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
2016-03-29 12:13:41	ga_s2am_ard_3-2-1_49KHR_2016-03-29_final.stac-item
2016-08-20 11:56:10	ga_s2am_ard_3-2-1_50JLM_2016-08-20_final.stac-item
2016-08-21 11:26:11	ga_s2am_ard_3-2-1_51JVF_2016-08-21_final.stac-item
2016-11-11 12:02:48	ga_s2am_ard_3-2-1_50KMC_2016-11-11_final.stac-item
2016-11-16 11:11:49	ga_s2am_ard_3-2-1_51HWD_2016-11-16_final.stac-item
2016-12-11 12:02:45	ga_s2am_ard_3-2-1_50KLU_2016-12-11_final.stac-item
2017-07-29 12:02:51	ga_s2am_ard_3-2-1_50KLC_2017-07-29_final.stac-item
2018-03-30 11:44:57	ga_s2am_ard_3-2-1_50HPK_2018-03-30_final.stac-item
2018-05-03 11:21:11	ga_s2am_ard_3-2-1_51HUD_2018-05-03_final.stac-item
2018-05-20 11:11:46	ga_s2am_ard_3-2-1_51HYE_2018-05-20_final.stac-item
2018-07-04 12:02:50	ga_s2am_ard_3-2-1_50KMC_2018-07-04_final.stac-item
2018-08-17 11:45:55	ga_s2am_ard_3-2-1_50HQK_2018-08-17_final.stac-item
2018-11-18 11:56:01	ga_s2am_ard_3-2-1_50JMM_2018-11-18_final.stac-item
2018-11-24 12:14:19	ga_s2am_ard_3-2-1_49KGP_2018-11-24_final.stac-item
2018-11-28 11:53:02	ga_s2am_ard_3-2-1_50KRC_2018-11-28_final.stac-item
2018-12-21 12:04:37	ga_s2am_ard_3-2-1_49JGN_2018-12-21_final.stac-item
2019-02-19 12:03:55	ga_s2am_ard_3-2-1_49KHR_2019-02-19_final.stac-item
2019-04-17 11:53:13	ga_s2am_ard_3-2-1_50KRC_2019-04-17_final.stac-item
2019-05-30 12:04:09	ga_s2am_ard_3-2-1_50KKV_2019-05-30_final.stac-item
2019-06-20 11:34:47	ga_s2am_ard_3-2-1_51JVM_2019-06-20_final.stac-item
2019-07-24 11:15:47	ga_s2am_ard_3-2-1_51JXH_2019-07-24_final.stac-item
2019-08-02 11:45:22	ga_s2am_ard_3-2-1_50JQQ_2019-08-02_final.stac-item
2019-09-01 11:44:02	ga_s2am_ard_3-2-1_50KRV_2019-09-01_final.stac-item
2019-11-23 11:56:00	ga_s2am_ard_3-2-1_50JKN_2019-11-23_final.stac-item
2019-12-30 11:47:01	ga_s2am_ard_3-2-1_50HNH_2019-12-30_final.stac-item
2020-02-28 11:45:13	ga_s2am_ard_3-2-1_50JQQ_2020-02-28_final.stac-item
2020-03-19 11:45:43	ga_s2am_ard_3-2-1_50JQN_2020-03-19_final.stac-item
2020-04-15 11:36:42	ga_s2am_ard_3-2-1_51HUD_2020-04-15_final.stac-item
2020-04-21 11:53:25	ga_s2am_ard_3-2-1_50KNC_2020-04-21_final.stac-item
2020-04-28 11:46:58	ga_s2am_ard_3-2-1_50HMJ_2020-04-28_final.stac-item
2020-07-11 11:25:46	ga_s2am_ard_3-2-1_51JWH_2020-07-11_final.stac-item
2020-08-06 11:46:00	ga_s2am_ard_3-2-1_50JNN_2020-08-06_final.stac-item
2020-09-05 11:44:49	ga_s2am_ard_3-2-1_50JRS_2020-09-05_final.stac-item
2020-09-22 11:37:06	ga_s2am_ard_3-2-1_51HTC_2020-09-22_final.stac-item
2020-12-10 12:04:24	ga_s2am_ard_3-2-1_50KKU_2020-12-10_final.stac-item
2020-12-21 11:36:45	ga_s2am_ard_3-2-1_51HTD_2020-12-21_final.stac-item
2021-01-07 11:24:30	ga_s2am_ard_3-2-1_51JWN_2021-01-07_final.stac-item
2021-01-23 11:46:16	ga_s2am_ard_3-2-1_50JQL_2021-01-23_final.stac-item
2021-02-16 11:26:39	ga_s2am_ard_3-2-1_51HWD_2021-02-16_final.stac-item
2021-02-18 12:05:22	ga_s2am_ard_3-2-1_50JLQ_2021-02-18_final.stac-item
2021-03-10 12:05:40	ga_s2am_ard_3-2-1_50JKP_2021-03-10_final.stac-item
2021-03-11 11:37:10	ga_s2am_ard_3-2-1_50HQG_2021-03-11_final
2021-03-27 11:52:18	ga_s2am_ard_3-2-1_50KQG_2021-03-27_final
2021-04-02 12:13:51	ga_s2am_ard_3-2-1_50KKA_2021-04-02_final.stac-item
2021-04-10 11:36:27	ga_s2am_ard_3-2-1_51HTE_2021-04-10_final.stac-item
2021-04-23 11:43:00	ga_s2am_ard_3-2-1_50KRD_2021-04-23_final.stac-item
2021-04-30 11:36:55	ga_s2am_ard_3-2-1_51HUC_2021-04-30_final.stac-item
2021-05-03 11:43:20	ga_s2am_ard_3-2-1_50KQC_2021-05-03_final.stac-item
2021-05-06 11:53:55	ga_s2am_ard_3-2-1_50KMA_2021-05-06_final.stac-item
2021-05-13 11:45:46	ga_s2am_ard_3-2-1_50JQN_2021-05-13_final.stac-item
2021-07-28 12:03:44	ga_s2am_ard_3-2-1_50KLB_2021-07-28_final.stac-item
2021-08-07 12:05:03	ga_s2am_ard_3-2-1_49JGM_2021-08-07_final.stac-item
2021-08-21 11:47:23	ga_s2am_ard_3-2-1_50HNG_2021-08-21_final
2021-09-20 11:46:50	ga_s2am_ard_3-2-1_50HPJ_2021-09-20_final.stac-item
2021-09-30 11:46:38	ga_s2am_ard_3-2-1_50HPK_2021-09-30_final.stac-item
2021-10-07 11:34:30	ga_s2am_ard_3-2-1_51JWN_2021-10-07_final.stac-item
2021-10-07 11:36:39	ga_s2am_ard_3-2-1_50HQK_2021-10-07_final.stac-item
2021-10-16 12:03:29	ga_s2am_ard_3-2-1_50KMC_2021-10-16_final.stac-item
2021-11-02 11:55:46	ga_s2am_ard_3-2-1_50JLP_2021-11-02_final.stac-item
2021-11-26 11:34:32	ga_s2am_ard_3-2-1_51JUN_2021-11-26_final.stac-item
2021-12-03 11:25:03	ga_s2am_ard_3-2-1_51JVL_2021-12-03_final.stac-item
2021-12-16 11:36:48	ga_s2am_ard_3-2-1_50HQJ_2021-12-16_final.stac-item
2021-12-19 11:43:22	ga_s2am_ard_3-2-1_50KQC_2021-12-19_final.stac-item
2022-01-05 11:35:52	ga_s2am_ard_3-2-1_50JQN_2022-01-05_final.stac-item
2022-03-15 12:03:27	ga_s2am_ard_3-2-1_50KMC_2022-03-15_final.stac-item
2022-03-15 12:05:48	ga_s2am_ard_3-2-1_49JGJ_2022-03-15_final.stac-item
2022-04-05 11:36:12	ga_s2am_ard_3-2-1_51JVF_2022-04-05_final.stac-item
2022-05-05 11:34:37	ga_s2am_ard_3-2-1_51JUN_2022-05-05_final.stac-item
2022-05-21 11:53:27	ga_s2am_ard_3-2-1_50KPC_2022-05-21_final.stac-item
2022-06-07 11:47:10	ga_s2am_ard_3-2-1_50HPH_2022-06-07_final.stac-item
2022-06-08 11:15:38	ga_s2am_ard_3-2-1_51JXJ_2022-06-08_final.stac-item
2022-07-13 12:06:04	ga_s2am_ard_3-2-1_50JLN_2022-07-13_final.stac-item
2022-08-03 11:36:39	ga_s2am_ard_3-2-1_51HUE_2022-08-03_final.stac-item
2022-10-06 11:15:54	ga_s2am_ard_3-2-1_51JXH_2022-10-06_final.stac-item
2022-10-15 11:43:22	ga_s2am_ard_3-2-1_50KRC_2022-10-15_final.stac-item
2022-11-18 11:26:49	ga_s2am_ard_3-2-1_51HUD_2022-11-18_final.stac-item
2022-11-27 11:56:07	ga_s2am_ard_3-2-1_50JMM_2022-11-27_final.stac-item
2022-12-21 11:36:46	ga_s2am_ard_3-2-1_50HQJ_2022-12-21_final.stac-item
2023-01-19 12:04:34	ga_s2am_ard_3-2-1_50JLT_2023-01-19_final.stac-item
2023-02-08 12:05:40	ga_s2am_ard_3-2-1_50JKP_2023-02-08_final
2023-03-10 12:03:18	ga_s2am_ard_3-2-1_50KMC_2023-03-10_final
2023-05-14 11:16:30	ga_s2am_ard_3-2-1_51HYD_2023-05-14_final
2023-05-20 11:36:53	ga_s2am_ard_3-2-1_51HUD_2023-05-20_final
2023-06-06 11:26:11	ga_s2am_ard_3-2-1_51JXF_2023-06-06_final
2023-06-12 11:47:21	ga_s2am_ard_3-2-1_50HPG_2023-06-12_final
2023-06-15 11:53:29	ga_s2am_ard_3-2-1_50KNC_2023-06-15_final
2023-06-18 12:05:27	ga_s2am_ard_3-2-1_50JLQ_2023-06-18_final
2023-07-05 11:52:39	ga_s2am_ard_3-2-1_50KQF_2023-07-05_final
2023-07-08 12:03:49	ga_s2am_ard_3-2-1_50KKB_2023-07-08_final
2023-07-18 12:04:36	ga_s2am_ard_3-2-1_49KGP_2023-07-18_final
2023-08-10 12:14:02	ga_s2am_ard_3-2-1_49KGR_2023-08-10_final
2023-08-22 11:15:49	ga_s2am_ard_3-2-1_51JXH_2023-08-22_final
2023-09-30 11:46:21	ga_s2am_ard_3-2-1_50JPL_2023-09-30_final
2023-09-30 11:47:12	ga_s2am_ard_3-2-1_50HMH_2023-09-30_final
2023-10-13 11:55:44	ga_s2am_ard_3-2-1_50JKP_2023-10-13_final
2023-11-25 12:05:24	ga_s2am_ard_3-2-1_49JGK_2023-11-25_final
2024-01-01 11:52:21	ga_s2am_ard_3-2-1_50KQG_2024-01-01_final
2024-03-04 12:03:45	ga_s2am_ard_3-2-1_50KKB_2024-03-04_final
2024-03-05 11:36:14	ga_s2am_ard_3-2-1_51JUF_2024-03-05_final
2024-03-11 11:54:05	ga_s2am_ard_3-2-1_50KPV_2024-03-11_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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