---

Monthly optical images

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Short description

This notebook demonstrates a general usecase for the SpaceSense library.

In this notebook, you will search for, select, and obtain Sentinel-2 data. The selected data will be cloud free and the expected result is to have a single image per month of the year.

---

1 - Import spacesense object(s) and other dependencies

from spacesense import Client
import json
import pandas as pd
import matplotlib.pyplot as plt
import numpy as np

import os
if "SS_API_KEY" not in os.environ:
    from getpass import getpass
    api_key = getpass('Enter your api key : ')
    os.environ["SS_API_KEY"] = api_key

2 - Define AOI and output options

The GeoJSON of this AOI, containing the Cirque de Garvanie in the Pyrenees Mountains, can be downloaded here

# Define the AOI
with open("../resources/aois/cirque_de_garvanie.geojson", mode="r") as file:
    aoi = json.load(file)

# Get an instance of the SpaceSense Client object
client = Client(id="s2_optical_monthly")

# Enable to save data in local files
client.enable_local_output()

3 - Search S2

start_date = "2020-01-01"
end_date = "2021-01-01"
# Create a query filter, limiting cloud coverage to 10% or less, and only taking scenes with 100% swath coverage
query_filter = {"cloud_medium_probability" : {"<=": 10},
                "cloud_high_probability" : {"<=": 10},
                "cloud_shadows" : {"<=": 10},
                "swath_coverage_percentage": {"==": 100}}
res_S2 = client.s2_search(aoi=aoi, start_date=start_date, end_date=end_date, query_filters = query_filter)
res_S2.filter_duplicate_dates()
res_S2.dataframe

	id	date	tile	valid_pixel_percentage	platform	relative_orbit_number	product_id	datetime	swath_coverage_percentage	no_data	cloud_shadows	vegetation	not_vegetated	water	cloud_medium_probability	cloud_high_probability	thin_cirrus	snow
32	S2A_30TYN_20200101_0_L2A	2020-01-01	30TYN	57.50	sentinel-2a	051	S2A_MSIL2A_20200101T105441_N0213_R051_T30TYN_2...	2020-01-01T10:59:11Z	100.0	0.0	0.80	0.85	1.97	7.58	0.15	0.62	0.01	40.92
31	S2B_30TYN_20200106_0_L2A	2020-01-06	30TYN	57.40	sentinel-2b	051	S2B_MSIL2A_20200106T105339_N0213_R051_T30TYN_2...	2020-01-06T10:59:11Z	100.0	0.0	1.06	0.93	2.48	7.29	0.18	0.74	0.00	40.62
30	S2B_30TYN_20200116_0_L2A	2020-01-16	30TYN	56.71	sentinel-2b	051	S2B_MSIL2A_20200116T105309_N0213_R051_T30TYN_2...	2020-01-16T10:59:10Z	100.0	0.0	1.39	1.03	5.02	6.10	0.17	0.98	0.00	40.75
29	S2A_30TYN_20200131_0_L2A	2020-01-31	30TYN	44.29	sentinel-2a	051	S2A_MSIL2A_20200131T105251_N0213_R051_T30TYN_2...	2020-01-31T10:59:09Z	100.0	0.0	0.14	0.36	0.33	4.16	0.09	0.12	0.00	55.36
28	S2B_30TYN_20200205_0_L2A	2020-02-05	30TYN	46.67	sentinel-2b	051	S2B_MSIL2A_20200205T105129_N0214_R051_T30TYN_2...	2020-02-05T10:59:10Z	100.0	0.0	1.02	1.27	2.69	3.77	0.28	0.65	0.00	51.38
27	S2A_30TYN_20200210_0_L2A	2020-02-10	30TYN	46.38	sentinel-2a	051	S2A_MSIL2A_20200210T105201_N0214_R051_T30TYN_2...	2020-02-10T10:59:09Z	100.0	0.0	1.30	1.55	4.72	3.06	0.05	0.53	0.00	51.74
26	S2B_30TYN_20200215_0_L2A	2020-02-15	30TYN	44.83	sentinel-2b	051	S2B_MSIL2A_20200215T105029_N0214_R051_T30TYN_2...	2020-02-15T10:59:12Z	100.0	0.0	1.47	1.72	5.97	2.42	0.28	0.93	0.00	52.49
25	S2A_30TYN_20200220_0_L2A	2020-02-20	30TYN	43.61	sentinel-2a	051	S2A_MSIL2A_20200220T105051_N0214_R051_T30TYN_2...	2020-02-20T10:59:11Z	100.0	0.0	1.58	2.65	7.60	1.83	0.27	1.00	0.00	53.54
24	S2A_30TYN_20200301_0_L2A	2020-03-01	30TYN	0.15	sentinel-2a	051	S2A_MSIL2A_20200301T105021_N0214_R051_T30TYN_2...	2020-03-01T10:59:12Z	100.0	0.0	0.00	0.00	0.14	0.00	4.42	6.33	0.00	89.10
23	S2A_30TYN_20200311_0_L2A	2020-03-11	30TYN	20.14	sentinel-2a	051	S2A_MSIL2A_20200311T105021_N0214_R051_T30TYN_2...	2020-03-11T10:59:12Z	100.0	0.0	0.48	0.91	0.48	0.66	0.16	0.10	0.00	79.12
22	S2A_30TYN_20200321_0_L2A	2020-03-21	30TYN	32.57	sentinel-2a	051	S2A_MSIL2A_20200321T105021_N0214_R051_T30TYN_2...	2020-03-21T10:59:13Z	100.0	0.0	0.69	2.08	13.17	0.35	0.96	0.57	0.00	65.21
21	S2A_30TYN_20200410_0_L2A	2020-04-10	30TYN	24.57	sentinel-2a	051	S2A_MSIL2A_20200410T105031_N0214_R051_T30TYN_2...	2020-04-10T10:59:15Z	100.0	0.0	1.53	6.33	8.60	0.50	1.63	9.39	0.00	62.88
20	S2A_30TYN_20200520_0_L2A	2020-05-20	30TYN	53.65	sentinel-2a	051	S2A_MSIL2A_20200520T105031_N0214_R051_T30TYN_2...	2020-05-20T10:59:22Z	100.0	0.0	0.04	32.74	16.87	0.16	0.82	1.63	0.00	43.86
19	S2A_30TYN_20200530_0_L2A	2020-05-30	30TYN	58.93	sentinel-2a	051	S2A_MSIL2A_20200530T105031_N0214_R051_T30TYN_2...	2020-05-30T10:59:22Z	100.0	0.0	1.28	37.27	16.95	0.44	1.22	4.56	0.00	34.01
18	S2B_30TYN_20200624_0_L2A	2020-06-24	30TYN	68.65	sentinel-2b	051	S2B_MSIL2A_20200624T104629_N0214_R051_T30TYN_2...	2020-06-24T10:59:19Z	100.0	0.0	0.74	46.94	17.59	0.13	1.62	4.27	0.00	24.72
17	S2B_30TYN_20200704_0_L2A	2020-07-04	30TYN	78.03	sentinel-2b	051	S2B_MSIL2A_20200704T104619_N0214_R051_T30TYN_2...	2020-07-04T10:59:18Z	100.0	0.0	0.27	51.08	22.21	0.04	2.49	3.78	0.00	15.43
16	S2A_30TYN_20200709_0_L2A	2020-07-09	30TYN	71.78	sentinel-2a	051	S2A_MSIL2A_20200709T105031_N0214_R051_T30TYN_2...	2020-07-09T10:59:20Z	100.0	0.0	2.89	46.26	19.83	0.20	4.11	9.80	0.00	11.42
15	S2B_30TYN_20200714_0_L2A	2020-07-14	30TYN	80.79	sentinel-2b	051	S2B_MSIL2A_20200714T104619_N0214_R051_T30TYN_2...	2020-07-14T10:59:18Z	100.0	0.0	0.47	51.64	23.57	0.02	4.04	5.64	0.00	9.06
14	S2A_30TYN_20200719_0_L2A	2020-07-19	30TYN	83.65	sentinel-2a	051	S2A_MSIL2A_20200719T105031_N0214_R051_T30TYN_2...	2020-07-19T10:59:21Z	100.0	0.0	0.62	51.89	25.35	0.14	3.40	7.23	0.00	5.10
13	S2A_30TYN_20200729_0_L2A	2020-07-29	30TYN	86.59	sentinel-2a	051	S2A_MSIL2A_20200729T105031_N0214_R051_T30TYN_2...	2020-07-29T10:59:22Z	100.0	0.0	0.80	50.98	28.16	0.02	4.23	5.34	0.00	3.04
12	S2B_30TYN_20200803_0_L2A	2020-08-03	30TYN	88.64	sentinel-2b	051	S2B_MSIL2A_20200803T104629_N0214_R051_T30TYN_2...	2020-08-03T10:59:19Z	100.0	0.0	0.69	49.30	29.98	0.02	4.78	4.17	0.00	1.72
11	S2A_30TYN_20200808_0_L2A	2020-08-08	30TYN	82.37	sentinel-2a	051	S2A_MSIL2A_20200808T105031_N0214_R051_T30TYN_2...	2020-08-08T10:59:22Z	100.0	0.0	1.43	42.20	27.85	0.02	7.56	7.13	0.00	1.51
10	S2B_30TYN_20200823_0_L2A	2020-08-23	30TYN	94.14	sentinel-2b	051	S2B_MSIL2A_20200823T104629_N0214_R051_T30TYN_2...	2020-08-23T10:59:20Z	100.0	0.0	1.26	49.93	33.76	0.05	2.31	1.56	0.00	0.73
9	S2B_30TYN_20200902_0_L2A	2020-09-02	30TYN	91.57	sentinel-2b	051	S2B_MSIL2A_20200902T104629_N0214_R051_T30TYN_2...	2020-09-02T10:59:23Z	100.0	0.0	2.29	48.40	29.39	0.08	2.16	3.03	0.00	0.95
8	S2B_30TYN_20200912_0_L2A	2020-09-12	30TYN	81.70	sentinel-2b	051	S2B_MSIL2A_20200912T104629_N0214_R051_T30TYN_2...	2020-09-12T10:59:18Z	100.0	0.0	7.72	35.06	28.64	0.05	4.22	6.24	0.00	0.12
7	S2A_30TYN_20200927_0_L2A	2020-09-27	30TYN	19.97	sentinel-2a	051	S2A_MSIL2A_20200927T105031_N0214_R051_T30TYN_2...	2020-09-27T10:59:22Z	100.0	0.0	0.43	6.86	0.17	0.40	0.52	0.05	0.00	79.03
6	S2B_30TYN_20201012_0_L2A	2020-10-12	30TYN	26.43	sentinel-2b	051	S2B_MSIL2A_20201012T104909_N0214_R051_T30TYN_2...	2020-10-12T10:59:20Z	100.0	0.0	1.58	6.88	0.70	1.15	0.77	9.60	0.00	61.62
5	S2A_30TYN_20201017_0_L2A	2020-10-17	30TYN	40.49	sentinel-2a	051	S2A_MSIL2A_20201017T105041_N0214_R051_T30TYN_2...	2020-10-17T10:59:22Z	100.0	0.0	2.80	9.13	6.44	0.83	2.37	2.35	0.07	51.92
4	S2B_30TYN_20201101_0_L2A	2020-11-01	30TYN	69.09	sentinel-2b	051	S2B_MSIL2A_20201101T105209_N0214_R051_T30TYN_2...	2020-11-01T10:59:19Z	100.0	0.0	6.71	12.92	22.02	0.85	1.59	2.62	0.85	19.14
3	S2B_30TYN_20201111_0_L2A	2020-11-11	30TYN	75.71	sentinel-2b	051	S2B_MSIL2A_20201111T105259_N0214_R051_T30TYN_2...	2020-11-11T10:59:17Z	100.0	0.0	4.41	14.47	17.84	2.60	0.41	1.37	0.00	18.10
2	S2B_30TYN_20201121_0_L2A	2020-11-21	30TYN	78.88	sentinel-2b	051	S2B_MSIL2A_20201121T105349_N0214_R051_T30TYN_2...	2020-11-21T10:59:17Z	100.0	0.0	4.08	11.20	19.91	3.74	4.06	2.80	0.00	10.18
1	S2A_30TYN_20201216_0_L2A	2020-12-16	30TYN	46.80	sentinel-2a	051	S2A_MSIL2A_20201216T105441_N0214_R051_T30TYN_2...	2020-12-16T10:59:14Z	100.0	0.0	0.40	0.16	0.24	5.98	0.33	0.15	0.51	51.81
0	S2A_30TYN_20201226_0_L2A	2020-12-26	30TYN	52.51	sentinel-2a	051	S2A_MSIL2A_20201226T105451_N0214_R051_T30TYN_2...	2020-12-26T10:59:16Z	100.0	0.0	0.09	0.11	0.47	7.34	2.80	0.57	0.03	44.00

4 - Specify bands

Only selecting blue, green, and red bands from S2

res_S2.output_bands = ["B02","B03","B04"]

5 - Filter search results

While we initially filtered the search results by 10% or less on cloud coverage, we may want to be more selective. We can then set a higher threshold for our monthly images, such as limiting some clouds to 5% or less as shown below.

res_S2.dataframe = res_S2.dataframe[(res_S2.dataframe["cloud_medium_probability"] < 5) & (res_S2.dataframe["cloud_shadows"] < 5)]
res_S2.dataframe

	id	date	tile	valid_pixel_percentage	platform	relative_orbit_number	product_id	datetime	swath_coverage_percentage	no_data	cloud_shadows	vegetation	not_vegetated	water	cloud_medium_probability	cloud_high_probability	thin_cirrus	snow
32	S2A_30TYN_20200101_0_L2A	2020-01-01	30TYN	57.50	sentinel-2a	051	S2A_MSIL2A_20200101T105441_N0213_R051_T30TYN_2...	2020-01-01T10:59:11Z	100.0	0.0	0.80	0.85	1.97	7.58	0.15	0.62	0.01	40.92
31	S2B_30TYN_20200106_0_L2A	2020-01-06	30TYN	57.40	sentinel-2b	051	S2B_MSIL2A_20200106T105339_N0213_R051_T30TYN_2...	2020-01-06T10:59:11Z	100.0	0.0	1.06	0.93	2.48	7.29	0.18	0.74	0.00	40.62
30	S2B_30TYN_20200116_0_L2A	2020-01-16	30TYN	56.71	sentinel-2b	051	S2B_MSIL2A_20200116T105309_N0213_R051_T30TYN_2...	2020-01-16T10:59:10Z	100.0	0.0	1.39	1.03	5.02	6.10	0.17	0.98	0.00	40.75
29	S2A_30TYN_20200131_0_L2A	2020-01-31	30TYN	44.29	sentinel-2a	051	S2A_MSIL2A_20200131T105251_N0213_R051_T30TYN_2...	2020-01-31T10:59:09Z	100.0	0.0	0.14	0.36	0.33	4.16	0.09	0.12	0.00	55.36
28	S2B_30TYN_20200205_0_L2A	2020-02-05	30TYN	46.67	sentinel-2b	051	S2B_MSIL2A_20200205T105129_N0214_R051_T30TYN_2...	2020-02-05T10:59:10Z	100.0	0.0	1.02	1.27	2.69	3.77	0.28	0.65	0.00	51.38
27	S2A_30TYN_20200210_0_L2A	2020-02-10	30TYN	46.38	sentinel-2a	051	S2A_MSIL2A_20200210T105201_N0214_R051_T30TYN_2...	2020-02-10T10:59:09Z	100.0	0.0	1.30	1.55	4.72	3.06	0.05	0.53	0.00	51.74
26	S2B_30TYN_20200215_0_L2A	2020-02-15	30TYN	44.83	sentinel-2b	051	S2B_MSIL2A_20200215T105029_N0214_R051_T30TYN_2...	2020-02-15T10:59:12Z	100.0	0.0	1.47	1.72	5.97	2.42	0.28	0.93	0.00	52.49
25	S2A_30TYN_20200220_0_L2A	2020-02-20	30TYN	43.61	sentinel-2a	051	S2A_MSIL2A_20200220T105051_N0214_R051_T30TYN_2...	2020-02-20T10:59:11Z	100.0	0.0	1.58	2.65	7.60	1.83	0.27	1.00	0.00	53.54
24	S2A_30TYN_20200301_0_L2A	2020-03-01	30TYN	0.15	sentinel-2a	051	S2A_MSIL2A_20200301T105021_N0214_R051_T30TYN_2...	2020-03-01T10:59:12Z	100.0	0.0	0.00	0.00	0.14	0.00	4.42	6.33	0.00	89.10
23	S2A_30TYN_20200311_0_L2A	2020-03-11	30TYN	20.14	sentinel-2a	051	S2A_MSIL2A_20200311T105021_N0214_R051_T30TYN_2...	2020-03-11T10:59:12Z	100.0	0.0	0.48	0.91	0.48	0.66	0.16	0.10	0.00	79.12
22	S2A_30TYN_20200321_0_L2A	2020-03-21	30TYN	32.57	sentinel-2a	051	S2A_MSIL2A_20200321T105021_N0214_R051_T30TYN_2...	2020-03-21T10:59:13Z	100.0	0.0	0.69	2.08	13.17	0.35	0.96	0.57	0.00	65.21
21	S2A_30TYN_20200410_0_L2A	2020-04-10	30TYN	24.57	sentinel-2a	051	S2A_MSIL2A_20200410T105031_N0214_R051_T30TYN_2...	2020-04-10T10:59:15Z	100.0	0.0	1.53	6.33	8.60	0.50	1.63	9.39	0.00	62.88
20	S2A_30TYN_20200520_0_L2A	2020-05-20	30TYN	53.65	sentinel-2a	051	S2A_MSIL2A_20200520T105031_N0214_R051_T30TYN_2...	2020-05-20T10:59:22Z	100.0	0.0	0.04	32.74	16.87	0.16	0.82	1.63	0.00	43.86
19	S2A_30TYN_20200530_0_L2A	2020-05-30	30TYN	58.93	sentinel-2a	051	S2A_MSIL2A_20200530T105031_N0214_R051_T30TYN_2...	2020-05-30T10:59:22Z	100.0	0.0	1.28	37.27	16.95	0.44	1.22	4.56	0.00	34.01
18	S2B_30TYN_20200624_0_L2A	2020-06-24	30TYN	68.65	sentinel-2b	051	S2B_MSIL2A_20200624T104629_N0214_R051_T30TYN_2...	2020-06-24T10:59:19Z	100.0	0.0	0.74	46.94	17.59	0.13	1.62	4.27	0.00	24.72
17	S2B_30TYN_20200704_0_L2A	2020-07-04	30TYN	78.03	sentinel-2b	051	S2B_MSIL2A_20200704T104619_N0214_R051_T30TYN_2...	2020-07-04T10:59:18Z	100.0	0.0	0.27	51.08	22.21	0.04	2.49	3.78	0.00	15.43
16	S2A_30TYN_20200709_0_L2A	2020-07-09	30TYN	71.78	sentinel-2a	051	S2A_MSIL2A_20200709T105031_N0214_R051_T30TYN_2...	2020-07-09T10:59:20Z	100.0	0.0	2.89	46.26	19.83	0.20	4.11	9.80	0.00	11.42
15	S2B_30TYN_20200714_0_L2A	2020-07-14	30TYN	80.79	sentinel-2b	051	S2B_MSIL2A_20200714T104619_N0214_R051_T30TYN_2...	2020-07-14T10:59:18Z	100.0	0.0	0.47	51.64	23.57	0.02	4.04	5.64	0.00	9.06
14	S2A_30TYN_20200719_0_L2A	2020-07-19	30TYN	83.65	sentinel-2a	051	S2A_MSIL2A_20200719T105031_N0214_R051_T30TYN_2...	2020-07-19T10:59:21Z	100.0	0.0	0.62	51.89	25.35	0.14	3.40	7.23	0.00	5.10
13	S2A_30TYN_20200729_0_L2A	2020-07-29	30TYN	86.59	sentinel-2a	051	S2A_MSIL2A_20200729T105031_N0214_R051_T30TYN_2...	2020-07-29T10:59:22Z	100.0	0.0	0.80	50.98	28.16	0.02	4.23	5.34	0.00	3.04
12	S2B_30TYN_20200803_0_L2A	2020-08-03	30TYN	88.64	sentinel-2b	051	S2B_MSIL2A_20200803T104629_N0214_R051_T30TYN_2...	2020-08-03T10:59:19Z	100.0	0.0	0.69	49.30	29.98	0.02	4.78	4.17	0.00	1.72
10	S2B_30TYN_20200823_0_L2A	2020-08-23	30TYN	94.14	sentinel-2b	051	S2B_MSIL2A_20200823T104629_N0214_R051_T30TYN_2...	2020-08-23T10:59:20Z	100.0	0.0	1.26	49.93	33.76	0.05	2.31	1.56	0.00	0.73
9	S2B_30TYN_20200902_0_L2A	2020-09-02	30TYN	91.57	sentinel-2b	051	S2B_MSIL2A_20200902T104629_N0214_R051_T30TYN_2...	2020-09-02T10:59:23Z	100.0	0.0	2.29	48.40	29.39	0.08	2.16	3.03	0.00	0.95
7	S2A_30TYN_20200927_0_L2A	2020-09-27	30TYN	19.97	sentinel-2a	051	S2A_MSIL2A_20200927T105031_N0214_R051_T30TYN_2...	2020-09-27T10:59:22Z	100.0	0.0	0.43	6.86	0.17	0.40	0.52	0.05	0.00	79.03
6	S2B_30TYN_20201012_0_L2A	2020-10-12	30TYN	26.43	sentinel-2b	051	S2B_MSIL2A_20201012T104909_N0214_R051_T30TYN_2...	2020-10-12T10:59:20Z	100.0	0.0	1.58	6.88	0.70	1.15	0.77	9.60	0.00	61.62
5	S2A_30TYN_20201017_0_L2A	2020-10-17	30TYN	40.49	sentinel-2a	051	S2A_MSIL2A_20201017T105041_N0214_R051_T30TYN_2...	2020-10-17T10:59:22Z	100.0	0.0	2.80	9.13	6.44	0.83	2.37	2.35	0.07	51.92
3	S2B_30TYN_20201111_0_L2A	2020-11-11	30TYN	75.71	sentinel-2b	051	S2B_MSIL2A_20201111T105259_N0214_R051_T30TYN_2...	2020-11-11T10:59:17Z	100.0	0.0	4.41	14.47	17.84	2.60	0.41	1.37	0.00	18.10
2	S2B_30TYN_20201121_0_L2A	2020-11-21	30TYN	78.88	sentinel-2b	051	S2B_MSIL2A_20201121T105349_N0214_R051_T30TYN_2...	2020-11-21T10:59:17Z	100.0	0.0	4.08	11.20	19.91	3.74	4.06	2.80	0.00	10.18
1	S2A_30TYN_20201216_0_L2A	2020-12-16	30TYN	46.80	sentinel-2a	051	S2A_MSIL2A_20201216T105441_N0214_R051_T30TYN_2...	2020-12-16T10:59:14Z	100.0	0.0	0.40	0.16	0.24	5.98	0.33	0.15	0.51	51.81
0	S2A_30TYN_20201226_0_L2A	2020-12-26	30TYN	52.51	sentinel-2a	051	S2A_MSIL2A_20201226T105451_N0214_R051_T30TYN_2...	2020-12-26T10:59:16Z	100.0	0.0	0.09	0.11	0.47	7.34	2.80	0.57	0.03	44.00

6 - Select one image per month

Here we use Pandas and its “groupby” function to select the first available image for each month. The frequency, “freq”, can be changed to a large number of time frequencies, called offset aliases. Among them are, daily (‘D’), weekly (‘W’), monthly (‘M’), quarterly (‘Q’), twice monthly (‘SM’) and yearly (‘A’ or ‘Y’). A full list can be found here.

Custom frequencies can be also made and applied using the general pd.Grouper function and/or pd.DateOffset and pd.cut.

# Clone the search result so as to not need to re-run the search if our manipulation doesn't work as intended
new_S2 = res_S2
# Set the Dataframe index as the "date" column, in order to apply the grouper function
new_S2.dataframe.set_index('date', inplace=True)
# Group search result by taking only the first image of the month
new_S2.dataframe = new_S2.dataframe.groupby(pd.Grouper(freq='M')).first()
new_S2.dataframe

	id	tile	valid_pixel_percentage	platform	relative_orbit_number	product_id	datetime	swath_coverage_percentage	no_data	cloud_shadows	vegetation	not_vegetated	water	cloud_medium_probability	cloud_high_probability	thin_cirrus	snow
date
2020-01-31	S2A_30TYN_20200101_0_L2A	30TYN	57.50	sentinel-2a	051	S2A_MSIL2A_20200101T105441_N0213_R051_T30TYN_2...	2020-01-01T10:59:11Z	100.0	0.0	0.80	0.85	1.97	7.58	0.15	0.62	0.01	40.92
2020-02-29	S2B_30TYN_20200205_0_L2A	30TYN	46.67	sentinel-2b	051	S2B_MSIL2A_20200205T105129_N0214_R051_T30TYN_2...	2020-02-05T10:59:10Z	100.0	0.0	1.02	1.27	2.69	3.77	0.28	0.65	0.00	51.38
2020-03-31	S2A_30TYN_20200301_0_L2A	30TYN	0.15	sentinel-2a	051	S2A_MSIL2A_20200301T105021_N0214_R051_T30TYN_2...	2020-03-01T10:59:12Z	100.0	0.0	0.00	0.00	0.14	0.00	4.42	6.33	0.00	89.10
2020-04-30	S2A_30TYN_20200410_0_L2A	30TYN	24.57	sentinel-2a	051	S2A_MSIL2A_20200410T105031_N0214_R051_T30TYN_2...	2020-04-10T10:59:15Z	100.0	0.0	1.53	6.33	8.60	0.50	1.63	9.39	0.00	62.88
2020-05-31	S2A_30TYN_20200520_0_L2A	30TYN	53.65	sentinel-2a	051	S2A_MSIL2A_20200520T105031_N0214_R051_T30TYN_2...	2020-05-20T10:59:22Z	100.0	0.0	0.04	32.74	16.87	0.16	0.82	1.63	0.00	43.86
2020-06-30	S2B_30TYN_20200624_0_L2A	30TYN	68.65	sentinel-2b	051	S2B_MSIL2A_20200624T104629_N0214_R051_T30TYN_2...	2020-06-24T10:59:19Z	100.0	0.0	0.74	46.94	17.59	0.13	1.62	4.27	0.00	24.72
2020-07-31	S2B_30TYN_20200704_0_L2A	30TYN	78.03	sentinel-2b	051	S2B_MSIL2A_20200704T104619_N0214_R051_T30TYN_2...	2020-07-04T10:59:18Z	100.0	0.0	0.27	51.08	22.21	0.04	2.49	3.78	0.00	15.43
2020-08-31	S2B_30TYN_20200803_0_L2A	30TYN	88.64	sentinel-2b	051	S2B_MSIL2A_20200803T104629_N0214_R051_T30TYN_2...	2020-08-03T10:59:19Z	100.0	0.0	0.69	49.30	29.98	0.02	4.78	4.17	0.00	1.72
2020-09-30	S2B_30TYN_20200902_0_L2A	30TYN	91.57	sentinel-2b	051	S2B_MSIL2A_20200902T104629_N0214_R051_T30TYN_2...	2020-09-02T10:59:23Z	100.0	0.0	2.29	48.40	29.39	0.08	2.16	3.03	0.00	0.95
2020-10-31	S2B_30TYN_20201012_0_L2A	30TYN	26.43	sentinel-2b	051	S2B_MSIL2A_20201012T104909_N0214_R051_T30TYN_2...	2020-10-12T10:59:20Z	100.0	0.0	1.58	6.88	0.70	1.15	0.77	9.60	0.00	61.62
2020-11-30	S2B_30TYN_20201111_0_L2A	30TYN	75.71	sentinel-2b	051	S2B_MSIL2A_20201111T105259_N0214_R051_T30TYN_2...	2020-11-11T10:59:17Z	100.0	0.0	4.41	14.47	17.84	2.60	0.41	1.37	0.00	18.10
2020-12-31	S2A_30TYN_20201216_0_L2A	30TYN	46.80	sentinel-2a	051	S2A_MSIL2A_20201216T105441_N0214_R051_T30TYN_2...	2020-12-16T10:59:14Z	100.0	0.0	0.40	0.16	0.24	5.98	0.33	0.15	0.51	51.81

7 - Obtain S2 data through Fuse function

We pass the filtered S2 search result object to the “fuse” function in order to download the organize the S2 result

fusion = client.fuse(
    catalogs_list=[new_S2],
    additional_info={"Info": "You can put any additional information, such as custom non-raster or non-vector data, in this parameter"}
    )
fusion.dataset

2022-11-28 10:14:08,114 INFO spacesense.core : created everything

<xarray.Dataset>
Dimensions:  (time: 12, y: 651, x: 1014)
Coordinates:
  * time     (time) datetime64[ns] 2020-01-01 2020-02-05 ... 2020-12-16
  * y        (y) float32 42.74 42.74 42.74 42.74 ... 42.68 42.68 42.68 42.68
  * x        (x) float64 -0.07173 -0.07164 -0.07155 ... 0.01909 0.01918 0.01927
Data variables:
    S2_B02   (time, y, x) float32 0.0 0.0 0.0 0.0 0.0 ... 0.0 0.668 0.6718 0.0
    S2_B03   (time, y, x) float32 0.0 0.0 0.0 0.0 0.0 ... 0.0 0.692 0.6976 0.0
    S2_B04   (time, y, x) float32 0.0 0.0 0.0 0.0 0.0 ... 0.0 0.6932 0.6968 0.0
Attributes:
    crs:              +init=epsg:4326
    transform:        [ 8.98360017e-05  0.00000000e+00 -7.17789654e-02  0.000...
    res:              [8.98360017e-05 9.04414549e-05]
    ulx, uly:         [-0.07177897 42.73801908]
    s2_data_lineage:  {"Data origin": "S3 bucket (ARN=arn:aws:s3:::sentinel-c...
    additional_info:  {'Info': 'You can put any additional information, such ...

xarray.Dataset

• Dimensions:
  • time: 12
  • y: 651
  • x: 1014
• Coordinates: (3)
  • time
    (time)
    datetime64[ns]
    2020-01-01 ... 2020-12-16

    array(['2020-01-01T00:00:00.000000000', '2020-02-05T00:00:00.000000000',
           '2020-03-01T00:00:00.000000000', '2020-04-10T00:00:00.000000000',
           '2020-05-20T00:00:00.000000000', '2020-06-24T00:00:00.000000000',
           '2020-07-04T00:00:00.000000000', '2020-08-03T00:00:00.000000000',
           '2020-09-02T00:00:00.000000000', '2020-10-12T00:00:00.000000000',
           '2020-11-11T00:00:00.000000000', '2020-12-16T00:00:00.000000000'],
          dtype='datetime64[ns]')

  • y
    (y)
    float32
    42.74 42.74 42.74 ... 42.68 42.68

    _FillValue :

    nan

    array([42.737972, 42.737885, 42.737793, ..., 42.679367, 42.679276, 42.679188],
          dtype=float32)

  • x
    (x)
    float64
    -0.07173 -0.07164 ... 0.01927

    _FillValue :

    nan

    array([-0.071734, -0.071644, -0.071554, ...,  0.01909 ,  0.01918 ,  0.01927 ])

• Data variables: (3)
  • S2_B02
    (time, y, x)
    float32
    0.0 0.0 0.0 ... 0.668 0.6718 0.0

    _FillValue :

    nan

    transform :

    [ 8.98360017e-05 0.00000000e+00 -7.17789654e-02 0.00000000e+00 -9.04414549e-05 4.27380191e+01]

    crs :

    +init=epsg:4326

    descriptions :

    S2_B02

    AREA_OR_POINT :

    Area

    color_description :

    BLUE

    band_wavelength :

    490 nm

    scene_id :

    {"2020-01-01": "S2A_30TYN_20200101_0_L2A", "2020-02-05": "S2B_30TYN_20200205_0_L2A", "2020-03-01": "S2A_30TYN_20200301_0_L2A", "2020-04-10": "S2A_30TYN_20200410_0_L2A", "2020-05-20": "S2A_30TYN_20200520_0_L2A", "2020-06-24": "S2B_30TYN_20200624_0_L2A", "2020-07-04": "S2B_30TYN_20200704_0_L2A", "2020-08-03": "S2B_30TYN_20200803_0_L2A", "2020-09-02": "S2B_30TYN_20200902_0_L2A", "2020-10-12": "S2B_30TYN_20201012_0_L2A", "2020-11-11": "S2B_30TYN_20201111_0_L2A", "2020-12-16": "S2A_30TYN_20201216_0_L2A"}

    scene_classification :

    {'2020-01-01': '{"unclassified": 1.29, "saturated_or_defective": 0.0, "cloud_shadows": 0.8, "snow": 40.92, "water": 7.58, "vegetation": 0.85, "no_data": 0.0, "cloud_medium_probability": 0.15, "cloud_high_probability": 0.62, "thin_cirrus": 0.01, "dark_area_pixels": 45.82, "not_vegetated": 1.97}', '2020-02-05': '{"saturated_or_defective": 0.0, "vegetation": 1.27, "water": 3.77, "dark_area_pixels": 36.82, "snow": 51.38, "cloud_medium_probability": 0.28, "unclassified": 2.12, "not_vegetated": 2.69, "cloud_shadows": 1.02, "no_data": 0.0, "thin_cirrus": 0.0, "cloud_high_probability": 0.65}', '2020-03-01': '{"snow": 89.1, "dark_area_pixels": 0.01, "water": 0.0, "cloud_shadows": 0.0, "no_data": 0.0, "not_vegetated": 0.14, "vegetation": 0.0, "unclassified": 0.0, "cloud_high_probability": 6.33, "cloud_medium_probability": 4.42, "saturated_or_defective": 0.0, "thin_cirrus": 0.0}', '2020-04-10': '{"unclassified": 4.64, "saturated_or_defective": 0.0, "thin_cirrus": 0.0, "no_data": 0.0, "not_vegetated": 8.6, "snow": 62.88, "water": 0.5, "cloud_medium_probability": 1.63, "cloud_high_probability": 9.39, "vegetation": 6.33, "cloud_shadows": 1.53, "dark_area_pixels": 4.5}', '2020-05-20': '{"snow": 43.86, "cloud_medium_probability": 0.82, "unclassified": 2.34, "vegetation": 32.74, "no_data": 0.0, "not_vegetated": 16.87, "water": 0.16, "thin_cirrus": 0.0, "dark_area_pixels": 1.55, "saturated_or_defective": 0.0, "cloud_high_probability": 1.63, "cloud_shadows": 0.04}', '2020-06-24': '{"not_vegetated": 17.59, "cloud_medium_probability": 1.62, "saturated_or_defective": 0.0, "cloud_high_probability": 4.27, "vegetation": 46.94, "thin_cirrus": 0.0, "no_data": 0.0, "dark_area_pixels": 1.53, "water": 0.13, "unclassified": 2.48, "snow": 24.72, "cloud_shadows": 0.74}', '2020-07-04': '{"cloud_shadows": 0.27, "water": 0.04, "dark_area_pixels": 2.3, "unclassified": 2.39, "cloud_high_probability": 3.78, "cloud_medium_probability": 2.49, "thin_cirrus": 0.0, "vegetation": 51.08, "no_data": 0.0, "snow": 15.43, "saturated_or_defective": 0.0, "not_vegetated": 22.21}', '2020-08-03': '{"cloud_high_probability": 4.17, "vegetation": 49.3, "saturated_or_defective": 0.0, "no_data": 0.0, "dark_area_pixels": 4.98, "not_vegetated": 29.98, "unclassified": 4.36, "water": 0.02, "snow": 1.72, "cloud_shadows": 0.69, "cloud_medium_probability": 4.78, "thin_cirrus": 0.0}', '2020-09-02': '{"cloud_high_probability": 3.03, "water": 0.08, "cloud_shadows": 2.29, "unclassified": 3.64, "thin_cirrus": 0.0, "not_vegetated": 29.39, "vegetation": 48.4, "saturated_or_defective": 0.0, "cloud_medium_probability": 2.16, "no_data": 0.0, "snow": 0.95, "dark_area_pixels": 10.06}', '2020-10-12': '{"unclassified": 2.16, "cloud_shadows": 1.58, "water": 1.15, "not_vegetated": 0.7, "saturated_or_defective": 0.0, "snow": 61.62, "thin_cirrus": 0.0, "cloud_high_probability": 9.6, "dark_area_pixels": 15.54, "no_data": 0.0, "cloud_medium_probability": 0.77, "vegetation": 6.88}', '2020-11-11': '{"saturated_or_defective": 0.0, "cloud_shadows": 4.41, "cloud_medium_probability": 0.41, "not_vegetated": 17.84, "unclassified": 3.24, "snow": 18.1, "no_data": 0.0, "thin_cirrus": 0.0, "dark_area_pixels": 37.55, "water": 2.6, "cloud_high_probability": 1.37, "vegetation": 14.47}', '2020-12-16': '{"water": 5.98, "dark_area_pixels": 38.86, "cloud_medium_probability": 0.33, "unclassified": 1.56, "cloud_high_probability": 0.15, "cloud_shadows": 0.4, "saturated_or_defective": 0.0, "snow": 51.81, "no_data": 0.0, "vegetation": 0.16, "not_vegetated": 0.24, "thin_cirrus": 0.51}'}

    array([[[0.    , 0.    , 0.    , ..., 0.    , 0.    , 0.    ],
            [0.    , 0.9408, 0.9785, ..., 0.5464, 0.    , 0.    ],
            [0.    , 0.9289, 1.0696, ..., 0.5448, 0.5492, 0.5492],
            ...,
            [1.1184, 0.9967, 0.9967, ..., 0.5796, 0.6148, 0.    ],
            [1.1648, 1.0048, 1.0048, ..., 0.674 , 0.6784, 0.    ],
            [1.0792, 0.9681, 0.9681, ..., 0.682 , 0.684 , 0.    ]],
    
           [[0.    , 0.    , 0.    , ..., 0.    , 0.    , 0.    ],
            [0.    , 0.9663, 0.9832, ..., 0.5555, 0.    , 0.    ],
            [0.    , 0.8656, 0.9664, ..., 0.5561, 0.5556, 0.5556],
            ...,
            [0.9039, 0.8248, 0.8248, ..., 0.566 , 0.4708, 0.    ],
            [0.9608, 0.8768, 0.8768, ..., 0.6343, 0.6555, 0.    ],
            [0.9352, 0.8544, 0.8544, ..., 0.6683, 0.6739, 0.    ]],
    
           [[0.    , 0.    , 0.    , ..., 0.    , 0.    , 0.    ],
            [0.    , 1.1752, 1.1872, ..., 1.4152, 0.    , 0.    ],
            [0.    , 1.1536, 1.1776, ..., 1.416 , 1.416 , 1.416 ],
            ...,
    ...
            [0.4308, 0.4544, 0.4544, ..., 0.0703, 0.0932, 0.    ],
            [0.4688, 0.4728, 0.4728, ..., 0.2008, 0.2202, 0.    ],
            [0.6676, 0.4992, 0.4992, ..., 0.3754, 0.218 , 0.    ]],
    
           [[0.    , 0.    , 0.    , ..., 0.    , 0.    , 0.    ],
            [0.    , 0.0637, 0.0623, ..., 0.1874, 0.    , 0.    ],
            [0.    , 0.0706, 0.0698, ..., 0.2862, 0.3494, 0.3494],
            ...,
            [0.538 , 0.4672, 0.4672, ..., 0.7204, 0.7492, 0.    ],
            [0.4772, 0.4208, 0.4208, ..., 0.728 , 0.7496, 0.    ],
            [0.6624, 0.5292, 0.5292, ..., 0.7364, 0.7464, 0.    ]],
    
           [[0.    , 0.    , 0.    , ..., 0.    , 0.    , 0.    ],
            [0.    , 1.0792, 1.0415, ..., 0.6812, 0.    , 0.    ],
            [0.    , 1.0256, 1.096 , ..., 0.6827, 0.6764, 0.6764],
            ...,
            [1.0919, 1.0472, 1.0472, ..., 0.6532, 0.6697, 0.    ],
            [1.1008, 0.9504, 0.9504, ..., 0.6596, 0.6775, 0.    ],
            [1.036 , 0.8862, 0.8862, ..., 0.668 , 0.6718, 0.    ]]],
          dtype=float32)

  • S2_B03
    (time, y, x)
    float32
    0.0 0.0 0.0 ... 0.692 0.6976 0.0

    _FillValue :

    nan

    transform :

    [ 8.98360017e-05 0.00000000e+00 -7.17789654e-02 0.00000000e+00 -9.04414549e-05 4.27380191e+01]

    crs :

    +init=epsg:4326

    descriptions :

    S2_B03

    AREA_OR_POINT :

    Area

    color_description :

    GREEN

    band_wavelength :

    560 nm

    scene_id :

    {"2020-01-01": "S2A_30TYN_20200101_0_L2A", "2020-02-05": "S2B_30TYN_20200205_0_L2A", "2020-03-01": "S2A_30TYN_20200301_0_L2A", "2020-04-10": "S2A_30TYN_20200410_0_L2A", "2020-05-20": "S2A_30TYN_20200520_0_L2A", "2020-06-24": "S2B_30TYN_20200624_0_L2A", "2020-07-04": "S2B_30TYN_20200704_0_L2A", "2020-08-03": "S2B_30TYN_20200803_0_L2A", "2020-09-02": "S2B_30TYN_20200902_0_L2A", "2020-10-12": "S2B_30TYN_20201012_0_L2A", "2020-11-11": "S2B_30TYN_20201111_0_L2A", "2020-12-16": "S2A_30TYN_20201216_0_L2A"}

    scene_classification :

    {'2020-01-01': '{"unclassified": 1.29, "saturated_or_defective": 0.0, "cloud_shadows": 0.8, "snow": 40.92, "water": 7.58, "vegetation": 0.85, "no_data": 0.0, "cloud_medium_probability": 0.15, "cloud_high_probability": 0.62, "thin_cirrus": 0.01, "dark_area_pixels": 45.82, "not_vegetated": 1.97}', '2020-02-05': '{"saturated_or_defective": 0.0, "vegetation": 1.27, "water": 3.77, "dark_area_pixels": 36.82, "snow": 51.38, "cloud_medium_probability": 0.28, "unclassified": 2.12, "not_vegetated": 2.69, "cloud_shadows": 1.02, "no_data": 0.0, "thin_cirrus": 0.0, "cloud_high_probability": 0.65}', '2020-03-01': '{"snow": 89.1, "dark_area_pixels": 0.01, "water": 0.0, "cloud_shadows": 0.0, "no_data": 0.0, "not_vegetated": 0.14, "vegetation": 0.0, "unclassified": 0.0, "cloud_high_probability": 6.33, "cloud_medium_probability": 4.42, "saturated_or_defective": 0.0, "thin_cirrus": 0.0}', '2020-04-10': '{"unclassified": 4.64, "saturated_or_defective": 0.0, "thin_cirrus": 0.0, "no_data": 0.0, "not_vegetated": 8.6, "snow": 62.88, "water": 0.5, "cloud_medium_probability": 1.63, "cloud_high_probability": 9.39, "vegetation": 6.33, "cloud_shadows": 1.53, "dark_area_pixels": 4.5}', '2020-05-20': '{"snow": 43.86, "cloud_medium_probability": 0.82, "unclassified": 2.34, "vegetation": 32.74, "no_data": 0.0, "not_vegetated": 16.87, "water": 0.16, "thin_cirrus": 0.0, "dark_area_pixels": 1.55, "saturated_or_defective": 0.0, "cloud_high_probability": 1.63, "cloud_shadows": 0.04}', '2020-06-24': '{"not_vegetated": 17.59, "cloud_medium_probability": 1.62, "saturated_or_defective": 0.0, "cloud_high_probability": 4.27, "vegetation": 46.94, "thin_cirrus": 0.0, "no_data": 0.0, "dark_area_pixels": 1.53, "water": 0.13, "unclassified": 2.48, "snow": 24.72, "cloud_shadows": 0.74}', '2020-07-04': '{"cloud_shadows": 0.27, "water": 0.04, "dark_area_pixels": 2.3, "unclassified": 2.39, "cloud_high_probability": 3.78, "cloud_medium_probability": 2.49, "thin_cirrus": 0.0, "vegetation": 51.08, "no_data": 0.0, "snow": 15.43, "saturated_or_defective": 0.0, "not_vegetated": 22.21}', '2020-08-03': '{"cloud_high_probability": 4.17, "vegetation": 49.3, "saturated_or_defective": 0.0, "no_data": 0.0, "dark_area_pixels": 4.98, "not_vegetated": 29.98, "unclassified": 4.36, "water": 0.02, "snow": 1.72, "cloud_shadows": 0.69, "cloud_medium_probability": 4.78, "thin_cirrus": 0.0}', '2020-09-02': '{"cloud_high_probability": 3.03, "water": 0.08, "cloud_shadows": 2.29, "unclassified": 3.64, "thin_cirrus": 0.0, "not_vegetated": 29.39, "vegetation": 48.4, "saturated_or_defective": 0.0, "cloud_medium_probability": 2.16, "no_data": 0.0, "snow": 0.95, "dark_area_pixels": 10.06}', '2020-10-12': '{"unclassified": 2.16, "cloud_shadows": 1.58, "water": 1.15, "not_vegetated": 0.7, "saturated_or_defective": 0.0, "snow": 61.62, "thin_cirrus": 0.0, "cloud_high_probability": 9.6, "dark_area_pixels": 15.54, "no_data": 0.0, "cloud_medium_probability": 0.77, "vegetation": 6.88}', '2020-11-11': '{"saturated_or_defective": 0.0, "cloud_shadows": 4.41, "cloud_medium_probability": 0.41, "not_vegetated": 17.84, "unclassified": 3.24, "snow": 18.1, "no_data": 0.0, "thin_cirrus": 0.0, "dark_area_pixels": 37.55, "water": 2.6, "cloud_high_probability": 1.37, "vegetation": 14.47}', '2020-12-16': '{"water": 5.98, "dark_area_pixels": 38.86, "cloud_medium_probability": 0.33, "unclassified": 1.56, "cloud_high_probability": 0.15, "cloud_shadows": 0.4, "saturated_or_defective": 0.0, "snow": 51.81, "no_data": 0.0, "vegetation": 0.16, "not_vegetated": 0.24, "thin_cirrus": 0.51}'}

    array([[[0.    , 0.    , 0.    , ..., 0.    , 0.    , 0.    ],
            [0.    , 0.9728, 1.0129, ..., 0.4584, 0.    , 0.    ],
            [0.    , 0.9505, 1.0945, ..., 0.4598, 0.4621, 0.4621],
            ...,
            [1.0751, 0.9606, 0.9606, ..., 0.6068, 0.6529, 0.    ],
            [1.1416, 0.9767, 0.9767, ..., 0.6944, 0.7016, 0.    ],
            [1.0761, 0.944 , 0.944 , ..., 0.7036, 0.7051, 0.    ]],
    
           [[0.    , 0.    , 0.    , ..., 0.    , 0.    , 0.    ],
            [0.    , 0.9775, 1.0033, ..., 0.4311, 0.    , 0.    ],
            [0.    , 0.8982, 0.9952, ..., 0.4396, 0.4405, 0.4405],
            ...,
            [0.8855, 0.8032, 0.8032, ..., 0.5648, 0.5096, 0.    ],
            [0.9432, 0.8545, 0.8545, ..., 0.6586, 0.6817, 0.    ],
            [0.932 , 0.8472, 0.8472, ..., 0.6835, 0.7016, 0.    ]],
    
           [[0.    , 0.    , 0.    , ..., 0.    , 0.    , 0.    ],
            [0.    , 1.1976, 1.2176, ..., 1.4504, 0.    , 0.    ],
            [0.    , 1.1832, 1.2032, ..., 1.4512, 1.4512, 1.4512],
            ...,
    ...
            [0.4355, 0.45  , 0.45  , ..., 0.0977, 0.1196, 0.    ],
            [0.484 , 0.4752, 0.4752, ..., 0.2728, 0.2364, 0.    ],
            [0.6952, 0.5331, 0.5331, ..., 0.3484, 0.2852, 0.    ]],
    
           [[0.    , 0.    , 0.    , ..., 0.    , 0.    , 0.    ],
            [0.    , 0.104 , 0.1042, ..., 0.1498, 0.    , 0.    ],
            [0.    , 0.1062, 0.1082, ..., 0.2066, 0.2684, 0.2684],
            ...,
            [0.498 , 0.4284, 0.4284, ..., 0.748 , 0.7676, 0.    ],
            [0.4648, 0.3918, 0.3918, ..., 0.7508, 0.772 , 0.    ],
            [0.6392, 0.5048, 0.5048, ..., 0.7628, 0.7764, 0.    ]],
    
           [[0.    , 0.    , 0.    , ..., 0.    , 0.    , 0.    ],
            [0.    , 1.0936, 1.1047, ..., 0.6464, 0.    , 0.    ],
            [0.    , 1.0449, 1.1336, ..., 0.6408, 0.6369, 0.6369],
            ...,
            [1.0976, 1.0392, 1.0392, ..., 0.6732, 0.69  , 0.    ],
            [1.0784, 0.9192, 0.9192, ..., 0.6808, 0.6997, 0.    ],
            [1.0496, 0.8848, 0.8848, ..., 0.692 , 0.6976, 0.    ]]],
          dtype=float32)

  • S2_B04
    (time, y, x)
    float32
    0.0 0.0 0.0 ... 0.6932 0.6968 0.0

    _FillValue :

    nan

    transform :

    [ 8.98360017e-05 0.00000000e+00 -7.17789654e-02 0.00000000e+00 -9.04414549e-05 4.27380191e+01]

    crs :

    +init=epsg:4326

    descriptions :

    S2_B04

    AREA_OR_POINT :

    Area

    color_description :

    RED

    band_wavelength :

    665 nm

    scene_id :

    {"2020-01-01": "S2A_30TYN_20200101_0_L2A", "2020-02-05": "S2B_30TYN_20200205_0_L2A", "2020-03-01": "S2A_30TYN_20200301_0_L2A", "2020-04-10": "S2A_30TYN_20200410_0_L2A", "2020-05-20": "S2A_30TYN_20200520_0_L2A", "2020-06-24": "S2B_30TYN_20200624_0_L2A", "2020-07-04": "S2B_30TYN_20200704_0_L2A", "2020-08-03": "S2B_30TYN_20200803_0_L2A", "2020-09-02": "S2B_30TYN_20200902_0_L2A", "2020-10-12": "S2B_30TYN_20201012_0_L2A", "2020-11-11": "S2B_30TYN_20201111_0_L2A", "2020-12-16": "S2A_30TYN_20201216_0_L2A"}

    scene_classification :

    {'2020-01-01': '{"unclassified": 1.29, "saturated_or_defective": 0.0, "cloud_shadows": 0.8, "snow": 40.92, "water": 7.58, "vegetation": 0.85, "no_data": 0.0, "cloud_medium_probability": 0.15, "cloud_high_probability": 0.62, "thin_cirrus": 0.01, "dark_area_pixels": 45.82, "not_vegetated": 1.97}', '2020-02-05': '{"saturated_or_defective": 0.0, "vegetation": 1.27, "water": 3.77, "dark_area_pixels": 36.82, "snow": 51.38, "cloud_medium_probability": 0.28, "unclassified": 2.12, "not_vegetated": 2.69, "cloud_shadows": 1.02, "no_data": 0.0, "thin_cirrus": 0.0, "cloud_high_probability": 0.65}', '2020-03-01': '{"snow": 89.1, "dark_area_pixels": 0.01, "water": 0.0, "cloud_shadows": 0.0, "no_data": 0.0, "not_vegetated": 0.14, "vegetation": 0.0, "unclassified": 0.0, "cloud_high_probability": 6.33, "cloud_medium_probability": 4.42, "saturated_or_defective": 0.0, "thin_cirrus": 0.0}', '2020-04-10': '{"unclassified": 4.64, "saturated_or_defective": 0.0, "thin_cirrus": 0.0, "no_data": 0.0, "not_vegetated": 8.6, "snow": 62.88, "water": 0.5, "cloud_medium_probability": 1.63, "cloud_high_probability": 9.39, "vegetation": 6.33, "cloud_shadows": 1.53, "dark_area_pixels": 4.5}', '2020-05-20': '{"snow": 43.86, "cloud_medium_probability": 0.82, "unclassified": 2.34, "vegetation": 32.74, "no_data": 0.0, "not_vegetated": 16.87, "water": 0.16, "thin_cirrus": 0.0, "dark_area_pixels": 1.55, "saturated_or_defective": 0.0, "cloud_high_probability": 1.63, "cloud_shadows": 0.04}', '2020-06-24': '{"not_vegetated": 17.59, "cloud_medium_probability": 1.62, "saturated_or_defective": 0.0, "cloud_high_probability": 4.27, "vegetation": 46.94, "thin_cirrus": 0.0, "no_data": 0.0, "dark_area_pixels": 1.53, "water": 0.13, "unclassified": 2.48, "snow": 24.72, "cloud_shadows": 0.74}', '2020-07-04': '{"cloud_shadows": 0.27, "water": 0.04, "dark_area_pixels": 2.3, "unclassified": 2.39, "cloud_high_probability": 3.78, "cloud_medium_probability": 2.49, "thin_cirrus": 0.0, "vegetation": 51.08, "no_data": 0.0, "snow": 15.43, "saturated_or_defective": 0.0, "not_vegetated": 22.21}', '2020-08-03': '{"cloud_high_probability": 4.17, "vegetation": 49.3, "saturated_or_defective": 0.0, "no_data": 0.0, "dark_area_pixels": 4.98, "not_vegetated": 29.98, "unclassified": 4.36, "water": 0.02, "snow": 1.72, "cloud_shadows": 0.69, "cloud_medium_probability": 4.78, "thin_cirrus": 0.0}', '2020-09-02': '{"cloud_high_probability": 3.03, "water": 0.08, "cloud_shadows": 2.29, "unclassified": 3.64, "thin_cirrus": 0.0, "not_vegetated": 29.39, "vegetation": 48.4, "saturated_or_defective": 0.0, "cloud_medium_probability": 2.16, "no_data": 0.0, "snow": 0.95, "dark_area_pixels": 10.06}', '2020-10-12': '{"unclassified": 2.16, "cloud_shadows": 1.58, "water": 1.15, "not_vegetated": 0.7, "saturated_or_defective": 0.0, "snow": 61.62, "thin_cirrus": 0.0, "cloud_high_probability": 9.6, "dark_area_pixels": 15.54, "no_data": 0.0, "cloud_medium_probability": 0.77, "vegetation": 6.88}', '2020-11-11': '{"saturated_or_defective": 0.0, "cloud_shadows": 4.41, "cloud_medium_probability": 0.41, "not_vegetated": 17.84, "unclassified": 3.24, "snow": 18.1, "no_data": 0.0, "thin_cirrus": 0.0, "dark_area_pixels": 37.55, "water": 2.6, "cloud_high_probability": 1.37, "vegetation": 14.47}', '2020-12-16': '{"water": 5.98, "dark_area_pixels": 38.86, "cloud_medium_probability": 0.33, "unclassified": 1.56, "cloud_high_probability": 0.15, "cloud_shadows": 0.4, "saturated_or_defective": 0.0, "snow": 51.81, "no_data": 0.0, "vegetation": 0.16, "not_vegetated": 0.24, "thin_cirrus": 0.51}'}

    array([[[0.    , 0.    , 0.    , ..., 0.    , 0.    , 0.    ],
            [0.    , 0.984 , 0.9944, ..., 0.3522, 0.    , 0.    ],
            [0.    , 0.9552, 1.1114, ..., 0.3528, 0.3507, 0.3507],
            ...,
            [1.0208, 0.8887, 0.8887, ..., 0.6248, 0.6644, 0.    ],
            [1.0793, 0.9136, 0.9136, ..., 0.692 , 0.7056, 0.    ],
            [1.0216, 0.8839, 0.8839, ..., 0.7132, 0.7072, 0.    ]],
    
           [[0.    , 0.    , 0.    , ..., 0.    , 0.    , 0.    ],
            [0.    , 0.9455, 1.0056, ..., 0.3273, 0.    , 0.    ],
            [0.    , 0.8871, 1.0031, ..., 0.3251, 0.3147, 0.3147],
            ...,
            [0.8456, 0.7595, 0.7595, ..., 0.5656, 0.5352, 0.    ],
            [0.9152, 0.8248, 0.8248, ..., 0.6475, 0.6704, 0.    ],
            [0.9151, 0.8286, 0.8286, ..., 0.6801, 0.7013, 0.    ]],
    
           [[0.    , 0.    , 0.    , ..., 0.    , 0.    , 0.    ],
            [0.    , 1.2472, 1.2728, ..., 1.472 , 0.    , 0.    ],
            [0.    , 1.2376, 1.2624, ..., 1.472 , 1.472 , 1.472 ],
            ...,
    ...
            [0.4328, 0.4517, 0.4517, ..., 0.133 , 0.1502, 0.    ],
            [0.4884, 0.4692, 0.4692, ..., 0.2536, 0.2636, 0.    ],
            [0.6752, 0.5352, 0.5352, ..., 0.373 , 0.2612, 0.    ]],
    
           [[0.    , 0.    , 0.    , ..., 0.    , 0.    , 0.    ],
            [0.    , 0.11  , 0.107 , ..., 0.0867, 0.    , 0.    ],
            [0.    , 0.11  , 0.1118, ..., 0.141 , 0.1776, 0.1776],
            ...,
            [0.4708, 0.3786, 0.3786, ..., 0.742 , 0.7616, 0.    ],
            [0.4252, 0.352 , 0.352 , ..., 0.7464, 0.7656, 0.    ],
            [0.6056, 0.4752, 0.4752, ..., 0.7572, 0.7724, 0.    ]],
    
           [[0.    , 0.    , 0.    , ..., 0.    , 0.    , 0.    ],
            [0.    , 1.0912, 1.0896, ..., 0.582 , 0.    , 0.    ],
            [0.    , 1.0096, 1.1136, ..., 0.5812, 0.5756, 0.5756],
            ...,
            [1.0496, 0.9912, 0.9912, ..., 0.6764, 0.6904, 0.    ],
            [1.0744, 0.8928, 0.8928, ..., 0.686 , 0.7028, 0.    ],
            [0.9944, 0.844 , 0.844 , ..., 0.6932, 0.6968, 0.    ]]],
          dtype=float32)

• Attributes: (6)

  crs :

  +init=epsg:4326

  transform :

  [ 8.98360017e-05 0.00000000e+00 -7.17789654e-02 0.00000000e+00 -9.04414549e-05 4.27380191e+01]

  res :

  [8.98360017e-05 9.04414549e-05]

  ulx, uly :

  [-0.07177897 42.73801908]

  s2_data_lineage :

  {"Data origin": "S3 bucket (ARN=arn:aws:s3:::sentinel-cogs-inventory)"}

  additional_info :

  {'Info': 'You can put any additional information, such as custom non-raster or non-vector data, in this parameter'}

8 - Plot using matplotlib

This code sets up and plots each time in the dataset. Because we had high cloud and swath requirements, only 9 of 12 months have valid images

# Define a function to normalize reflectance from S2 bands
rgb = fusion.plot_rgb(all_dates = True, brightness_factor = 3)

2022-11-28 10:14:08,531 WARNING matplotlib.image : Clipping input data to the valid range for imshow with RGB data ([0..1] for floats or [0..255] for integers).
2022-11-28 10:14:08,566 WARNING matplotlib.image : Clipping input data to the valid range for imshow with RGB data ([0..1] for floats or [0..255] for integers).
2022-11-28 10:14:08,602 WARNING matplotlib.image : Clipping input data to the valid range for imshow with RGB data ([0..1] for floats or [0..255] for integers).
2022-11-28 10:14:08,637 WARNING matplotlib.image : Clipping input data to the valid range for imshow with RGB data ([0..1] for floats or [0..255] for integers).
2022-11-28 10:14:08,671 WARNING matplotlib.image : Clipping input data to the valid range for imshow with RGB data ([0..1] for floats or [0..255] for integers).
2022-11-28 10:14:08,705 WARNING matplotlib.image : Clipping input data to the valid range for imshow with RGB data ([0..1] for floats or [0..255] for integers).
2022-11-28 10:14:08,740 WARNING matplotlib.image : Clipping input data to the valid range for imshow with RGB data ([0..1] for floats or [0..255] for integers).
2022-11-28 10:14:08,778 WARNING matplotlib.image : Clipping input data to the valid range for imshow with RGB data ([0..1] for floats or [0..255] for integers).
2022-11-28 10:14:08,815 WARNING matplotlib.image : Clipping input data to the valid range for imshow with RGB data ([0..1] for floats or [0..255] for integers).
2022-11-28 10:14:08,853 WARNING matplotlib.image : Clipping input data to the valid range for imshow with RGB data ([0..1] for floats or [0..255] for integers).
2022-11-28 10:14:08,890 WARNING matplotlib.image : Clipping input data to the valid range for imshow with RGB data ([0..1] for floats or [0..255] for integers).
2022-11-28 10:14:08,927 WARNING matplotlib.image : Clipping input data to the valid range for imshow with RGB data ([0..1] for floats or [0..255] for integers).