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
2016-10-02 12:02:45	ga_s2am_ard_3-2-1_50KKU_2016-10-02_final.stac-item
2016-11-28 11:49:54	ga_s2am_ard_3-2-1_50JLN_2016-11-28_final.stac-item
2016-12-05 11:36:19	ga_s2am_ard_3-2-1_50HQJ_2016-12-05_final.stac-item
2017-01-14 11:45:31	ga_s2am_ard_3-2-1_50HMH_2017-01-14_final.stac-item
2017-02-02 12:13:15	ga_s2am_ard_3-2-1_49KGP_2017-02-02_final.stac-item
2017-03-25 11:44:58	ga_s2am_ard_3-2-1_50HQJ_2017-03-25_final.stac-item
2017-06-22 12:13:20	ga_s2am_ard_3-2-1_49JGN_2017-06-22_final.stac-item
2017-08-08 12:03:49	ga_s2am_ard_3-2-1_49KHR_2017-08-08_final.stac-item
2017-10-31 11:42:00	ga_s2am_ard_3-2-1_50JPL_2017-10-31_final.stac-item
2018-02-07 12:14:38	ga_s2am_ard_3-2-1_49JGL_2018-02-07_final.stac-item
2018-03-13 11:52:23	ga_s2am_ard_3-2-1_50JLM_2018-03-13_final.stac-item
2018-03-23 11:53:37	ga_s2am_ard_3-2-1_50JKP_2018-03-23_final.stac-item
2018-04-09 11:40:31	ga_s2am_ard_3-2-1_50HMK_2018-04-09_final.stac-item
2018-04-12 11:47:43	ga_s2am_ard_3-2-1_50KPC_2018-04-12_final.stac-item
2018-05-02 11:53:21	ga_s2am_ard_3-2-1_50JLM_2018-05-02_final.stac-item
2018-05-18 12:13:23	ga_s2am_ard_3-2-1_49KGP_2018-05-18_final.stac-item
2018-05-22 11:53:30	ga_s2am_ard_3-2-1_50HLH_2018-05-22_final.stac-item
2018-07-05 11:35:08	ga_s2am_ard_3-2-1_50HPJ_2018-07-05_final.stac-item
2018-07-27 12:13:47	ga_s2am_ard_3-2-1_50KKA_2018-07-27_final.stac-item
2018-08-27 11:45:54	ga_s2am_ard_3-2-1_50HPJ_2018-08-27_final.stac-item
2018-10-06 11:40:38	ga_s2am_ard_3-2-1_50JPL_2018-10-06_final.stac-item
2019-01-17 11:53:13	ga_s2am_ard_3-2-1_50KQC_2019-01-17_final.stac-item
2019-04-11 11:37:05	ga_s2am_ard_3-2-1_50HQH_2019-04-11_final.stac-item
2019-04-17 11:55:56	ga_s2am_ard_3-2-1_50JMN_2019-04-17_final.stac-item
2019-04-20 12:03:59	ga_s2am_ard_3-2-1_50KLA_2019-04-20_final.stac-item
2019-05-03 12:14:31	ga_s2am_ard_3-2-1_49KGP_2019-05-03_final.stac-item
2019-08-02 11:45:51	ga_s2am_ard_3-2-1_50JQN_2019-08-02_final.stac-item
2019-09-17 12:04:24	ga_s2am_ard_3-2-1_50KLU_2019-09-17_final.stac-item
2019-10-21 11:45:57	ga_s2am_ard_3-2-1_50JNN_2019-10-21_final.stac-item
2019-11-23 11:53:39	ga_s2am_ard_3-2-1_50KNB_2019-11-23_final.stac-item
2020-02-04 12:03:36	ga_s2am_ard_3-2-1_50KKB_2020-02-04_final.stac-item
2020-03-12 11:54:07	ga_s2am_ard_3-2-1_50KMV_2020-03-12_final.stac-item
2020-04-08 11:46:27	ga_s2am_ard_3-2-1_50HQK_2020-04-08_final.stac-item
2020-04-21 11:56:23	ga_s2am_ard_3-2-1_50JML_2020-04-21_final.stac-item
2020-05-31 11:56:28	ga_s2am_ard_3-2-1_50JML_2020-05-31_final.stac-item
2020-06-06 12:15:02	ga_s2am_ard_3-2-1_49JGM_2020-06-06_final.stac-item
2020-06-27 11:46:53	ga_s2am_ard_3-2-1_50HPJ_2020-06-27_final.stac-item
2020-09-15 11:46:19	ga_s2am_ard_3-2-1_50JQL_2020-09-15_final.stac-item
2020-10-21 12:04:48	ga_s2am_ard_3-2-1_50JKT_2020-10-21_final.stac-item
2020-12-04 11:47:05	ga_s2am_ard_3-2-1_50HNH_2020-12-04_final.stac-item
2020-12-20 12:04:26	ga_s2am_ard_3-2-1_50KKU_2020-12-20_final.stac-item
2021-01-03 11:46:34	ga_s2am_ard_3-2-1_50HPK_2021-01-03_final.stac-item
2021-01-09 12:04:19	ga_s2am_ard_3-2-1_49KGQ_2021-01-09_final.stac-item
2021-01-23 11:46:34	ga_s2am_ard_3-2-1_50HPK_2021-01-23_final.stac-item
2021-01-29 12:03:59	ga_s2am_ard_3-2-1_50KKA_2021-01-29_final.stac-item
2021-02-12 11:46:36	ga_s2am_ard_3-2-1_50HNK_2021-02-12_final.stac-item
2021-02-18 12:04:45	ga_s2am_ard_3-2-1_49JGN_2021-02-18_final.stac-item
2021-02-18 12:05:00	ga_s2am_ard_3-2-1_49JGM_2021-02-18_final.stac-item
2021-02-25 11:52:34	ga_s2am_ard_3-2-1_50KQF_2021-02-25_final
2021-02-25 11:56:07	ga_s2am_ard_3-2-1_50JMM_2021-02-25_final.stac-item
2021-03-13 12:13:54	ga_s2am_ard_3-2-1_49KHR_2021-03-13_final.stac-item
2021-05-06 11:54:03	ga_s2am_ard_3-2-1_50KPV_2021-05-06_final.stac-item
2021-05-13 11:46:15	ga_s2am_ard_3-2-1_50JQL_2021-05-13_final.stac-item
2021-05-19 12:03:44	ga_s2am_ard_3-2-1_50KKB_2021-05-19_final.stac-item
2021-05-23 11:45:12	ga_s2am_ard_3-2-1_50JNR_2021-05-23_final.stac-item
2021-06-08 12:05:38	ga_s2am_ard_3-2-1_50JLP_2021-06-08_final.stac-item
2021-06-18 12:05:01	ga_s2am_ard_3-2-1_49JGM_2021-06-18_final.stac-item
2021-06-22 11:46:53	ga_s2am_ard_3-2-1_50HNJ_2021-06-22_final.stac-item
2021-06-25 11:55:54	ga_s2am_ard_3-2-1_50JMN_2021-06-25_final.stac-item
2021-07-18 12:04:17	ga_s2am_ard_3-2-1_49KHQ_2021-07-18_final.stac-item
2021-07-19 11:37:10	ga_s2am_ard_3-2-1_50HPH_2021-07-19_final.stac-item
2021-08-11 11:46:54	ga_s2am_ard_3-2-1_50HNJ_2021-08-11_final.stac-item
2021-08-27 12:04:01	ga_s2am_ard_3-2-1_49KHR_2021-08-27_final.stac-item
2021-08-31 11:47:18	ga_s2am_ard_3-2-1_50HPG_2021-08-31_final
2021-09-20 11:46:03	ga_s2am_ard_3-2-1_50JQM_2021-09-20_final.stac-item
2021-11-25 12:04:39	ga_s2am_ard_3-2-1_50JLT_2021-11-25_final.stac-item
2021-12-12 11:53:16	ga_s2am_ard_3-2-1_50KQC_2021-12-12_final.stac-item
2021-12-22 11:53:18	ga_s2am_ard_3-2-1_50KQC_2021-12-22_final.stac-item
2021-12-28 12:14:43	ga_s2am_ard_3-2-1_49JGN_2021-12-28_final.stac-item
2022-02-06 12:14:41	ga_s2am_ard_3-2-1_49JGN_2022-02-06_final.stac-item
2022-03-29 11:45:24	ga_s2am_ard_3-2-1_50JPQ_2022-03-29_final.stac-item
2022-05-24 12:04:40	ga_s2am_ard_3-2-1_50KKU_2022-05-24_final.stac-item
2022-10-15 11:46:05	ga_s2am_ard_3-2-1_50JQM_2022-10-15_final.stac-item
2022-11-20 12:05:42	ga_s2am_ard_3-2-1_50JKP_2022-11-20_final.stac-item
2022-11-23 12:14:27	ga_s2am_ard_3-2-1_49KGP_2022-11-23_final.stac-item
2022-11-27 11:53:17	ga_s2am_ard_3-2-1_50KQC_2022-11-27_final.stac-item
2022-12-21 11:34:35	ga_s2am_ard_3-2-1_50JRT_2022-12-21_final.stac-item
2023-01-03 11:46:22	ga_s2am_ard_3-2-1_50JNL_2023-01-03_final.stac-item
2023-02-21 12:14:39	ga_s2am_ard_3-2-1_49JGN_2023-02-21_final
2023-03-01 11:36:46	ga_s2am_ard_3-2-1_50HQJ_2023-03-01_final
2023-03-30 12:06:02	ga_s2am_ard_3-2-1_50JLM_2023-03-30_final
2023-03-31 11:37:05	ga_s2am_ard_3-2-1_50HPH_2023-03-31_final
2023-04-09 12:05:01	ga_s2am_ard_3-2-1_49JGM_2023-04-09_final
2023-04-23 11:44:44	ga_s2am_ard_3-2-1_50JRS_2023-04-23_final
2023-05-16 11:53:22	ga_s2am_ard_3-2-1_50KPC_2023-05-16_final
2023-06-08 12:04:03	ga_s2am_ard_3-2-1_49KHR_2023-06-08_final
2023-06-22 11:47:28	ga_s2am_ard_3-2-1_50HMG_2023-06-22_final
2023-06-25 11:55:42	ga_s2am_ard_3-2-1_50JMP_2023-06-25_final
2023-08-21 11:46:47	ga_s2am_ard_3-2-1_50HMK_2023-08-21_final
2023-08-24 11:53:23	ga_s2am_ard_3-2-1_50KQC_2023-08-24_final
2023-09-20 11:46:36	ga_s2am_ard_3-2-1_50HPK_2023-09-20_final
2023-10-03 11:55:48	ga_s2am_ard_3-2-1_50JKP_2023-10-03_final
2023-10-26 12:05:51	ga_s2am_ard_3-2-1_50JLN_2023-10-26_final
2023-12-12 11:53:16	ga_s2am_ard_3-2-1_50KPC_2023-12-12_final
2024-01-04 12:05:11	ga_s2am_ard_3-2-1_49JGL_2024-01-04_final
2024-01-11 11:56:46	ga_s2am_ard_3-2-1_50HMJ_2024-01-11_final
2024-02-03 12:04:24	ga_s2am_ard_3-2-1_49KHP_2024-02-03_final
2024-02-13 12:03:38	ga_s2am_ard_3-2-1_50KLB_2024-02-13_final
2024-04-10 11:57:20	ga_s2am_ard_3-2-1_50HMG_2024-04-10_final
2024-04-17 11:46:40	ga_s2am_ard_3-2-1_50HNK_2024-04-17_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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