def get_landsat_scenes(wlon, nlat, elon, slat, startdate, enddate, cloud,
formal_name: str):
"""List landsat scenes from USGS."""
credentials = get_credentials()['landsat']
api = API(credentials['username'], credentials['password'])
landsat_folder_id = EE_FOLDER.get(formal_name)
if landsat_folder_id is None:
raise ValueError(
'Invalid Landsat product name. Expected one of {}'.format(
EE_FOLDER.keys()))
# Request
scenes_result = api.search(dataset=formal_name,
bbox=(slat, wlon, nlat, elon),
start_date=startdate,
end_date=enddate,
max_cloud_cover=cloud or 100,
max_results=50000)
scenes_output = {}
for scene in scenes_result:
if scene['displayId'].endswith('RT'):
logging.warning('Skipping Real Time {}'.format(scene['displayId']))
continue
copy_scene = dict()
copy_scene['sceneid'] = scene['displayId']
copy_scene['scene_id'] = scene['entityId']
copy_scene['cloud'] = int(scene['cloudCover'])
copy_scene['date'] = scene['acquisitionDate']
xmin, ymin, xmax, ymax = scene['sceneBounds'].split(',')
copy_scene['wlon'] = float(xmin)
copy_scene['slat'] = float(ymin)
copy_scene['elon'] = float(xmax)
copy_scene['nlat'] = float(ymax)
copy_scene['link'] = EE_DOWNLOAD_URL.format(folder=landsat_folder_id,
sid=scene['entityId'])
pathrow = scene['displayId'].split('_')[2]
copy_scene['path'] = pathrow[:3]
copy_scene['row'] = pathrow[3:]
scenes_output[scene['displayId']] = copy_scene
return scenes_output
def get_landsat_scenes(wlon, nlat, elon, slat, startdate, enddate, cloud,
limit):
"""List landsat scenes from USGS."""
credentials = get_credentials()['landsat']
api = API(credentials['username'], credentials['password'])
# Request
scenes_result = api.search(dataset='LANDSAT_8_C1',
bbox=(slat, wlon, nlat, elon),
start_date=startdate,
end_date=enddate,
max_cloud_cover=cloud or 100,
max_results=10000)
scenes_output = {}
for scene in scenes_result:
if scene['displayId'].endswith('RT'):
logging.warning('Skipping Real Time {}'.format(scene['displayId']))
continue
copy_scene = dict()
copy_scene['sceneid'] = scene['displayId']
copy_scene['scene_id'] = scene['entityId']
copy_scene['cloud'] = int(scene['cloudCover'])
copy_scene['date'] = scene['acquisitionDate']
xmin, ymin, xmax, ymax = scene['sceneBounds'].split(',')
copy_scene['wlon'] = float(xmin)
copy_scene['slat'] = float(ymin)
copy_scene['elon'] = float(xmax)
copy_scene['nlat'] = float(ymax)
copy_scene[
'link'] = 'https://earthexplorer.usgs.gov/download/12864/{}/STANDARD/EE'.format(
scene['entityId'])
pathrow = scene['displayId'].split('_')[2]
copy_scene['path'] = pathrow[:3]
copy_scene['row'] = pathrow[3:]
scenes_output[scene['displayId']] = copy_scene
return scenes_output
def search(
username, password, dataset, location, bbox, clouds, start, end, output, limit
):
"""Search for scenes."""
api = API(username, password)
where = {"dataset": dataset}
if location:
latitude, longitude = location
where.update(latitude=latitude, longitude=longitude)
if bbox:
where.update(bbox=bbox)
if clouds:
where.update(max_cloud_cover=clouds)
if start:
where.update(start_date=start)
if end:
where.update(end_date=end)
if limit:
where.update(max_results=limit)
results = api.search(**where)
api.logout()
if not results:
return
if output == "entity_id":
for scene in results:
click.echo(scene["entity_id"])
if output == "display_id":
for scene in results:
click.echo(scene["display_id"])
if output == "json":
dump = json.dumps(results, indent=True)
click.echo(dump)
if output == "csv":
with StringIO("tmp.csv") as f:
w = csv.DictWriter(f, results[0].keys())
w.writeheader()
w.writerows(results)
click.echo(f.getvalue())
class QCConnectLandsat:
def __init__(self, username, password, archive, backup_archive):
"""Connect API.
Raise ProcessorFailedError on failure
:param str username: username
:param str password: password
:param str archive: not used by Landsat implementation
:param str backup_archive: not used by Landsat implementation
"""
from landsatxplore.api import API as LandsatAPI
from landsatxplore.exceptions import EarthExplorerError
try:
self.api = LandsatAPI(
username, password
)
except EarthExplorerError as e:
raise ProcessorFailedError(
self,
"Unable to connect API: {}".format(e),
set_status=False
)
except json.JSONDecodeError as e:
raise ProcessorFailedError(
self,
"Landsat server is down. It raised a JSON exception: "
"{}".format(e),
set_status=False
)
def __del__(self):
if not hasattr(self, "api"):
return
from landsatxplore.exceptions import EarthExplorerError
try:
self.api.logout()
except EarthExplorerError as e:
Logger.error("Landsat server is down. {}".format(e))
def query(self, footprint, kwargs):
"""Query API.
:return: result
"""
from landsatxplore.exceptions import EarthExplorerError
kwargs['bbox'] = wkt2bbox(footprint, switch_axis=True)
kwargs['max_results'] = 500
del kwargs['producttype'] # used only for testing
try:
items = self.api.search(**kwargs)
except EarthExplorerError as e:
raise ProcessorFailedError(
self,
"Landsat server is down. "
"{}".format(e),
set_status=False
)
dict_items = {}
for item in items:
selected = False
if self.filter_by_tiles:
for tile in self.filter_by_tiles:
if str(tile) in item['entityId']:
selected = True
break
else:
selected = True
if selected:
dict_items[item['entityId']] = item
# used tests only
dict_items[item['entityId']]['producttype'] = item['displayId'].split('_')[1]
dict_items[item['entityId']]['beginposition'] = \
datetime.strptime(item['startTime'], '%Y-%m-%d')
else:
Logger.info("IP {} skipped by tile filter".format(item['entityId']))
return dict_items
dataset = "landsat_8_c1"
# https://pypi.org/project/landsatxplore/
# Landsat 7 ETM+ Collection 1 Level 1 landsat_etm_c1
# Landsat 7 ETM+ Collection 2 Level 1 landsat_etm_c2_l1
# Landsat 7 ETM+ Collection 2 Level 2 landsat_etm_c2_l2
# Landsat 8 Collection 1 Level 1 landsat_8_c1
# Landsat 8 Collection 2 Level 1 landsat_ot_c2_l1
# Landsat 8 Collection 2 Level 2 landsat_ot_c2_l2
# Initialize a new API instance and search for Landsat TM scenes
print("Searching from " + str(start_date) + " to " + str(end_date))
password = keyring.get_password("EarthExplorer", username)
api = API(username, password)
scenes = api.search(dataset=dataset,
latitude=latitude,
longitude=longitude,
start_date=str(start_date),
end_date=(str(end_date)),
max_cloud_cover=10)
print(f"{len(scenes)} scenes found:")
for scene in scenes:
print(scene['acquisition_date'])
# Initialize nvdi_array
nvdi_array = np.zeros((len(scenes), YSize, XSize))
nvdi_array = nvdi_array.astype('float32')
print(nvdi_array.shape)
# Iterate through list of scenes
for i in range(len(scenes)):
scene = scenes[i]
landsat_product_id = scene['landsat_product_id']
latitude, longitude = sys.argv[1], sys.argv[2]
start_date = sys.argv[3]
end_date = None
months=None
max_cloud_cover=None
path = "/mnt/c/Users/avaro/Desktop/LST/" + site_id + "/"
user = "******"
pw = "pepsiav123pepsiav123"
api = api(user,pw)
# scenes = api.search( dataset, latitude=latitude, longitude=longitude, bbox=None, start_date=start_date, end_date=end_date, max_cloud_cover=max_cloud_cover, months=months, max_results=2)
scenes = api.search( dataset, latitude=latitude, longitude=longitude,max_cloud_cover=max_cloud_cover, months=months)
print('{} scenes found.'.format(len(scenes)))
api.logout()
#init downloader
downloader = ee(user, pw)
# entity id of latest
print(scenes[0]['entityId'])
# download & persist
downloader.download(scenes[0]['entityId'],path)
#close session
downloader.logout()