SangaySenA18
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_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
20150428
geo_velocity.kmz
Download file.
SangaySenA18.template
######################################################
ssaraopt.platform = SENTINEL-1A,SENTINEL-1B # [Sentinel-1 / ALOS2 / RADARSAT2 / TerraSAR-X / COSMO-Skymed]
ssaraopt.relativeOrbit = 18
ssaraopt.startDate = 20141031 # YYYYMMDD
ssaraopt.endDate = 20150930 # YYYYMMDD
######################################################
topsStack.subswath = 1 2 3 # '1 2'
topsStack.numConnections = 3 # comment
topsStack.azimuthLooks = 5 # comment
topsStack.rangeLooks = 20 # comment
topsStack.filtStrength = 0.2 # comment
topsStack.unwMethod = snaphu # comment
topsStack.coregistration = auto # [NESD geometry], auto for NESD
#topsStack.excludeDates = 20240926
######################################################
mintpy.load.autoPath = yes
mintpy.compute.cluster = local #[local / slurm / pbs / lsf / none], auto for none, cluster type
mintpy.compute.numWorker = 40 #[int > 1 / all], auto for 4 (local) or 40 (non-local), num of workers
mintpy.plot.maxMemory = 180 #[float], auto for 4, max memory used by one call of view.py for plotting.
mintpy.networkInversion.parallel = yes #[yes / no], auto for no, parallel processing using dask
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 subset range info in output filename
mintpy.save.kmz = yes #[yes / no], auto for yes, save geocoded velocity to Google Earth KMZ file
mintpy.reference.minCoherence = auto #[0.0-1.0], auto for 0.85, minimum coherence for auto method
mintpy.troposphericDelay.method = auto # pyaps #[pyaps / height_correlation / base_trop_cor / no], auto for pyaps
mintpy.networkInversion.minTempCoh = 0.6 #[0.0-1.0], auto for 0.7, min temporal coherence for mask
######################################################
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.interferograms.networkType = delaunay # network
miaplpy.unwrap.snaphu.tileNumPixels = 10000000000 # number of pixels in a tile, auto for 10000000
######################################################
minsar.miaplpyDir.addition = date #[name / lalo / no] auto for no (miaply_$name_startDate_endDate))
mintpy.subset.lalo = -2.12:-1.93,-78.43:-78.24
miaplpy.subset.lalo = -2.12:-1.93,-78.43:-78.24 #[S:N,W:E / no], auto for no
miaplpy.load.startDate = auto # 20200101
miaplpy.load.endDate = auto
mintpy.geocode.laloStep = 0.008,0.00801
miaplpy.timeseries.minTempCoh = 0.75 # auto for 0.5
mintpy.networkInversion.minTempCoh = 0.75
######################################################
minsar.insarmaps_flag = True
minsar.upload_flag = True
minsar.insarmaps_dataset = filt*DS