def search(aoi, start_date=None, end_date=None, satellite='L8',
sensor='OLITIRS', api='devseed'):
"""
Search Landsat images covering an AOI and timespan using a given API.
Args:
aoi (geojson.Polygon): area of interest
start_date (datetime.datetime): start of the search time range
end_date (datetime.datetime): end of the search time range
api (str, optional): either gcloud (default), scihub, planet or devseed
satellite (str, optional): either L1...L8
sensor (str, optional): MSS, TM, ETM, OLITIRS
see https://landsat.usgs.gov/what-are-band-designations-landsat-satellites
Returns:
list of image objects
"""
# list available images
if api == 'gcloud':
from tsd import search_gcloud
images = search_gcloud.search(aoi, start_date, end_date, satellite=satellite, sensor=sensor)
elif api == 'devseed':
from tsd import search_devseed
images = search_devseed.search(aoi, start_date, end_date, satellite='Landsat-8')
images = [l8_metadata_parser.LandsatImage(img, api) for img in images]
# sort images by acquisition day, then by mgrs id
images.sort(key=(lambda k: (k.date.date(), k.row, k.path)))
print('Found {} images'.format(len(images)))
return images
def search(aoi,
start_date=None,
end_date=None,
product_type=None,
api='devseed'):
"""
Search Sentinel-2 images covering an AOI and timespan using a given API.
Args:
aoi (geojson.Polygon): area of interest
start_date (datetime.datetime): start of the search time range
end_date (datetime.datetime): end of the search time range
product_type (str, optional): either 'L1C' or 'L2A'
api (str, optional): either devseed (default), scihub, planet or gcloud
Returns:
list of image objects
"""
# list available images
if api == 'devseed':
from tsd import search_devseed
images = search_devseed.search(aoi, start_date, end_date, 'Sentinel-2')
elif api == 'scihub':
from tsd import search_scihub
if product_type is not None:
product_type = 'S2MSI{}'.format(product_type[1:])
images = search_scihub.search(aoi,
start_date,
end_date,
satellite='Sentinel-2',
product_type=product_type)
elif api == 'planet':
from tsd import search_planet
images = search_planet.search(aoi,
start_date,
end_date,
item_types=['Sentinel2L1C'])
elif api == 'gcloud':
from tsd import search_gcloud
images = search_gcloud.search(aoi, start_date, end_date)
# parse the API metadata
images = [s2_metadata_parser.Sentinel2Image(img, api) for img in images]
# sort images by acquisition day, then by mgrs id
images.sort(key=(lambda k: (k.date.date(), k.mgrs_id)))
# remove duplicates (same acquisition date but different mgrs tile id)
seen = set()
unique_images = []
for img in images:
if img.date not in seen:
seen.add(img.date)
unique_images.append(img)
print('Found {} images'.format(len(unique_images)))
return unique_images
def search(aoi, start_date=None, end_date=None, satellite='L8',
sensor='OLITIRS', api='stac', unique_path_row_per_datatake=True):
"""
Search Landsat images covering an AOI and timespan using a given API.
Args:
aoi (geojson.Polygon): area of interest
start_date (datetime.datetime): start of the search time range
end_date (datetime.datetime): end of the search time range
api (str, optional): either stac (default) or gcloud
satellite (str, optional): either L4, L5, L7 or L8
sensor (str, optional): MSS, TM, ETM, OLITIRS. See:
https://landsat.usgs.gov/what-are-band-designations-landsat-satellites
unique_path_row_per_datatake (bool): if True, only one path/row tile per
datatake is considered. The selected path/row is the first in
alphabetical order.
Returns:
list of image objects
"""
# list available images
if api == 'gcloud':
from tsd import search_gcloud
images = search_gcloud.search(aoi, start_date, end_date, satellite=satellite, sensor=sensor)
elif api == 'stac':
from tsd import search_stac
images = search_stac.search(aoi, start_date, end_date, satellite='Landsat-8')
else:
raise ValueError('The api "{}" is not available for {}.'.format(api, __file__))
# parse the API metadata
images = [l8_metadata_parser.LandsatImage(img, api) for img in images]
# sort images by acquisition date, then by row/path
images.sort(key=(lambda k: (k.date.date(), k.row, k.path)))
# remove duplicates (same acquisition date but different path/row)
if unique_path_row_per_datatake:
seen = set()
unique_images = []
for img in images:
if img.date.date() not in seen:
seen.add(img.date.date())
unique_images.append(img)
images = unique_images
print('Found {} images'.format(len(images)))
return images
def search(aoi=None,
start_date=None,
end_date=None,
product_type="L2A",
tile_id=None,
title=None,
relative_orbit_number=None,
api='stac',
search_type='contains',
unique_mgrs_tile_per_orbit=True):
"""
Search Sentinel-2 images covering an AOI and timespan using a given API.
Args:
aoi (geojson.Polygon): area of interest
start_date (datetime.datetime): start of the search time range
end_date (datetime.datetime): end of the search time range
tile_id (str): MGRS tile identifier, e.g. "31TCJ"
title (str): product title, e.g. "S2A_MSIL1C_20160105T143732_N0201_R096_T19KGT_20160105T143758"
relative_orbit_number (int): relative orbit number, from 1 to 143
product_type (str, optional): either "L1C" or "L2A" (default). Ignored
with planet and gcloud APIs.
api (str, optional): either stac (default), scihub, planet or gcloud
search_type (str): either "contains" or "intersects"
unique_mgrs_tile_per_orbit (bool): if True, only one MGRS tile per
orbit is considered. The selected MGRS tile is the first in
alphabetical order. This is useful to remove duplicates when the
input AOI intersects several MGRS tiles.
Returns:
list of image objects
"""
# list available images
if api == 'scihub':
from tsd import search_scihub
if product_type is not None:
product_type = 'S2MSI{}'.format(product_type[1:])
images = search_scihub.search(
aoi,
start_date,
end_date,
satellite="Sentinel-2",
product_type=product_type,
relative_orbit_number=relative_orbit_number,
tile_id=tile_id,
title=title,
search_type=search_type)
elif api == 'stac':
from tsd import search_stac
images = search_stac.search(aoi,
start_date,
end_date,
satellite="Sentinel-2",
product_type=product_type)
elif api == 'planet':
from tsd import search_planet
images = search_planet.search(aoi,
start_date,
end_date,
item_types=['Sentinel2L1C'])
elif api == 'gcloud':
from tsd import search_gcloud
images = search_gcloud.search(aoi, start_date, end_date)
# parse the API metadata
images = [s2_metadata_parser.Sentinel2Image(img, api) for img in images]
# sort images by date, relative_orbit, mgrs_id
images.sort(key=(lambda k: (k.date.date(), k.relative_orbit, k.mgrs_id)))
# remove duplicates (same pair (date, relative_orbit) but different mgrs_id)
if unique_mgrs_tile_per_orbit:
seen = set()
unique_images = []
for img in images:
if (img.date.date(), img.relative_orbit) not in seen:
seen.add((img.date.date(), img.relative_orbit))
unique_images.append(img)
images = unique_images
print('Found {} images'.format(len(images)))
return images
def search(aoi,
start_date=None,
end_date=None,
product_type=None,
api='devseed',
search_type='contains',
unique_mgrs_tile_per_datatake=True):
"""
Search Sentinel-2 images covering an AOI and timespan using a given API.
Args:
aoi (geojson.Polygon): area of interest
start_date (datetime.datetime): start of the search time range
end_date (datetime.datetime): end of the search time range
product_type (str, optional): either 'L1C' or 'L2A'
api (str, optional): either devseed (default), scihub, planet or gcloud
search_type (str): either "contains" or "intersects"
unique_mgrs_tile_per_datatake (bool): if True, only one MGRS tile per
datatake is considered. The selected MGRS tile is the first in
alphabetical order.
Returns:
list of image objects
"""
# list available images
if api == 'devseed':
from tsd import search_devseed
images = search_devseed.search(aoi, start_date, end_date, 'Sentinel-2')
elif api == 'scihub':
from tsd import search_scihub
if product_type is not None:
product_type = 'S2MSI{}'.format(product_type[1:])
images = search_scihub.search(aoi,
start_date,
end_date,
satellite='Sentinel-2',
product_type=product_type,
search_type=search_type)
elif api == 'planet':
from tsd import search_planet
images = search_planet.search(aoi,
start_date,
end_date,
item_types=['Sentinel2L1C'])
elif api == 'gcloud':
from tsd import search_gcloud
images = search_gcloud.search(aoi, start_date, end_date)
# parse the API metadata
images = [s2_metadata_parser.Sentinel2Image(img, api) for img in images]
# remove images that have no datatake_id
images = [img for img in images if hasattr(img, "datatake_id")]
# sort images by datatake_id, then by mgrs id
images.sort(key=(lambda k: (k.datatake_id, k.mgrs_id)))
# remove duplicates (same datatake_id but different mgrs tile id)
if unique_mgrs_tile_per_datatake:
seen = set()
unique_images = []
for img in images:
if img.datatake_id not in seen:
seen.add(img.datatake_id)
unique_images.append(img)
images = unique_images
print('Found {} images'.format(len(images)))
return images