DelhiSenAT27
network: delaunay
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
coherence_1.png
coherence_2.png
coherence_3.png
unwrapPhase_wrap_1.png
unwrapPhase_wrap_2.png
unwrapPhase_wrap_3.png
unwrapPhase_1.png
unwrapPhase_2.png
unwrapPhase_3.png
connectComponent_1.png
connectComponent_2.png
connectComponent_3.png
timeseries_demErr_wrap10_2.png
timeseries_demErr_wrap10_1.png
geo_timeseries_demErr_wrap10_2.png
geo_timeseries_demErr_wrap10_1.png
timeseries_wrap10_2.png
timeseries_wrap10_1.png
pbaseHistory.png
avgPhaseVelocity.png
reference_date.txt
20201210
DelhiSenAT27.template
process_flag = TRUE
frequency = 1
login = pegasus.ccs.miami.edu
user = famelung
####################
####################
email_pysar = famelung@rsmas.miami.edu jaz101@rsmas.miami.edu bvarugu@rsmas.miami.edu
email_insarmaps = famelung@rsmas.miami.edu jaz101@rsmas.miami.edu bvarugu@rsmas.miami.edu
####################
every_day_flag = yes
processor = isce
cleanopt = 0
hazard_products_flag = TRUE
ssaraopt.platform = SENTINEL-1A,SENTINEL-1B
ssaraopt.relativeOrbit = 27
ssaropt.startDate = 20141091
####################
#topsStack.boundingBox = 28.15 28.5 74.0 79.0 # '-1 0.15 -91.6 -90.9'
topsStack.boundingBox = 28.1 28.5 74.0 79.0 # '-1 0.15 -91.6 -90.9'
topsStack.boundingBox = 28.3 28.8 74.0 79.0 # '-1 0.15 -91.6 -90.9'
topsStack.boundingBox = 28.3 28.8 76.7 77.7 # '-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 = 0.4 # comment
topsStack.unwMethod = snaphu # comment
topsStack.coregistration = auto # [NESD geometry], auto for NESD
####################
mintpy.load.autoPath = yes
mintpy.troposphericDelay.method = no #[pyaps / height_correlation / base_trop_cor / no], auto for pyaps
mintpy.networkInversion.parallel = no #[yes / no], auto for no, parallel processing
#mintpy.networkInversion.minTempCoh = 0.7 #[0.0-1.0], auto for 0.7, min temporal coherence for mask
mintpy.save.hdfEos5 = yes # [yes / update / no], auto for no, save timeseries to UNAVCO InSAR Archive format
mintpy.save.hdfEos5.subset = yes #[yes / no], auto for no, put subset range info in output filenam
mintpy.save.hdfEos5.update = no # [yes / no], auto for no, put XXXXXXXX as endDate in output filename
mintpy.save.kml = yes # [yes / no], auto for yes, save geocoded velocity to Google Earth KMZ file
mintpy.compute.cluster = local
mintpy.compute.numWorker = 32
####################
###### Dwarka #######
miaplpy.subset.lalo = 28.55:28.66,77.0:77.2 #[S:N,W:E / no], auto for no
miaplpy.subset.lalo = 28.55:28.74,77.0:77.2 #[S:N,W:E / no], auto for no
mintpy.subset.lalo = 28.55:28.74,77.0:77.2 #[S:N,W:E / no], auto for no
mintpy.reference.lalo = auto # 25.8248,-80.1222 # auto refPointLat=25.82477&refPointLon=-80.12222 # 25.8791,-80.1259 # W Brickel Marquis condo
minsar.miaplpyDir.addition = Dwarka #[name / lalo / no ] auto for no (miaply_$name_startDate_endDate))
miaplpy.load.startDate = auto
miaplpy.load.endDate = auto
###### Dwarka east #######
miaplpy.subset.lalo = 28.55:28.66,77.195:77.405 #[S:N,W:E / no], auto for no
miaplpy.subset.lalo = 28.55:28.74,77.195:77.405 #[S:N,W:E / no], auto for no
mintpy.subset.lalo = 28.55:28.74,77.195:77.405 #[S:N,W:E / no], auto for no
mintpy.reference.lalo = auto # 25.8248,-80.1222 # auto refPointLat=25.82477&refPointLon=-80.12222 # 25.8791,-80.1259 # W Brickel Marquis condo
minsar.miaplpyDir.addition = Dwarka2 #[name / lalo / no ] auto for no (miaply_$name_startDate_endDate))
miaplpy.load.startDate = auto
miaplpy.load.endDate = auto
###### Gurgaon East #######
miaplpy.subset.lalo = 28.395:28.565,77.195:77.405 #[S:N,W:E / no], auto for no
mintpy.subset.lalo = 28.395:28.565,77.195:77.405 #[S:N,W:E / no], auto for no
mintpy.reference.lalo = auto # 25.8248,-80.1222 # auto refPointLat=25.82477&refPointLon=-80.12222 # 25.8791,-80.1259 # W Brickel Marquis condo
minsar.miaplpyDir.addition = Gurgaon2 #[name / lalo / no ] auto for no (miaply_$name_startDate_endDate))
miaplpy.load.startDate = auto
miaplpy.load.endDate = auto
###### Gurgaon #######
miaplpy.subset.lalo = 28.425:28.565,77.0:77.2 #[S:N,W:E / no], auto for no
mintpy.subset.lalo = 28.425:28.565,77.0:77.2 #[S:N,W:E / no], auto for no
mintpy.reference.lalo = auto # 25.8248,-80.1222 # auto refPointLat=25.82477&refPointLon=-80.12222 # 25.8791,-80.1259 # W Brickel Marquis condo
minsar.miaplpyDir.addition = Gurgaon #[name / lalo / no ] auto for no (miaply_$name_startDate_endDate))
miaplpy.load.startDate = auto
miaplpy.load.endDate = auto
###### WestDCR #######
minsar.miaplpyDir.addition = WestDCR #[name / lalo / no ] auto for no (miaply_$name_startDate_endDate))
mintpy.subset.lalo = 28.403:28.879,76.841:77.431 #[S:N,W:E / no], auto for no
miaplpy.subset.lalo = 28.403:28.879,76.841:77.431 #[S:N,W:E / no], auto for no
mintpy.subset.lalo = 28.403:28.879,76.84:77.14 #[S:N,W:E / no], auto for no
miaplpy.subset.lalo = 28.403:28.879,76.84:77.14 #[S:N,W:E / no], auto for no
mintpy.reference.lalo = auto # 25.8248,-80.1222 # auto refPointLat=25.82477&refPointLon=-80.12222 # 25.8791,-80.1259 # W Brickel Marquis condo
miaplpy.load.startDate = auto
miaplpy.load.endDate = auto
###### EastDCR #######
minsar.miaplpyDir.addition = EastDCR #[name / lalo / no ] auto for no (miaply_$name_startDate_endDate))
mintpy.subset.lalo = 28.403:28.879,77.11:77.431 #[S:N,W:E / no], auto for no
miaplpy.subset.lalo = 28.403:28.879,77.11:77.431 #[S:N,W:E / no], auto for no
mintpy.reference.lalo = auto # 25.8248,-80.1222 # auto refPointLat=25.82477&refPointLon=-80.12222 # 25.8791,-80.1259 # W Brickel Marquis condo
miaplpy.load.startDate = auto
miaplpy.load.endDate = auto
###### DCR #######
minsar.miaplpyDir.addition = DCR #[name / lalo / no ] auto for no (miaply_$name_startDate_endDate))
mintpy.subset.lalo = 28.403:28.879,76.841:77.431 #[S:N,W:E / no], auto for no
miaplpy.subset.lalo = 28.403:28.879,76.841:77.431 #[S:N,W:E / no], auto for no
mintpy.reference.lalo = auto # 25.8248,-80.1222 # auto refPointLat=25.82477&refPointLon=-80.12222 # 25.8791,-80.1259 # W Brickel Marquis condo
miaplpy.load.startDate = auto
miaplpy.load.endDate = auto
###### Gurgaon #######
miaplpy.subset.lalo = 28.425:28.565,77.0:77.2 #[S:N,W:E / no], auto for no
mintpy.subset.lalo = 28.425:28.565,77.0:77.2 #[S:N,W:E / no], auto for no
mintpy.reference.lalo = auto # 25.8248,-80.1222 # auto refPointLat=25.82477&refPointLon=-80.12222 # 25.8791,-80.1259 # W Brickel Marquis condo
minsar.miaplpyDir.addition = Gurgaon #[name / lalo / no ] auto for no (miaply_$name_startDate_endDate))
miaplpy.load.startDate = 20141031
miaplpy.load.endDate = 20161231
miaplpy.load.startDate = 20161031
miaplpy.load.endDate = 20180930
miaplpy.load.startDate = 20180901
miaplpy.load.endDate = 20191231
miaplpy.load.startDate = 20191201
miaplpy.load.endDate = 20210731
miaplpy.load.startDate = 20210701
miaplpy.load.endDate = 20231031
miaplpy.load.startDate = 20141031
miaplpy.load.endDate = 20231031
#############################################
miaplpy.load.processor = isce
miaplpy.multiprocessing.numProcessor = 40
miaplpy.inversion.rangeWindow = 24 # range window size for searching SHPs, auto for 15
miaplpy.inversion.azimuthWindow = 9 # azimuth window size for searching SHPs, auto for 15
miaplpy.timeseries.tempCohType = auto # [full, average], auto for full.
miaplpy.timeseries.minTempCoh = auto # auto for 0.5
miaplpy.interferograms.delaunayBaselineRatio = 4 # [1, 4, 9] Ratio between perpendiclar and temporal baselines, auto for 4
miaplpy.interferograms.networkType = single_reference # network
miaplpy.interferograms.networkType = mini_stacks # network
miaplpy.interferograms.networkType = delaunay # network
miaplpy.timeseries.residualNorm = L1 # [L1, L2], auto for L2, norm minimization solution
miaplpy.interferograms.ministackRefMonth = 1 # The month of the year that coherence is high to choose reference from, default: 6
miaplpy.interferograms.connNum = auto # Number of connections in sequential interferograms, auto for 3
miaplpy.timeseries.residualNorm = auto # [L1, L2], auto for L2, norm minimization solution
#############################################
insarmaps_flag = False