input_options:
# If passing HDF5/NetCDF files, subdataset to use from CSLC files. .
# Type: string | null.
subdataset:
# Format of dates contained in CSLC filenames.
# Type: string.
cslc_date_fmt: '%Y%m%d'
# Radar wavelength (in meters) of the transmitted data. used to convert the units in the
# rasters in `timeseries/` to from radians to meters. If None and sensor is not
# recognized, outputs remain in radians.
# Type: number | null.
wavelength:
# Mask file used to ignore low correlation/bad data (e.g water mask). Convention is 0 for no
# data/invalid, and 1 for good data. Dtype must be uint8.
# Type: string | null.
mask_file:
# Name of sub-directory to use for writing output files.
# Type: string.
work_directory: .
# Don't resolve filepaths that are given as relative to be absolute.
# Type: boolean.
keep_paths_relative: false
worker_settings:
# Whether to use GPU for processing (if available).
# Type: boolean.
gpu_enabled: false
# Number of threads to use per worker. This sets the OMP_NUM_THREADS environment variable in
# each python process.
# Type: integer.
threads_per_worker: 1
# If processing separate spatial bursts, number of bursts to run in parallel for wrapped-
# phase-estimation.
# Type: integer.
n_parallel_bursts: 1
# Size (rows, columns) of blocks of data to load at a time.
# Type: array.
block_shape:
- 512
- 512
# Path to output log file (in addition to logging to `stderr`). Default logs to
# `dolphin.log` within `work_directory`.
# Type: string | null.
log_file:
# Time the config file was created.
# Type: string.
# REQUIRED: list of CSLC files, or newline-delimited file containing list of CSLC files.
# Type: array.
cslc_file_list: []
output_options:
# Output (x, y) resolution (in units of input data).
# Type: object | null.
output_resolution:
# Alternative to specifying output resolution: Specify the (x, y) strides (decimation
# factor) to perform while processing input. For example, strides of [4, 2] would turn an
# input resolution of [5, 10] into an output resolution of [20, 20].
# Type: object.
strides:
x: 1
y: 1
# Area of interest: [left, bottom, right, top] coordinates. e.g.
# `bbox=[-150.2,65.0,-150.1,65.5]`.
# Type: array | null.
bounds:
# EPSG code for the `bounds` coordinates, if specified.
# Type: integer.
bounds_epsg: 4326
# Options for `create_dataset` with h5py.
# Type: object.
hdf5_creation_options:
chunks:
- 128
- 128
compression: gzip
compression_opts: 4
shuffle: true
# GDAL creation options for GeoTIFF files.
# Type: array.
gtiff_creation_options:
- COMPRESS=lzw
- ZLEVEL=4
- BIGTIFF=yes
- TILED=yes
- INTERLEAVE=band
- BLOCKXSIZE=128
- BLOCKYSIZE=128
# Whether to add overviews to the output GeoTIFF files. This will increase file size, but
# can be useful for visualizing the data with web mapping tools. See
# https://gdal.org/programs/gdaladdo.html for more.
# Type: boolean.
add_overviews: true
# List of overview levels to create (if `add_overviews=True`).
# Type: array.
overview_levels:
- 4
- 8
- 16
- 32
- 64
# Specify an extra reference datetime in UTC. Adding this lets you to create and unwrap two
# single reference networks; the later resets at the given date (e.g. for a large
# earthquake event). If passing strings, formats accepted are YYYY-MM-
# DD[T]HH:MM[:SS[.ffffff]][Z or [±]HH[:]MM], or YYYY-MM-DD.
# Type: string | null.
extra_reference_date:
ps_options:
# Amplitude dispersion threshold to consider a pixel a PS.
# Type: number.
amp_dispersion_threshold: 0.25
# Paths to existing Amplitude Dispersion file (1 per SLC region) for PS update calculation.
# If none provided, computed using the input SLC stack.
# Type: array.
amplitude_dispersion_files: []
# Paths to an existing Amplitude Mean files (1 per SLC region) for PS update calculation. If
# none provided, computed using the input SLC stack.
# Type: array.
amplitude_mean_files: []
phase_linking:
# Size of the ministack for sequential estimator.
# Type: integer.
ministack_size: 10
# Maximum number of compressed images to use in sequential estimator. If there are more
# ministacks than this, the earliest CCSLCs will be left out of the later stacks. .
# Type: integer.
max_num_compressed: 100
# Index of input SLC to use for making phase linked interferograms after EVD/EMI.
# Type: integer.
output_reference_idx: 0
half_window:
# Half window size (in pixels) for x direction.
# Type: integer.
x: 11
# Half window size (in pixels) for y direction.
# Type: integer.
y: 5
# Use EVD on the coherence instead of using the EMI algorithm.
# Type: boolean.
use_evd: false
# Beta regularization parameter for correlation matrix inversion. 0 is no regularization.
# Type: number.
beta: 0.0
# Method for finding SHPs during phase linking.
# Type: string.
# Options: ['glrt', 'ks', 'rect', 'rect'].
shp_method: glrt
# Significance level (probability of false alarm) for SHP tests.
# Type: number.
shp_alpha: 0.005
# If True, pixels labeled as PS will get set to NaN during phase linking to avoid summing
# their phase. Default of False means that the SHP algorithm will decide if a pixel should
# be included, regardless of its PS label.
# Type: boolean.
mask_input_ps: false
# StBAS parameter to include only nearest-N interferograms forphase linking. A
# `baseline_lag` of `n` will only include the closest`n` interferograms. `baseline_line`
# must be positive.
# Type: integer | null.
baseline_lag:
interferogram_network:
# For single-reference network: Index of the reference image in the network.
# Type: integer | null.
reference_idx: 0
# Max `n` to form the nearest-`n` interferograms by index.
# Type: integer | null.
max_bandwidth:
# Maximum temporal baseline of interferograms.
# Type: integer | null.
max_temporal_baseline:
# For manual-index network: list of (ref_idx, sec_idx) defining the interferograms to form.
# Type: array | null.
indexes:
unwrap_options:
# Whether to run the unwrapping step after wrapped phase estimation.
# Type: boolean.
run_unwrap: true
# Whether to run Goldstein filtering step on wrapped interferogram.
# Type: boolean.
run_goldstein: false
# Whether to run interpolation step on wrapped interferogram.
# Type: boolean.
run_interpolation: false
# Phase unwrapping method.
# Type: string.
# Options: ['snaphu', 'icu', 'phass', 'spurt', 'whirlwind'].
unwrap_method: snaphu
# Number of interferograms to unwrap in parallel.
# Type: integer.
n_parallel_jobs: 1
# Set wrapped phase/correlation to 0 where mask is 0 before unwrapping. .
# Type: boolean.
zero_where_masked: false
preprocess_options:
# Adaptive phase (Goldstein) filter exponent parameter.
# Type: number.
alpha: 0.5
# (for interpolation) Maximum radius to find scatterers.
# Type: integer.
max_radius: 51
# Threshold on the correlation raster to use for interpolation. Pixels with less than this
# value are replaced by a weighted combination of neighboring pixels.
# Type: number.
interpolation_cor_threshold: 0.5
snaphu_options:
# Number of tiles to split the inputs into using SNAPHU's internal tiling.
# Type: array.
ntiles:
- 1
- 1
# Amount of tile overlap (in pixels) along the (row, col) directions.
# Type: array.
tile_overlap:
- 0
- 0
# Number of tiles to unwrap in parallel for each interferogram.
# Type: integer.
n_parallel_tiles: 1
# Initialization method for SNAPHU.
# Type: string.
# Options: ['mcf', 'mst'].
init_method: mcf
# Statistical cost mode method for SNAPHU.
# Type: string.
# Options: ['defo', 'smooth'].
cost: smooth
tophu_options:
# Number of tiles to split the inputs into.
# Type: array.
ntiles:
- 1
- 1
# Extra multilook factor to use for the coarse unwrap.
# Type: array.
downsample_factor:
- 1
- 1
# Initialization method for SNAPHU.
# Type: string.
# Options: ['mcf', 'mst'].
init_method: mcf
# Statistical cost mode method for SNAPHU.
# Type: string.
# Options: ['defo', 'smooth'].
cost: smooth
spurt_options:
# Temporal coherence to pick pixels used on an irregular grid.
# Type: number.
temporal_coherence_threshold: 0.6
general_settings:
# Tile up data spatially.
# Type: boolean.
use_tiles: true
tiler_settings:
# Maximum number of tiles allowed.
# Type: integer.
max_tiles: 16
# Number of points used for determining tiles based on density.
# Type: integer.
target_points_for_generation: 120000
# Target points per tile when generating tiles.
# Type: integer.
target_points_per_tile: 800000
# Dilation factor of non-overlapping tiles. 0.05 would lead to 5 percent dilation of the
# tile.
# Type: number.
dilation_factor: 0.05
solver_settings:
# Number of workers for temporal unwrapping in parallel. Set value to <=0 to let workflow
# use default workers (ncpus - 1).
# Type: integer.
t_worker_count: 1
# Number of workers for spatial unwrapping in parallel. Set value to <=0 to let workflow use
# (ncpus - 1).
# Type: integer.
s_worker_count: 1
# Temporal unwrapping operations over spatial links are performed in batches and each batch
# is solved in parallel.
# Type: integer.
links_per_batch: 150000
# Temporal unwrapping costs.
# Type: string.
# Options: ['constant', 'distance', 'centroid'].
t_cost_type: constant
# Scale factor used to compute edge costs for temporal unwrapping.
# Type: number.
t_cost_scale: 100.0
# Spatial unwrapping costs.
# Type: string.
# Options: ['constant', 'distance', 'centroid'].
s_cost_type: constant
# Scale factor used to compute edge costs for spatial unwrapping.
# Type: number.
s_cost_scale: 100.0
# Number of tiles to process in parallel. Set to 0 for all tiles.
# Type: integer.
num_parallel_tiles: 1
merger_settings:
# Minimum number of overlap pixels to be considered valid.
# Type: integer.
min_overlap_points: 25
# Currently, only 'dirichlet' is supported.
# Type: dirichlet.
# Options: ['dirichlet'].
method: dirichlet
# Method used to estimate bulk offset between tiles.
# Type: string.
# Options: ['integer', 'L2'].
bulk_method: L2
# Number of interferograms to merge in one batch. Use zero to merge all interferograms in a
# single batch.
# Type: integer.
num_parallel_ifgs: 3
timeseries_options:
# Whether to run the inversion step after unwrapping, if more than a single-reference
# network is used.
# Type: boolean.
run_inversion: true
# Norm to use during timeseries inversion.
# Type: string.
# Options: ['L1', 'L2'].
method: L2
# Reference point (row, col) used if performing a time series inversion. If not provided, a
# point will be selected from a consistent connected component with low amplitude
# dispersion.
# Type: array | null.
reference_point:
# Run the velocity estimation from the phase time series.
# Type: boolean.
run_velocity: true
# Pixels with correlation below this value will be masked out.
# Type: number.
correlation_threshold: 0.2
# Size (rows, columns) of blocks of data to load at a time. 3D dimsion is number of
# interferograms (during inversion) and number of SLC dates (during velocity fitting).
# Type: array.
block_shape:
- 256
- 256
# Number of parallel blocks to process at once.
# Type: integer.
num_parallel_blocks: 4
correction_options:
# List of weather-model files (one per date) for tropospheric corrections.
# Type: array.
troposphere_files: []
# Format of dates contained in weather-model filenames.
# Type: string.
tropo_date_fmt: '%Y%m%d'
# Package for tropospheric correction. Choices: pyaps, raider.
# Type: string.
tropo_package: pyaps
# Enumeration representing different tropospheric models.
# Type: string.
# Options: ['ECMWF', 'ERA5', 'HRES', 'ERAINT', 'ERAI', 'MERRA', 'NARR', 'HRRR', 'GMAO'].
tropo_model: ECMWF
# Type of tropospheric delay.
# Type: string.
# Options: ['wet', 'dry', 'hydrostatic', 'comb'].
tropo_delay_type: comb
# List of GNSS-derived TEC maps for ionospheric corrections (one per date). Source is
# https://cddis.nasa.gov/archive/gnss/products/ionex/.
# Type: array.
ionosphere_files: []
# Line-of-sight geometry files for each burst/SLC stack area, for use in correction
# computations.
# Type: array.
geometry_files: []
# DEM file for tropospheric/ topographic phase corrections.
# Type: string | null.
dem_file: