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config.yaml
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config.yaml
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# list of scenes to download and process
scenes: [
# Antarctica - Maitri Station (-70.76683, 11.7308)
# 'S1B_IW_SLC__1SSH_20190327T195016_20190327T195045_015544_01D236_9504',
# 'S1B_IW_SLC__1SSH_20190526T195018_20190526T195048_016419_01EE8D_53BC',
# 'S1B_IW_SLC__1SSH_20190315T195015_20190315T195045_015369_01CC73_DB8B',
# Antarctica - Bharati Station (-69.4068, 76.19525)
# 'S1B_IW_SLC__1SSH_20190223T222639_20190223T222706_015079_01C2E9_1D63',
# 'S1A_IW_SLC__1SSH_20190605T222724_20190605T222751_027550_031BE1_AD3A',
# # Antarctica - Law Dome (-66.163448 113.66396)
# 'S1B_IW_SLC__1SSH_20211204T123606_20211204T123635_029875_039105_E7EC',
# 'S1A_IW_SLC__1SSH_20211210T123647_20211210T123716_040946_04DCF0_9FBA',
# 'S1B_IW_SLC__1SSH_20211216T123605_20211216T123634_030050_03968D_9501',
# # Antarctica - Ross Island (-77.7018, 166.7541)
# 'S1A_IW_SLC__1SSH_20211208T124745_20211208T124815_040917_04DBED_5CFF',
# 'S1A_IW_SLC__1SSH_20211220T124745_20211220T124815_041092_04E1C2_0475',
# 'S1A_IW_SLC__1SSH_20220101T124744_20220101T124814_041267_04E7A2_1DAD',
# # Antarctica - Heard/McDonald Island (-53.1057, 73.543)
# 'S1A_IW_SLC__1SSH_20220103T141935_20220103T142005_041297_04E8B4_9B44',
# 'S1A_IW_SLC__1SSH_20220108T142747_20220108T142815_041370_04EB2C_4E64',
# 'S1A_IW_SLC__1SSH_20220115T141935_20220115T142005_041472_04EE7C_9E3D',
# # Antarctica - Antimeridian (-70, 180) approx - These Failed through hyp3
# 'S1A_IW_SLC__1SSH_20220203T153614_20220203T153644_041750_04F7DF_8C3E',
# 'S1A_IW_SLC__1SSH_20220122T153615_20220122T153645_041575_04F1EF_9254',
# # Antarctica - Antimeridian (-75, 180) approx
# 'S1A_IW_SLC__1SDV_20191028T131928_20191028T131947_029659_0360CA_A1A0',
# 'S1A_IW_SLC__1SDH_20161201T131103_20161201T131131_014186_016EB7_F766',
# # Australia - Yaragadee (-29.0474, 115.3461) Descending (Only Avail)
# 'S1B_IW_SLC__1SDV_20211201T214143_20211201T214210_029837_038FD8_81C3',
# 'S1B_IW_SLC__1SDV_20211201T214208_20211201T214240_029837_038FD8_8B37',
# 'S1B_IW_SLC__1SDV_20211213T214143_20211213T214210_030012_039555_8753',
# # Australia - Queensland Forest (-25.533333 147.533333)
# 'S1A_IW_SLC__1SDV_20220121T193807_20220121T193834_041563_04F181_5804',
# 'S1A_IW_SLC__1SDV_20220202T084138_20220202T084206_041731_04F740_197D',
# 'S1A_IW_SLC__1SDV_20220202T084204_20220202T084231_041731_04F740_400F',
# # Australia - SURAT QLD corner reflector (-27.0252,150.5759) - ASCENDING MODE (REQUIRED)
# 'S1A_IW_SLC__1SSV_20230312T083311_20230312T083339_047608_05B7B4_9E47',
# 'S1A_IW_SLC__1SSH_20230417T083309_20230417T083337_048133_05C96C_990D',
# 'S1A_IW_SLC__1SSV_20230523T083310_20230523T083338_048658_05DA2F_A8C3',
# 'S1A_IW_SLC__1SSH_20230722T083317_20230722T083345_049533_05F4C7_7C1C',
# 'S1A_IW_SLC__1SSV_20230803T083315_20230803T083342_049708_05FA2F_3DCE',
# 'S1A_IW_SLC__1SSH_20230908T083317_20230908T083344_050233_060BEC_D8D5',
# 'S1A_IW_SLC__1SSV_20231014T083317_20231014T083345_050758_061DE7_512C',
# 'S1A_IW_SLC__1SSH_20231119T083317_20231119T083345_051283_062FEC_0B2C',
# 'S1A_IW_SLC__1SSV_20231225T083315_20231225T083343_051808_064216_090C',
# 'S1A_IW_SLC__1SSH_20240106T083314_20240106T083342_051983_064812_8D7E',
# 'S1A_IW_SLC__1SSV_20240118T083314_20240118T083341_052158_064E01_F2FB',
# 'S1A_IW_SLC__1SSH_20240130T083313_20240130T083341_052333_0653F0_B544',
# Australia - QLD Forest time series (sigma0) (147.533333 -25.533333)
# 'S1A_IW_SLC__1SDV_20220109T084205_20220109T084232_041381_04EB86_4CA4',
# 'S1A_IW_SLC__1SDV_20220214T084204_20220214T084231_041906_04FD5B_3E6A',
# 'S1A_IW_SLC__1SDV_20220322T084204_20220322T084231_042431_050F45_D995',
# 'S1A_IW_SLC__1SDV_20220427T084205_20220427T084232_042956_0520DA_A334',
# 'S1A_IW_SLC__1SDV_20220509T084206_20220509T084232_043131_0526B1_B779',
# 'S1A_IW_SLC__1SDV_20220602T084207_20220602T084234_043481_053115_3E34',
# 'S1A_IW_SLC__1SDV_20220708T084210_20220708T084237_044006_0540C0_A559',
# 'S1A_IW_SLC__1SDV_20220813T084212_20220813T084239_044531_055086_7B90',
# 'S1A_IW_SLC__1SDV_20220918T084213_20220918T084240_045056_056239_CBF0',
# 'S1A_IW_SLC__1SDV_20221024T084214_20221024T084241_045581_057328_A643',
# 'S1A_IW_SLC__1SDV_20221129T084213_20221129T084240_046106_0584E7_6C64',
# 'S1A_IW_SLC__1SDV_20221223T084212_20221223T084238_046456_0590D9_7BFF',
# Queensland - Rainforest timeseries (152.604 -26.637)
# 'S1A_IW_SLC__1SDV_20220106T191355_20220106T191422_041344_04EA48_E185',
# 'S1A_IW_SLC__1SDV_20220130T191354_20220130T191421_041694_04F5F9_1AFD',
# 'S1A_IW_SLC__1SDV_20220211T191354_20220211T191421_041869_04FC03_7559',
# 'S1A_IW_SLC__1SDV_20220307T191354_20220307T191421_042219_050811_3A95',
# 'S1A_IW_SLC__1SDV_20220331T191354_20220331T191421_042569_0513ED_EDBB',
# 'S1A_IW_SLC__1SDV_20220424T191355_20220424T191422_042919_051FA1_3965',
# 'S1A_IW_SLC__1SDV_20220611T191358_20220611T191425_043619_053532_39C3',
# 'S1A_IW_SLC__1SDV_20220705T191359_20220705T191426_043969_053FA4_EAFD',
# 'S1A_IW_SLC__1SDV_20220729T191401_20220729T191428_044319_054A0A_E294',
# 'S1A_IW_SLC__1SDV_20220822T191402_20220822T191429_044669_05552A_4729',
# 'S1A_IW_SLC__1SDV_20220915T191403_20220915T191430_045019_0560F2_B29C',
# 'S1A_IW_SLC__1SDV_20221009T191404_20221009T191431_045369_056CB2_5D9E',
# 'S1A_IW_SLC__1SDV_20221102T191403_20221102T191430_045719_0577C9_B76C',
# 'S1A_IW_SLC__1SDV_20221126T191403_20221126T191430_046069_05839D_9DD9',
# 'S1A_IW_SLC__1SDV_20221208T191403_20221208T191430_046244_058998_28A3',
# 'S1A_IW_SLC__1SDV_20221220T191402_20221220T191429_046419_058F94_70A0',
# tets sites pat wongpan
# S1A_IW_SLC__1SSH_20240301T212157_20240301T212223_052793_066382_8D95,
# S1A_IW_SLC__1SSH_20240302T034858_20240302T034926_052797_066396_0B8A,
# daintree rainforest
# 'S1A_IW_SLC__1SDV_20240719T195219_20240719T195246_054834_06AD81_2850', # Done 20m
# 'S1A_IW_SLC__1SDV_20240625T195220_20240625T195247_054484_06A15E_25DD', # Done 20m
# 'S1A_IW_SLC__1SDV_20240601T195221_20240601T195248_054134_06953D_BA35', # Done 20m, done etad
# 'S1A_IW_SLC__1SDV_20240508T195222_20240508T195249_053784_06892A_14BF', # Done 20m, done etad
# 'S1A_IW_SLC__1SDV_20240414T195221_20240414T195248_053434_067B76_7297', # Done 20m, done etad
# 'S1A_IW_SLC__1SDV_20240321T195221_20240321T195248_053084_066DEF_BB5C', # Done 20m, done etad
# 'S1A_IW_SLC__1SDV_20240226T195220_20240226T195247_052734_066181_BA46', # Done 20m, done etad
# 'S1A_IW_SLC__1SDV_20240202T195221_20240202T195248_052384_0655AE_65A0', # to do, done etad
# 'S1A_IW_SLC__1SDV_20240109T195221_20240109T195248_052034_0649D6_1FF6', # Done 20m, done etad
# 'S1A_IW_SLC__1SDV_20231216T195223_20231216T195250_051684_063DCD_4ADC', # Done 20m, done erad
# 'S1A_IW_SLC__1SDV_20231122T195224_20231122T195251_051334_0631B4_AC2B', # Done 20m, done etad
# 'S1A_IW_SLC__1SDV_20231029T195225_20231029T195251_050984_06259C_6024', # Done 20m
# 'S1A_IW_SLC__1SDV_20231005T195224_20231005T195251_050634_0619A2_216F', # Done 20m, done etad
# 'S1A_IW_SLC__1SDV_20230911T195224_20230911T195251_050284_060DB2_CC96', # Done 20m
#'S1A_IW_SLC__1SDV_20230818T195223_20230818T195250_049934_0601BA_AE0C', # Done 20m
]
# the name of the software. This will form part of the path
# where the products are writted
software : pyrosar
# we will mount this folder in the docker container so all data can be accessed
# this folder should contain all the downloaded scenes, dems, etc specified below
data_folder: '/data'
#save directory for final opera products
# a sub directory for each scene will be made
pyrosar_output_folder: /data/pyroSAR/outdir
# location of SNAP installation
snap_path: /home/ec2-user/SNAP9/bin #'/Applications/snap/bin'
# location of earthdata credentials to download data.
earthdata_credentials: credentials/credentials_earthdata.yaml
# location of aws credentials
aws_credentials: credentials/credentials_aws.yaml
# location of copernicus data space ecosystem credentials
copernicus_credentials: credentials/credentials_copernicus.yaml
# directory to save scenes
scene_folder: /data/scenes
# whether to unzip the safe file
unzip_scene: False
# directory where DEM will be saved - a sub folder is made for each DEM type
dem_folder: /data/dem
# type of dem to download for each scene
# list of valid dems in https://pypi.org/project/dem-stitcher/
dem_type: glo_30
# File path to a DEM to use (skip download process and use DEM specified)
# leave empty to ignore
dem_path:
# Apply ETAD corrections to the slc
# Note - These must be available locally
apply_ETAD : False
# number of gdal threads to process the ETAD file with
gdal_threads : 4
# Locally accessible folder containing ETAD files
ETAD_folder : /data/ETAD
# overwrite the dem if it already exists
overwrite_dem : False
# add a prefix to the scene in the s3 bucket
# mostly for testing, leave blank to exclude
scene_prefix:
# specify the folder in the s3 bucket
# sar-software-comparison-Xm, qld-rainforest-timeseries-Xm-2022 daintree-rainforest-timeseries-XXXm-2024
s3_bucket_folder: sar-comparison-study/s1-rtc-scenes/daintree-rainforest-timeseries-20m-2024
# s3 bucket to push the results
# note, output crs (trg_crs) is set in opera config
# formatting will be {s3_bucket}/{s3_bucket_folder}/{opera-rtc}/{dem_type}/{trg_crs}/{prefix}{scene}/{product_id}
s3_bucket: deant-data-public-dev
# whether to push to s3
push_to_s3: True
# whether to push the DEM to the S3 bucket
upload_dem: True
# delete files after run
delete_local_files: True
#pyrosar settings - pixel size
pyrosar_spacing: 20
#pyrosar settings - scale of final product
# e.g. linear, db
pyrosar_scaling: linear
# pyrosar settings - reference area
# e.g. gamma0, sigma0, beta0 or ['gamma0','sigma0']
pyrosar_refarea: ['gamma0','sigma0']
# pyrosar settings
# A target geographic reference system in WKT, EPSG, PROJ4 or OPENGIS format.
# See function :func:`spatialist.auxil.crsConvert()` for details.
# e.g. 4326, 3031
# set 'default' to set the crs based on the UTM location of the scene centre
# pyrosar_t_srs: default
pyrosar_t_srs: default
# turn off terrain flattening, e.g. testing for dem artifacts
# default = True (i.e. we want to perform rtc)
pyrosar_terrainFlattening : True
# remve scattering area if no rtc
pyrosar_export_extra: ['incidenceAngleFromEllipsoid','localIncidenceAngle','DEM','layoverShadowMask','scatteringArea','gammaSigmaRatio']
# pyrosar_export_extra: ['DEM']
# a list of arguments to pass to the snap gpt interperator
# -Djava.io.tmpdir=/data/tmp -> change temp dir, fills up root space on aws
# gpt_args : ['-Djava.io.tmpdir=/data/tmp']