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
2016-01-07 11:37:54	ga_s2am_ard_3-2-1_50HQH_2016-01-07_final.stac-item
2016-03-06 12:04:37	ga_s2am_ard_3-2-1_50JKR_2016-03-06_final.stac-item
2016-06-05 11:32:15	ga_s2am_ard_3-2-1_50HNG_2016-06-05_final
2016-06-11 11:48:29	ga_s2am_ard_3-2-1_50HMK_2016-06-11_final.stac-item
2016-06-27 12:13:22	ga_s2am_ard_3-2-1_49KHP_2016-06-27_final.stac-item
2016-08-10 11:48:22	ga_s2am_ard_3-2-1_50JKM_2016-08-10_final.stac-item
2016-08-13 12:04:45	ga_s2am_ard_3-2-1_50JKS_2016-08-13_final.stac-item
2016-10-05 12:13:17	ga_s2am_ard_3-2-1_49KGQ_2016-10-05_final.stac-item
2016-10-22 12:02:45	ga_s2am_ard_3-2-1_49KGQ_2016-10-22_final.stac-item
2016-11-04 12:13:19	ga_s2am_ard_3-2-1_49KHR_2016-11-04_final.stac-item
2016-11-05 11:39:53	ga_s2am_ard_3-2-1_50HMK_2016-11-05_final.stac-item
2016-12-05 11:46:51	ga_s2am_ard_3-2-1_50HNG_2016-12-05_final
2016-12-21 12:04:53	ga_s2am_ard_3-2-1_50JKM_2016-12-21_final.stac-item
2017-01-30 12:02:43	ga_s2am_ard_3-2-1_50JKT_2017-01-30_final.stac-item
2017-02-03 11:41:40	ga_s2am_ard_3-2-1_50HMH_2017-02-03_final.stac-item
2017-04-07 11:49:43	ga_s2am_ard_3-2-1_50JLP_2017-04-07_final.stac-item
2017-04-14 11:45:07	ga_s2am_ard_3-2-1_50HNH_2017-04-14_final.stac-item
2017-08-05 11:51:57	ga_s2am_ard_3-2-1_50JLP_2017-08-05_final.stac-item
2017-10-30 12:13:43	ga_s2am_ard_3-2-1_49KGR_2017-10-30_final.stac-item
2018-04-05 12:03:47	ga_s2am_ard_3-2-1_49KHQ_2018-04-05_final.stac-item
2018-04-25 12:02:51	ga_s2am_ard_3-2-1_50JKS_2018-04-25_final.stac-item
2018-05-19 11:45:58	ga_s2am_ard_3-2-1_50HNH_2018-05-19_final.stac-item
2018-07-01 11:52:21	ga_s2am_ard_3-2-1_50HMJ_2018-07-01_final.stac-item
2018-07-01 11:52:21	ga_s2am_ard_3-2-1_50JLQ_2018-07-01_final.stac-item
2018-07-11 11:51:05	ga_s2am_ard_3-2-1_50HNK_2018-07-11_final.stac-item
2018-07-24 12:02:50	ga_s2am_ard_3-2-1_50JKR_2018-07-24_final.stac-item
2018-09-05 12:13:19	ga_s2am_ard_3-2-1_49KHQ_2018-09-05_final.stac-item
2018-10-29 11:54:48	ga_s2am_ard_3-2-1_50HMK_2018-10-29_final.stac-item
2018-12-05 11:46:21	ga_s2am_ard_3-2-1_50HQK_2018-12-05_final.stac-item
2018-12-21 12:04:37	ga_s2am_ard_3-2-1_49JGN_2018-12-21_final.stac-item
2018-12-31 12:05:20	ga_s2am_ard_3-2-1_50JKQ_2018-12-31_final.stac-item
2019-03-02 11:36:29	ga_s2am_ard_3-2-1_50HQK_2019-03-02_final.stac-item
2019-05-10 12:05:33	ga_s2am_ard_3-2-1_49JGK_2019-05-10_final.stac-item
2019-05-17 11:56:40	ga_s2am_ard_3-2-1_50HMK_2019-05-17_final.stac-item
2019-05-20 12:05:15	ga_s2am_ard_3-2-1_50JKR_2019-05-20_final.stac-item
2019-06-29 12:04:47	ga_s2am_ard_3-2-1_49JHN_2019-06-29_final.stac-item
2019-07-16 11:55:47	ga_s2am_ard_3-2-1_50JLP_2019-07-16_final.stac-item
2019-09-14 11:55:40	ga_s2am_ard_3-2-1_50JLP_2019-09-14_final.stac-item
2019-09-17 12:04:45	ga_s2am_ard_3-2-1_49JGN_2019-09-17_final.stac-item
2019-09-27 12:05:27	ga_s2am_ard_3-2-1_50JKQ_2019-09-27_final.stac-item
2019-10-08 11:36:40	ga_s2am_ard_3-2-1_50HPK_2019-10-08_final.stac-item
2019-10-21 11:46:59	ga_s2am_ard_3-2-1_50HMJ_2019-10-21_final.stac-item
2019-11-06 12:04:16	ga_s2am_ard_3-2-1_49KHQ_2019-11-06_final.stac-item
2019-12-03 11:56:35	ga_s2am_ard_3-2-1_50HMK_2019-12-03_final.stac-item
2019-12-06 12:05:09	ga_s2am_ard_3-2-1_50JKR_2019-12-06_final.stac-item
2019-12-27 11:37:03	ga_s2am_ard_3-2-1_50HQH_2019-12-27_final.stac-item
2019-12-30 11:46:35	ga_s2am_ard_3-2-1_50HMK_2019-12-30_final.stac-item
2020-01-25 12:05:58	ga_s2am_ard_3-2-1_50JLM_2020-01-25_final.stac-item
2020-02-04 12:04:38	ga_s2am_ard_3-2-1_49JGN_2020-02-04_final.stac-item
2020-03-28 12:13:54	ga_s2am_ard_3-2-1_49KGR_2020-03-28_final.stac-item
2020-05-01 11:55:45	ga_s2am_ard_3-2-1_50JLP_2020-05-01_final.stac-item
2020-10-11 12:04:52	ga_s2am_ard_3-2-1_49JGN_2020-10-11_final.stac-item
2020-11-07 11:55:32	ga_s2am_ard_3-2-1_50JLQ_2020-11-07_final.stac-item
2020-11-30 12:04:28	ga_s2am_ard_3-2-1_49KHP_2020-11-30_final.stac-item
2020-11-30 12:05:23	ga_s2am_ard_3-2-1_50JLQ_2020-11-30_final.stac-item
2020-12-24 11:46:46	ga_s2am_ard_3-2-1_50HNJ_2020-12-24_final.stac-item
2021-01-13 11:47:22	ga_s2am_ard_3-2-1_50HNG_2021-01-13_final
2021-02-22 11:46:55	ga_s2am_ard_3-2-1_50HMJ_2021-02-22_final.stac-item
2021-05-19 12:04:57	ga_s2am_ard_3-2-1_50JKS_2021-05-19_final.stac-item
2021-05-26 11:57:07	ga_s2am_ard_3-2-1_50HLH_2021-05-26_final.stac-item
2021-06-25 11:56:52	ga_s2am_ard_3-2-1_50HMJ_2021-06-25_final.stac-item
2021-08-14 11:56:39	ga_s2am_ard_3-2-1_50HMK_2021-08-14_final.stac-item
2021-08-24 11:57:22	ga_s2am_ard_3-2-1_50HMG_2021-08-24_final
2021-09-13 11:56:12	ga_s2am_ard_3-2-1_50JLM_2021-09-13_final.stac-item
2021-09-29 12:14:25	ga_s2am_ard_3-2-1_49KGP_2021-09-29_final.stac-item
2021-09-30 11:47:28	ga_s2am_ard_3-2-1_50HMG_2021-09-30_final
2021-10-06 12:04:23	ga_s2am_ard_3-2-1_49KGQ_2021-10-06_final.stac-item
2021-10-06 12:04:47	ga_s2am_ard_3-2-1_50JKT_2021-10-06_final.stac-item
2021-10-23 11:55:47	ga_s2am_ard_3-2-1_50JLP_2021-10-23_final.stac-item
2021-11-29 11:46:30	ga_s2am_ard_3-2-1_50HQK_2021-11-29_final.stac-item
2021-12-08 12:14:07	ga_s2am_ard_3-2-1_49KHQ_2021-12-08_final.stac-item
2021-12-09 11:46:40	ga_s2am_ard_3-2-1_50HMK_2021-12-09_final.stac-item
2021-12-16 11:36:34	ga_s2am_ard_3-2-1_50HQK_2021-12-16_final.stac-item
2022-01-05 11:36:35	ga_s2am_ard_3-2-1_50HQK_2022-01-05_final.stac-item
2022-01-18 11:46:56	ga_s2am_ard_3-2-1_50HMJ_2022-01-18_final.stac-item
2022-02-27 11:46:33	ga_s2am_ard_3-2-1_50HQK_2022-02-27_final.stac-item
2022-04-27 12:14:26	ga_s2am_ard_3-2-1_49KHP_2022-04-27_final.stac-item
2022-05-04 12:05:42	ga_s2am_ard_3-2-1_50JLP_2022-05-04_final.stac-item
2022-06-23 12:04:45	ga_s2am_ard_3-2-1_49JHN_2022-06-23_final.stac-item
2022-08-09 11:55:24	ga_s2am_ard_3-2-1_50JLR_2022-08-09_final.stac-item
2022-10-18 11:56:39	ga_s2am_ard_3-2-1_50HMK_2022-10-18_final.stac-item
2022-11-27 11:55:41	ga_s2am_ard_3-2-1_50JLP_2022-11-27_final.stac-item
2022-11-30 12:04:13	ga_s2am_ard_3-2-1_49KHQ_2022-11-30_final.stac-item
2023-01-19 12:04:08	ga_s2am_ard_3-2-1_49KHQ_2023-01-19_final.stac-item
2023-03-10 12:04:37	ga_s2am_ard_3-2-1_50JKT_2023-03-10_final
2023-04-12 12:14:09	ga_s2am_ard_3-2-1_49KHQ_2023-04-12_final
2023-04-23 11:47:13	ga_s2am_ard_3-2-1_50HLH_2023-04-23_final
2023-04-29 12:05:38	ga_s2am_ard_3-2-1_50JLP_2023-04-29_final
2023-05-03 11:47:21	ga_s2am_ard_3-2-1_50HNG_2023-05-03_final
2023-05-09 12:04:18	ga_s2am_ard_3-2-1_49KGQ_2023-05-09_final
2023-05-09 12:05:37	ga_s2am_ard_3-2-1_50JLP_2023-05-09_final
2023-06-02 11:47:18	ga_s2am_ard_3-2-1_50HLH_2023-06-02_final
2023-07-08 12:05:02	ga_s2am_ard_3-2-1_50JKS_2023-07-08_final
2023-08-24 11:55:48	ga_s2am_ard_3-2-1_50JLP_2023-08-24_final
2023-11-05 12:04:56	ga_s2am_ard_3-2-1_50JKS_2023-11-05_final
2023-12-09 11:46:35	ga_s2am_ard_3-2-1_50HMK_2023-12-09_final
2024-01-14 12:04:39	ga_s2am_ard_3-2-1_49JGN_2024-01-14_final
2024-01-24 12:05:05	ga_s2am_ard_3-2-1_50JKR_2024-01-24_final
2024-02-27 11:46:51	ga_s2am_ard_3-2-1_50HNJ_2024-02-27_final
2024-04-03 12:04:40	ga_s2am_ard_3-2-1_50JKT_2024-04-03_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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