Search ga_s2am_ard_3 whole collection

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud pixels.\n\nFor these ARD products, this value comes from the Fmask algorithm.\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud pixels.\n\nFor these ARD products, this value comes from the Fmask algorithm.\n to (exclusive):

Time when dataset was created (processed) From

Time when dataset was created (processed) to (exclusive)

The raw CRS string as it appears in metadata\n\n(e.g. ‘epsg:32654’)\n:

One of - final|interim|nrt (near real time):

ID of a dataset type:

Ground sampling distance of the sensor’s best resolution band\nin metres; represents the size (or spatial resolution) of one pixel.\n from:

Ground sampling distance of the sensor’s best resolution band\nin metres; represents the size (or spatial resolution) of one pixel.\n to (exclusive):

The azimuth angle of the sun at the moment of acquisition, in degree units measured clockwise from due north\n from:

The azimuth angle of the sun at the moment of acquisition, in degree units measured clockwise from due north\n to (exclusive):

The elevation angle of the sun at the moment of acquisition, in degree units relative to the horizon.\n from:

The elevation angle of the sun at the moment of acquisition, in degree units relative to the horizon.\n to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to the Fmask algorithm\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to the Fmask algorithm\n to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud shadow pixels according to the Fmask algorithm\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud shadow pixels according to the Fmask algorithm\n to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains clear snow pixels according to the Fmask algorithm\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear snow pixels according to the Fmask algorithm\n to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains clear water pixels according to the Fmask algorithm\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear water pixels according to the Fmask algorithm\n to (exclusive):

File format (GeoTiff, NetCDF):

Mean of the absolute values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Mean of the absolute values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Mean of the absolute values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Mean of the absolute values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Mean of the absolute values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Mean of the absolute values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Absolute value of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Absolute value of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Absolute value of the total GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Absolute value of the total GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Absolute value of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Absolute value of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Circular error probable (90%) of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Circular error probable (90%) of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Mean of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Mean of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Mean of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Mean of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Mean of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Mean of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Standard Deviation of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Standard Deviation of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Mean of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Mean of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Mean of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Mean of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Mean of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Mean of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Standard Deviation of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Standard Deviation of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Dataset UUID:

User who indexed the dataset:

When dataset was indexed:

Label:

Latitude range from:

Latitude range to (exclusive):

Longitude range from:

Longitude range to (exclusive):

Full metadata document:

Metadata type name of dataset:

ID of a metadata type:

Spatial reference code from the provider.\nFor Sentinel it is MGRS code.\n:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to s3cloudless\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to s3cloudless\n to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud land pixels according to s3cloudless\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud land pixels according to s3cloudless\n to (exclusive):

Unique identifier for a datastrip relative to a given Datatake.\n\n(e.g. ‘S2A_OPER_MSI_L1C_DS_SGS__20161214T040601_S20161214T005840_N02.04’)\n:

ESA product URI, with the '.SAFE' ending removed.\n\n(e.g. 'S2A_MSIL1C_20220303T000731_N0400_R073_T56LNM_20220303T012845')\n:

Granule ID according to the ESA naming convention\n\n(e.g. ‘S2A_OPER_MSI_L1C_TL_SGS__20161214T040601_A007721_T53KRB_N02.04’)\n:

Acquisition time range From

Acquisition time range to (exclusive)

Dataset URI:

Add field

First 100 results (query limit)

Time (local)	Label
2016-03-06 12:04:37	ga_s2am_ard_3-2-1_49JGM_2016-03-06_final.stac-item
2016-04-15 11:55:08	ga_s2am_ard_3-2-1_50KNC_2016-04-15_final.stac-item
2016-04-19 11:37:58	ga_s2am_ard_3-2-1_50HNK_2016-04-19_final.stac-item
2016-05-15 12:02:55	ga_s2am_ard_3-2-1_50JKN_2016-05-15_final.stac-item
2016-05-28 12:14:47	ga_s2am_ard_3-2-1_49JGM_2016-05-28_final.stac-item
2016-08-26 12:13:22	ga_s2am_ard_3-2-1_50KKA_2016-08-26_final.stac-item
2017-09-07 12:02:48	ga_s2am_ard_3-2-1_49KGP_2017-09-07_final.stac-item
2017-11-19 12:13:18	ga_s2am_ard_3-2-1_49KHR_2017-11-19_final.stac-item
2017-12-29 12:13:37	ga_s2am_ard_3-2-1_50KKA_2017-12-29_final.stac-item
2018-02-02 11:24:26	ga_s2am_ard_3-2-1_51HTC_2018-02-02_final.stac-item
2018-02-11 11:50:47	ga_s2am_ard_3-2-1_50JNS_2018-02-11_final.stac-item
2018-02-25 11:27:26	ga_s2am_ard_3-2-1_51HUC_2018-02-25_final.stac-item
2018-04-09 11:40:31	ga_s2am_ard_3-2-1_50KRD_2018-04-09_final.stac-item
2018-04-09 11:40:31	ga_s2am_ard_3-2-1_51KUV_2018-04-09_final.stac-item
2018-04-25 12:02:51	ga_s2am_ard_3-2-1_49JGM_2018-04-25_final.stac-item
2018-05-02 11:53:21	ga_s2am_ard_3-2-1_50JMN_2018-05-02_final.stac-item
2018-05-06 11:32:02	ga_s2am_ard_3-2-1_51KUT_2018-05-06_final.stac-item
2018-06-28 11:45:31	ga_s2am_ard_3-2-1_50JQN_2018-06-28_final.stac-item
2018-10-26 11:46:33	ga_s2am_ard_3-2-1_50HPK_2018-10-26_final.stac-item
2018-11-21 12:05:22	ga_s2am_ard_3-2-1_49JGK_2018-11-21_final.stac-item
2018-12-02 11:32:11	ga_s2am_ard_3-2-1_51KVB_2018-12-02_final.stac-item
2018-12-11 12:05:47	ga_s2am_ard_3-2-1_50JKN_2018-12-11_final.stac-item
2018-12-12 11:32:11	ga_s2am_ard_3-2-1_51KVB_2018-12-12_final.stac-item
2019-01-11 11:36:53	ga_s2am_ard_3-2-1_51HUC_2019-01-11_final.stac-item
2019-04-10 12:05:45	ga_s2am_ard_3-2-1_49JGJ_2019-04-10_final.stac-item
2019-05-17 11:53:14	ga_s2am_ard_3-2-1_50KRC_2019-05-17_final.stac-item
2019-05-28 11:24:22	ga_s2am_ard_3-2-1_51JZN_2019-05-28_final.stac-item
2019-06-20 11:37:10	ga_s2am_ard_3-2-1_50HPH_2019-06-20_final.stac-item
2019-06-30 11:36:47	ga_s2am_ard_3-2-1_51HUD_2019-06-30_final.stac-item
2019-07-03 11:43:23	ga_s2am_ard_3-2-1_51KTT_2019-07-03_final.stac-item
2019-07-06 11:57:11	ga_s2am_ard_3-2-1_50HMH_2019-07-06_final.stac-item
2019-07-09 12:05:49	ga_s2am_ard_3-2-1_49JGJ_2019-07-09_final.stac-item
2019-07-12 12:13:59	ga_s2am_ard_3-2-1_50KKA_2019-07-12_final.stac-item
2019-09-07 12:03:43	ga_s2am_ard_3-2-1_50KKB_2019-09-07_final.stac-item
2019-11-16 12:03:25	ga_s2am_ard_3-2-1_50KMC_2019-11-16_final.stac-item
2019-12-20 11:43:12	ga_s2am_ard_3-2-1_51KTT_2019-12-20_final.stac-item
2020-04-01 11:52:15	ga_s2am_ard_3-2-1_50KQG_2020-04-01_final
2020-04-21 11:53:18	ga_s2am_ard_3-2-1_50KQC_2020-04-21_final.stac-item
2020-05-31 11:52:26	ga_s2am_ard_3-2-1_50KQG_2020-05-31_final
2020-05-31 11:56:14	ga_s2am_ard_3-2-1_50JMM_2020-05-31_final.stac-item
2020-07-06 12:14:46	ga_s2am_ard_3-2-1_49JGN_2020-07-06_final.stac-item
2020-07-16 12:14:03	ga_s2am_ard_3-2-1_49KGR_2020-07-16_final.stac-item
2020-07-23 12:05:43	ga_s2am_ard_3-2-1_50JLP_2020-07-23_final.stac-item
2020-08-02 12:06:01	ga_s2am_ard_3-2-1_50JKN_2020-08-02_final.stac-item
2020-08-12 12:05:18	ga_s2am_ard_3-2-1_50JKR_2020-08-12_final.stac-item
2020-09-08 11:52:24	ga_s2am_ard_3-2-1_50KQG_2020-09-08_final
2020-10-02 11:36:54	ga_s2am_ard_3-2-1_50HQJ_2020-10-02_final.stac-item
2020-10-08 11:56:05	ga_s2am_ard_3-2-1_50JKN_2020-10-08_final.stac-item
2020-10-25 11:43:35	ga_s2am_ard_3-2-1_51KUS_2020-10-25_final.stac-item
2020-11-15 11:16:47	ga_s2am_ard_3-2-1_51HWD_2020-11-15_final.stac-item
2020-11-27 11:53:11	ga_s2am_ard_3-2-1_50KRC_2020-11-27_final.stac-item
2021-01-03 11:42:28	ga_s2am_ard_3-2-1_51KVA_2021-01-03_final.stac-item
2021-01-07 11:24:45	ga_s2am_ard_3-2-1_51JWM_2021-01-07_final.stac-item
2021-04-16 11:57:14	ga_s2am_ard_3-2-1_50HMG_2021-04-16_final
2021-05-03 11:42:11	ga_s2am_ard_3-2-1_51KVB_2021-05-03_final.stac-item
2021-05-23 11:43:01	ga_s2am_ard_3-2-1_51KUU_2021-05-23_final.stac-item
2021-06-02 11:46:13	ga_s2am_ard_3-2-1_50JMM_2021-06-02_final.stac-item
2021-07-02 11:43:02	ga_s2am_ard_3-2-1_51KUU_2021-07-02_final.stac-item
2021-07-21 12:14:45	ga_s2am_ard_3-2-1_49JGN_2021-07-21_final.stac-item
2021-07-28 12:03:44	ga_s2am_ard_3-2-1_50KLB_2021-07-28_final.stac-item
2021-08-01 11:43:21	ga_s2am_ard_3-2-1_51KTT_2021-08-01_final.stac-item
2021-09-20 11:47:27	ga_s2am_ard_3-2-1_50HMG_2021-09-20_final
2021-12-12 11:57:22	ga_s2am_ard_3-2-1_50HLG_2021-12-12_final
2022-01-28 11:43:29	ga_s2am_ard_3-2-1_51KUS_2022-01-28_final.stac-item
2022-02-07 11:46:51	ga_s2am_ard_3-2-1_50HNJ_2022-02-07_final.stac-item
2022-04-01 11:56:32	ga_s2am_ard_3-2-1_50HNK_2022-04-01_final.stac-item
2022-04-02 11:25:59	ga_s2am_ard_3-2-1_51JWG_2022-04-02_final.stac-item
2022-04-05 11:36:28	ga_s2am_ard_3-2-1_50JPL_2022-04-05_final.stac-item
2022-04-18 11:43:33	ga_s2am_ard_3-2-1_51KUS_2022-04-18_final.stac-item
2022-05-08 11:42:32	ga_s2am_ard_3-2-1_51KVA_2022-05-08_final.stac-item
2022-05-15 11:37:02	ga_s2am_ard_3-2-1_51HUC_2022-05-15_final.stac-item
2022-06-07 11:42:25	ga_s2am_ard_3-2-1_51KUB_2022-06-07_final
2022-07-03 12:03:57	ga_s2am_ard_3-2-1_50KKB_2022-07-03_final.stac-item
2022-08-03 11:36:42	ga_s2am_ard_3-2-1_51HTE_2022-08-03_final.stac-item
2022-09-09 11:25:56	ga_s2am_ard_3-2-1_51JWH_2022-09-09_final.stac-item
2022-10-05 11:43:07	ga_s2am_ard_3-2-1_51KUU_2022-10-05_final.stac-item
2022-10-05 11:47:17	ga_s2am_ard_3-2-1_50HMH_2022-10-05_final.stac-item
2022-12-04 11:46:34	ga_s2am_ard_3-2-1_50HPK_2022-12-04_final.stac-item
2022-12-31 11:37:02	ga_s2am_ard_3-2-1_50HQH_2022-12-31_final.stac-item
2023-01-13 11:47:22	ga_s2am_ard_3-2-1_50HMG_2023-01-13_final
2023-01-20 11:34:34	ga_s2am_ard_3-2-1_51JWM_2023-01-20_final.stac-item
2023-01-26 11:53:14	ga_s2am_ard_3-2-1_50KQC_2023-01-26_final.stac-item
2023-02-22 11:43:30	ga_s2am_ard_3-2-1_50KRB_2023-02-22_nrt.stac-item
2023-02-22 11:43:30	ga_s2am_ard_3-2-1_50KRB_2023-02-22_final
2023-02-26 11:26:59	ga_s2am_ard_3-2-1_51HUC_2023-02-26_final
2023-03-01 11:34:13	ga_s2am_ard_3-2-1_51JXN_2023-03-01_final
2023-03-31 11:36:41	ga_s2am_ard_3-2-1_51HUD_2023-03-31_final
2023-04-06 11:53:17	ga_s2am_ard_3-2-1_50KQC_2023-04-06_final
2023-04-26 11:55:56	ga_s2am_ard_3-2-1_50JLN_2023-04-26_final
2023-06-12 11:42:17	ga_s2am_ard_3-2-1_51KVB_2023-06-12_final
2023-06-22 11:42:17	ga_s2am_ard_3-2-1_51KVB_2023-06-22_final
2023-09-10 11:46:53	ga_s2am_ard_3-2-1_50HPJ_2023-09-10_final
2023-11-05 12:05:55	ga_s2am_ard_3-2-1_50JKN_2023-11-05_final
2023-11-15 12:03:25	ga_s2am_ard_3-2-1_50KLC_2023-11-15_final
2024-01-15 11:33:15	ga_s2am_ard_3-2-1_51KUT_2024-01-15_final
2024-02-20 11:53:19	ga_s2am_ard_3-2-1_50KPC_2024-02-20_final
2024-03-18 11:45:54	ga_s2am_ard_3-2-1_50JNN_2024-03-18_final
2024-04-14 11:32:21	ga_s2am_ard_3-2-1_51KVB_2024-04-14_final
2024-04-17 11:42:19	ga_s2am_ard_3-2-1_51KUB_2024-04-17_final
2024-04-27 11:43:06	ga_s2am_ard_3-2-1_51KTU_2024-04-27_final

Return to ga_s2am_ard_3 whole collection overview

ga_s2am_ard_3: Geoscience Australia Sentinel 2A MSI Analysis Ready Data Collection 3

Baseline satellite data

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

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