def test_scihub_unresponsive():
timeout_connect = 6
timeout_read = 6.6
timeout = (timeout_connect, timeout_read)
api = SentinelAPI("mock_user", "mock_password", timeout=timeout)
with requests_mock.mock() as rqst:
rqst.request(requests_mock.ANY, requests_mock.ANY, exc=requests.exceptions.ConnectTimeout)
with pytest.raises(requests.exceptions.ConnectTimeout):
api.query(**_small_query)
with pytest.raises(requests.exceptions.ConnectTimeout):
api.get_product_odata('8df46c9e-a20c-43db-a19a-4240c2ed3b8b')
with pytest.raises(requests.exceptions.ConnectTimeout):
api.download('8df46c9e-a20c-43db-a19a-4240c2ed3b8b')
with pytest.raises(requests.exceptions.ConnectTimeout):
api.download_all(['8df46c9e-a20c-43db-a19a-4240c2ed3b8b'])
with requests_mock.mock() as rqst:
rqst.request(requests_mock.ANY, requests_mock.ANY, exc=requests.exceptions.ReadTimeout)
with pytest.raises(requests.exceptions.ReadTimeout):
api.query(**_small_query)
with pytest.raises(requests.exceptions.ReadTimeout):
api.get_product_odata('8df46c9e-a20c-43db-a19a-4240c2ed3b8b')
with pytest.raises(requests.exceptions.ReadTimeout):
api.download('8df46c9e-a20c-43db-a19a-4240c2ed3b8b')
with pytest.raises(requests.exceptions.ReadTimeout):
api.download_all(['8df46c9e-a20c-43db-a19a-4240c2ed3b8b'])
def test_scihub_unresponsive():
api = SentinelAPI("mock_user", "mock_password")
with requests_mock.mock() as rqst:
rqst.request(requests_mock.ANY,
requests_mock.ANY,
exc=requests.exceptions.ConnectTimeout)
with pytest.raises(requests.exceptions.Timeout):
api.query(**_small_query)
with pytest.raises(requests.exceptions.Timeout):
api.get_product_odata('8df46c9e-a20c-43db-a19a-4240c2ed3b8b')
with pytest.raises(requests.exceptions.Timeout):
api.download('8df46c9e-a20c-43db-a19a-4240c2ed3b8b')
with pytest.raises(requests.exceptions.Timeout):
api.download_all(['8df46c9e-a20c-43db-a19a-4240c2ed3b8b'])
def test_SentinelAPI_wrong_credentials(small_query):
api = SentinelAPI("wrong_user", "wrong_password")
@contextmanager
def assert_exception():
with pytest.raises(UnauthorizedError) as excinfo:
yield
assert excinfo.value.response.status_code == 401
assert "Invalid user name or password" in excinfo.value.msg
with assert_exception():
api.query(**small_query)
with assert_exception():
api.get_product_odata("8df46c9e-a20c-43db-a19a-4240c2ed3b8b")
with assert_exception():
api.download("8df46c9e-a20c-43db-a19a-4240c2ed3b8b")
with assert_exception():
api.download_all(["8df46c9e-a20c-43db-a19a-4240c2ed3b8b"])
def _get_quicklook(api_kwargs, cassette):
api = SentinelAPI(**api_kwargs)
ids = [
"6b126ea4-fe27-440c-9a5c-686f386b7291",
"1a9401bc-6986-4707-b38d-f6c29ca58c00",
"54e6c4ad-6f4e-4fbf-b163-1719f60bfaeb",
]
with cassette:
odata = [api.get_product_odata(x) for x in ids]
return odata
def test_SentinelAPI_wrong_credentials():
api = SentinelAPI(
"wrong_user",
"wrong_password"
)
with pytest.raises(SentinelAPIError) as excinfo:
api.query(**_small_query)
assert excinfo.value.response.status_code == 401
with pytest.raises(SentinelAPIError) as excinfo:
api.get_product_odata('8df46c9e-a20c-43db-a19a-4240c2ed3b8b')
assert excinfo.value.response.status_code == 401
with pytest.raises(SentinelAPIError) as excinfo:
api.download('8df46c9e-a20c-43db-a19a-4240c2ed3b8b')
assert excinfo.value.response.status_code == 401
with pytest.raises(SentinelAPIError) as excinfo:
api.download_all(['8df46c9e-a20c-43db-a19a-4240c2ed3b8b'])
assert excinfo.value.response.status_code == 401
def test_SentinelAPI_wrong_credentials():
api = SentinelAPI(
"wrong_user",
"wrong_password"
)
with pytest.raises(SentinelAPIError) as excinfo:
api.query(**_small_query)
assert excinfo.value.response.status_code == 401
with pytest.raises(SentinelAPIError) as excinfo:
api.get_product_odata('8df46c9e-a20c-43db-a19a-4240c2ed3b8b')
assert excinfo.value.response.status_code == 401
with pytest.raises(SentinelAPIError) as excinfo:
api.download('8df46c9e-a20c-43db-a19a-4240c2ed3b8b')
assert excinfo.value.response.status_code == 401
with pytest.raises(SentinelAPIError) as excinfo:
api.download_all(['8df46c9e-a20c-43db-a19a-4240c2ed3b8b'])
assert excinfo.value.response.status_code == 401
def test_get_product_odata_short():
api = SentinelAPI(**_api_auth)
expected_short = {
'8df46c9e-a20c-43db-a19a-4240c2ed3b8b': {
'id':
'8df46c9e-a20c-43db-a19a-4240c2ed3b8b',
'size':
143549851,
'md5':
'D5E4DF5C38C6E97BF7E7BD540AB21C05',
'url':
"https://scihub.copernicus.eu/apihub/odata/v1/Products('8df46c9e-a20c-43db-a19a-4240c2ed3b8b')/$value",
'date':
datetime(2015, 11, 21, 10, 3, 56, 675000),
'footprint':
'POLYGON((-63.852531 -5.880887,-67.495872 -5.075419,-67.066071 -3.084356,-63.430576 -3.880541,'
'-63.852531 -5.880887))',
'title':
'S1A_EW_GRDM_1SDV_20151121T100356_20151121T100429_008701_00C622_A0EC'
},
'44517f66-9845-4792-a988-b5ae6e81fd3e': {
'id':
'44517f66-9845-4792-a988-b5ae6e81fd3e',
'date':
datetime(2015, 12, 27, 14, 22, 29),
'footprint':
'POLYGON((-58.80274769505742 -4.565257232533263,-58.80535376268811 -5.513960396525286,'
'-57.90315169909761 -5.515947033626909,-57.903151791669515 -5.516014389089381,-57.85874693129081 -5.516044812342758,'
'-57.814323596961835 -5.516142631941845,-57.81432351345917 -5.516075248310466,-57.00018056571297 -5.516633044843839,'
'-57.000180565731384 -5.516700066819259,-56.95603179187787 -5.51666329264377,-56.91188395837315 -5.516693539799448,'
'-56.91188396736038 -5.51662651925904,-56.097209386295305 -5.515947927683427,-56.09720929423562 -5.516014937246069,'
'-56.053056977999596 -5.5159111504805916,-56.00892491028779 -5.515874390220655,-56.00892501130261 -5.515807411549814,'
'-55.10621586418906 -5.513685455771881,-55.108821882251775 -4.6092845892233,-54.20840287327946 -4.606372862374043,'
'-54.21169990975238 -3.658594390979672,-54.214267703869346 -2.710949551849636,-55.15704255065496 -2.7127451087194463,'
'-56.0563616875051 -2.71378646425769,-56.9561852630143 -2.7141556791285275,-57.8999998009875 -2.713837142510183,'
'-57.90079161941062 -3.6180222056692726,-58.800616247288836 -3.616721351843382,-58.80274769505742 -4.565257232533263))',
'md5':
'48C5648C2644CE07207B3C943DEDEB44',
'size':
5854429622,
'title':
'S2A_OPER_PRD_MSIL1C_PDMC_20151228T112523_R110_V20151227T142229_20151227T142229',
'url':
"https://scihub.copernicus.eu/apihub/odata/v1/Products('44517f66-9845-4792-a988-b5ae6e81fd3e')/$value"
}
}
for id, expected in expected_short.items():
ret = api.get_product_odata(id)
assert set(ret) == set(expected)
for k in ret:
assert ret[k] == expected[k]
def test_scihub_unresponsive(small_query):
timeout_connect = 6
timeout_read = 6.6
timeout = (timeout_connect, timeout_read)
api = SentinelAPI("mock_user", "mock_password", timeout=timeout)
with requests_mock.mock() as rqst:
rqst.request(requests_mock.ANY,
requests_mock.ANY,
exc=requests.exceptions.ConnectTimeout)
with pytest.raises(requests.exceptions.ConnectTimeout):
api.query(**small_query)
with pytest.raises(requests.exceptions.ConnectTimeout):
api.get_product_odata("8df46c9e-a20c-43db-a19a-4240c2ed3b8b")
with pytest.raises(requests.exceptions.ConnectTimeout):
api.download("8df46c9e-a20c-43db-a19a-4240c2ed3b8b")
with pytest.raises(requests.exceptions.ConnectTimeout):
api.download_all(["8df46c9e-a20c-43db-a19a-4240c2ed3b8b"])
with requests_mock.mock() as rqst:
rqst.request(requests_mock.ANY,
requests_mock.ANY,
exc=requests.exceptions.ReadTimeout)
with pytest.raises(requests.exceptions.ReadTimeout):
api.query(**small_query)
with pytest.raises(requests.exceptions.ReadTimeout):
api.get_product_odata("8df46c9e-a20c-43db-a19a-4240c2ed3b8b")
with pytest.raises(requests.exceptions.ReadTimeout):
api.download("8df46c9e-a20c-43db-a19a-4240c2ed3b8b")
with pytest.raises(requests.exceptions.ReadTimeout):
api.download_all(["8df46c9e-a20c-43db-a19a-4240c2ed3b8b"])
def _get_smallest(api_kwargs, cassette, online, n=3):
time_range = ("NOW-1MONTH", None) if online else (None, "20170101")
odatas = []
with cassette:
api = SentinelAPI(**api_kwargs)
products = api.query(date=time_range, size="/.+KB/", limit=15)
for uuid in products:
odata = api.get_product_odata(uuid)
if odata["Online"] == online:
odatas.append(odata)
if len(odatas) == n:
break
assert len(odatas) == n
return odatas
def test_get_product_odata_scihub_down():
api = SentinelAPI("mock_user", "mock_password")
with requests_mock.mock() as rqst:
rqst.get(
"https://scihub.copernicus.eu/apihub/odata/v1/Products('8df46c9e-a20c-43db-a19a-4240c2ed3b8b')?$format=json",
text="Mock SciHub is Down",
status_code=503)
with pytest.raises(SentinelAPIError) as excinfo:
api.get_product_odata('8df46c9e-a20c-43db-a19a-4240c2ed3b8b')
rqst.get(
"https://scihub.copernicus.eu/apihub/odata/v1/Products('8df46c9e-a20c-43db-a19a-4240c2ed3b8b')/?$format=json",
text="Mock SciHub is Down",
status_code=200)
with pytest.raises(SentinelAPIError) as excinfo:
api.get_product_odata('8df46c9e-a20c-43db-a19a-4240c2ed3b8b')
assert excinfo.value.msg == "Mock SciHub is Down"
# Test with a real server response
rqst.get(
"https://scihub.copernicus.eu/apihub/odata/v1/Products('8df46c9e-a20c-43db-a19a-4240c2ed3b8b')?$format=json",
text=textwrap.dedent("""\
<!doctype html>
<title>The Sentinels Scientific Data Hub</title>
<link href='https://fonts.googleapis.com/css?family=Open+Sans' rel='stylesheet' type='text/css'>
<style>
body { text-align: center; padding: 125px; background: #fff;}
h1 { font-size: 50px; }
body { font: 20px 'Open Sans',Helvetica, sans-serif; color: #333; }
article { display: block; text-align: left; width: 820px; margin: 0 auto; }
a { color: #0062a4; text-decoration: none; font-size: 26px }
a:hover { color: #1b99da; text-decoration: none; }
</style>
<article>
<img alt="" src="/datahub.png" style="float: left;margin: 20px;">
<h1>The Sentinels Scientific Data Hub will be back soon!</h1>
<div style="margin-left: 145px;">
<p>
Sorry for the inconvenience,<br/>
we're performing some maintenance at the moment.<br/>
</p>
<!--<p><a href="https://scihub.copernicus.eu/news/News00098">https://scihub.copernicus.eu/news/News00098</a></p>-->
<p>
We'll be back online shortly!
</p>
</div>
</article>
"""),
status_code=502)
with pytest.raises(SentinelAPIError) as excinfo:
api.get_product_odata('8df46c9e-a20c-43db-a19a-4240c2ed3b8b')
assert "The Sentinels Scientific Data Hub will be back soon!" in excinfo.value.msg
def test_get_product_odata_scihub_down():
api = SentinelAPI("mock_user", "mock_password")
with requests_mock.mock() as rqst:
rqst.get(
"https://scihub.copernicus.eu/apihub/odata/v1/Products('8df46c9e-a20c-43db-a19a-4240c2ed3b8b')?$format=json",
text="Mock SciHub is Down", status_code=503
)
with pytest.raises(SentinelAPIError) as excinfo:
api.get_product_odata('8df46c9e-a20c-43db-a19a-4240c2ed3b8b')
rqst.get(
"https://scihub.copernicus.eu/apihub/odata/v1/Products('8df46c9e-a20c-43db-a19a-4240c2ed3b8b')/?$format=json",
text="Mock SciHub is Down", status_code=200
)
with pytest.raises(SentinelAPIError) as excinfo:
api.get_product_odata('8df46c9e-a20c-43db-a19a-4240c2ed3b8b')
assert excinfo.value.msg == "Mock SciHub is Down"
# Test with a real server response
rqst.get(
"https://scihub.copernicus.eu/apihub/odata/v1/Products('8df46c9e-a20c-43db-a19a-4240c2ed3b8b')?$format=json",
text=textwrap.dedent("""\
<!doctype html>
<title>The Sentinels Scientific Data Hub</title>
<link href='https://fonts.googleapis.com/css?family=Open+Sans' rel='stylesheet' type='text/css'>
<style>
body { text-align: center; padding: 125px; background: #fff;}
h1 { font-size: 50px; }
body { font: 20px 'Open Sans',Helvetica, sans-serif; color: #333; }
article { display: block; text-align: left; width: 820px; margin: 0 auto; }
a { color: #0062a4; text-decoration: none; font-size: 26px }
a:hover { color: #1b99da; text-decoration: none; }
</style>
<article>
<img alt="" src="/datahub.png" style="float: left;margin: 20px;">
<h1>The Sentinels Scientific Data Hub will be back soon!</h1>
<div style="margin-left: 145px;">
<p>
Sorry for the inconvenience,<br/>
we're performing some maintenance at the moment.<br/>
</p>
<!--<p><a href="https://scihub.copernicus.eu/news/News00098">https://scihub.copernicus.eu/news/News00098</a></p>-->
<p>
We'll be back online shortly!
</p>
</div>
</article>
"""),
status_code=502)
with pytest.raises(SentinelAPIError) as excinfo:
api.get_product_odata('8df46c9e-a20c-43db-a19a-4240c2ed3b8b')
assert "The Sentinels Scientific Data Hub will be back soon!" in excinfo.value.msg
def smallest_archived_products(api_kwargs, vcr):
n = 3
api = SentinelAPI(**api_kwargs)
# Find some small and old products expecting them to be archived due to age.
# Can't use the OData API for this as we do for the online products
# because the ContentLength value there is not match the true product size.
odatas = []
with vcr.use_cassette("smallest_archived_products"):
products = api.query(date=(None, "20170101"), size="/.+KB/", limit=10)
for uuid in products:
odata = api.get_product_odata(uuid)
if not odata["Online"]:
odatas.append(odata)
if len(odatas) == n:
break
assert len(odatas) == n
return odatas
def test_get_product_odata_scihub_down(read_fixture_file):
api = SentinelAPI("mock_user", "mock_password")
request_url = "https://scihub.copernicus.eu/apihub/odata/v1/Products('8df46c9e-a20c-43db-a19a-4240c2ed3b8b')?$format=json"
with requests_mock.mock() as rqst:
rqst.get(
request_url,
text="Mock SciHub is Down", status_code=503
)
with pytest.raises(SentinelAPIError) as excinfo:
api.get_product_odata('8df46c9e-a20c-43db-a19a-4240c2ed3b8b')
assert excinfo.value.msg == "Mock SciHub is Down"
rqst.get(
request_url,
text='{"error":{"code":null,"message":{"lang":"en","value":'
'"No Products found with key \'8df46c9e-a20c-43db-a19a-4240c2ed3b8b\' "}}}',
status_code=500
)
with pytest.raises(SentinelAPIError) as excinfo:
api.get_product_odata('8df46c9e-a20c-43db-a19a-4240c2ed3b8b')
assert excinfo.value.msg == "No Products found with key \'8df46c9e-a20c-43db-a19a-4240c2ed3b8b\' "
rqst.get(
request_url,
text="Mock SciHub is Down", status_code=200
)
with pytest.raises(SentinelAPIError) as excinfo:
api.get_product_odata('8df46c9e-a20c-43db-a19a-4240c2ed3b8b')
assert excinfo.value.msg == "Mock SciHub is Down"
# Test with a real "server under maintenance" response
rqst.get(
request_url,
text=read_fixture_file('server_maintenance.html'),
status_code=502)
with pytest.raises(SentinelAPIError) as excinfo:
api.get_product_odata('8df46c9e-a20c-43db-a19a-4240c2ed3b8b')
assert "The Sentinels Scientific Data Hub will be back soon!" in excinfo.value.msg
def test_get_product_odata_scihub_down(read_fixture_file):
api = SentinelAPI("mock_user", "mock_password")
request_url = "https://scihub.copernicus.eu/apihub/odata/v1/Products('8df46c9e-a20c-43db-a19a-4240c2ed3b8b')?$format=json"
with requests_mock.mock() as rqst:
rqst.get(
request_url,
text="Mock SciHub is Down", status_code=503
)
with pytest.raises(SentinelAPIError) as excinfo:
api.get_product_odata('8df46c9e-a20c-43db-a19a-4240c2ed3b8b')
assert excinfo.value.msg == "Mock SciHub is Down"
rqst.get(
request_url,
text='{"error":{"code":null,"message":{"lang":"en","value":'
'"No Products found with key \'8df46c9e-a20c-43db-a19a-4240c2ed3b8b\' "}}}',
status_code=500
)
with pytest.raises(SentinelAPIError) as excinfo:
api.get_product_odata('8df46c9e-a20c-43db-a19a-4240c2ed3b8b')
assert excinfo.value.msg == "No Products found with key \'8df46c9e-a20c-43db-a19a-4240c2ed3b8b\' "
rqst.get(
request_url,
text="Mock SciHub is Down", status_code=200
)
with pytest.raises(SentinelAPIError) as excinfo:
api.get_product_odata('8df46c9e-a20c-43db-a19a-4240c2ed3b8b')
assert excinfo.value.msg == "Mock SciHub is Down"
# Test with a real "server under maintenance" response
rqst.get(
request_url,
text=read_fixture_file('server_maintenance.html'),
status_code=502)
with pytest.raises(SentinelAPIError) as excinfo:
api.get_product_odata('8df46c9e-a20c-43db-a19a-4240c2ed3b8b')
assert "The Sentinels Scientific Data Hub will be back soon!" in excinfo.value.msg
def test_get_product_odata_short():
api = SentinelAPI(**_api_auth)
expected_short = {
'8df46c9e-a20c-43db-a19a-4240c2ed3b8b': {
'id': '8df46c9e-a20c-43db-a19a-4240c2ed3b8b',
'size': 143549851,
'md5': 'D5E4DF5C38C6E97BF7E7BD540AB21C05',
'url': "https://scihub.copernicus.eu/apihub/odata/v1/Products('8df46c9e-a20c-43db-a19a-4240c2ed3b8b')/$value",
'date': datetime(2015, 11, 21, 10, 3, 56, 675000),
'footprint': 'POLYGON((-63.852531 -5.880887,-67.495872 -5.075419,-67.066071 -3.084356,-63.430576 -3.880541,'
'-63.852531 -5.880887))',
'title': 'S1A_EW_GRDM_1SDV_20151121T100356_20151121T100429_008701_00C622_A0EC'
},
'44517f66-9845-4792-a988-b5ae6e81fd3e': {
'id': '44517f66-9845-4792-a988-b5ae6e81fd3e',
'date': datetime(2015, 12, 27, 14, 22, 29),
'footprint': 'POLYGON((-58.80274769505742 -4.565257232533263,-58.80535376268811 -5.513960396525286,'
'-57.90315169909761 -5.515947033626909,-57.903151791669515 -5.516014389089381,-57.85874693129081 -5.516044812342758,'
'-57.814323596961835 -5.516142631941845,-57.81432351345917 -5.516075248310466,-57.00018056571297 -5.516633044843839,'
'-57.000180565731384 -5.516700066819259,-56.95603179187787 -5.51666329264377,-56.91188395837315 -5.516693539799448,'
'-56.91188396736038 -5.51662651925904,-56.097209386295305 -5.515947927683427,-56.09720929423562 -5.516014937246069,'
'-56.053056977999596 -5.5159111504805916,-56.00892491028779 -5.515874390220655,-56.00892501130261 -5.515807411549814,'
'-55.10621586418906 -5.513685455771881,-55.108821882251775 -4.6092845892233,-54.20840287327946 -4.606372862374043,'
'-54.21169990975238 -3.658594390979672,-54.214267703869346 -2.710949551849636,-55.15704255065496 -2.7127451087194463,'
'-56.0563616875051 -2.71378646425769,-56.9561852630143 -2.7141556791285275,-57.8999998009875 -2.713837142510183,'
'-57.90079161941062 -3.6180222056692726,-58.800616247288836 -3.616721351843382,-58.80274769505742 -4.565257232533263))',
'md5': '48C5648C2644CE07207B3C943DEDEB44',
'size': 5854429622,
'title': 'S2A_OPER_PRD_MSIL1C_PDMC_20151228T112523_R110_V20151227T142229_20151227T142229',
'url': "https://scihub.copernicus.eu/apihub/odata/v1/Products('44517f66-9845-4792-a988-b5ae6e81fd3e')/$value"
}
}
for id, expected in expected_short.items():
ret = api.get_product_odata(id)
assert set(ret) == set(expected)
for k in ret:
assert ret[k] == expected[k]
def test_get_product_odata_full():
api = SentinelAPI(**_api_auth)
expected_full = {
'8df46c9e-a20c-43db-a19a-4240c2ed3b8b': {
'id': '8df46c9e-a20c-43db-a19a-4240c2ed3b8b',
'title': 'S1A_EW_GRDM_1SDV_20151121T100356_20151121T100429_008701_00C622_A0EC',
'size': 143549851,
'md5': 'D5E4DF5C38C6E97BF7E7BD540AB21C05',
'date': datetime(2015, 11, 21, 10, 3, 56, 675000),
'footprint': 'POLYGON((-63.852531 -5.880887,-67.495872 -5.075419,-67.066071 -3.084356,-63.430576 -3.880541,-63.852531 -5.880887))',
'url': "https://scihub.copernicus.eu/apihub/odata/v1/Products('8df46c9e-a20c-43db-a19a-4240c2ed3b8b')/$value",
'Acquisition Type': 'NOMINAL',
'Carrier rocket': 'Soyuz',
'Cycle number': 64,
'Date': datetime(2015, 11, 21, 10, 3, 56, 675000),
'Filename': 'S1A_EW_GRDM_1SDV_20151121T100356_20151121T100429_008701_00C622_A0EC.SAFE',
'Footprint': '<gml:Polygon srsName="http://www.opengis.net/gml/srs/epsg.xml#4326" xmlns:gml="http://www.opengis.net/gml">\n <gml:outerBoundaryIs>\n <gml:LinearRing>\n <gml:coordinates>-5.880887,-63.852531 -5.075419,-67.495872 -3.084356,-67.066071 -3.880541,-63.430576 -5.880887,-63.852531</gml:coordinates>\n </gml:LinearRing>\n </gml:outerBoundaryIs>\n</gml:Polygon>',
'Format': 'SAFE',
'Identifier': 'S1A_EW_GRDM_1SDV_20151121T100356_20151121T100429_008701_00C622_A0EC',
'Ingestion Date': datetime(2015, 11, 21, 13, 22, 4, 992000),
'Instrument': 'SAR-C',
'Instrument abbreviation': 'SAR-C SAR',
'Instrument description': '<a target="_blank" href="https://sentinel.esa.int/web/sentinel/missions/sentinel-1">https://sentinel.esa.int/web/sentinel/missions/sentinel-1</a>',
'Instrument description text': 'The SAR Antenna Subsystem (SAS) is developed and build by AstriumGmbH. It is a large foldable planar phased array antenna, which isformed by a centre panel and two antenna side wings. In deployedconfiguration the antenna has an overall aperture of 12.3 x 0.84 m.The antenna provides a fast electronic scanning capability inazimuth and elevation and is based on low loss and highly stablewaveguide radiators build in carbon fibre technology, which arealready successfully used by the TerraSAR-X radar imaging mission.The SAR Electronic Subsystem (SES) is developed and build byAstrium Ltd. It provides all radar control, IF/ RF signalgeneration and receive data handling functions for the SARInstrument. The fully redundant SES is based on a channelisedarchitecture with one transmit and two receive chains, providing amodular approach to the generation and reception of wide-bandsignals and the handling of multi-polarisation modes. One keyfeature is the implementation of the Flexible Dynamic BlockAdaptive Quantisation (FD-BAQ) data compression concept, whichallows an efficient use of on-board storage resources and minimisesdownlink times.',
'Instrument mode': 'EW',
'Instrument name': 'Synthetic Aperture Radar (C-band)',
'Instrument swath': 'EW',
'JTS footprint': 'POLYGON ((-63.852531 -5.880887,-67.495872 -5.075419,-67.066071 -3.084356,-63.430576 -3.880541,-63.852531 -5.880887))',
'Launch date': 'April 3rd, 2014',
'Mission datatake id': 50722,
'Mission type': 'Earth observation',
'Mode': 'EW',
'NSSDC identifier': '0000-000A',
'Operator': 'European Space Agency',
'Orbit number (start)': 8701,
'Orbit number (stop)': 8701,
'Pass direction': 'DESCENDING',
'Phase identifier': 1,
'Polarisation': 'VV VH',
'Product class': 'S',
'Product class description': 'SAR Standard L1 Product',
'Product composition': 'Slice',
'Product level': 'L1',
'Product type': 'GRD',
'Relative orbit (start)': 54, 'Relative orbit (stop)': 54, 'Resolution': 'Medium',
'Satellite': 'Sentinel-1',
'Satellite description': '<a target="_blank" href="https://sentinel.esa.int/web/sentinel/missions/sentinel-1">https://sentinel.esa.int/web/sentinel/missions/sentinel-1</a>',
'Satellite name': 'Sentinel-1',
'Satellite number': 'A',
'Sensing start': datetime(2015, 11, 21, 10, 3, 56, 675000),
'Sensing stop': datetime(2015, 11, 21, 10, 4, 29, 714000),
'Size': '223.88 MB',
'Slice number': 1,
'Start relative orbit number': 54,
'Status': 'ARCHIVED',
'Stop relative orbit number': 54,
'Timeliness Category': 'Fast-24h'
},
'44517f66-9845-4792-a988-b5ae6e81fd3e': {
'id': '44517f66-9845-4792-a988-b5ae6e81fd3e',
'title': 'S2A_OPER_PRD_MSIL1C_PDMC_20151228T112523_R110_V20151227T142229_20151227T142229',
'size': 5854429622,
'md5': '48C5648C2644CE07207B3C943DEDEB44',
'date': datetime(2015, 12, 27, 14, 22, 29),
'footprint': 'POLYGON((-58.80274769505742 -4.565257232533263,-58.80535376268811 -5.513960396525286,-57.90315169909761 -5.515947033626909,-57.903151791669515 -5.516014389089381,-57.85874693129081 -5.516044812342758,-57.814323596961835 -5.516142631941845,-57.81432351345917 -5.516075248310466,-57.00018056571297 -5.516633044843839,-57.000180565731384 -5.516700066819259,-56.95603179187787 -5.51666329264377,-56.91188395837315 -5.516693539799448,-56.91188396736038 -5.51662651925904,-56.097209386295305 -5.515947927683427,-56.09720929423562 -5.516014937246069,-56.053056977999596 -5.5159111504805916,-56.00892491028779 -5.515874390220655,-56.00892501130261 -5.515807411549814,-55.10621586418906 -5.513685455771881,-55.108821882251775 -4.6092845892233,-54.20840287327946 -4.606372862374043,-54.21169990975238 -3.658594390979672,-54.214267703869346 -2.710949551849636,-55.15704255065496 -2.7127451087194463,-56.0563616875051 -2.71378646425769,-56.9561852630143 -2.7141556791285275,-57.8999998009875 -2.713837142510183,-57.90079161941062 -3.6180222056692726,-58.800616247288836 -3.616721351843382,-58.80274769505742 -4.565257232533263))',
'url': "https://scihub.copernicus.eu/apihub/odata/v1/Products('44517f66-9845-4792-a988-b5ae6e81fd3e')/$value",
'Cloud cover percentage': 18.153846153846153,
'Date': datetime(2015, 12, 27, 14, 22, 29),
'Degraded MSI data percentage': 0, 'Degraded ancillary data percentage': 0,
'Filename': 'S2A_OPER_PRD_MSIL1C_PDMC_20151228T112523_R110_V20151227T142229_20151227T142229.SAFE',
'Footprint': '<gml:Polygon srsName="http://www.opengis.net/gml/srs/epsg.xml#4326" xmlns:gml="http://www.opengis.net/gml">\n <gml:outerBoundaryIs>\n <gml:LinearRing>\n <gml:coordinates>-4.565257232533263,-58.80274769505742 -5.513960396525286,-58.80535376268811 -5.515947033626909,-57.90315169909761 -5.516014389089381,-57.903151791669515 -5.516044812342758,-57.85874693129081 -5.516142631941845,-57.814323596961835 -5.516075248310466,-57.81432351345917 -5.516633044843839,-57.00018056571297 -5.516700066819259,-57.000180565731384 -5.51666329264377,-56.95603179187787 -5.516693539799448,-56.91188395837315 -5.51662651925904,-56.91188396736038 -5.515947927683427,-56.097209386295305 -5.516014937246069,-56.09720929423562 -5.5159111504805916,-56.053056977999596 -5.515874390220655,-56.00892491028779 -5.515807411549814,-56.00892501130261 -5.513685455771881,-55.10621586418906 -4.6092845892233,-55.108821882251775 -4.606372862374043,-54.20840287327946 -3.658594390979672,-54.21169990975238 -2.710949551849636,-54.214267703869346 -2.7127451087194463,-55.15704255065496 -2.71378646425769,-56.0563616875051 -2.7141556791285275,-56.9561852630143 -2.713837142510183,-57.8999998009875 -3.6180222056692726,-57.90079161941062 -3.616721351843382,-58.800616247288836 -4.565257232533263,-58.80274769505742</gml:coordinates>\n </gml:LinearRing>\n </gml:outerBoundaryIs>\n</gml:Polygon>',
'Format': 'SAFE',
'Format correctness': 'PASSED',
'General quality': 'PASSED',
'Generation time': datetime(2015, 12, 28, 11, 25, 23, 357),
'Geometric quality': 'PASSED',
'Identifier': 'S2A_OPER_PRD_MSIL1C_PDMC_20151228T112523_R110_V20151227T142229_20151227T142229',
'Ingestion Date': datetime(2015, 12, 28, 10, 57, 13, 725000),
'Instrument': 'MSI',
'Instrument abbreviation': 'MSI',
'Instrument mode': 'INS-NOBS',
'Instrument name': 'Multi-Spectral Instrument',
'JTS footprint': 'POLYGON ((-58.80274769505742 -4.565257232533263,-58.80535376268811 -5.513960396525286,-57.90315169909761 -5.515947033626909,-57.903151791669515 -5.516014389089381,-57.85874693129081 -5.516044812342758,-57.814323596961835 -5.516142631941845,-57.81432351345917 -5.516075248310466,-57.00018056571297 -5.516633044843839,-57.000180565731384 -5.516700066819259,-56.95603179187787 -5.51666329264377,-56.91188395837315 -5.516693539799448,-56.91188396736038 -5.51662651925904,-56.097209386295305 -5.515947927683427,-56.09720929423562 -5.516014937246069,-56.053056977999596 -5.5159111504805916,-56.00892491028779 -5.515874390220655,-56.00892501130261 -5.515807411549814,-55.10621586418906 -5.513685455771881,-55.108821882251775 -4.6092845892233,-54.20840287327946 -4.606372862374043,-54.21169990975238 -3.658594390979672,-54.214267703869346 -2.710949551849636,-55.15704255065496 -2.7127451087194463,-56.0563616875051 -2.71378646425769,-56.9561852630143 -2.7141556791285275,-57.8999998009875 -2.713837142510183,-57.90079161941062 -3.6180222056692726,-58.800616247288836 -3.616721351843382,-58.80274769505742 -4.565257232533263))',
'Mission datatake id': 'GS2A_20151227T140932_002681_N02.01',
'NSSDC identifier': '2015-000A',
'Orbit number (start)': 2681,
'Pass direction': 'DESCENDING',
'Platform serial identifier': 'Sentinel-2A',
'Processing baseline': 2.01,
'Processing level': 'Level-1C',
'Product type': 'S2MSI1C',
'Radiometric quality': 'PASSED',
'Relative orbit (start)': 110,
'Satellite': 'Sentinel-2',
'Satellite name': 'Sentinel-2',
'Satellite number': 'A',
'Sensing start': datetime(2015, 12, 27, 14, 22, 29),
'Sensing stop': datetime(2015, 12, 27, 14, 22, 29),
'Sensor quality': 'PASSED',
'Size': '5.50 GB'
}
}
for id, expected in expected_full.items():
ret = api.get_product_odata(id, full=True)
assert set(ret) == set(expected)
for k in ret:
assert ret[k] == expected[k]
def badana(self):
global kappa
kappa=1
self.deneme="badana içine girdiğini gösteren kod"
print(self.deneme)
print(self.adana)
api = SentinelAPI('flavves', 'şifre', 'https://scihub.copernicus.eu/dhus')
footprint = geojson_to_wkt(read_geojson('media/map.geojson'))
print(footprint)
self.products = api.query(footprint,date=('20191219', date(2019, 12, 29)),platformname='Sentinel-2')
products_df = api.to_dataframe(self.products)
print("oluyor galiba")
self.products_df_sorted = products_df.sort_values(['cloudcoverpercentage', 'ingestiondate'], ascending=[True, True])
self.products_df_sorted = self.products_df_sorted.head(1)
self.df=self.products_df_sorted
self.NotDefteriKaydi = self.df.values.tolist()
self.str_denemesi=str(self.NotDefteriKaydi)
self.Kaydetmeye_basla=list(self.str_denemesi.split(","))
self.yerler=[0,7,8,9,12,14,18,19,20]
self.isimler=["Dosya adı:","Uydu adı","Dosya boyutu","Çekim tarihi","Orbit numarası","Bulut yüzdesi","vejetasyon yüzdesi","su yüzdesi","not vejetasyon yüzdesi"]
self.i=0
with open("media/books/txt/deneme.txt", "w") as self.dosya:
for self.sira in self.yerler:
print(self.isimler[self.i]+":"+self.Kaydetmeye_basla[self.sira])
self.yaz=(self.isimler[self.i]+":"+self.Kaydetmeye_basla[self.sira])
self.i=self.i+1
self.dosya.write(self.yaz)
self.dosya.write("\n")
self.dosya.close()
print(self.products_df_sorted)
print("indirme başladı")
#burasını blockladım çünkü 1 gb arşiv indiriyor
#api.download_all(self.products_df_sorted.index)
print("indirme bitti")
self.veri_cekme=self.products_df_sorted.index
self.veri_cekme1=self.veri_cekme[0]
"""
Bu işlem arşivden çıkarmak için gerekli arşivin adı indirdiğimiz verinin title adı oluyor
"""
self.arsiv_adi=api.get_product_odata(self.veri_cekme1)
self.arsiv_adi=self.arsiv_adi["title"]
self.arsiv_adi=str(self.arsiv_adi)
print(self.arsiv_adi)
self.a = Archive(self.arsiv_adi+'.zip')
self.a.extract()
self.img_data_klasor_ismi=os.listdir((self.arsiv_adi+".SAFE"+'/GRANULE'))
self.img_data_klasor_ismi=self.img_data_klasor_ismi[0]
self.img_data_klasor_ismi=str(self.img_data_klasor_ismi)
self.dosya_yer_=(self.arsiv_adi+".SAFE"+'/GRANULE/'+self.img_data_klasor_ismi+'/IMG_DATA')
self.resim_isim=os.listdir(self.dosya_yer_)
print(self.dosya_yer_)
"""
şimdi ise resimleri rasterio ile bi kullanalım
"""
if self.resim_isim == "R10m" or "R20m" or "R60m":
self.dosya_yer_=(self.arsiv_adi+".SAFE"+'/GRANULE/'+self.img_data_klasor_ismi+'/IMG_DATA/R60m')
self.resim_isim=os.listdir(self.dosya_yer_)
self.resim_isim[2]
self.resim_isim[3]
self.jp2ler = [self.resim_isim[2],self.resim_isim[3]]
self.bands = []
#burası bizim jp2 dosyalarımızı okuyacak
for self.jp2 in self.jp2ler:
with rasterio.open(self.dosya_yer_+"/"+self.jp2) as self.f:
self.bands.append(self.f.read(1))
#resimlerimizi ayrıştırdık özel bantlara
self.band_red=self.bands[0]
self.band_nir=self.bands[1]
print("bant değerleri hesaplandı")
print(self.bands[0],self.bands[1])
else:
self.resim_isim[2]
self.resim_isim[3]
self.jp2ler = [self.resim_isim[2],self.resim_isim[3]]
self.bands = []
#burası bizim jp2 dosyalarımızı okuyacak
for self.jp2 in self.jp2ler:
with rasterio.open(self.dosya_yer_+"/"+self.jp2) as f:
self.bands.append(self.f.read(1))
#resimlerimizi ayrıştırdık özel bantlara
self.band_red=self.bands[0]
self.band_nir=self.bands[1]
print("bant değerleri hesaplandı")
print(self.bands[0],self.bands[1])
# Klasik NDVI denklemi ile hesaplama
print("ndvı hesaplanıyor")
np.seterr(divide='ignore', invalid='ignore')
# Calculate NDVI. This is the equation at the top of this guide expressed in code
self.ndvi = (self.band_nir.astype(float) - self.band_red.astype(float)) / (self.band_nir + self.band_red)
#su için yapıyorum bu analizi
##
###
self.ndvi=(self.band_red.astype(float) - self.band_nir.astype(float)) / (self.band_red + self.band_nir)
###
###
np.nanmin(self.ndvi), np.nanmax(self.ndvi)
print("ndvı değerler aralıkları")
print(np.nanmin(self.ndvi), np.nanmax(self.ndvi))
# görüntümüze bakalım renklerine ayrılmış bir görüntümüz var
# çizim yapacağız bunun için gerekli kütüphaneler ekleniyor
# NDVI bilindiği üzere 1 ve -1 arasındaki değerlerde sınıflandırılır.
# Biz de bu değerleri renklerle göstermek istiyoruz.
# Bunun için alınan sayısal değerleri farklı renk spektrumlarına atayarak elimizde NDVI için renklendirilmiş bir görüntümüz olacaktır
#
# Bir orta nokta belirledik ve bu sola ve sağa olacak şekilde renklendiriyoru renk spekturumunu da aşağıda paylaşacağım
class RenkNormalizasyonu(colors.Normalize):
def __init__(self, vmin=None, vmax=None, midpoint=None, clip=False):
self.midpoint = midpoint
colors.Normalize.__init__(self, vmin, vmax, clip)
def __call__(self, value, clip=None):
x, y = [self.vmin, self.midpoint, self.vmax], [0, 0.5, 1]
return np.ma.masked_array(np.interp(value, x, y), np.isnan(value))
self.min=np.nanmin(self.ndvi)
self.max=np.nanmax(self.ndvi)
self.mid=0.1
print("bitti mi şimdi bok biter")
print(self.min,self.max)
self.fig = plt.figure(figsize=(20,10))
self.ax = self.fig.add_subplot(111)
self.cmap = plt.cm.RdYlGn
self.cax = self.ax.imshow(self.ndvi, cmap=self.cmap, clim=(self.min, self.max), norm=RenkNormalizasyonu(midpoint=self.mid,vmin=self.min, vmax=self.max))
self.ax.axis('off')
self.ax.set_title('NDVI görüntüsü', fontsize=18, fontweight='bold')
self.cbar = self.fig.colorbar(self.cax, orientation='horizontal', shrink=0.65)
#normalde byu alttaki gibi kaydetsin ama şimdilik benim yazdığım gibi yapsın olur mu cnm muck
#self.fig_kaydet="resimler/"+self.resim_isim[2]+".tif"
self.fig_kaydet="media/books/covers/denemeresmi.png"
self.fig.savefig(self.fig_kaydet, dpi=200, bbox_inches='tight', pad_inches=0.7)
self.fig_kaydet_tif="media/books/covers/denemeresmi.tif"
self.fig.savefig(self.fig_kaydet_tif, dpi=200, bbox_inches='tight', pad_inches=0.7)
from sentinelsat import SentinelAPI, read_geojson, geojson_to_wkt
api = SentinelAPI('', '', "https://scihub.copernicus.eu/dhus")
footprint = geojson_to_wkt(read_geojson(r'D:\Sentinel-2Data\Hubei.json'))
print(footprint)
products = api.query(footprint,
producttype='SLC',
date=("20180601", "20180615"),
orbitdirection='ASCENDING',
platformname='Sentinel-1')
print(len(products))
for prod in products:
print(api.get_product_odata(prod))
# api.download_all(products,directory_path="D:\Sentinel-2Data")
# api.download_all(products)
class SentinelDownloader(object):
def __init__(self,
user,
password,
api_url='https://scihub.copernicus.eu/dhus'):
try:
from sentinelsat import SentinelAPI
except ImportError as e:
gs.fatal(_("Module requires sentinelsat library: {}").format(e))
try:
import pandas
except ImportError as e:
gs.fatal(_("Module requires pandas library: {}").format(e))
# init logger
root = logging.getLogger()
root.addHandler(logging.StreamHandler(sys.stderr))
# connect SciHub via API
self._api = SentinelAPI(user, password, api_url=api_url)
self._products_df_sorted = None
def filter(self,
area,
area_relation,
clouds=None,
producttype=None,
limit=None,
query={},
start=None,
end=None,
sortby=[],
asc=True):
args = {}
if clouds:
args['cloudcoverpercentage'] = (0, int(clouds))
if producttype:
args['producttype'] = producttype
if producttype.startswith('S2'):
args['platformname'] = 'Sentinel-2'
else:
args['platformname'] = 'Sentinel-1'
if not start:
start = 'NOW-60DAYS'
else:
start = start.replace('-', '')
if not end:
end = 'NOW'
else:
end = end.replace('-', '')
if query:
redefined = [
value for value in args.keys() if value in query.keys()
]
if redefined:
gs.warning(
"Query overrides already defined options ({})".format(
','.join(redefined)))
args.update(query)
gs.verbose(
"Query: area={} area_relation={} date=({}, {}) args={}".format(
area, area_relation, start, end, args))
products = self._api.query(area=area,
area_relation=area_relation,
date=(start, end),
**args)
products_df = self._api.to_dataframe(products)
if len(products_df) < 1:
gs.message(_('No product found'))
return
# sort and limit to first sorted product
if sortby:
self._products_df_sorted = products_df.sort_values(
sortby, ascending=[asc] * len(sortby))
else:
self._products_df_sorted = products_df
if limit:
self._products_df_sorted = self._products_df_sorted.head(
int(limit))
gs.message(
_('{} Sentinel product(s) found').format(
len(self._products_df_sorted)))
def list(self):
if self._products_df_sorted is None:
return
for idx in range(len(self._products_df_sorted['uuid'])):
if 'cloudcoverpercentage' in self._products_df_sorted:
ccp = '{0:2.0f}%'.format(
self._products_df_sorted['cloudcoverpercentage'][idx])
else:
ccp = 'cloudcover_NA'
print('{0} {1} {2} {3} {4}'.format(
self._products_df_sorted['uuid'][idx],
self._products_df_sorted['identifier'][idx],
self._products_df_sorted['beginposition'][idx].strftime(
"%Y-%m-%dT%H:%M:%SZ"),
ccp,
self._products_df_sorted['producttype'][idx],
))
def download(self, output):
if self._products_df_sorted is None:
return
if not os.path.exists(output):
os.makedirs(output)
gs.message(_('Downloading data into <{}>...').format(output))
for idx in range(len(self._products_df_sorted['uuid'])):
gs.message('{} -> {}.SAFE'.format(
self._products_df_sorted['uuid'][idx],
os.path.join(output,
self._products_df_sorted['identifier'][idx])))
# download
self._api.download(self._products_df_sorted['uuid'][idx], output)
def save_footprints(self, map_name):
if self._products_df_sorted is None:
return
try:
from osgeo import ogr, osr
except ImportError as e:
gs.fatal(
_("Option <footprints> requires GDAL library: {}").format(e))
gs.message(_("Writing footprints into <{}>...").format(map_name))
driver = ogr.GetDriverByName("GPKG")
tmp_name = gs.tempfile() + '.gpkg'
data_source = driver.CreateDataSource(tmp_name)
srs = osr.SpatialReference()
srs.ImportFromEPSG(4326)
# features can be polygons or multi-polygons
layer = data_source.CreateLayer(str(map_name), srs,
ogr.wkbMultiPolygon)
# attributes
attrs = OrderedDict([("uuid", ogr.OFTString),
("ingestiondate", ogr.OFTString),
("cloudcoverpercentage", ogr.OFTInteger),
("producttype", ogr.OFTString),
("identifier", ogr.OFTString)])
for key in attrs.keys():
field = ogr.FieldDefn(key, attrs[key])
layer.CreateField(field)
# features
for idx in range(len(self._products_df_sorted['uuid'])):
wkt = self._products_df_sorted['footprint'][idx]
feature = ogr.Feature(layer.GetLayerDefn())
newgeom = ogr.CreateGeometryFromWkt(wkt)
# convert polygons to multi-polygons
newgeomtype = ogr.GT_Flatten(newgeom.GetGeometryType())
if newgeomtype == ogr.wkbPolygon:
multigeom = ogr.Geometry(ogr.wkbMultiPolygon)
multigeom.AddGeometryDirectly(newgeom)
feature.SetGeometry(multigeom)
else:
feature.SetGeometry(newgeom)
for key in attrs.keys():
if key == 'ingestiondate':
value = self._products_df_sorted[key][idx].strftime(
"%Y-%m-%dT%H:%M:%SZ")
else:
value = self._products_df_sorted[key][idx]
feature.SetField(key, value)
layer.CreateFeature(feature)
feature = None
data_source = None
# coordinates of footprints are in WKT -> fp precision issues
# -> snap
gs.run_command('v.import',
input=tmp_name,
output=map_name,
layer=map_name,
snap=1e-10,
quiet=True)
def set_uuid(self, uuid_list):
"""Set products by uuid.
TODO: Find better implementation
:param uuid: uuid to download
"""
from sentinelsat.sentinel import SentinelAPIError
self._products_df_sorted = {'uuid': []}
for uuid in uuid_list:
try:
odata = self._api.get_product_odata(uuid, full=True)
except SentinelAPIError as e:
gs.error('{0}. UUID {1} skipped'.format(e, uuid))
continue
for k, v in odata.items():
if k == 'id':
k = 'uuid'
elif k == 'Sensing start':
k = 'beginposition'
elif k == 'Product type':
k = 'producttype'
elif k == 'Cloud cover percentage':
k = 'cloudcoverpercentage'
elif k == 'Identifier':
k = 'identifier'
elif k == 'Ingestion Date':
k = 'ingestiondate'
elif k == 'footprint':
pass
else:
continue
if k not in self._products_df_sorted:
self._products_df_sorted[k] = []
self._products_df_sorted[k].append(v)
def main(dwndir, csvpath, logpath, apipath):
# Configure file for logging
# ==========================
logging.basicConfig(
filename=logpath,
format="%(asctime)s - %(module)s - %(levelname)s - %(message)s",
level=logging.INFO)
with open(logpath, "a") as f:
loghead = f"\nStarting a new session\n{datetime.now()}\n" + 26 * "=" + "\n"
f.write(loghead)
print("Started script download_LTA.py")
logging.info("Started script download_LTA.py")
# Read password file
# ==================
try:
with open(apipath) as f:
(usrnam, psswrd) = f.readline().split(" ")
if psswrd.endswith("\n"):
psswrd = psswrd[:-1]
except IOError:
logging.info("Error reading the password file!")
sys.exit("Error reading the password file!")
# Connect to API using <username> and <password>
# ==============================================
print("Connecting to SciHub API...")
api = SentinelAPI(usrnam, psswrd, "https://scihub.copernicus.eu/dhus")
# Read CSV file
# =============
try:
dwnfil = pd.read_csv(csvpath)
print(f"Import CSV file: {basename(csvpath)}")
logging.info(f"Import CSV file: {basename(csvpath)}")
except IOError:
logging.info("Error reading the CSV file!")
sys.exit("Error reading the CSV file!")
# Download files from the CSV list
# ================================
max_attempts = 10
checksum = True
product_ids = list(dwnfil['uuid'])
# product_example = "672e5131-c79d-4500-b825-9dabf40662e3"
print(f"Found {len(product_ids)} products in CSV list.\n")
logging.info(f"Found {len(product_ids)} products in CSV list.\n")
# Main loop for download
# ======================
for i, product_id in enumerate(product_ids):
if not dwnfil['downloaded'].get(i):
current_file = api.get_product_odata(product_id)
print(f" Next file: {current_file['title']}")
print(f" File uuid: {product_id}")
logging.info(f" Next file: {current_file['title']}")
logging.info(f" File uuid: {product_id}")
# If product isn't online (it is in LTA), wait and check every 5 min
waiting = 0
while not current_file['Online']:
if waiting == 0:
print("File is offline, waiting 5 min...")
logging.info("File is offline, waiting 5 min...")
sleep(5 * 60)
waiting += 5
print(f"{waiting} min has passed, file still Offline..")
logging.info(f"{waiting} min has passed, file still Offline..")
# When file goes online proceed with download
for attempt_num in range(max_attempts):
try:
api.download(product_id, dwndir, checksum)
# Update CSV file
dwnfil.at[i, 'downloaded'] = True
dwnfil.to_csv(csvpath, index=False)
logging.info("CSV file updated\n")
break
except (KeyboardInterrupt, SystemExit):
raise
except InvalidChecksumError as e:
logging.info(
f"Invalid checksum. The downloaded file for '{product_id}' is corrupted."
)
logging.error(e)
except Exception as e:
logging.info(
f"There was an error downloading {product_id}")
logging.error(e)
else:
logging.info(f" **** File {product_id} was not Online!\n")
else:
logging.info(
f"SKIP! File {product_id} has already been downloaded.\n")
# End message
# ============
print("--------- Session finished ---------")
logging.info(f"--------- Session {dwndir} finished ---------\n")
logging.shutdown()
def classification(footprint,o_footprint,start,end):
# setup API and login info
api =SentinelAPI('mom_sentinel2', 'sentinel2Download!','https://scihub.copernicus.eu/apihub/')
# search data with some limits like range of date and cloud cover using given footprint.
products =api.query(footprint,date=(start,end), platformname='Sentinel-2', producttype = 'S2MSI2A', cloudcoverpercentage=(0,30))
product_name = []
date = start
# download searched data to local
for product in products:
product_info = api.get_product_odata(product)
product_name.append(product_info['title'])
api.download(product)
product_name.reverse()
# use terminal quary to translate B2, B3, B4, and B8 as one multiple tif file.
for file_name in product_name:
quary = 'gdal_pansharpen.py -h'
info = os.popen(quary)
d = info.read()
d = d.split('SUBDATASET_1_NAME=')
d = d[1].split('\n')
q = 'gdal_translate ' + d[0] + ' '+file_name+'.tif'
info = os.popen(q)
d = info.read()
minX, maxY, maxX, minY = get_extent(product_name[0])
if len(product_name)> 1:
for fn in product_name[1:]:
minx, maxy, maxx, miny = get_extent(fn)
minX = min(minX, minx)
maxY = max(maxY, maxy)
maxX = max(maxX, maxx)
minY = min(minY, miny)
in_ds = gdal.Open(product_name[0])
gt = in_ds.GetGeoTransform()
rows = int(int(maxX - minX) / abs(gt[5]))
cols = int(int(maxY - minY) / gt[1])
driver = gdal.GetDriverByName("GTiff")
out_ds = driver.Create('union.tif', rows, cols, 4, gdal.GDT_Byte)
out_ds.SetProjection(in_ds.GetProjection())
gt = list(in_ds.GetGeoTransform())
gt[0], gt[3] = minX, maxY
out_ds.SetGeoTransform(gt)
for fn in product_name:
in_ds = gdal.Open(fn)
trans = gdal.Transformer(in_ds, out_ds, [])
success, xyz = trans.TransformPoint(False, 0, 0)
x, y, z = map(int, xyz)
data = in_ds.GetRasterBand(1).ReadAsArray()
for i in range(4):
out_ds.GetRasterBand(i+1).WriteArray(data[i],x,y)
del in_ds, out_band, out_ds
src_path = date+'union.tif'
src = rio.open(src_path)
shpdata = GeoDataFrame.from_file('../shapefile/Polygon.shp')
out_shpdata = shpdata.copy()
shpdata=shpdata.to_crs(src.crs)
features = shpdata.geometry[0].__geo_interface__
out_image, out_transform = rio.mask.mask(src, [features], crop=True, nodata=src.nodata)
out_meta = src.meta.copy()
out_meta.update({"driver": "GTiff",
"height": out_image.shape[1],
"width": out_image.shape[2],
"transform": out_transform})
band_mask = rasterio.open('../geo_tiff/'+date+'cutted.tif', "w", **out_meta)
band_mask.write(out_image)
#model = create_model()
model = load_model('../saved_model/MD_model.txt')
# calculate NDVI & MDWI band for each file
dataset=gdal.Open('../geo_tiff/'date+'cutted.tif')
im_proj,im_geotrans,im_data = read_img(dataset)
ndvi = get_ndvi(im_data)
ndwi = get_ndwi(im_data)
c,h,w = im_data.shape
new_data = np.zeros((6,h,w))
for i in range(4) :
temp = np.max(im_data[i])
new_data[i,:,:] = im_data[i]/temp
new_data[4,:,:] = ndvi
new_data[5,:,:] = ndwi
input_pic = new_data
# detect and save result
ans = cal_box_new(model,input_pic)
save_path = '../geo_tiff_test/'
write_img(date+'_class.tif',im_proj,im_geotrans,ans)
while len(ids):
while cont>=0:
print(n,m)
if cont==0:
api = SentinelAPI('biancasantana', '988245535', 'https://scihub.copernicus.eu/dhus',show_progressbars=True)
elif cont==1:
api = SentinelAPI('_labgis', '988245535', 'https://scihub.copernicus.eu/dhus',show_progressbars=True)
else:
api = SentinelAPI('labgis_', '988245535', 'https://scihub.copernicus.eu/dhus',show_progressbars=True)
for e in range(n,m,1):
if (m!=(e)):
list.append(ids[e])
break
product_info = api.get_product_odata(list[0])
product_info1 = api.get_product_odata(list[1])
if product_info['Online']:
print('Product {} is online. Starting download.'.format(list[0]))
api.download(list[0])
elif product_info1['Online']:
print('Product {} is online. Starting download.'.format(list[1]))
api.download(list[1])
else:
print('Product {} is not online.'.format(list[0]))
print('Product {} is not online.'.format(list[1]))
print(list)
n+=2
m+=2
list=[]
def test_get_product_info_bad_key():
api = SentinelAPI(**_api_auth)
with pytest.raises(SentinelAPIError) as excinfo:
api.get_product_odata('invalid-xyz')
assert excinfo.value.msg == "InvalidKeyException : Invalid key (invalid-xyz) to access Products"
def download_imagedata(footprint_geojson, startdate, enddate):
""" download image data with SentinelAPI """
# .netrc method is not working
api = SentinelAPI('flooda31', 'floodproject',
'https://scihub.copernicus.eu/dhus')
footprint = geojson_to_wkt(read_geojson(footprint_geojson))
products = api.query(footprint,
date=(startdate, enddate),
platformname='Sentinel-2',
producttype='S2MSI2A',
cloudcoverpercentage=(0, 30))
product_name = []
date = startdate
# download searched data to local
for product in products:
product_info = api.get_product_odata(product)
is_online = product_info['Online']
if is_online:
product_name.append(product_info['title'])
api.download(product)
else:
# offline data issue:
# https://scihub.copernicus.eu/userguide/LongTermArchive
# https://sentinelsat.readthedocs.io/en/latest/api_overview.html#lta-products
# may try asf
print('Product {} is not online.'.format(product))
product_name.reverse()
# use terminal quary to translate B2, B3, B4, and B8 as one multiple tif file.
for file_name in product_name:
print(file_name)
quary = 'gdalinfo ' + file_name + ".zip"
info = os.popen(quary)
d = info.read()
d = d.split('SUBDATASET_1_NAME=')
d = d[1].split('\n')
q = 'gdal_translate ' + d[0] + ' ' + file_name + '.tif'
info = os.popen(q)
d = info.read()
minX, maxY, maxX, minY = get_extent(product_name[0] + ".tif")
if len(product_name) > 1:
for fn in product_name[1:]:
minx, maxy, maxx, miny = get_extent(fn + ".tif")
minX = min(minX, minx)
maxY = max(maxY, maxy)
maxX = max(maxX, maxx)
minY = min(minY, miny)
in_ds = gdal.Open(product_name[0] + ".tif")
gt = in_ds.GetGeoTransform()
rows = int(int(maxX - minX) / abs(gt[5]))
cols = int(int(maxY - minY) / gt[1])
driver = gdal.GetDriverByName("GTiff")
out_ds = driver.Create('union.tif', rows, cols, 4, gdal.GDT_Byte)
out_ds.SetProjection(in_ds.GetProjection())
gt = list(in_ds.GetGeoTransform())
gt[0], gt[3] = minX, maxY
out_ds.SetGeoTransform(gt)
for fn in product_name:
in_ds = gdal.Open(fn + ".tif")
trans = gdal.Transformer(in_ds, out_ds, [])
success, xyz = trans.TransformPoint(False, 0, 0)
x, y, z = map(int, xyz)
for i in range(4):
data = in_ds.GetRasterBand(i + 1).ReadAsArray()
out_ds.GetRasterBand(i + 1).WriteArray(data, x, y)
del in_ds, out_ds
# cut image
src_path = 'union.tif'
src = rio.open(src_path)
shpdata = gpd.read_file(footprint_geojson)
out_shpdata = shpdata.copy()
shpdata = shpdata.to_crs(src.crs)
features = shpdata.geometry[0].__geo_interface__
out_image, out_transform = rio.mask.mask(src, [features],
crop=True,
nodata=src.nodata)
out_meta = src.meta.copy()
out_meta.update({
"driver": "GTiff",
"height": out_image.shape[1],
"width": out_image.shape[2],
"transform": out_transform
})
cutted_tif = "cutted.tif"
band_mask = rio.open(cutted_tif, "w", **out_meta)
band_mask.write(out_image)
return cutted_tif
def test_get_product_info_bad_key():
api = SentinelAPI(**_api_auth)
with pytest.raises(SentinelAPIError) as excinfo:
api.get_product_odata('invalid-xyz')
assert excinfo.value.msg == "InvalidKeyException : Invalid key (invalid-xyz) to access Products"
class SentinelDownloader(object):
def __init__(
self,
user,
password,
api_url="https://apihub.copernicus.eu/apihub",
cred_req=True,
):
self._apiname = api_url
self._user = user
self._password = password
self._cred_req = cred_req
# init logger
root = logging.getLogger()
root.addHandler(logging.StreamHandler(sys.stderr))
if self._apiname not in ["USGS_EE", "GCS"]:
try:
from sentinelsat import SentinelAPI
except ImportError as e:
gs.fatal(
_("Module requires sentinelsat library: {}").format(e))
# connect SciHub via API
self._api = SentinelAPI(self._user,
self._password,
api_url=self._apiname)
elif self._apiname == "USGS_EE":
api_login = False
while api_login is False:
# avoid login conflict in possible parallel execution
try:
self._api = landsatxplore.api.API(self._user,
self._password)
api_login = True
except EarthExplorerError as e:
time.sleep(1)
self._products_df_sorted = None
def filter(
self,
area,
area_relation,
clouds=None,
producttype=None,
limit=None,
query={},
start=None,
end=None,
sortby=[],
asc=True,
relativeorbitnumber=None,
):
# Dict to identify plaforms from requested product
platforms = {
"SL": "Sentinel-1",
"GR": "Sentinel-1",
"OC": "Sentinel-1",
"S2": "Sentinel-2",
"S3": "Sentinel-3",
}
args = {}
if clouds:
args["cloudcoverpercentage"] = (0, int(clouds))
if relativeorbitnumber:
args["relativeorbitnumber"] = relativeorbitnumber
if producttype.startswith("S2") and int(relativeorbitnumber) > 143:
gs.warning("This relative orbit number is out of range")
elif int(relativeorbitnumber) > 175:
gs.warning(_("This relative orbit number is out of range"))
if producttype:
if producttype.startswith("S3"):
# Using custom product names for Sentinel-3 products that look less cryptic
split = [0, 2, 4, 5, 8]
args["producttype"] = "_".join([
producttype[i:j] for i, j in zip(split, split[1:] + [None])
][1:]).ljust(11, "_")
else:
args["producttype"] = producttype
args["platformname"] = platforms[producttype[0:2]]
if not start:
start = "NOW-60DAYS"
else:
start = start.replace("-", "")
if not end:
end = "NOW"
else:
end = end.replace("-", "")
if query:
redefined = [
value for value in args.keys() if value in query.keys()
]
if redefined:
gs.warning(
_("Query overrides already defined options ({})").format(
",".join(redefined)))
args.update(query)
gs.verbose(
_("Query: area={} area_relation={} date=({}, {}) args={}").format(
area, area_relation, start, end, args))
if self._cred_req is False:
# in the main function it is ensured that there is an "identifier" query
self._products_df_sorted = pandas.DataFrame(
{"identifier": [query["identifier"]]})
return
products = self._api.query(area=area,
area_relation=area_relation,
date=(start, end),
**args)
products_df = self._api.to_dataframe(products)
if len(products_df) < 1:
gs.message(_("No product found"))
return
# sort and limit to first sorted product
if sortby:
self._products_df_sorted = products_df.sort_values(
sortby, ascending=[asc] * len(sortby))
else:
self._products_df_sorted = products_df
if limit:
self._products_df_sorted = self._products_df_sorted.head(
int(limit))
gs.message(
_("{} Sentinel product(s) found").format(
len(self._products_df_sorted)))
def list(self):
if self._products_df_sorted is None:
return
id_kw = ("uuid", "entity_id")
identifier_kw = ("identifier", "display_id")
cloud_kw = ("cloudcoverpercentage", "cloud_cover")
time_kw = ("beginposition", "acquisition_date")
kw_idx = 1 if self._apiname == "USGS_EE" else 0
for idx in range(len(self._products_df_sorted[id_kw[kw_idx]])):
if cloud_kw[kw_idx] in self._products_df_sorted:
ccp = "{0:2.0f}%".format(
float(self._products_df_sorted[cloud_kw[kw_idx]][idx]))
else:
ccp = "cloudcover_NA"
print_str = "{0} {1}".format(
self._products_df_sorted[id_kw[kw_idx]][idx],
self._products_df_sorted[identifier_kw[kw_idx]][idx],
)
if kw_idx == 1:
time_string = self._products_df_sorted[time_kw[kw_idx]][idx]
else:
time_string = self._products_df_sorted[
time_kw[kw_idx]][idx].strftime("%Y-%m-%dT%H:%M:%SZ")
print_str += " {0} {1}".format(time_string, ccp)
if kw_idx == 0:
print_str += " {0}".format(
self._products_df_sorted["producttype"][idx])
print_str += " {0}".format(
self._products_df_sorted["size"][idx])
print(print_str)
def skip_existing(self, output, pattern_file):
prod_df_type = type(self._products_df_sorted)
# Check i skipping is possible/required
if prod_df_type != dict:
if self._products_df_sorted.empty:
return
elif not self._products_df_sorted or os.path.exists(output) == False:
return
# Check if ingestion date is returned by API
if "ingestiondate" not in self._products_df_sorted:
gs.warning(
_("Ingestiondate not returned. Cannot filter previously downloaded scenes"
))
return
# Check for previously downloaded scenes
existing_files = [
f for f in os.listdir(output)
if re.search(r".zip$|.safe$|.ZIP$|.SAFE$", f)
]
if len(existing_files) <= 1:
return
# Filter by ingestion date
skiprows = []
for idx, display_id in enumerate(
self._products_df_sorted["identifier"]):
existing_file = [
sfile for sfile in existing_files if display_id in sfile
]
if existing_file:
creation_time = datetime.fromtimestamp(
os.path.getctime(existing_file[0]))
if self._products_df_sorted["ingestiondate"][
idx] <= creation_time:
gs.message(
_("Skipping scene: {} which is already downloaded.".
format(self._products_df_sorted["identifier"][idx])))
skiprows.append(display_id)
if prod_df_type == dict:
for scene in skiprows:
idx = self._products_df_sorted["identifier"].index(scene)
for key in self._products_df_sorted:
self._products_df_sorted[key].pop(idx)
else:
self._products_df_sorted = self._products_df_sorted[
~self._products_df_sorted["identifier"].isin(skiprows)]
def download(self,
output,
sleep=False,
maxretry=False,
datasource="ESA_COAH"):
if self._products_df_sorted is None:
return
create_dir(output)
gs.message(_("Downloading data into <{}>...").format(output))
if datasource == "USGS_EE":
from landsatxplore.earthexplorer import EarthExplorer
from landsatxplore.errors import EarthExplorerError
from zipfile import ZipFile
ee_login = False
while ee_login is False:
# avoid login conflict in possible parallel execution
try:
ee = EarthExplorer(self._user, self._password)
ee_login = True
except EarthExplorerError as e:
time.sleep(1)
for idx in range(len(self._products_df_sorted["entity_id"])):
scene = self._products_df_sorted["entity_id"][idx]
identifier = self._products_df_sorted["display_id"][idx]
zip_file = os.path.join(output, "{}.zip".format(identifier))
gs.message(_("Downloading {}...").format(identifier))
try:
ee.download(identifier=identifier,
output_dir=output,
timeout=600)
except EarthExplorerError as e:
gs.fatal(_(e))
ee.logout()
# extract .zip to get "usual" .SAFE
with ZipFile(zip_file, "r") as zip:
safe_name = zip.namelist()[0].split("/")[0]
outpath = os.path.join(output, safe_name)
zip.extractall(path=output)
gs.message(_("Downloaded to <{}>").format(outpath))
try:
os.remove(zip_file)
except Exception as e:
gs.warning(
_("Unable to remove {0}:{1}").format(zip_file, e))
elif datasource == "ESA_COAH":
for idx in range(len(self._products_df_sorted["uuid"])):
gs.message("{} -> {}.SAFE".format(
self._products_df_sorted["uuid"][idx],
os.path.join(output,
self._products_df_sorted["identifier"][idx]),
))
# download
out = self._api.download(self._products_df_sorted["uuid"][idx],
output)
if sleep:
x = 1
online = out["Online"]
while not online:
# sleep is in minutes so multiply by 60
time.sleep(int(sleep) * 60)
out = self._api.download(
self._products_df_sorted["uuid"][idx], output)
x += 1
if x > maxretry:
online = True
elif datasource == "GCS":
for scene_id in self._products_df_sorted["identifier"]:
gs.message(_("Downloading {}...").format(scene_id))
dl_code = download_gcs(scene_id, output)
if dl_code == 0:
gs.message(
_("Downloaded to {}").format(
os.path.join(output, "{}.SAFE".format(scene_id))))
else:
# remove incomplete file
del_folder = os.path.join(output,
"{}.SAFE".format(scene_id))
try:
shutil.rmtree(del_folder)
except Exception as e:
gs.warning(
_("Unable to removed unfinished "
"download {}".format(del_folder)))
def save_footprints(self, map_name):
if self._products_df_sorted is None:
return
if self._apiname == "USGS_EE":
gs.fatal(
_("USGS Earth Explorer does not support footprint download."))
try:
from osgeo import ogr, osr
except ImportError as e:
gs.fatal(
_("Option <footprints> requires GDAL library: {}").format(e))
gs.message(_("Writing footprints into <{}>...").format(map_name))
driver = ogr.GetDriverByName("GPKG")
tmp_name = gs.tempfile() + ".gpkg"
data_source = driver.CreateDataSource(tmp_name)
srs = osr.SpatialReference()
srs.ImportFromEPSG(4326)
# features can be polygons or multi-polygons
layer = data_source.CreateLayer(str(map_name), srs,
ogr.wkbMultiPolygon)
# attributes
attrs = OrderedDict([
("uuid", ogr.OFTString),
("ingestiondate", ogr.OFTString),
("cloudcoverpercentage", ogr.OFTInteger),
("producttype", ogr.OFTString),
("identifier", ogr.OFTString),
])
# Sentinel-1 data does not have cloudcoverpercentage
prod_types = [type for type in self._products_df_sorted["producttype"]]
if not any(type in prod_types for type in cloudcover_products):
del attrs["cloudcoverpercentage"]
for key in attrs.keys():
field = ogr.FieldDefn(key, attrs[key])
layer.CreateField(field)
# features
for idx in range(len(self._products_df_sorted["uuid"])):
wkt = self._products_df_sorted["footprint"][idx]
feature = ogr.Feature(layer.GetLayerDefn())
newgeom = ogr.CreateGeometryFromWkt(wkt)
# convert polygons to multi-polygons
newgeomtype = ogr.GT_Flatten(newgeom.GetGeometryType())
if newgeomtype == ogr.wkbPolygon:
multigeom = ogr.Geometry(ogr.wkbMultiPolygon)
multigeom.AddGeometryDirectly(newgeom)
feature.SetGeometry(multigeom)
else:
feature.SetGeometry(newgeom)
for key in attrs.keys():
if key == "ingestiondate":
value = self._products_df_sorted[key][idx].strftime(
"%Y-%m-%dT%H:%M:%SZ")
else:
value = self._products_df_sorted[key][idx]
feature.SetField(key, value)
layer.CreateFeature(feature)
feature = None
data_source = None
# coordinates of footprints are in WKT -> fp precision issues
# -> snap
gs.run_command(
"v.import",
input=tmp_name,
output=map_name,
layer=map_name,
snap=1e-10,
quiet=True,
)
def get_products_from_uuid_usgs(self, uuid_list):
scenes = []
for uuid in uuid_list:
metadata = self._api.metadata(uuid, "SENTINEL_2A")
scenes.append(metadata)
scenes_df = pandas.DataFrame.from_dict(scenes)
self._products_df_sorted = scenes_df
gs.message(
_("{} Sentinel product(s) found").format(
len(self._products_df_sorted)))
def set_uuid(self, uuid_list):
"""Set products by uuid.
TODO: Find better implementation
:param uuid: uuid to download
"""
if self._apiname == "USGS_EE":
self.get_products_from_uuid_usgs(uuid_list)
else:
from sentinelsat.sentinel import SentinelAPIError
self._products_df_sorted = {"uuid": []}
for uuid in uuid_list:
try:
odata = self._api.get_product_odata(uuid, full=True)
except SentinelAPIError as e:
gs.error(_("{0}. UUID {1} skipped".format(e, uuid)))
continue
for k, v in odata.items():
if k == "id":
k = "uuid"
elif k == "Sensing start":
k = "beginposition"
elif k == "Product type":
k = "producttype"
elif k == "Cloud cover percentage":
k = "cloudcoverpercentage"
elif k == "Identifier":
k = "identifier"
elif k == "Ingestion Date":
k = "ingestiondate"
elif k == "footprint":
pass
else:
continue
if k not in self._products_df_sorted:
self._products_df_sorted[k] = []
self._products_df_sorted[k].append(v)
def filter_USGS(
self,
area,
area_relation,
clouds=None,
producttype=None,
limit=None,
query={},
start=None,
end=None,
sortby=[],
asc=True,
relativeorbitnumber=None,
):
if area_relation != "Intersects":
gs.fatal(
_("USGS Earth Explorer only supports area_relation"
" 'Intersects'"))
if relativeorbitnumber:
gs.fatal(
_("USGS Earth Explorer does not support 'relativeorbitnumber'"
" option."))
if producttype and producttype != "S2MSI1C":
gs.fatal(
_("USGS Earth Explorer only supports producttype S2MSI1C"))
if query:
if not any(
key in query
for key in ["identifier", "filename", "usgs_identifier"]):
gs.fatal(
_("USGS Earth Explorer only supports query options"
" 'filename', 'identifier' or 'usgs_identifier'."))
if "usgs_identifier" in query:
# get entityId from usgs identifier and directly save results
usgs_id = query["usgs_identifier"]
check_s2l1c_identifier(usgs_id, source="usgs")
# entity_id = self._api.lookup('SENTINEL_2A', [usgs_id],
# inverse=True)
entity_id = self._api.get_entity_id([usgs_id], "SENTINEL_2A")
self.get_products_from_uuid_usgs(entity_id)
return
else:
if "filename" in query:
esa_id = query["filename"].replace(".SAFE", "")
else:
esa_id = query["identifier"]
check_s2l1c_identifier(esa_id, source="esa")
esa_prod_id = esa_id.split("_")[-1]
utm_tile = esa_id.split("_")[-2]
acq_date = esa_id.split("_")[2].split("T")[0]
acq_date_string = "{0}-{1}-{2}".format(acq_date[:4],
acq_date[4:6],
acq_date[6:])
start_date = end_date = acq_date_string
# build the USGS style S2-identifier
if utm_tile.startswith("T"):
utm_tile_base = utm_tile[1:]
bbox = get_bbox_from_S2_UTMtile(utm_tile_base)
else:
# get coordinate pairs from wkt string
str_1 = "POLYGON(("
str_2 = "))"
coords = area[area.find(str_1) +
len(str_1):area.rfind(str_2)].split(",")
# add one space to first pair for consistency
coords[0] = " " + coords[0]
lons = [float(pair.split(" ")[1]) for pair in coords]
lats = [float(pair.split(" ")[2]) for pair in coords]
bbox = (min(lons), min(lats), max(lons), max(lats))
start_date = start
end_date = end
usgs_args = {
"dataset": "SENTINEL_2A",
"bbox": bbox,
"start_date": start_date,
"end_date": end_date,
}
if clouds:
usgs_args["max_cloud_cover"] = clouds
if limit:
usgs_args["max_results"] = limit
scenes = self._api.search(**usgs_args)
self._api.logout()
if query:
# check if the UTM-Tile is correct, remove otherwise
for scene in scenes:
if scene["display_id"].split("_")[1] != utm_tile:
scenes.remove(scene)
# remove redundant scene
if len(scenes) == 2:
for scene in scenes:
prod_id = scene["display_id"].split("_")[-1]
if prod_id != esa_prod_id:
scenes.remove(scene)
if len(scenes) < 1:
gs.message(_("No product found"))
return
scenes_df = pandas.DataFrame.from_dict(scenes)
if sortby:
# replace sortby keywords with USGS keywords
for idx, keyword in enumerate(sortby):
if keyword == "cloudcoverpercentage":
sortby[idx] = "cloud_cover"
# turn cloudcover to float to make it sortable
scenes_df["cloud_cover"] = pandas.to_numeric(
scenes_df["cloud_cover"])
elif keyword == "ingestiondate":
sortby[idx] = "acquisition_date"
# what does sorting by footprint mean
elif keyword == "footprint":
sortby[idx] = "display_id"
self._products_df_sorted = scenes_df.sort_values(sortby,
ascending=[asc] *
len(sortby),
ignore_index=True)
else:
self._products_df_sorted = scenes_df
gs.message(
_("{} Sentinel product(s) found").format(
len(self._products_df_sorted)))
def satdownload(product_id, geojson, download_path='./downloads/',
remove_trash=False, api=None, download_only=False):
"""
Downloads, extracts and crops products.
Args:
product_id: str
Example: "e3fea737-a83b-4fec-8a5a-68ed8d647c71"
geojson: str
Path to geojson file.
download_path: str, optional
location to download products.
remove_trash: bool, default Fasle
remove unnecessary files after downloading.
download_only: bool, default False
Download only (Do not extract).
api: SentinelAPI api object
"""
print('Satdownload for ' + product_id)
logging.debug('satdownload: ' + product_id)
# create downloads folder
if os.path.isdir(download_path) is False:
os.mkdir(download_path)
if api is None:
api = SentinelAPI(USERNAME, PASSWORD,
'https://scihub.copernicus.eu/dhus')
# query product information
product_info = api.get_product_odata(product_id, full=True)
sentinel = product_info['Satellite']
# directory for images only
target_directory = os.path.join(download_path, product_info['title'])
if os.path.isdir(target_directory):
print('Product is already processed, skipping product...')
return
# download
if os.path.isfile(os.path.join(
download_path, product_info['title'] + '.zip')) is True:
print(product_info['title'] + '.zip' + ' exist.')
else:
satdownload_zip(product_info['id'], download_path, api=api)
# skip extraction part
if download_only is True:
return
# extract zip file
zipfile_path = os.path.join(download_path, product_info['title'] + '.zip')
zip_ref = zipfile.ZipFile(zipfile_path, 'r')
zip_ref.extractall(download_path)
zip_ref.close()
if os.path.isdir(
os.path.join(download_path, product_info['Filename'])) is False:
raise Exception('Directory not found after unzipping.')
# clearing target directory
if os.path.isdir(target_directory) is True:
shutil.rmtree(target_directory)
os.mkdir(target_directory)
selection = transform_coordinates(coordinates_from_geojson(geojson))
if sentinel == 'Sentinel-2':
# product can contain many tails (located in ./GRANULE/)
granule = os.path.join(download_path, product_info['Filename'],
'GRANULE')
for i, tail_name in enumerate(os.listdir(granule)):
print('\ttail name: ' + tail_name)
tail_folder_name = 'tail.{}'.format(i)
os.mkdir(os.path.join(target_directory, tail_folder_name))
# image directories are different for different product types
image_dir = os.path.join(granule, tail_name, 'IMG_DATA')
if product_info['Product type'] == 'S2MSI2Ap':
image_dir = os.path.join(image_dir, 'R10m')
# move bands into target directory
for image in os.listdir(image_dir):
image_prime = image
if product_info['Product type'] == 'S2MSI2Ap':
image_prime = image_prime[4:-8] + '.jp2'
os.rename(os.path.join(image_dir, image),
os.path.join(target_directory,
tail_folder_name, image_prime))
elif sentinel == 'Sentinel-1':
# shift selection for sentinel-1 products
dx, dy = 130.54544882194287, 20.162166196209284
selection[:, 0] = selection[:, 0] + dx
selection[:, 1] = selection[:, 1] - dy
# create tail folder
tail_folder_name = 'tail.{}'.format(0)
os.mkdir(os.path.join(target_directory, tail_folder_name))
# image directories are different for different product types
image_dir = os.path.join(download_path, product_info['Filename'],
'measurement')
# move bands into target directory
for image in os.listdir(image_dir):
image_path = os.path.join(image_dir, image)
gdal.Warp(image_path, gdal.Open(image_path), dstSRS='EPSG:32638')
os.rename(image_path, os.path.join(target_directory,
tail_folder_name, image))
else:
print('Unknown satellite')
# save info file
product_info_series = pandas.Series(product_info)
with open(os.path.join(target_directory, 'info.txt'), 'w') as f:
f.write(product_info_series.to_string())
with open(os.path.join(target_directory, 'info.json'), 'w') as f:
product_info_series.to_json(f)
# remove unnecessary files
if remove_trash is True:
os.remove(zipfile_path)
shutil.rmtree(os.path.join(download_path, product_info['Filename']))
# cropping images
print(target_directory)
for tail_name in os.listdir(target_directory):
if os.path.isdir(os.path.join(target_directory, tail_name)) is False:
continue
print('\tprocessing ' + tail_name + ' ...')
process_tail(os.path.join(target_directory, tail_name), selection,
remove_trash=remove_trash)
print('\n\n')
def apirequest(year="2017"):
full_path = os.getcwd()
os.chdir(Path(full_path).parents[0])
downloadfolder = r"Produtos_Sentinel"
try:
if not os.path.exists(downloadfolder):
os.makedirs(downloadfolder)
except OSError:
print("Erro: Criar Pasta " + downloadfolder)
api = SentinelAPI('pfmacf', '4mcTUobqdf',
'https://scihub.copernicus.eu/dhus')
path = "Dataset" + str(year)
my_dir_path = Path(path)
if not my_dir_path.is_dir():
switcherfunc = {
0: convertshapeepsg,
1: createindividualshp,
2: datatxt,
3: getgeojson
}
for func in switcherfunc:
_func_exec = switcherfunc[func](year)
num_sub_folders = [name for name in os.listdir(path)]
json_folder = check_jsonstats_folder("JsonApis")
index_filename = "LastIndex_SentinelApi" + " " + str(year) + ".json"
jpath = os.path.join(json_folder, index_filename)
jsonstring = "Last Iteration" + " " + str(year)
unique_txt = r"Unique_Products.txt"
open(unique_txt, 'a').close()
contador_vazios = 0
my_file_index = Path(index_filename)
if my_file_index.is_file():
with open(index_filename, "r") as file:
data = file.read()
file_dict = json.loads(data)
index = file_dict[jsonstring]
else:
index = 0
for i in range(index, len(num_sub_folders)):
pathfinal = os.path.join(path, str(i))
pathtxt = os.path.join(pathfinal, "Data.txt")
pathgeojson = os.path.join(pathfinal, "bbox4326.geojson")
data = linecache.getline(pathtxt, 2)
date_fire = data.rstrip('\n').split(" ")
ano = int(date_fire[2].split("-")[0])
mes = int(date_fire[2].split("-")[1])
dia = int(date_fire[2].split("-")[2])
search_date = [ano, mes, dia]
products = get_footprint(api, pathgeojson, search_date, 14)
print('\nNumero de produtos encontrados = ', (len(products)))
print('\nIndex = ', i)
if not len(products):
products = get_footprint(api, pathgeojson, search_date, 30)
if not len(products):
products = get_footprint(api, pathgeojson, search_date, 60)
if not len(products):
filename = "Sem_Produtos.txt"
filepath = os.path.join(pathfinal, filename)
write_to_file(filepath, mode="w", text="Invalido")
contador_vazios += 1
continue
# converter para DataFrame
products_df = api.to_dataframe(products)
products_geojson = api.to_geojson(products)
valid_list = validate_footprints(products_geojson, pathfinal, i, year)
if valid_list:
product_id, product_title = get_final_product(
valid_list, products_df, pathfinal)
product_info = api.get_product_odata(product_id)
file = open(unique_txt, "r+", encoding="utf-8")
line_found = any(product_title in line for line in file)
if not line_found:
write_to_file(unique_txt, mode="a", text=product_title)
open("Products_to_Download.txt", 'a').close()
check_availability_download(product_info, product_title,
product_id, api, downloadfolder)
file.close()
else:
file.close()
else:
filename = "Sem_Produtos.txt"
filepath = os.path.join(pathfinal, filename)
write_to_file(filepath, mode="w", text="Invalido")
contador_vazios += 1
json_dict = {jsonstring: i}
json_dict_exception = {jsonstring: 0}
if i < len(num_sub_folders) - 1:
with open(jpath, 'w') as output:
json.dump(json_dict, output, indent=4)
else:
with open(jpath, 'w') as output:
json.dump(json_dict_exception, output, indent=4)
print("Contagem de incendios sem Produto: ", contador_vazios)
def test_get_product_odata_full():
api = SentinelAPI(**_api_auth)
expected_full = {
'8df46c9e-a20c-43db-a19a-4240c2ed3b8b': {
'id': '8df46c9e-a20c-43db-a19a-4240c2ed3b8b',
'title':
'S1A_EW_GRDM_1SDV_20151121T100356_20151121T100429_008701_00C622_A0EC',
'size': 143549851,
'md5': 'D5E4DF5C38C6E97BF7E7BD540AB21C05',
'date': datetime(2015, 11, 21, 10, 3, 56, 675000),
'footprint':
'POLYGON((-63.852531 -5.880887,-67.495872 -5.075419,-67.066071 -3.084356,-63.430576 -3.880541,-63.852531 -5.880887))',
'url':
"https://scihub.copernicus.eu/apihub/odata/v1/Products('8df46c9e-a20c-43db-a19a-4240c2ed3b8b')/$value",
'Acquisition Type': 'NOMINAL',
'Carrier rocket': 'Soyuz',
'Cycle number': 64,
'Date': datetime(2015, 11, 21, 10, 3, 56, 675000),
'Filename':
'S1A_EW_GRDM_1SDV_20151121T100356_20151121T100429_008701_00C622_A0EC.SAFE',
'Footprint':
'<gml:Polygon srsName="http://www.opengis.net/gml/srs/epsg.xml#4326" xmlns:gml="http://www.opengis.net/gml"> <gml:outerBoundaryIs> <gml:LinearRing> <gml:coordinates>-5.880887,-63.852531 -5.075419,-67.495872 -3.084356,-67.066071 -3.880541,-63.430576 -5.880887,-63.852531</gml:coordinates> </gml:LinearRing> </gml:outerBoundaryIs></gml:Polygon>',
'Format': 'SAFE',
'Identifier':
'S1A_EW_GRDM_1SDV_20151121T100356_20151121T100429_008701_00C622_A0EC',
'Ingestion Date': datetime(2015, 11, 21, 13, 22, 4, 992000),
'Instrument': 'SAR-C',
'Instrument abbreviation': 'SAR-C SAR',
'Instrument description':
'<a target="_blank" href="https://sentinel.esa.int/web/sentinel/missions/sentinel-1">https://sentinel.esa.int/web/sentinel/missions/sentinel-1</a>',
'Instrument description text':
'The SAR Antenna Subsystem (SAS) is developed and build by AstriumGmbH. It is a large foldable planar phased array antenna, which isformed by a centre panel and two antenna side wings. In deployedconfiguration the antenna has an overall aperture of 12.3 x 0.84 m.The antenna provides a fast electronic scanning capability inazimuth and elevation and is based on low loss and highly stablewaveguide radiators build in carbon fibre technology, which arealready successfully used by the TerraSAR-X radar imaging mission.The SAR Electronic Subsystem (SES) is developed and build byAstrium Ltd. It provides all radar control, IF/ RF signalgeneration and receive data handling functions for the SARInstrument. The fully redundant SES is based on a channelisedarchitecture with one transmit and two receive chains, providing amodular approach to the generation and reception of wide-bandsignals and the handling of multi-polarisation modes. One keyfeature is the implementation of the Flexible Dynamic BlockAdaptive Quantisation (FD-BAQ) data compression concept, whichallows an efficient use of on-board storage resources and minimisesdownlink times.',
'Instrument mode': 'EW',
'Instrument name': 'Synthetic Aperture Radar (C-band)',
'Instrument swath': 'EW',
'JTS footprint':
'POLYGON ((-63.852531 -5.880887,-67.495872 -5.075419,-67.066071 -3.084356,-63.430576 -3.880541,-63.852531 -5.880887))',
'Launch date': 'April 3rd, 2014',
'Mission datatake id': 50722,
'Mission type': 'Earth observation',
'Mode': 'EW',
'NSSDC identifier': '0000-000A',
'Operator': 'European Space Agency',
'Orbit number (start)': 8701,
'Orbit number (stop)': 8701,
'Pass direction': 'DESCENDING',
'Phase identifier': 1,
'Polarisation': 'VV VH',
'Product class': 'S',
'Product class description': 'SAR Standard L1 Product',
'Product composition': 'Slice',
'Product level': 'L1',
'Product type': 'GRD',
'Relative orbit (start)': 54,
'Relative orbit (stop)': 54,
'Resolution': 'Medium',
'Satellite': 'Sentinel-1',
'Satellite description':
'<a target="_blank" href="https://sentinel.esa.int/web/sentinel/missions/sentinel-1">https://sentinel.esa.int/web/sentinel/missions/sentinel-1</a>',
'Satellite name': 'Sentinel-1',
'Satellite number': 'A',
'Sensing start': datetime(2015, 11, 21, 10, 3, 56, 675000),
'Sensing stop': datetime(2015, 11, 21, 10, 4, 29, 714000),
'Size': '223.88 MB',
'Slice number': 1,
'Start relative orbit number': 54,
'Status': 'ARCHIVED',
'Stop relative orbit number': 54,
'Timeliness Category': 'Fast-24h'
},
'44517f66-9845-4792-a988-b5ae6e81fd3e': {
'id': '44517f66-9845-4792-a988-b5ae6e81fd3e',
'title':
'S2A_OPER_PRD_MSIL1C_PDMC_20151228T112523_R110_V20151227T142229_20151227T142229',
'size': 5854429622,
'md5': '48C5648C2644CE07207B3C943DEDEB44',
'date': datetime(2015, 12, 27, 14, 22, 29),
'footprint':
'POLYGON((-58.80274769505742 -4.565257232533263,-58.80535376268811 -5.513960396525286,-57.90315169909761 -5.515947033626909,-57.903151791669515 -5.516014389089381,-57.85874693129081 -5.516044812342758,-57.814323596961835 -5.516142631941845,-57.81432351345917 -5.516075248310466,-57.00018056571297 -5.516633044843839,-57.000180565731384 -5.516700066819259,-56.95603179187787 -5.51666329264377,-56.91188395837315 -5.516693539799448,-56.91188396736038 -5.51662651925904,-56.097209386295305 -5.515947927683427,-56.09720929423562 -5.516014937246069,-56.053056977999596 -5.5159111504805916,-56.00892491028779 -5.515874390220655,-56.00892501130261 -5.515807411549814,-55.10621586418906 -5.513685455771881,-55.108821882251775 -4.6092845892233,-54.20840287327946 -4.606372862374043,-54.21169990975238 -3.658594390979672,-54.214267703869346 -2.710949551849636,-55.15704255065496 -2.7127451087194463,-56.0563616875051 -2.71378646425769,-56.9561852630143 -2.7141556791285275,-57.8999998009875 -2.713837142510183,-57.90079161941062 -3.6180222056692726,-58.800616247288836 -3.616721351843382,-58.80274769505742 -4.565257232533263))',
'url':
"https://scihub.copernicus.eu/apihub/odata/v1/Products('44517f66-9845-4792-a988-b5ae6e81fd3e')/$value",
'Cloud cover percentage': 18.153846153846153,
'Date': datetime(2015, 12, 27, 14, 22, 29),
'Degraded MSI data percentage': 0,
'Degraded ancillary data percentage': 0,
'Filename':
'S2A_OPER_PRD_MSIL1C_PDMC_20151228T112523_R110_V20151227T142229_20151227T142229.SAFE',
'Footprint':
'<gml:Polygon srsName="http://www.opengis.net/gml/srs/epsg.xml#4326" xmlns:gml="http://www.opengis.net/gml"> <gml:outerBoundaryIs> <gml:LinearRing> <gml:coordinates>-4.565257232533263,-58.80274769505742 -5.513960396525286,-58.80535376268811 -5.515947033626909,-57.90315169909761 -5.516014389089381,-57.903151791669515 -5.516044812342758,-57.85874693129081 -5.516142631941845,-57.814323596961835 -5.516075248310466,-57.81432351345917 -5.516633044843839,-57.00018056571297 -5.516700066819259,-57.000180565731384 -5.51666329264377,-56.95603179187787 -5.516693539799448,-56.91188395837315 -5.51662651925904,-56.91188396736038 -5.515947927683427,-56.097209386295305 -5.516014937246069,-56.09720929423562 -5.5159111504805916,-56.053056977999596 -5.515874390220655,-56.00892491028779 -5.515807411549814,-56.00892501130261 -5.513685455771881,-55.10621586418906 -4.6092845892233,-55.108821882251775 -4.606372862374043,-54.20840287327946 -3.658594390979672,-54.21169990975238 -2.710949551849636,-54.214267703869346 -2.7127451087194463,-55.15704255065496 -2.71378646425769,-56.0563616875051 -2.7141556791285275,-56.9561852630143 -2.713837142510183,-57.8999998009875 -3.6180222056692726,-57.90079161941062 -3.616721351843382,-58.800616247288836 -4.565257232533263,-58.80274769505742</gml:coordinates> </gml:LinearRing> </gml:outerBoundaryIs></gml:Polygon>',
'Format': 'SAFE',
'Format correctness': 'PASSED',
'General quality': 'PASSED',
'Generation time': datetime(2015, 12, 28, 11, 25, 23, 357),
'Geometric quality': 'PASSED',
'Identifier':
'S2A_OPER_PRD_MSIL1C_PDMC_20151228T112523_R110_V20151227T142229_20151227T142229',
'Ingestion Date': datetime(2015, 12, 28, 10, 57, 13, 725000),
'Instrument': 'MSI',
'Instrument abbreviation': 'MSI',
'Instrument mode': 'INS-NOBS',
'Instrument name': 'Multi-Spectral Instrument',
'JTS footprint':
'POLYGON ((-58.80274769505742 -4.565257232533263,-58.80535376268811 -5.513960396525286,-57.90315169909761 -5.515947033626909,-57.903151791669515 -5.516014389089381,-57.85874693129081 -5.516044812342758,-57.814323596961835 -5.516142631941845,-57.81432351345917 -5.516075248310466,-57.00018056571297 -5.516633044843839,-57.000180565731384 -5.516700066819259,-56.95603179187787 -5.51666329264377,-56.91188395837315 -5.516693539799448,-56.91188396736038 -5.51662651925904,-56.097209386295305 -5.515947927683427,-56.09720929423562 -5.516014937246069,-56.053056977999596 -5.5159111504805916,-56.00892491028779 -5.515874390220655,-56.00892501130261 -5.515807411549814,-55.10621586418906 -5.513685455771881,-55.108821882251775 -4.6092845892233,-54.20840287327946 -4.606372862374043,-54.21169990975238 -3.658594390979672,-54.214267703869346 -2.710949551849636,-55.15704255065496 -2.7127451087194463,-56.0563616875051 -2.71378646425769,-56.9561852630143 -2.7141556791285275,-57.8999998009875 -2.713837142510183,-57.90079161941062 -3.6180222056692726,-58.800616247288836 -3.616721351843382,-58.80274769505742 -4.565257232533263))',
'Mission datatake id': 'GS2A_20151227T140932_002681_N02.01',
'NSSDC identifier': '2015-000A',
'Orbit number (start)': 2681,
'Pass direction': 'DESCENDING',
'Platform serial identifier': 'Sentinel-2A',
'Processing baseline': 2.01,
'Processing level': 'Level-1C',
'Product type': 'S2MSI1C',
'Radiometric quality': 'PASSED',
'Relative orbit (start)': 110,
'Satellite': 'Sentinel-2',
'Satellite name': 'Sentinel-2',
'Satellite number': 'A',
'Sensing start': datetime(2015, 12, 27, 14, 22, 29),
'Sensing stop': datetime(2015, 12, 27, 14, 22, 29),
'Sensor quality': 'PASSED',
'Size': '5.50 GB'
}
}
for id, expected in expected_full.items():
ret = api.get_product_odata(id, full=True)
assert set(ret) == set(expected)
for k in ret:
assert ret[k] == expected[k]
for line in out.splitlines():
# Product bb7a7783-f91b-4a35-907d-a6ddb807da73 - Date: 2019-07-09T02:55:59.024Z, Instrument: MSI, Mode: , Satellite: Sentinel-2, Size: 1.09 GB
m = re.search('Product\s+(\S+)', line)
if not m:
continue
uuids.append(m.group(1))
names = []
sizes = []
stats = []
if opts.url is not None:
api = SentinelAPI(opts.user, opts.password, opts.url)
else:
api = SentinelAPI(opts.user, opts.password)
for i, uuid in enumerate(uuids):
out = api.get_product_odata(uuid)
name = out['title']
size = out['size']
stat = out['Online']
names.append(name)
sizes.append(size)
stats.append(stat)
sys.stderr.write('{:4d} {:40s} {:70s} {:10d} {:7s}\n'.format(
i + 1, uuid, name, size, 'Online' if stat else 'Offline'))
api.session.close() # has any effect?
if opts.download:
path = '.' if opts.path is None else opts.path
for i in range(len(uuids)):
# Check data availability
if opts.sort_year:
class SentinelDownloader(object):
def __init__(self, user, password, api_url='https://scihub.copernicus.eu/apihub'):
self._apiname = api_url
self._user = user
self._password = password
# init logger
root = logging.getLogger()
root.addHandler(logging.StreamHandler(
sys.stderr
))
if self._apiname == 'https://scihub.copernicus.eu/apihub':
try:
from sentinelsat import SentinelAPI
except ImportError as e:
gs.fatal(_("Module requires sentinelsat library: {}").format(e))
# connect SciHub via API
self._api = SentinelAPI(self._user, self._password,
api_url=self._apiname
)
elif self._apiname == 'USGS_EE':
try:
import landsatxplore.api
from landsatxplore.errors import EarthExplorerError
except ImportError as e:
gs.fatal(_("Module requires landsatxplore library: {}").format(e))
api_login = False
while api_login is False:
# avoid login conflict in possible parallel execution
try:
self._api = landsatxplore.api.API(self._user,
self._password)
api_login = True
except EarthExplorerError as e:
time.sleep(1)
self._products_df_sorted = None
def filter(self, area, area_relation,
clouds=None, producttype=None, limit=None, query={},
start=None, end=None, sortby=[], asc=True, relativeorbitnumber=None):
args = {}
if clouds:
args['cloudcoverpercentage'] = (0, int(clouds))
if relativeorbitnumber:
args['relativeorbitnumber'] = relativeorbitnumber
if producttype.startswith('S2') and int(relativeorbitnumber) > 143:
gs.warning("This relative orbit number is out of range")
elif int(relativeorbitnumber) > 175:
gs.warning(_("This relative orbit number is out of range"))
if producttype:
args['producttype'] = producttype
if producttype.startswith('S2'):
args['platformname'] = 'Sentinel-2'
else:
args['platformname'] = 'Sentinel-1'
if not start:
start = 'NOW-60DAYS'
else:
start = start.replace('-', '')
if not end:
end = 'NOW'
else:
end = end.replace('-', '')
if query:
redefined = [value for value in args.keys() if value in query.keys()]
if redefined:
gs.warning(_("Query overrides already defined options ({})").format(
','.join(redefined)
))
args.update(query)
gs.verbose(_("Query: area={} area_relation={} date=({}, {}) args={}").format(
area, area_relation, start, end, args
))
products = self._api.query(
area=area, area_relation=area_relation,
date=(start, end),
**args
)
products_df = self._api.to_dataframe(products)
if len(products_df) < 1:
gs.message(_("No product found"))
return
# sort and limit to first sorted product
if sortby:
self._products_df_sorted = products_df.sort_values(
sortby,
ascending=[asc] * len(sortby)
)
else:
self._products_df_sorted = products_df
if limit:
self._products_df_sorted = self._products_df_sorted.head(int(limit))
gs.message(_("{} Sentinel product(s) found").format(len(self._products_df_sorted)))
def list(self):
if self._products_df_sorted is None:
return
id_kw = ('uuid', 'entity_id')
identifier_kw = ('identifier', 'display_id')
cloud_kw = ('cloudcoverpercentage', 'cloud_cover')
time_kw = ('beginposition', 'acquisition_date')
kw_idx = 1 if self._apiname == 'USGS_EE' else 0
for idx in range(len(self._products_df_sorted[id_kw[kw_idx]])):
if cloud_kw[kw_idx] in self._products_df_sorted:
ccp = '{0:2.0f}%'.format(
float(self._products_df_sorted[cloud_kw[kw_idx]][idx]))
else:
ccp = 'cloudcover_NA'
print_str = '{0} {1}'.format(
self._products_df_sorted[id_kw[kw_idx]][idx],
self._products_df_sorted[identifier_kw[kw_idx]][idx])
if kw_idx == 1:
time_string = self._products_df_sorted[time_kw[kw_idx]][idx]
else:
time_string = self._products_df_sorted[
time_kw[kw_idx]][idx].strftime("%Y-%m-%dT%H:%M:%SZ")
print_str += ' {0} {1}'.format(time_string, ccp)
if kw_idx == 0:
print_str += ' {0}'.format(
self._products_df_sorted['producttype'][idx])
print(print_str)
def download(self, output, sleep=False, maxretry=False,
datasource='ESA_COAH'):
if self._products_df_sorted is None:
return
create_dir(output)
gs.message(_("Downloading data into <{}>...").format(output))
if datasource == 'USGS_EE':
from landsatxplore.earthexplorer import EarthExplorer
from landsatxplore.errors import EarthExplorerError
from zipfile import ZipFile
ee_login = False
while ee_login is False:
# avoid login conflict in possible parallel execution
try:
ee = EarthExplorer(self._user, self._password)
ee_login = True
except EarthExplorerError as e:
time.sleep(1)
for idx in range(len(self._products_df_sorted['entity_id'])):
scene = self._products_df_sorted['entity_id'][idx]
identifier = self._products_df_sorted['display_id'][idx]
zip_file = os.path.join(output, '{}.zip'.format(identifier))
gs.message(_("Downloading {}...").format(identifier))
try:
ee.download(identifier=identifier, output_dir=output, timeout=600)
except EarthExplorerError as e:
gs.fatal(_(e))
ee.logout()
# extract .zip to get "usual" .SAFE
with ZipFile(zip_file, 'r') as zip:
safe_name = zip.namelist()[0].split('/')[0]
outpath = os.path.join(output, safe_name)
zip.extractall(path=output)
gs.message(_("Downloaded to <{}>").format(outpath))
try:
os.remove(zip_file)
except Exception as e:
gs.warning(_("Unable to remove {0}:{1}").format(
zip_file, e))
elif datasource == "ESA_COAH":
for idx in range(len(self._products_df_sorted['uuid'])):
gs.message('{} -> {}.SAFE'.format(
self._products_df_sorted['uuid'][idx],
os.path.join(output, self._products_df_sorted['identifier'][idx])
))
# download
out = self._api.download(self._products_df_sorted['uuid'][idx],
output)
if sleep:
x = 1
online = out['Online']
while not online:
# sleep is in minutes so multiply by 60
time.sleep(int(sleep) * 60)
out = self._api.download(self._products_df_sorted['uuid'][idx],
output)
x += 1
if x > maxretry:
online = True
elif datasource == 'GCS':
for scene_id in self._products_df_sorted['identifier']:
gs.message(_("Downloading {}...").format(scene_id))
dl_code = download_gcs(scene_id, output)
if dl_code == 0:
gs.message(_("Downloaded to {}").format(
os.path.join(output, '{}.SAFE'.format(scene_id))))
else:
# remove incomplete file
del_folder = os.path.join(output,
'{}.SAFE'.format(scene_id))
try:
shutil.rmtree(del_folder)
except Exception as e:
gs.warning(_("Unable to removed unfinished "
"download {}".format(del_folder)))
def save_footprints(self, map_name):
if self._products_df_sorted is None:
return
if self._apiname == 'USGS_EE':
gs.fatal(_(
"USGS Earth Explorer does not support footprint download."))
try:
from osgeo import ogr, osr
except ImportError as e:
gs.fatal(_("Option <footprints> requires GDAL library: {}").format(e))
gs.message(_("Writing footprints into <{}>...").format(map_name))
driver = ogr.GetDriverByName("GPKG")
tmp_name = gs.tempfile() + '.gpkg'
data_source = driver.CreateDataSource(tmp_name)
srs = osr.SpatialReference()
srs.ImportFromEPSG(4326)
# features can be polygons or multi-polygons
layer = data_source.CreateLayer(str(map_name), srs, ogr.wkbMultiPolygon)
# attributes
attrs = OrderedDict([
("uuid", ogr.OFTString),
("ingestiondate", ogr.OFTString),
("cloudcoverpercentage", ogr.OFTInteger),
("producttype", ogr.OFTString),
("identifier", ogr.OFTString)
])
# Sentinel-1 data does not have cloudcoverpercentage
prod_types = [type for type in self._products_df_sorted["producttype"]]
s1_types = ["SLC", "GRD"]
if any(type in prod_types for type in s1_types):
del attrs["cloudcoverpercentage"]
for key in attrs.keys():
field = ogr.FieldDefn(key, attrs[key])
layer.CreateField(field)
# features
for idx in range(len(self._products_df_sorted['uuid'])):
wkt = self._products_df_sorted['footprint'][idx]
feature = ogr.Feature(layer.GetLayerDefn())
newgeom = ogr.CreateGeometryFromWkt(wkt)
# convert polygons to multi-polygons
newgeomtype = ogr.GT_Flatten(newgeom.GetGeometryType())
if newgeomtype == ogr.wkbPolygon:
multigeom = ogr.Geometry(ogr.wkbMultiPolygon)
multigeom.AddGeometryDirectly(newgeom)
feature.SetGeometry(multigeom)
else:
feature.SetGeometry(newgeom)
for key in attrs.keys():
if key == 'ingestiondate':
value = self._products_df_sorted[key][idx].strftime("%Y-%m-%dT%H:%M:%SZ")
else:
value = self._products_df_sorted[key][idx]
feature.SetField(key, value)
layer.CreateFeature(feature)
feature = None
data_source = None
# coordinates of footprints are in WKT -> fp precision issues
# -> snap
gs.run_command('v.import', input=tmp_name, output=map_name,
layer=map_name, snap=1e-10, quiet=True
)
def get_products_from_uuid_usgs(self, uuid_list):
scenes = []
for uuid in uuid_list:
metadata = self._api.metadata(uuid, 'SENTINEL_2A')
scenes.append(metadata)
scenes_df = pandas.DataFrame.from_dict(scenes)
self._products_df_sorted = scenes_df
gs.message(_("{} Sentinel product(s) found").format(
len(self._products_df_sorted)))
def set_uuid(self, uuid_list):
"""Set products by uuid.
TODO: Find better implementation
:param uuid: uuid to download
"""
if self._apiname == 'USGS_EE':
self.get_products_from_uuid_usgs(uuid_list)
else:
from sentinelsat.sentinel import SentinelAPIError
self._products_df_sorted = {'uuid': []}
for uuid in uuid_list:
try:
odata = self._api.get_product_odata(uuid, full=True)
except SentinelAPIError as e:
gs.error(_("{0}. UUID {1} skipped".format(e, uuid)))
continue
for k, v in odata.items():
if k == 'id':
k = 'uuid'
elif k == 'Sensing start':
k = 'beginposition'
elif k == 'Product type':
k = 'producttype'
elif k == 'Cloud cover percentage':
k = 'cloudcoverpercentage'
elif k == 'Identifier':
k = 'identifier'
elif k == 'Ingestion Date':
k = 'ingestiondate'
elif k == 'footprint':
pass
else:
continue
if k not in self._products_df_sorted:
self._products_df_sorted[k] = []
self._products_df_sorted[k].append(v)
def filter_USGS(self, area, area_relation, clouds=None, producttype=None,
limit=None, query={}, start=None, end=None, sortby=[],
asc=True, relativeorbitnumber=None):
if area_relation != 'Intersects':
gs.fatal(_(
"USGS Earth Explorer only supports area_relation"
" 'Intersects'"))
if relativeorbitnumber:
gs.fatal(_(
"USGS Earth Explorer does not support 'relativeorbitnumber'"
" option."))
if producttype and producttype != 'S2MSI1C':
gs.fatal(_(
"USGS Earth Explorer only supports producttype S2MSI1C"))
if query:
if not any(key in query for key in ['identifier', 'filename',
'usgs_identifier']):
gs.fatal(_(
"USGS Earth Explorer only supports query options"
" 'filename', 'identifier' or 'usgs_identifier'."))
if 'usgs_identifier' in query:
# get entityId from usgs identifier and directly save results
usgs_id = query['usgs_identifier']
check_s2l1c_identifier(usgs_id, source='usgs')
# entity_id = self._api.lookup('SENTINEL_2A', [usgs_id],
# inverse=True)
entity_id = self._api.get_entity_id([usgs_id], 'SENTINEL_2A')
self.get_products_from_uuid_usgs(entity_id)
return
else:
if "filename" in query:
esa_id = query['filename'].replace('.SAFE', '')
else:
esa_id = query['identifier']
check_s2l1c_identifier(esa_id, source='esa')
esa_prod_id = esa_id.split('_')[-1]
utm_tile = esa_id.split('_')[-2]
acq_date = esa_id.split('_')[2].split('T')[0]
acq_date_string = '{0}-{1}-{2}'.format(
acq_date[:4], acq_date[4:6], acq_date[6:])
start_date = end_date = acq_date_string
# build the USGS style S2-identifier
if utm_tile.startswith('T'):
utm_tile_base = utm_tile[1:]
bbox = get_bbox_from_S2_UTMtile(utm_tile_base)
else:
# get coordinate pairs from wkt string
str_1 = 'POLYGON(('
str_2 = '))'
coords = area[area.find(str_1)+len(str_1):area.rfind(str_2)].split(',')
# add one space to first pair for consistency
coords[0] = ' ' + coords[0]
lons = [float(pair.split(' ')[1]) for pair in coords]
lats = [float(pair.split(' ')[2]) for pair in coords]
bbox = (min(lons), min(lats), max(lons), max(lats))
start_date = start
end_date = end
usgs_args = {
'dataset': 'SENTINEL_2A',
'bbox': bbox,
'start_date': start_date,
'end_date': end_date
}
if clouds:
usgs_args['max_cloud_cover'] = clouds
if limit:
usgs_args['max_results'] = limit
scenes = self._api.search(**usgs_args)
self._api.logout()
if query:
# check if the UTM-Tile is correct, remove otherwise
for scene in scenes:
if scene['display_id'].split('_')[1] != utm_tile:
scenes.remove(scene)
# remove redundant scene
if len(scenes) == 2:
for scene in scenes:
prod_id = scene['display_id'].split('_')[-1]
if prod_id != esa_prod_id:
scenes.remove(scene)
if len(scenes) < 1:
gs.message(_("No product found"))
return
scenes_df = pandas.DataFrame.from_dict(scenes)
if sortby:
# replace sortby keywords with USGS keywords
for idx, keyword in enumerate(sortby):
if keyword == 'cloudcoverpercentage':
sortby[idx] = 'cloud_cover'
# turn cloudcover to float to make it sortable
scenes_df['cloud_cover'] = pandas.to_numeric(
scenes_df['cloud_cover'])
elif keyword == 'ingestiondate':
sortby[idx] = 'acquisition_date'
# what does sorting by footprint mean
elif keyword == 'footprint':
sortby[idx] = 'display_id'
self._products_df_sorted = scenes_df.sort_values(
sortby,
ascending=[asc] * len(sortby), ignore_index=True
)
else:
self._products_df_sorted = scenes_df
gs.message(_("{} Sentinel product(s) found").format(
len(self._products_df_sorted)))
class SentinelWrapper:
def __init__(self):
logger.info("connect to sentinel API")
# connection to API for search queries and download requests
self.api = SentinelAPI(config.copernicusUser, config.copernicusPW,
config.copernicusURL)
logger.info("sentinel API connected")
def get_sentinel_products(self, lat, lon, date_from, date_to, platform,
**kwargs):
logger.info("start sentinel query")
# convert geolocation coordinates to wkt format
footprint = geojson_to_wkt(Point((lon, lat)))
# prepare parameter for cloud coverage
if "cloudcoverpercentage" in kwargs:
kwargs["cloudcoverpercentage"] = (0,
kwargs["cloudcoverpercentage"])
# search query
for attempt in range(1, config.serverFailureRequestRepeats + 1):
try:
result = self.api.query(footprint,
date=(date_from, date_to),
platformname=platform,
**kwargs)
break
except SentinelAPIError as e:
print(repr(e))
if attempt < config.serverFailureRequestRepeats:
print(
f"Attempt {attempt} failed. Next try in {config.serverFailureRequestDelay} minutes."
)
logger.info(
f"Attempt {attempt} to connect to Sentinel server failed. Next try in {config.serverFailureRequestDelay} minutes."
)
time.sleep(60 * config.serverFailureRequestDelay)
else:
print("Last attempt failed. Aborting.")
logger.info(
"Last attempt to connect to Sentinel server failed. Aborting."
)
logger.info("sentinel query complete")
return result
# download multiple sentinel products (list of product IDs)
def download_sentinel_products(self, products):
for attempt in range(1, config.serverFailureRequestRepeats + 1):
try:
logger.info("start downloading sentinel product list")
self.api.download_all(products, config.bigTilesDir)
logger.info("download complete")
break
except SentinelAPIError as e:
print(repr(e))
if attempt < config.serverFailureRequestRepeats:
print(
f"Attempt {attempt} failed. Next try in {config.serverFailureRequestDelay} minutes."
)
logger.info(
f"Attempt {attempt} to connect to Sentinel server failed. Next try in {config.serverFailureRequestDelay} minutes."
)
time.sleep(60 * config.serverFailureRequestDelay)
else:
print("Last attempt failed. Aborting.")
logger.info(
"Last attempt to connect to Sentinel server failed. Aborting."
)
# download sentinel product with certain product ID
def download_sentinel_product(self, product_id):
for attempt in range(1, config.serverFailureRequestRepeats + 1):
try:
logger.info("start downloading sentinel product")
product_info = self.api.download(product_id,
config.bigTilesDir)
if not product_info["Online"]:
logger.info("archived download triggered")
return False
else:
# TODO: Download should be checked
logger.info("download complete")
return True
except SentinelAPIError as e:
print(repr(e))
if attempt < config.serverFailureRequestRepeats:
print(
f"Attempt {attempt} failed. Next try in {config.serverFailureRequestDelay} minutes."
)
logger.info(
f"Attempt {attempt} to connect to Sentinel server failed. Next try in {config.serverFailureRequestDelay} minutes."
)
time.sleep(60 * config.serverFailureRequestDelay)
else:
print("Last attempt failed. Aborting.")
logger.info(
"Last attempt to connect to Sentinel server failed. Aborting."
)
def get_product_data(self, product_id):
for attempt in range(1, config.serverFailureRequestRepeats + 1):
try:
return self.api.get_product_odata(product_id)
except SentinelAPIError as e:
print(repr(e))
if attempt < config.serverFailureRequestRepeats:
print(
f"Attempt {attempt} failed. Next try in {config.serverFailureRequestDelay} minutes."
)
logger.info(
f"Attempt {attempt} to connect to Sentinel server failed. Next try in {config.serverFailureRequestDelay} minutes."
)
time.sleep(60 * config.serverFailureRequestDelay)
else:
print("Last attempt failed. Aborting.")
logger.info(
"Last attempt to connect to Sentinel server failed. Aborting."
)
def ready_for_download(self, product_id):
for attempt in range(1, config.serverFailureRequestRepeats + 1):
try:
return self.api.is_online(product_id)
except SentinelAPIError as e:
print(repr(e))
if attempt < config.serverFailureRequestRepeats:
print(
f"Attempt {attempt} failed. Next try in {config.serverFailureRequestDelay} minutes."
)
logger.info(
f"Attempt {attempt} to connect to Sentinel server failed. Next try in {config.serverFailureRequestDelay} minutes."
)
time.sleep(60 * config.serverFailureRequestDelay)
else:
print("Last attempt failed. Aborting.")
logger.info(
"Last attempt to connect to Sentinel server failed. Aborting."
)
def request_offline_tile(self, last_tile_download_request, product_id):
# check if last request not within request delay
last_request = utils.minutes_since_last_download_request()
if last_request == None or last_request > config.copernicusRequestDelay:
if last_tile_download_request == None or \
utils.minutes_since_timestamp(last_tile_download_request) > config.copernicusRepeatRequestAfterMin:
for attempt in range(1,
config.serverFailureRequestRepeats + 1):
try:
# HTTP-Code 202: Accepted for retrieval
# TODO: handle other HTTP-Codes as well...
product_info = self.api.get_product_odata(product_id)
if self.api._trigger_offline_retrieval(
product_info["url"]) == 202:
return True
else:
return False
except SentinelAPIError as e:
print(repr(e))
if attempt < config.serverFailureRequestRepeats:
print(
f"Attempt {attempt} failed. Next try in {config.serverFailureRequestDelay} minutes."
)
logger.info(
f"Attempt {attempt} to connect to Sentinel server failed. Next try in {config.serverFailureRequestDelay} minutes."
)
time.sleep(60 * config.serverFailureRequestDelay)
else:
print("Last attempt failed. Aborting.")
logger.info(
"Last attempt to connect to Sentinel server failed. Aborting."
)
else:
return False