RaungSenDT105
geo_velocity.png
geo_temporalCoherence.png
geo_maskTempCoh.png
geo_avgSpatialCoh.png
temporalCoherence.png
maskTempCoh.png
avgSpatialCoh.png
maskConnComp.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_wrap10_1.png
timeseries_ERA5_demErr_wrap10_2.png
timeseries_ERA5_wrap10_2.png
geo_timeseries_ERA5_demErr_wrap10_2.png
geo_timeseries_ERA5_demErr_wrap10_1.png
timeseries_wrap10_1.png
avgPhaseVelocity.png
timeseries_wrap10_2.png
velocityERA5.png
reference_date.txt
20190531
RaungSenDT105.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 = 105
ssaraopt.startDate = 20160101
ssaraopt.endDate = 20231014
hazard_products_flag = False
insarmaps_flag = True
######################################################
topsStack.boundingBox = -8.2 -8.0 113.9 114.1 # -1 0.15 -91.6 -90.9
topsStack.subswath = 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 = -8.2:-8.0,113.9:114.1
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 = -8.30,115.55 # 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