NAME
i.sentinel.coverage - Checks the area coverage of Sentinel-1 or Sentinel-2 scenes selected by filters.
KEYWORDS
imagery,
satellite,
Sentinel,
geometry,
spatial query,
area
SYNOPSIS
i.sentinel.coverage
i.sentinel.coverage --help
i.sentinel.coverage settings=name area=name [start=string] [end=string] [producttype=string] [clouds=integer] [minpercent=integer] [names=string[,string,...]] [output=name] [--overwrite] [--help] [--verbose] [--quiet] [--ui]
Flags:
- --overwrite
- Allow output files to overwrite existing files
- --help
- Print usage summary
- --verbose
- Verbose module output
- --quiet
- Quiet module output
- --ui
- Force launching GUI dialog
Parameters:
- settings=name [required]
- Full path to settings file (user, password)
- Name of input file
- area=name [required]
- Name of input vector map
- Area input vector maps
- start=string
- Start date ('YYYY-MM-DD')
- end=string
- End date ('YYYY-MM-DD')
- producttype=string
- Sentinel product type to filter
- Options: SLC, GRD, OCN, S2MSI1C, S2MSI2A, S2MSI2Ap
- Default: S2MSI2A
- clouds=integer
- Maximum cloud cover percentage for Sentinel scene
- minpercent=integer
- Minimal percentage of coverage for Sentinel scene; error otherwise
- names=string[,string,...]
- Sentinel-1 or Sentinel-2 names
- output=name
- Output file with a list of Sentinel-1 or Sentinel-2 scene names
- Name for output file
i.sentinel.coverage is a GRASS GIS addon Python script to
check the area coverage by Sentinel scenes selected by a filter.
The coverage test considers only the geometric coverage by Sentinel
scene footprints and does not include the cloud covered pixels.
Note that only the last 12 months of Sentinel data are online available
ESA Hub, older scenes are stored in the Long Term Archive (LTA) and
cannot be retrieved immediately. The example is based on the North Carolina
dataset:
# extract Durham (NC) county
v.extract input=boundary_county output=county_durham where="NAME = 'DURHAM'"
# simplify geometry (needed for ESA Hub)
v.generalize input=county_durham output=county_durham_dp1000 method=douglas threshold=1000
# search for SLC scenes in certain period of time
i.sentinel.coverage settings=credentials.txt output=s1names.txt \
producttype=SLC minpercent=95 area=county_durham_dp1000 start=2020-10-01 end=2021-01-31
Note that only the last 12 months of Sentinel data are online available
ESA Hub, older scenes are stored in the Long Term Archive (LTA) and
cannot be retrieved immediately. The example is based on the North Carolina
dataset:
# extract Durham (NC) county
v.extract input=boundary_county output=county_durham where="NAME = 'DURHAM'"
# simplify geometry (needed for ESA Hub)
v.generalize input=county_durham output=county_durham_dp1000 method=douglas threshold=1000
# search for L2A scenes with minimal clouds in certain period of time
i.sentinel.coverage settings=credentials.txt output=s2names.txt \
producttype=S2MSI2A clouds=10 minpercent=95 area=county_durham_dp1000 start=2020-10-01 end=2021-01-31
i.sentinel.coverage settings=credentials.txt output=s2names.txt \
names=S2A_MSIL2A_20200104T024111_N0213_R089_T49MGU_20200104T061337,S2B_MSIL2A_20200129T023939_N0213_R089_T49MGU_20200201T153252 \
producttype=S2MSI2A clouds=20 minpercent=95 area=mangkawuk
When storing the list of scenes into a file, this resulting file can be used for
a parallelized import, using the
t.sentinel
set of addons:
# install t.sentinel.import and related addons
g.extension extension=t.sentinel url=https://github.com/mundialis/t.sentinel
# download and import into space-time cube (STRDS), using 4 CPUs
t.sentinel.import settings=credentials.txt s2names=s2names.txt nprocs=4 \
pattern='B(02_10|03_10|04_10|08_10)m' strds_output=s2_myarea directory=s2_data/
i.sentinel.download,
v.dissolve,
v.overlay,
v.to.db
Anika Weinmann,
mundialis
SOURCE CODE
Available at:
i.sentinel.coverage source code
(history)
Accessed: Thursday Nov 21 14:57:02 2024
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GRASS Development Team,
GRASS GIS 8.4.1dev Reference Manual