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
2016-01-03 11:57:46	ga_s2am_ard_3-2-1_50JPS_2016-01-03_final.stac-item
2016-01-06 12:04:05	ga_s2am_ard_3-2-1_50KMA_2016-01-06_final.stac-item
2016-01-07 11:37:54	ga_s2am_ard_3-2-1_51JWK_2016-01-07_final.stac-item
2016-01-20 11:47:47	ga_s2am_ard_3-2-1_51JUN_2016-01-20_final.stac-item
2016-02-08 12:10:34	ga_s2am_ard_3-2-1_49KGQ_2016-02-08_final.stac-item
2016-02-15 11:59:34	ga_s2am_ard_3-2-1_50KNB_2016-02-15_final.stac-item
2016-03-03 11:49:03	ga_s2am_ard_3-2-1_50KQC_2016-03-03_final.stac-item
2016-03-09 12:06:21	ga_s2am_ard_3-2-1_50KKV_2016-03-09_final.stac-item
2016-04-19 11:37:58	ga_s2am_ard_3-2-1_50HQJ_2016-04-19_final.stac-item
2016-04-19 11:37:58	ga_s2am_ard_3-2-1_51KUP_2016-04-19_final.stac-item
2016-04-29 11:42:00	ga_s2am_ard_3-2-1_51JTM_2016-04-29_final.stac-item
2016-05-03 11:23:12	ga_s2am_ard_3-2-1_51JYM_2016-05-03_final.stac-item
2016-05-16 11:32:16	ga_s2am_ard_3-2-1_51JVK_2016-05-16_final.stac-item
2016-05-18 12:13:27	ga_s2am_ard_3-2-1_49KHR_2016-05-18_final.stac-item
2016-05-23 11:22:44	ga_s2am_ard_3-2-1_51JYM_2016-05-23_final.stac-item
2016-05-28 12:13:49	ga_s2am_ard_3-2-1_49KHR_2016-05-28_final.stac-item
2016-05-29 11:40:18	ga_s2am_ard_3-2-1_50HQJ_2016-05-29_final.stac-item
2016-06-07 12:13:25	ga_s2am_ard_3-2-1_49KGQ_2016-06-07_final.stac-item
2016-07-01 11:48:31	ga_s2am_ard_3-2-1_50HLH_2016-07-01_final.stac-item
2016-07-08 11:40:16	ga_s2am_ard_3-2-1_50HLH_2016-07-08_final.stac-item
2016-11-11 12:02:48	ga_s2am_ard_3-2-1_50KLC_2016-11-11_final.stac-item
2016-12-22 11:29:07	ga_s2am_ard_3-2-1_50HNG_2016-12-22_final
2016-12-25 11:36:56	ga_s2am_ard_3-2-1_51JUN_2016-12-25_final.stac-item
2017-02-13 11:37:46	ga_s2am_ard_3-2-1_50KRB_2017-02-13_final.stac-item
2017-02-13 11:37:46	ga_s2am_ard_3-2-1_51KTS_2017-02-13_final.stac-item
2017-02-27 11:22:43	ga_s2am_ard_3-2-1_51JWM_2017-02-27_final.stac-item
2017-03-05 11:37:45	ga_s2am_ard_3-2-1_50JRT_2017-03-05_final.stac-item
2017-08-12 11:40:50	ga_s2am_ard_3-2-1_50KPV_2017-08-12_final.stac-item
2017-11-21 11:11:58	ga_s2am_ard_3-2-1_51JXJ_2017-11-21_final.stac-item
2017-12-16 12:02:44	ga_s2am_ard_3-2-1_49KGQ_2017-12-16_final.stac-item
2017-12-16 12:02:44	ga_s2am_ard_3-2-1_50KLC_2017-12-16_final.stac-item
2017-12-29 12:13:37	ga_s2am_ard_3-2-1_49KHR_2017-12-29_final.stac-item
2017-12-30 11:42:34	ga_s2am_ard_3-2-1_51KTU_2017-12-30_final.stac-item
2018-01-06 11:32:02	ga_s2am_ard_3-2-1_51JWM_2018-01-06_final.stac-item
2018-01-13 11:19:15	ga_s2am_ard_3-2-1_51JZN_2018-01-13_final.stac-item
2018-02-21 11:50:43	ga_s2am_ard_3-2-1_50KNB_2018-02-21_final.stac-item
2018-06-28 11:40:06	ga_s2am_ard_3-2-1_50KRD_2018-06-28_final.stac-item
2018-11-02 11:27:40	ga_s2am_ard_3-2-1_51KUP_2018-11-02_final.stac-item
2018-12-19 11:24:10	ga_s2am_ard_3-2-1_51JZN_2018-12-19_final.stac-item
2019-01-04 11:44:00	ga_s2am_ard_3-2-1_50KQV_2019-01-04_final.stac-item
2019-01-04 11:44:17	ga_s2am_ard_3-2-1_50KPU_2019-01-04_final.stac-item
2019-06-03 11:47:16	ga_s2am_ard_3-2-1_50HLH_2019-06-03_final.stac-item
2019-07-03 11:43:08	ga_s2am_ard_3-2-1_51KTU_2019-07-03_final.stac-item
2019-10-28 11:34:40	ga_s2am_ard_3-2-1_50JRT_2019-10-28_final.stac-item
2019-11-07 11:34:39	ga_s2am_ard_3-2-1_51JTN_2019-11-07_final.stac-item
2019-11-17 11:34:38	ga_s2am_ard_3-2-1_51JTN_2019-11-17_final.stac-item
2019-11-21 11:15:30	ga_s2am_ard_3-2-1_51JXJ_2019-11-21_final.stac-item
2019-11-24 11:24:30	ga_s2am_ard_3-2-1_51JWN_2019-11-24_final.stac-item
2019-12-24 11:24:24	ga_s2am_ard_3-2-1_51JWN_2019-12-24_final.stac-item
2019-12-30 11:43:31	ga_s2am_ard_3-2-1_50KQB_2019-12-30_final.stac-item
2020-02-11 11:53:32	ga_s2am_ard_3-2-1_50KNB_2020-02-11_final.stac-item
2020-02-28 11:42:58	ga_s2am_ard_3-2-1_51KTU_2020-02-28_final.stac-item
2020-11-21 11:34:27	ga_s2am_ard_3-2-1_51JWN_2020-11-21_final.stac-item
2020-12-04 11:44:12	ga_s2am_ard_3-2-1_51KUP_2020-12-04_final.stac-item
2020-12-21 11:34:30	ga_s2am_ard_3-2-1_51JUN_2020-12-21_final.stac-item
2020-12-24 11:44:15	ga_s2am_ard_3-2-1_51KTP_2020-12-24_final.stac-item
2020-12-30 12:04:18	ga_s2am_ard_3-2-1_49KGQ_2020-12-30_final.stac-item
2021-01-03 11:43:37	ga_s2am_ard_3-2-1_50KQB_2021-01-03_final.stac-item
2021-01-06 11:53:43	ga_s2am_ard_3-2-1_50KMB_2021-01-06_final.stac-item
2021-01-06 11:54:12	ga_s2am_ard_3-2-1_50KMV_2021-01-06_final.stac-item
2021-01-30 11:34:32	ga_s2am_ard_3-2-1_51JUN_2021-01-30_final.stac-item
2021-02-13 11:16:57	ga_s2am_ard_3-2-1_51HWC_2021-02-13_final
2021-02-22 11:43:03	ga_s2am_ard_3-2-1_51KTU_2021-02-22_final.stac-item
2021-03-04 11:43:32	ga_s2am_ard_3-2-1_51KTS_2021-03-04_final.stac-item
2021-05-09 12:03:43	ga_s2am_ard_3-2-1_49KHS_2021-05-09_final
2021-05-26 11:52:38	ga_s2am_ard_3-2-1_50KPF_2021-05-26_final
2021-06-13 11:16:08	ga_s2am_ard_3-2-1_51JYF_2021-06-13_final.stac-item
2021-08-12 11:15:27	ga_s2am_ard_3-2-1_51JYJ_2021-08-12_final.stac-item
2021-08-18 11:35:18	ga_s2am_ard_3-2-1_51JUK_2021-08-18_final.stac-item
2021-10-17 11:34:23	ga_s2am_ard_3-2-1_51KUP_2021-10-17_final.stac-item
2021-11-12 11:53:45	ga_s2am_ard_3-2-1_50KMB_2021-11-12_final.stac-item
2021-12-06 11:34:35	ga_s2am_ard_3-2-1_51JTN_2021-12-06_final.stac-item
2021-12-10 11:15:23	ga_s2am_ard_3-2-1_51JYJ_2021-12-10_final.stac-item
2021-12-16 11:34:25	ga_s2am_ard_3-2-1_51JWN_2021-12-16_final.stac-item
2021-12-26 11:37:22	ga_s2am_ard_3-2-1_50HPG_2021-12-26_final
2022-01-02 11:25:07	ga_s2am_ard_3-2-1_51JYK_2022-01-02_final.stac-item
2022-05-31 11:53:50	ga_s2am_ard_3-2-1_50KMB_2022-05-31_final.stac-item
2022-06-20 11:57:03	ga_s2am_ard_3-2-1_50HMJ_2022-06-20_final.stac-item
2022-11-01 11:36:00	ga_s2am_ard_3-2-1_51JVG_2022-11-01_final.stac-item
2022-12-28 11:24:48	ga_s2am_ard_3-2-1_51JXM_2022-12-28_final.stac-item
2022-12-31 11:34:31	ga_s2am_ard_3-2-1_51JUN_2022-12-31_final.stac-item
2023-01-10 11:34:34	ga_s2am_ard_3-2-1_51JTN_2023-01-10_final.stac-item
2023-01-20 11:37:16	ga_s2am_ard_3-2-1_50HPG_2023-01-20_final
2023-02-12 11:44:25	ga_s2am_ard_3-2-1_51JUN_2023-02-12_nrt.stac-item
2023-02-12 11:44:25	ga_s2am_ard_3-2-1_51JUN_2023-02-12_final
2023-02-25 11:53:51	ga_s2am_ard_3-2-1_50KQA_2023-02-25_final
2023-03-11 11:34:13	ga_s2am_ard_3-2-1_51KUP_2023-03-11_final
2023-06-09 11:36:52	ga_s2am_ard_3-2-1_50HQJ_2023-06-09_final
2023-10-17 11:37:26	ga_s2am_ard_3-2-1_50HNG_2023-10-17_final
2023-11-06 11:34:36	ga_s2am_ard_3-2-1_50JRT_2023-11-06_final
2023-11-26 11:34:30	ga_s2am_ard_3-2-1_51JTN_2023-11-26_final
2023-11-30 11:15:02	ga_s2am_ard_3-2-1_51JYK_2023-11-30_final
2023-12-03 11:26:47	ga_s2am_ard_3-2-1_51HWC_2023-12-03_final
2023-12-13 11:25:16	ga_s2am_ard_3-2-1_51JYJ_2023-12-13_final
2023-12-13 11:26:50	ga_s2am_ard_3-2-1_51HWC_2023-12-13_final
2023-12-16 11:34:32	ga_s2am_ard_3-2-1_51JTN_2023-12-16_final
2023-12-30 11:14:20	ga_s2am_ard_3-2-1_51JZN_2023-12-30_final
2024-01-18 11:44:07	ga_s2am_ard_3-2-1_51KTP_2024-01-18_final
2024-02-04 11:34:21	ga_s2am_ard_3-2-1_51JWN_2024-02-04_final
2024-02-17 11:44:25	ga_s2am_ard_3-2-1_51JUN_2024-02-17_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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