我正在使用 Sentinelsat API 使用 Sentinel-3 OLCI Level-2 数据产品，并且在查询和超出我的数据下载配额时遇到问题。总的来说，我想编写一个接受日期范围和特定地理位置的程序，然后在该位置的指定日期内下载“Oa04_radiance”波段中所有值的数据帧。这是我到目前为止所拥有的：
from sentinelsat import SentinelAPI, read_geojson, geojson_to_wkt
from datetime import date
from geojson import Feature, Point, Polygon
api = SentinelAPI('user', 'password', 'https://apihub.copernicus.eu/apihub')
lon = -123.312383
lat = 49.319269
my_point = Point((lon, lat))
footprint = geojson_to_wkt(my_point)
products = api.query(footprint,
date=(date(2021, 1, 1), date(2021, 6, 15)),
platformname='Sentinel-3',
producttype='OL_2_LRR___',
cloudcoverpercentage=(0, 80))
products_df = api.to_dataframe(products)
api.download_all(products_df.index)
错误输出：
Traceback (most recent call last):
File "C:/Users/t7dej/Desktop/Turbid Time Local/SentSat/SenSat_mdl.py", line 48, in <module>
api.download_all(products_df_sorted.index)
File "E:\Software\Anaconda\lib\site-packages\sentinelsat\sentinel.py", line 723, in download_all
is_online = not self.trigger_offline_retrieval(pid)
File "E:\Software\Anaconda\lib\site-packages\sentinelsat\sentinel.py", line 636, in trigger_offline_retrieval
raise LTAError(msg, r)
sentinelsat.exceptions.LTAError: HTTP status 403 Forbidden: User quota exceeded: MediaRegulationException : An exception occured while creating a stream: Maximum number of 4 concurrent flows achieved by the user
即使我设置了我的我也会api.query(limit=1)收到此错误消息。products_df 为 173 MB，并且有一个几何列，其值为：
MULTIPOLYGON (((-146.081 -49.2196, -145.768 -48.2668, -145.201 -46.4727, -144.658 -44.6765, -144.135 -42.8782, -143.63 -41.0787, -143.142 -39.2767, -142.667 -37.4733, -142.204 -35.6694, -141.753 -33.863, -141.312 -32.0559, -140.878 -30.2474, -140.453 -28.4377, -140.033 -26.6268, -139.62 -24.8151, -139.211 -23.0024, -138.806 -21.1887, -138.404 -19.3744, -138.006 -17.5593, -137.609 -15.7434, -137.213 -13.927, -136.819 -12.1101, -136.425 -10.2928, -136.031 -8.47512, -135.636 -6.65724, -135.24 -4.83889, -134.843 -3.02078, -134.443 -1.2025, -134.04 0.61575, -133.634 2.43352, -133.224 4.25148, -132.81 6.06894, -132.391 7.88578, -131.965 9.702120000000001, -131.534 11.5179, -131.095 13.3329, -130.649 15.1468, -130.194 16.9598, -129.729 18.7716, -129.253 20.582, -128.767 22.3916, -128.267 24.1992, -127.753 26.0043, -127.224 27.8086, -126.678 29.6103, -126.113 31.4098, -125.527 33.2067, -124.919 35.0007, -124.286 36.7919, -123.624 38.5795, -122.932 40.3637, -122.205 42.1436, -121.44 43.9188, -120.631 45.6892, -119.773 47.4541, -118.861 49.2124, -117.886 50.9639, -116.841 52.7073, -115.714 54.4414, -114.495 56.1652, -113.168 57.8769, -111.717 59.5747, -110.12 61.256, -108.352 62.9179, -106.382 64.5568, -104.173 66.16800000000001, -101.677 67.7456, -98.8378 69.2821, -95.5855 70.7672, -91.83369999999999 72.1889, -87.4884 73.5312, -82.44029999999999 74.7715, -76.5813 75.8849, -69.83199999999999 76.83880000000001, -62.1773 77.59399999999999, -53.7161 78.1165, -44.6976 78.3725, -35.5051 78.3451, -26.5677 78.03619999999999, -18.2457 77.46639999999999, -10.7612 76.6694, -4.18714 75.6829, 3.64587789990069e-15 74.8448206506109, 1.50843 74.5429, 6.41354 73.28100000000001, 10.6367 71.9226, 14.2845 70.4875, 17.4519 68.99160000000001, 20.2206 67.4469, 21.6077 67.77589999999999, 23.0264 68.09050000000001, 24.4837 68.3925, 25.9603 68.679, 27.4944 68.9546, 29.0662 69.2161, 30.6951 69.46680000000001, 32.3417 69.6985, 34.024 69.9145, 35.7316 70.10760000000001, 37.4774 70.2903, 39.2531 70.4558, 41.0752 70.6046, 42.9054 70.7343, 44.7579 70.8455, 46.6297 70.938, 48.5174 71.01139999999999, 50.4176 71.0655, 52.3019 71.10290000000001, 52.0832 72.8877, 51.8771 74.6721, 51.6876 76.4562, 51.5212 78.2398, 51.3914 80.0231, 51.3212 81.80629999999999, 51.3582 83.58880000000001, 51.57959163346614 85.05115000000001, 3.911836325497215e-15 85.05115000000001, -133.5599156744917 85.05115000000001, -133.35 83.92870000000001, -133.276 82.14530000000001, -133.33 80.3614, -133.453 78.57859999999999, -133.611 76.7949, -133.799 75.0104, -134.002 73.226, -134.218 71.4409, -134.445 69.6553, -134.678 67.8693, -134.918 66.0826, -135.163 64.2954, -135.413 62.5074, -135.666 60.719, -135.923 58.93, -136.183 57.1401, -136.447 55.3495, -136.712 53.5582, -136.982 51.7664, -137.253 49.9738, -137.528 48.1799, -137.805 46.3858, -138.085 44.5911, -138.368 42.7954, -138.653 40.9991, -138.942 39.2019, -139.234 37.4039, -139.528 35.6058, -139.826 33.8069, -140.128 32.0072, -140.433 30.207, -140.741 28.4055, -141.054 26.6057, -141.37 24.8042, -141.691 23.0012, -142.016 21.1992, -142.346 19.3968, -142.68 17.5942, -143.02 15.7915, -143.365 13.9887, -143.716 12.1859, -144.073 10.3832, -144.436 8.58104, -144.806 6.77937, -145.183 4.97715, -145.567 3.17639, -145.96 1.37623, -146.361 -0.423407, -146.77 -2.22189, -147.19 -4.01968, -147.62 -5.81594, -148.06 -7.61083, -148.512 -9.40438, -148.976 -11.1962, -149.454 -12.9862, -149.946 -14.7742, -150.453 -16.5599, -150.975 -18.343, -151.516 -20.1234, -152.076 -21.901, -152.655 -23.6751, -153.257 -25.4461, -153.883 -27.2129, -154.534 -28.9754, -155.214 -30.7335, -155.923 -32.487, -156.667 -34.2331, -157.447 -35.9749, -158.267 -37.7106, -159.131 -39.4374, -160.043 -41.1566, -161.008 -42.867, -162.033 -44.5672, -162.604 -45.4664, -161.805 -45.7119, -160.989 -45.9615, -160.165 -46.2051, -159.335 -46.4427, -158.497 -46.6742, -157.652 -46.8994, -156.79 -47.1211, -155.932 -47.3333, -155.068 -47.539, -154.207 -47.742, -153.329 -47.9343, -152.444 -48.1198, -151.538 -48.3011, -150.642 -48.4725, -149.738 -48.6368, -148.842 -48.7908, -147.928 -48.9408, -147.008 -49.0835, -146.081 -49.2196)))
我在产品查询中指定了一个 geojson 点对象，我想知道为什么它会在 products_df 中返回这么大的多面体对象。我在想这就是 products_df 如此之大并且超出我的配额的原因。有人对此有什么建议吗？此外，是否可以在下载之前仅查询特定波段“Oa04_radiance”，因为我不需要 Sentinel-3 OLCI Level-2 数据产品中的任何其他波段。