Search ga_s2bm_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
2019-08-09 10:41:27	ga_s2bm_ard_3-2-1_53LQD_2019-08-09_final.stac-item
2019-08-09 10:41:42	ga_s2bm_ard_3-2-1_53LQC_2019-08-09_final
2019-08-09 10:41:52	ga_s2bm_ard_3-2-1_53KRB_2019-08-09_final
2019-08-09 10:41:56	ga_s2bm_ard_3-2-1_53KQB_2019-08-09_final
2019-08-09 10:42:07	ga_s2bm_ard_3-2-1_53KQA_2019-08-09_final.stac-item
2019-08-09 10:42:13	ga_s2bm_ard_3-2-1_53KQA_2019-08-09_final.stac-item
2019-08-09 10:42:25	ga_s2bm_ard_3-2-1_53KQV_2019-08-09_final.stac-item
2019-08-09 10:42:39	ga_s2bm_ard_3-2-1_53KQU_2019-08-09_final.stac-item
2019-08-10 10:17:10	ga_s2bm_ard_3-2-1_54HTF_2019-08-10_final.stac-item
2019-08-10 10:17:12	ga_s2bm_ard_3-2-1_53HQA_2019-08-10_final.stac-item
2021-05-17 10:32:10	ga_s2bm_ard_3-2-1_53KQA_2021-05-17_final.stac-item
2021-05-17 10:32:22	ga_s2bm_ard_3-2-1_53KQV_2021-05-17_final.stac-item
2021-05-17 10:32:36	ga_s2bm_ard_3-2-1_53KQU_2021-05-17_final.stac-item
2021-05-17 10:32:51	ga_s2bm_ard_3-2-1_53KQT_2021-05-17_final.stac-item
2021-05-17 10:33:00	ga_s2bm_ard_3-2-1_53KQS_2021-05-17_final.stac-item
2021-05-17 10:33:07	ga_s2bm_ard_3-2-1_53KQS_2021-05-17_final.stac-item
2021-05-17 10:33:19	ga_s2bm_ard_3-2-1_53KQR_2021-05-17_final.stac-item
2021-05-17 10:33:34	ga_s2bm_ard_3-2-1_53KQQ_2021-05-17_final.stac-item
2021-05-17 10:33:49	ga_s2bm_ard_3-2-1_53KQP_2021-05-17_final.stac-item
2021-05-24 10:24:51	ga_s2bm_ard_3-2-1_53JQK_2021-05-24_final.stac-item
2021-05-24 10:24:57	ga_s2bm_ard_3-2-1_53JQK_2021-05-24_final.stac-item
2021-05-24 10:24:57	ga_s2bm_ard_3-2-1_53JQJ_2021-05-24_final.stac-item
2021-05-24 10:25:06	ga_s2bm_ard_3-2-1_53JQJ_2021-05-24_final.stac-item
2021-05-24 10:25:20	ga_s2bm_ard_3-2-1_53JQH_2021-05-24_final.stac-item
2021-05-24 10:25:35	ga_s2bm_ard_3-2-1_53JQG_2021-05-24_final.stac-item
2021-05-24 10:25:49	ga_s2bm_ard_3-2-1_53JQF_2021-05-24_final.stac-item
2021-05-24 10:26:01	ga_s2bm_ard_3-2-1_54HTK_2021-05-24_final.stac-item
2021-06-06 10:35:02	ga_s2bm_ard_3-2-1_53JQJ_2021-06-06_final.stac-item
2021-06-06 10:35:17	ga_s2bm_ard_3-2-1_53JQH_2021-06-06_final.stac-item
2021-06-06 10:35:31	ga_s2bm_ard_3-2-1_53JQG_2021-06-06_final.stac-item
2021-06-23 10:25:49	ga_s2bm_ard_3-2-1_53JQF_2021-06-23_final.stac-item
2021-06-23 10:26:02	ga_s2bm_ard_3-2-1_54HTK_2021-06-23_final.stac-item
2021-06-23 10:26:04	ga_s2bm_ard_3-2-1_53HQE_2021-06-23_final.stac-item
2021-06-23 10:26:16	ga_s2bm_ard_3-2-1_54HTJ_2021-06-23_final.stac-item
2021-06-23 10:26:18	ga_s2bm_ard_3-2-1_53HQD_2021-06-23_final.stac-item
2021-06-23 10:26:31	ga_s2bm_ard_3-2-1_54HTH_2021-06-23_final.stac-item
2021-06-23 10:26:33	ga_s2bm_ard_3-2-1_53HQC_2021-06-23_final.stac-item
2021-06-23 10:26:45	ga_s2bm_ard_3-2-1_54HTG_2021-06-23_final.stac-item
2021-06-23 10:26:47	ga_s2bm_ard_3-2-1_53HQB_2021-06-23_final.stac-item
2021-06-23 10:27:00	ga_s2bm_ard_3-2-1_54HTF_2021-06-23_final.stac-item
2021-06-23 10:27:01	ga_s2bm_ard_3-2-1_53HQA_2021-06-23_final.stac-item
2021-06-23 10:27:12	ga_s2bm_ard_3-2-1_54HTE_2021-06-23_final
2021-06-23 10:27:13	ga_s2bm_ard_3-2-1_53HQV_2021-06-23_final
2022-05-22 10:33:08	ga_s2bm_ard_3-2-1_53KQS_2022-05-22_final.stac-item
2022-05-22 10:33:20	ga_s2bm_ard_3-2-1_53KQR_2022-05-22_final.stac-item
2022-05-22 10:33:35	ga_s2bm_ard_3-2-1_53KQQ_2022-05-22_final.stac-item
2022-05-22 10:33:49	ga_s2bm_ard_3-2-1_53KQP_2022-05-22_final.stac-item
2022-05-22 10:34:04	ga_s2bm_ard_3-2-1_53JQN_2022-05-22_final.stac-item
2022-05-22 10:34:18	ga_s2bm_ard_3-2-1_53JQM_2022-05-22_final.stac-item
2022-05-22 10:34:30	ga_s2bm_ard_3-2-1_53JQL_2022-05-22_final.stac-item
2022-05-22 10:34:36	ga_s2bm_ard_3-2-1_53JQL_2022-05-22_final.stac-item
2022-05-22 10:34:47	ga_s2bm_ard_3-2-1_53JQK_2022-05-22_final.stac-item
2022-05-22 10:35:01	ga_s2bm_ard_3-2-1_53JQJ_2022-05-22_final.stac-item
2022-05-29 10:24:51	ga_s2bm_ard_3-2-1_53JQK_2022-05-29_final.stac-item
2022-05-29 10:24:57	ga_s2bm_ard_3-2-1_53JQK_2022-05-29_final.stac-item
2022-05-29 10:24:57	ga_s2bm_ard_3-2-1_53JQJ_2022-05-29_final.stac-item
2022-05-29 10:25:05	ga_s2bm_ard_3-2-1_53JQJ_2022-05-29_final.stac-item
2022-05-29 10:25:20	ga_s2bm_ard_3-2-1_53JQH_2022-05-29_final.stac-item
2022-05-29 10:25:35	ga_s2bm_ard_3-2-1_53JQG_2022-05-29_final.stac-item
2022-05-29 10:25:49	ga_s2bm_ard_3-2-1_53JQF_2022-05-29_final.stac-item
2022-05-29 10:26:01	ga_s2bm_ard_3-2-1_54HTK_2022-05-29_final.stac-item
2022-05-29 10:26:03	ga_s2bm_ard_3-2-1_53HQE_2022-05-29_final.stac-item
2022-05-29 10:26:16	ga_s2bm_ard_3-2-1_54HTJ_2022-05-29_final.stac-item
2022-05-29 10:26:18	ga_s2bm_ard_3-2-1_53HQD_2022-05-29_final.stac-item
2022-05-29 10:26:30	ga_s2bm_ard_3-2-1_54HTH_2022-05-29_final.stac-item
2022-05-29 10:26:32	ga_s2bm_ard_3-2-1_53HQC_2022-05-29_final.stac-item
2022-05-29 10:26:45	ga_s2bm_ard_3-2-1_54HTG_2022-05-29_final.stac-item
2022-05-29 10:26:47	ga_s2bm_ard_3-2-1_53HQB_2022-05-29_final.stac-item
2022-05-29 10:26:59	ga_s2bm_ard_3-2-1_54HTF_2022-05-29_final.stac-item
2022-05-29 10:27:01	ga_s2bm_ard_3-2-1_53HQA_2022-05-29_final.stac-item
2022-06-04 10:41:35	ga_s2bm_ard_3-2-1_53LQC_2022-06-04_final.stac-item
2022-06-04 10:41:45	ga_s2bm_ard_3-2-1_53KRB_2022-06-04_final.stac-item
2022-06-04 10:41:49	ga_s2bm_ard_3-2-1_53KQB_2022-06-04_final.stac-item
2022-06-04 10:42:03	ga_s2bm_ard_3-2-1_53KQA_2022-06-04_final.stac-item
2022-06-04 10:42:18	ga_s2bm_ard_3-2-1_53KQV_2022-06-04_final.stac-item
2022-06-04 10:42:32	ga_s2bm_ard_3-2-1_53KQU_2022-06-04_final.stac-item
2022-06-11 10:32:13	ga_s2bm_ard_3-2-1_53KQA_2022-06-11_final.stac-item
2022-06-11 10:32:25	ga_s2bm_ard_3-2-1_53KQV_2022-06-11_final.stac-item
2022-06-11 10:32:39	ga_s2bm_ard_3-2-1_53KQU_2022-06-11_final.stac-item
2022-06-11 10:32:47	ga_s2bm_ard_3-2-1_53KQT_2022-06-11_final.stac-item
2022-06-11 10:32:54	ga_s2bm_ard_3-2-1_53KQT_2022-06-11_final.stac-item
2022-06-11 10:33:08	ga_s2bm_ard_3-2-1_53KQS_2022-06-11_final.stac-item
2022-06-11 10:33:23	ga_s2bm_ard_3-2-1_53KQR_2022-06-11_final.stac-item
2022-06-11 10:33:37	ga_s2bm_ard_3-2-1_53KQQ_2022-06-11_final.stac-item
2022-06-11 10:33:52	ga_s2bm_ard_3-2-1_53KQP_2022-06-11_final.stac-item
2022-06-11 10:34:06	ga_s2bm_ard_3-2-1_53JQN_2022-06-11_final.stac-item
2022-06-11 10:34:20	ga_s2bm_ard_3-2-1_53JQM_2022-06-11_final.stac-item
2022-06-11 10:34:35	ga_s2bm_ard_3-2-1_53JQL_2022-06-11_final.stac-item
2022-06-11 10:34:49	ga_s2bm_ard_3-2-1_53JQK_2022-06-11_final.stac-item
2022-06-11 10:35:04	ga_s2bm_ard_3-2-1_53JQJ_2022-06-11_final.stac-item
2022-06-11 10:35:18	ga_s2bm_ard_3-2-1_53JQH_2022-06-11_final.stac-item
2022-12-28 10:32:10	ga_s2bm_ard_3-2-1_53KQA_2022-12-28_final.stac-item
2022-12-28 10:32:22	ga_s2bm_ard_3-2-1_53KQV_2022-12-28_final.stac-item
2022-12-28 10:32:36	ga_s2bm_ard_3-2-1_53KQU_2022-12-28_final.stac-item
2022-12-28 10:32:51	ga_s2bm_ard_3-2-1_53KQT_2022-12-28_final.stac-item
2022-12-28 10:33:05	ga_s2bm_ard_3-2-1_53KQS_2022-12-28_final.stac-item
2023-01-07 10:32:08	ga_s2bm_ard_3-2-1_53KQA_2023-01-07_final.stac-item
2023-01-07 10:32:20	ga_s2bm_ard_3-2-1_53KQV_2023-01-07_final.stac-item
2023-01-07 10:32:34	ga_s2bm_ard_3-2-1_53KQU_2023-01-07_final.stac-item
2023-01-07 10:32:49	ga_s2bm_ard_3-2-1_53KQT_2023-01-07_final.stac-item

Return to ga_s2bm_ard_3 whole collection overview

ga_s2bm_ard_3: Geoscience Australia Sentinel 2B 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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