使用Sentinelsat查询和下载Sentinel3 OLCI数据的问题

Question

我正在使用Sentinelsat API使用Sentinel-3 OLCI二级数据产品，在查询和超过我的数据下载配额时遇到问题。总的来说，我想编写一个程序，接受一个日期范围和一个特定的地理位置，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。这就是我到目前为止所做的：

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

即使在设置api.query(limit=1)时，我也会收到此错误消息。products_df为173MB，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products查询中指定了一个geojson point对象，我想知道为什么它在products_df中返回这么大的multipolygon对象。我想这就是为什么产品数量如此之大，超过了我的配额。有人对此有什么建议吗？此外，由于我不需要Sentinel-3 OLCI 2级数据产品中的任何其他波段，因此在下载之前是否可以仅查询特定波段“Oa04_radiance”