrap_2.png

unwrapPhase_1.png

unwrapPhase_2.png

connectComponent_1.png

connectComponent_2.png

avgPhaseVelocity.png

geo_timeseries_demErr_wrap10.png

pbaseHistory.png

timeseries_demErr_wrap10.png

timeseries_wrap10.png

reference_date.txt
20191125
geo_velocity.kmz
Download file.
AsosanSenA156.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 = 156
ssaraopt.startDate = 20190101
#ssaraopt.endDate = 20211130
hazard_products_flag = False
insarmaps_flag = True
######################################################
topsStack.excludeDates = 20160514,20160526,20160607,20160701,20160713,20160806,20160830,20160923,20161017,20161110,20161116,20161128,20161210,20161222,20170103,20170115,20170127,20170208,20170208,20170220,20170304,20170316,20170328,20170409,20170503,20170515,20170527,20170608,20170620,20170702,20170714,20170726,20170807,20170819,20170831,20170912,20170924,20171006,20171018,20171030,20171111,20171123,20171205,20171217,20171229,20180110,20180122,20180203,20180215,20180227,20180311,20180323,20180404,20180416,20180428,20180510,20180522,20180603,20180615,20180709,20181013
#topsStack.boundingBox = 32.86 32.91 133.51 128.67 # -1 0.15 -91.6 -90.9
topsStack.subswath = 1 2 # '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 = 32.86:32.91,131.05:131.13
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 = 32.86,131.05 # 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 = yes #[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.network.minCoherence = 0.6 #[0.0-1.0], auto for 0.7
mintpy.troposphericDelay.method = no # 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 = 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
####################
minsar.miaplpyDir.addition = date #[name / lalo / no ] auto for no (miaply_$name_startDate_endDate))
miaplpy.subset.lalo = 32.86:32.91,131.05:131.13 #[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 = True # [True / False ], upload to jetstream (Default: False)
minsar.insarmaps_flag = False # [True / False ], ingest into insarmaps (Default: False)
minsar.insarmaps_dataset = DS # [PS,DS,PSDS,geo,all], miaplpy dataset to ingest (Default: geo) (MintPy is always geo)