FernandinaSenAT106

geo_velocity.png

geo_temporalCoherence.png

geo_maskTempCoh.png

geo_avgSpatialCoh.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_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

20240505

FernandinaSenAT106.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            = 106
ssaraopt.startDate                = 20240101
#ssaraopt.endDate                  = 20240324
hazard_products_flag              = False
insarmaps_flag                     = True
######################################################
topsStack.boundingBox             = -0.54 -0.25 -91.69 -91.36    # -1 0.15 -91.6 -90.9
topsStack.subswath                = 2 3 # '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                  = -0.54:-0.25,-91.69:-91.36
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             = -0.54,-91.69     # S of SN
mintpy.networkInversion.parallel  = yes  #[yes / no], auto for no, parallel processing using dask
mintpy.troposphericDelay.method   = auto   # pyaps  #[pyaps / height_correlation / base_trop_cor / no], auto for pyaps
mintpy.geocode.laloStep             = 0.0008,0.0008                 #[-0.000555556,0.000555556 / None], auto for None
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                  = -0.54:-0.25,-91.61:-91.45    #[S:N,W:E / no], auto for no
miaplpy.load.startDate               = auto #  20200101
miaplpy.load.endDate                 = auto
mintpy.geocode.laloStep              = 0.0005,0.0005
mintpy.reference.minCoherence        = 0.5   #[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        = 0.70     # auto for 0.5
#############################################
insarmaps_flag                       = False