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
2019-09-20 09:46:01	ga_s2bm_ard_3-2-1_55HED_2019-09-20_final.stac-item
2019-09-20 09:46:16	ga_s2bm_ard_3-2-1_55HEC_2019-09-20_final.stac-item
2019-09-20 09:46:29	ga_s2bm_ard_3-2-1_55HEB_2019-09-20_final.stac-item
2019-10-07 09:37:04	ga_s2bm_ard_3-2-1_55HEV_2019-10-07_final.stac-item
2019-10-07 09:37:19	ga_s2bm_ard_3-2-1_55HEU_2019-10-07_final.stac-item
2019-10-07 09:37:34	ga_s2bm_ard_3-2-1_55HET_2019-10-07_final.stac-item
2019-10-07 09:37:48	ga_s2bm_ard_3-2-1_55HES_2019-10-07_final.stac-item
2019-10-07 09:38:03	ga_s2bm_ard_3-2-1_55GER_2019-10-07_final.stac-item
2019-10-07 09:38:17	ga_s2bm_ard_3-2-1_55GEQ_2019-10-07_final.stac-item
2019-10-07 09:38:25	ga_s2bm_ard_3-2-1_55GEQ_2019-10-07_final.stac-item
2019-10-07 09:38:25	ga_s2bm_ard_3-2-1_55GEP_2019-10-07_final.stac-item
2019-10-07 09:38:32	ga_s2bm_ard_3-2-1_55GEP_2019-10-07_final.stac-item
2023-03-29 09:59:54	ga_s2bm_ard_3-2-1_55LEJ_2023-03-29_nrt
2023-03-29 10:00:08	ga_s2bm_ard_3-2-1_55LEH_2023-03-29_nrt
2023-03-29 10:00:23	ga_s2bm_ard_3-2-1_55LEG_2023-03-29_nrt
2023-03-29 10:00:37	ga_s2bm_ard_3-2-1_55LEF_2023-03-29_nrt
2023-03-29 10:00:52	ga_s2bm_ard_3-2-1_55LEE_2023-03-29_nrt
2023-03-29 10:01:06	ga_s2bm_ard_3-2-1_55LED_2023-03-29_nrt
2023-03-29 10:01:21	ga_s2bm_ard_3-2-1_55LEC_2023-03-29_final
2023-03-29 10:01:35	ga_s2bm_ard_3-2-1_55KEB_2023-03-29_final
2023-03-29 10:01:50	ga_s2bm_ard_3-2-1_55KEA_2023-03-29_nrt
2023-03-29 10:02:04	ga_s2bm_ard_3-2-1_55KEV_2023-03-29_final
2023-03-29 10:02:19	ga_s2bm_ard_3-2-1_55KEU_2023-03-29_final
2023-03-30 09:37:07	ga_s2bm_ard_3-2-1_55HEV_2023-03-30_final
2023-03-30 09:37:22	ga_s2bm_ard_3-2-1_55HEU_2023-03-30_final
2023-03-30 09:37:36	ga_s2bm_ard_3-2-1_55HET_2023-03-30_final
2023-03-30 09:37:51	ga_s2bm_ard_3-2-1_55HES_2023-03-30_final
2023-03-30 09:38:05	ga_s2bm_ard_3-2-1_55GER_2023-03-30_final
2023-03-30 09:38:20	ga_s2bm_ard_3-2-1_55GEQ_2023-03-30_final
2023-03-30 09:38:34	ga_s2bm_ard_3-2-1_55GEP_2023-03-30_final
2023-03-30 09:38:48	ga_s2bm_ard_3-2-1_55GEN_2023-03-30_final
2023-03-30 09:39:03	ga_s2bm_ard_3-2-1_55GEM_2023-03-30_final
2023-04-08 09:59:53	ga_s2bm_ard_3-2-1_55LEJ_2023-04-08_nrt
2023-04-08 10:00:07	ga_s2bm_ard_3-2-1_55LEH_2023-04-08_nrt
2023-04-08 10:00:22	ga_s2bm_ard_3-2-1_55LEG_2023-04-08_nrt
2023-04-08 10:00:36	ga_s2bm_ard_3-2-1_55LEF_2023-04-08_nrt
2023-04-08 10:00:51	ga_s2bm_ard_3-2-1_55LEE_2023-04-08_nrt
2023-04-08 10:01:06	ga_s2bm_ard_3-2-1_55LED_2023-04-08_nrt
2023-04-08 10:01:20	ga_s2bm_ard_3-2-1_55LEC_2023-04-08_final
2023-04-08 10:01:35	ga_s2bm_ard_3-2-1_55KEB_2023-04-08_final
2023-04-09 09:37:06	ga_s2bm_ard_3-2-1_55HEV_2023-04-09_final
2023-04-12 09:44:37	ga_s2bm_ard_3-2-1_55JEK_2023-04-12_final
2023-04-12 09:44:50	ga_s2bm_ard_3-2-1_55JEJ_2023-04-12_final
2023-04-12 09:45:05	ga_s2bm_ard_3-2-1_55JEH_2023-04-12_final
2023-04-12 09:45:20	ga_s2bm_ard_3-2-1_55JEG_2023-04-12_final
2023-04-12 09:45:34	ga_s2bm_ard_3-2-1_55JEF_2023-04-12_final
2023-04-12 09:45:49	ga_s2bm_ard_3-2-1_55HEE_2023-04-12_final
2023-04-12 09:46:03	ga_s2bm_ard_3-2-1_55HED_2023-04-12_final
2023-04-12 09:46:18	ga_s2bm_ard_3-2-1_55HEC_2023-04-12_final
2023-04-15 09:52:06	ga_s2bm_ard_3-2-1_55KEV_2023-04-15_final
2023-04-15 09:52:21	ga_s2bm_ard_3-2-1_55KEU_2023-04-15_final
2023-04-15 09:52:36	ga_s2bm_ard_3-2-1_55KET_2023-04-15_final
2023-04-15 09:52:50	ga_s2bm_ard_3-2-1_55KES_2023-04-15_final
2023-04-15 09:53:05	ga_s2bm_ard_3-2-1_55KER_2023-04-15_final
2023-04-15 09:53:19	ga_s2bm_ard_3-2-1_55KEQ_2023-04-15_final
2023-04-15 09:53:34	ga_s2bm_ard_3-2-1_55KEP_2023-04-15_final
2023-04-15 09:53:48	ga_s2bm_ard_3-2-1_55JEN_2023-04-15_final
2023-04-15 09:54:03	ga_s2bm_ard_3-2-1_55JEM_2023-04-15_final
2023-06-04 09:54:21	ga_s2bm_ard_3-2-1_55JEL_2023-06-04_final
2023-06-04 09:54:35	ga_s2bm_ard_3-2-1_55JEK_2023-06-04_final
2023-06-04 09:54:49	ga_s2bm_ard_3-2-1_55JEJ_2023-06-04_final
2023-06-04 09:55:01	ga_s2bm_ard_3-2-1_55JEH_2023-06-04_final
2023-06-04 09:55:08	ga_s2bm_ard_3-2-1_55JEH_2023-06-04_final
2023-06-04 09:55:18	ga_s2bm_ard_3-2-1_55JEG_2023-06-04_final
2023-06-05 09:28:53	ga_s2bm_ard_3-2-1_55GEN_2023-06-04_final
2023-06-05 09:29:03	ga_s2bm_ard_3-2-1_55GEM_2023-06-04_final
2023-06-11 09:45:53	ga_s2bm_ard_3-2-1_55HEE_2023-06-11_final
2023-06-11 09:46:07	ga_s2bm_ard_3-2-1_55HED_2023-06-11_final
2023-06-11 09:46:22	ga_s2bm_ard_3-2-1_55HEC_2023-06-11_final
2023-06-11 09:46:36	ga_s2bm_ard_3-2-1_55HEB_2023-06-11_final
2023-06-11 09:46:51	ga_s2bm_ard_3-2-1_55HEA_2023-06-11_final
2023-06-11 09:47:05	ga_s2bm_ard_3-2-1_55HEV_2023-06-11_final
2023-06-11 09:47:19	ga_s2bm_ard_3-2-1_55HEU_2023-06-11_final
2023-06-11 09:47:34	ga_s2bm_ard_3-2-1_55HET_2023-06-11_final
2023-06-11 09:47:48	ga_s2bm_ard_3-2-1_55HES_2023-06-11_final
2023-06-17 10:00:39	ga_s2bm_ard_3-2-1_55LEF_2023-06-17_nrt
2023-06-17 10:00:53	ga_s2bm_ard_3-2-1_55LEE_2023-06-17_nrt
2023-06-17 10:01:08	ga_s2bm_ard_3-2-1_55LED_2023-06-17_nrt
2023-06-17 10:01:22	ga_s2bm_ard_3-2-1_55LEC_2023-06-17_final
2023-06-17 10:01:37	ga_s2bm_ard_3-2-1_55KEB_2023-06-17_final
2023-06-17 10:01:51	ga_s2bm_ard_3-2-1_55KEA_2023-06-17_nrt
2023-06-17 10:02:06	ga_s2bm_ard_3-2-1_55KEV_2023-06-17_final
2023-06-17 10:02:20	ga_s2bm_ard_3-2-1_55KEU_2023-06-17_final
2023-06-24 09:52:10	ga_s2bm_ard_3-2-1_55KEV_2023-06-24_final
2023-06-24 09:52:24	ga_s2bm_ard_3-2-1_55KEU_2023-06-24_final
2023-06-24 09:52:39	ga_s2bm_ard_3-2-1_55KET_2023-06-24_final
2023-06-24 09:52:53	ga_s2bm_ard_3-2-1_55KES_2023-06-24_final
2023-06-24 09:53:08	ga_s2bm_ard_3-2-1_55KER_2023-06-24_final
2023-06-24 09:53:22	ga_s2bm_ard_3-2-1_55KEQ_2023-06-24_final
2023-06-24 09:53:37	ga_s2bm_ard_3-2-1_55KEP_2023-06-24_final
2023-06-24 09:53:51	ga_s2bm_ard_3-2-1_55JEN_2023-06-24_final
2023-06-24 09:54:06	ga_s2bm_ard_3-2-1_55JEM_2023-06-24_final
2023-06-24 09:54:20	ga_s2bm_ard_3-2-1_55JEL_2023-06-24_final
2023-06-24 09:54:35	ga_s2bm_ard_3-2-1_55JEK_2023-06-24_final
2023-06-24 09:54:49	ga_s2bm_ard_3-2-1_55JEJ_2023-06-24_final
2023-06-24 09:54:57	ga_s2bm_ard_3-2-1_55JEH_2023-06-24_final
2023-06-24 09:54:58	ga_s2bm_ard_3-2-1_55JEJ_2023-06-24_final
2023-06-24 09:55:04	ga_s2bm_ard_3-2-1_55JEH_2023-06-24_final
2023-06-24 09:55:18	ga_s2bm_ard_3-2-1_55JEG_2023-06-24_final
2023-06-25 09:28:53	ga_s2bm_ard_3-2-1_55GEN_2023-06-24_final

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

All years