q4unittestGalapagosSenDT128
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
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
20160605
geo_velocity.kmz
Download file.
q4unittestGalapagosSenDT128.template
#####################################################
# If the data are in $TESTDATA_ISCE, run using
# minsarApp.bash /work2/05861/tg851601/stampede2/code/rsmas_insar/samples/unittestGalapagosSenDT128.template --miaplpy --start dem
######################################################
cleanopt = 0 # [ 0 / 1 / 2 / 3 / 4] 0,1: none 2: keep merged,geom_master,SLC 3: keep MINTPY 4: everything
ssaraopt.platform = SENTINEL-1A,SENTINEL-1B
ssaraopt.relativeOrbit = 128
ssaraopt.startDate = 20160601
ssaraopt.endDate = 20160831
minsar.upload_flag = False # [True / False / auto ], upload to jetstream (Default: True)
minsar.insarmaps_flag = False # [True / False / auto ], ingest into insarmaps (Default: False)
minsar.insarmaps_dataset = DS # [PS,DS,PSDS,geo,all], miaplpy dataset to ingest (Default: geo) (MintPy is always geo)
######################################################
topsStack.boundingBox = -1 -0.6 -91.9 -90.7 # -1 0.15 -91.9 -90.6
topsStack.boundingBox = -0.81 -0.80 -90.9 -90.86 # -1 0.15 -91.9 -90.6
topsStack.subswath = 1 # '1 2'
topsStack.numConnections = 3 # comment
topsStack.azimuthLooks = 5 # comment
topsStack.rangeLooks = 15 # comment
topsStack.filtStrength = 0.2 # comment
topsStack.unwMethod = snaphu # comment
topsStack.coregistration = geometry # [NESD geometry], auto for NESD
#topsStack.slcDir = $TESTDATA_ISCE/unittestGalapagosSenDT128/SLC
######################################################
mintpy.compute.cluster = local #[local / slurm / pbs / lsf / none], auto for none, cluster type
mintpy.compute.numWorker = 6 #[int > 1 / all], auto for 4 (local) or 40 (non-local), num of workers
mintpy.reference.lalo = auto # -0.82,-91.14 # S of SN
mintpy.networkInversion.parallel = yes #[yes / no], auto for no, parallel processing using dask
mintpy.troposphericDelay.method = no # pyaps #[pyaps / height_correlation / base_trop_cor / no], auto for pyaps
mintpy.save.hdfEos5 = yes #[yes / update / no], auto for no, save timeseries to UNAVCO InSAR Archive format
mintpy.save.hdfEos5.update = yes #[yes / no], auto for no, put XXXXXXXX as endDate in output filename
mintpy.save.hdfEos5.subset = yes #[yes / no], auto for no, put XXXXXXXX as endDate in output filename
mintpy.save.kmz = yes #[yes / no], auto for yes, save geocoded velocity to Google Earth KMZ file
mintpy.load.autoPath = yes
mintpy.subset.lalo = -0.86:-0.81,-91.19:-91.13 #[31.5:32.5,130.5:131.0 / no], auto for no
######################################################
miaplpy.load.processor = isce
miaplpy.load.autoPath = yes
miaplpy.multiprocessing.numProcessor = 40
miaplpy.subset.lalo = -0.86:-0.81,-91.19:-91.13 #[31.5:32.5,130.5:131.0 / no], auto for no
miaplpy.interferograms.networkType = single_reference # [single_reference, sequential, combine, list] default: single_reference
minsar.miaplpyDir.addition = SN #[name / lalo / no ] auto for no (miaply_$name_startDate_endDate))
minsar.insarmaps_dataset = DS
mintpy.networkInversion.minTempCoh = 0.6 # auto for 0.5
miaplpy.timeseries.minTempCoh = 0.6 # auto for 0.5
minsar.insarmaps_flag = False
minsar.upload_flag = True
minsar.insarmaps_dataset = DS