Chiles-CerroNegroSenAT120
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
coherence_3.png
coherence_4.png
coherence_5.png
coherence_6.png
unwrapPhase_wrap_1.png
unwrapPhase_wrap_2.png
unwrapPhase_wrap_3.png
unwrapPhase_wrap_4.png
unwrapPhase_wrap_5.png
unwrapPhase_wrap_6.png
unwrapPhase_1.png
unwrapPhase_2.png
unwrapPhase_3.png
unwrapPhase_4.png
unwrapPhase_5.png
unwrapPhase_6.png
connectComponent_1.png
connectComponent_2.png
connectComponent_3.png
connectComponent_4.png
connectComponent_5.png
connectComponent_6.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
20200625
geo_velocity.kmz
Download file.
Chiles-CerroNegroSenAT120.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 = 120
ssaraopt.startDate = 20140101
#ssaraopt.endDate = 20211130
hazard_products_flag = False
insarmaps_flag = True
######################################################
topsStack.boundingBox = 0.76 0.87 -80.45 -75.45 # -1 0.15 -91.6 -90.9
topsStack.subswath = 1 2 # '1 2'
topsStack.numConnections = 4 # comment
topsStack.azimuthLooks = 6 # comment
topsStack.rangeLooks = 24 # 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 = 0.76:0.87,-78.02:-77.88
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 = 0.76,-78.02 # 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.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 = 0.76:0.87,-78.02:-77.88 #[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)