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hyp3.cfg
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hyp3.cfg
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# vim: set filetype=cfg:
##------------------------ smallbaselineApp.cfg ------------------------##
########## computing resource configuration
mintpy.compute.maxMemory = 120 #[float > 0.0], auto for 4, max memory to allocate in GB
mintpy.compute.cluster = local #[local / slurm / pbs / lsf / none], auto for none, cluster type
mintpy.compute.numWorker = 16 #[int > 1 / all], auto for 4 (local) or 40 (slurm / pbs / lsf), num of workers
########## 1. load_data
mintpy.load.processor = hyp3 #[isce, aria, hyp3, gmtsar, snap, gamma, roipac], auto for isce
##---------interferogram datasets:
mintpy.load.unwFile = /home/micromamba/raw/desc_upper/*/*unw_phase_clip.tif #[path pattern of unwrapped interferogram files]
mintpy.load.corFile = /home/micromamba/raw/desc_upper/*/*corr_clip.tif #[path pattern of spatial coherence files]
##---------geometry datasets:
mintpy.load.demFile = /home/micromamba/raw/desc_upper/*/*_dem_clip.tif #[path of DEM file]
mintpy.load.incAngleFile = /home/micromamba/raw/desc_upper/*/*_lv_theta_clip.tif #[path of incidence angle file], optional but recommended
mintpy.load.waterMaskFile = /home/micromamba/raw/desc_upper/*/*_water_mask_clip.tif #[path of water mask file], optional but recommended
##---------subset (optional):
mintpy.subset.yx = 4988:6401,1584:6366
########## 2. modify_network
## 1) Network modification based on temporal/perpendicular baselines, date, num of connections etc.
mintpy.network.tempBaseMax = 100 #[1-inf, no], auto for no, max temporal baseline in days
mintpy.network.startDate = 20190101 #[20090101 / no], auto for no
mintpy.network.endDate = 20191115 #[20110101 / no], auto for no
mintpy.network.excludeDate = auto #[20080520,20090817 / no], auto for no
mintpy.network.excludeIfgIndex = auto #[1:5,25 / no], auto for no, list of ifg index (start from 0)
# 2021: 20210101 - 20220101
# 2020: 20200101 - 20210601
# 2019: 20190101 - 20191115
# 2021: 20210601 - 20220101
# 2020: 20200101 - 20200701
# 2019: 20190101 - 20191115
# 2018: 20180601 - 20190101
## 2) Data-driven network modification
mintpy.network.coherenceBased = yes #[yes / no], auto for no, exclude interferograms with coherence < minCoherence
mintpy.network.minCoherence = 0.4 #[0.0-1.0], auto for 0.7
## Additional common parameters for the 2) data-driven network modification
mintpy.network.keepMinSpanTree = no #[yes / no], auto for yes, keep interferograms in Min Span Tree network
mintpy.network.maskFile = waterMask.h5 #[file name, no], auto for waterMask.h5 or no [if no waterMask.h5 found]
########## 3. reference_point
mintpy.reference.yx = 567, 2866 #[257,151 / auto]
mintpy.reference.maskFile = waterMask.h5 #[filename / no], auto for maskConnComp.h5
# 567, 2866
# 556, 2644
########## 5. invert_network
## Temporal coherence is calculated and used to generate the mask as the reliability measure
## reference: Pepe & Lanari (2006, IEEE-TGRS)
mintpy.networkInversion.minTempCoh = 0.4 #[0.0-1.0], auto for 0.7, min temporal coherence for mask
mintpy.networkInversion.minNumPixel = 5 #[int > 1], auto for 100, min number of pixels in mask above\
########## 10. velocity
## Bootstrapping
## refernce: Efron and Tibshirani (1986, Stat. Sci.)
mintpy.velocity.bootstrap = yes #[yes / no], auto for no, use bootstrap
mintpy.velocity.bootstrapCount = 100 #[int>1], auto for 400, number of iterations for bootstrapping