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
2023-09-30 10:50:08	ga_s2bm_ard_3-2-1_53LPJ_2023-09-30_nrt
2023-09-30 10:50:23	ga_s2bm_ard_3-2-1_53LPH_2023-09-30_final
2023-09-30 10:50:37	ga_s2bm_ard_3-2-1_53LPG_2023-09-30_final
2023-09-30 10:50:51	ga_s2bm_ard_3-2-1_53LPF_2023-09-30_final
2023-10-01 10:26:09	ga_s2bm_ard_3-2-1_53HPE_2023-10-01_final
2023-10-01 10:26:23	ga_s2bm_ard_3-2-1_53HPD_2023-10-01_final
2023-10-01 10:26:38	ga_s2bm_ard_3-2-1_53HPC_2023-10-01_final
2023-10-01 10:26:52	ga_s2bm_ard_3-2-1_53HPB_2023-10-01_final
2023-10-01 10:27:07	ga_s2bm_ard_3-2-1_53HPA_2023-10-01_final
2023-10-01 10:27:16	ga_s2bm_ard_3-2-1_53HPV_2023-10-01_final
2023-10-04 10:33:38	ga_s2bm_ard_3-2-1_53KPQ_2023-10-04_final
2023-10-04 10:33:53	ga_s2bm_ard_3-2-1_53KPP_2023-10-04_final
2023-10-04 10:34:08	ga_s2bm_ard_3-2-1_53JPN_2023-10-04_final
2023-10-04 10:34:22	ga_s2bm_ard_3-2-1_53JPM_2023-10-04_final
2023-10-04 10:34:37	ga_s2bm_ard_3-2-1_53JPL_2023-10-04_final
2023-10-04 10:34:51	ga_s2bm_ard_3-2-1_53JPK_2023-10-04_final
2023-10-04 10:35:06	ga_s2bm_ard_3-2-1_53JPJ_2023-10-04_final
2023-10-04 10:35:20	ga_s2bm_ard_3-2-1_53JPH_2023-10-04_final
2023-10-04 10:35:35	ga_s2bm_ard_3-2-1_53JPG_2023-10-04_final
2023-10-04 10:35:49	ga_s2bm_ard_3-2-1_53JPF_2023-10-04_final
2023-10-04 10:36:03	ga_s2bm_ard_3-2-1_53HPE_2023-10-04_final
2023-10-07 10:40:40	ga_s2bm_ard_3-2-1_53LPG_2023-10-07_final
2023-10-07 10:40:50	ga_s2bm_ard_3-2-1_53LPF_2023-10-07_final
2023-10-07 10:40:57	ga_s2bm_ard_3-2-1_53LPF_2023-10-07_final
2023-10-07 10:41:09	ga_s2bm_ard_3-2-1_53LPE_2023-10-07_final
2023-10-07 10:41:24	ga_s2bm_ard_3-2-1_53LPD_2023-10-07_final
2023-10-07 10:41:38	ga_s2bm_ard_3-2-1_53LPC_2023-10-07_final
2023-10-07 10:41:53	ga_s2bm_ard_3-2-1_53KPB_2023-10-07_final
2023-10-11 10:26:09	ga_s2bm_ard_3-2-1_53HPE_2023-10-11_final
2023-10-14 10:34:38	ga_s2bm_ard_3-2-1_53JPL_2023-10-14_final
2023-10-14 10:34:53	ga_s2bm_ard_3-2-1_53JPK_2023-10-14_final
2023-10-14 10:35:07	ga_s2bm_ard_3-2-1_53JPJ_2023-10-14_final
2023-10-14 10:35:22	ga_s2bm_ard_3-2-1_53JPH_2023-10-14_final
2023-10-14 10:35:36	ga_s2bm_ard_3-2-1_53JPG_2023-10-14_final
2023-10-14 10:35:51	ga_s2bm_ard_3-2-1_53JPF_2023-10-14_final
2023-10-14 10:36:05	ga_s2bm_ard_3-2-1_53HPE_2023-10-14_final
2023-10-14 10:36:19	ga_s2bm_ard_3-2-1_53HPD_2023-10-14_final
2023-10-14 10:36:34	ga_s2bm_ard_3-2-1_53HPC_2023-10-14_final
2023-10-14 10:36:48	ga_s2bm_ard_3-2-1_53HPB_2023-10-14_final
2023-10-17 10:40:42	ga_s2bm_ard_3-2-1_53LPG_2023-10-17_final
2023-10-17 10:40:52	ga_s2bm_ard_3-2-1_53LPF_2023-10-17_final
2023-10-17 10:40:59	ga_s2bm_ard_3-2-1_53LPF_2023-10-17_final
2023-10-17 10:41:11	ga_s2bm_ard_3-2-1_53LPE_2023-10-17_final
2023-10-17 10:41:26	ga_s2bm_ard_3-2-1_53LPD_2023-10-17_final
2023-10-17 10:41:40	ga_s2bm_ard_3-2-1_53LPC_2023-10-17_final
2023-10-17 10:41:55	ga_s2bm_ard_3-2-1_53KPB_2023-10-17_final
2023-10-17 10:42:09	ga_s2bm_ard_3-2-1_53KPA_2023-10-17_final
2023-10-17 10:42:24	ga_s2bm_ard_3-2-1_53KPV_2023-10-17_final
2023-10-17 10:42:38	ga_s2bm_ard_3-2-1_53KPU_2023-10-17_final
2023-10-17 10:42:51	ga_s2bm_ard_3-2-1_53KPT_2023-10-17_final
2023-10-17 10:42:58	ga_s2bm_ard_3-2-1_53KPT_2023-10-17_final
2023-10-17 10:43:07	ga_s2bm_ard_3-2-1_53KPS_2023-10-17_final
2023-10-17 10:43:21	ga_s2bm_ard_3-2-1_53KPR_2023-10-17_final
2023-10-17 10:43:36	ga_s2bm_ard_3-2-1_53KPQ_2023-10-17_final
2023-10-17 10:43:50	ga_s2bm_ard_3-2-1_53KPP_2023-10-17_final
2023-10-17 10:44:05	ga_s2bm_ard_3-2-1_53JPN_2023-10-17_final
2024-01-02 10:36:18	ga_s2bm_ard_3-2-1_53HPD_2024-01-02_final
2024-01-02 10:36:33	ga_s2bm_ard_3-2-1_53HPC_2024-01-02_final
2024-01-02 10:36:47	ga_s2bm_ard_3-2-1_53HPB_2024-01-02_final
2024-01-05 10:40:40	ga_s2bm_ard_3-2-1_53LPG_2024-01-05_final
2024-01-05 10:40:54	ga_s2bm_ard_3-2-1_53LPF_2024-01-05_final
2024-01-05 10:41:09	ga_s2bm_ard_3-2-1_53LPE_2024-01-05_final
2024-01-05 10:41:23	ga_s2bm_ard_3-2-1_53LPD_2024-01-05_final
2024-01-05 10:41:38	ga_s2bm_ard_3-2-1_53LPC_2024-01-05_final
2024-01-05 10:41:52	ga_s2bm_ard_3-2-1_53KPB_2024-01-05_final
2024-01-05 10:42:07	ga_s2bm_ard_3-2-1_53KPA_2024-01-05_final
2024-01-05 10:42:21	ga_s2bm_ard_3-2-1_53KPV_2024-01-05_final
2024-01-05 10:42:36	ga_s2bm_ard_3-2-1_53KPU_2024-01-05_final
2024-01-05 10:42:50	ga_s2bm_ard_3-2-1_53KPT_2024-01-05_final
2024-01-05 10:43:05	ga_s2bm_ard_3-2-1_53KPS_2024-01-05_final
2024-01-05 10:43:19	ga_s2bm_ard_3-2-1_53KPR_2024-01-05_final
2024-01-05 10:43:33	ga_s2bm_ard_3-2-1_53KPQ_2024-01-05_final
2024-01-05 10:43:42	ga_s2bm_ard_3-2-1_53KPQ_2024-01-05_final
2024-01-05 10:43:42	ga_s2bm_ard_3-2-1_53KPP_2024-01-05_final
2024-01-05 10:43:48	ga_s2bm_ard_3-2-1_53KPP_2024-01-05_final
2024-01-05 10:44:03	ga_s2bm_ard_3-2-1_53JPN_2024-01-05_final
2024-01-08 10:50:05	ga_s2bm_ard_3-2-1_53LPJ_2024-01-08_nrt
2024-01-08 10:50:19	ga_s2bm_ard_3-2-1_53LPH_2024-01-08_final
2024-01-08 10:50:34	ga_s2bm_ard_3-2-1_53LPG_2024-01-08_final
2024-01-08 10:50:48	ga_s2bm_ard_3-2-1_53LPF_2024-01-08_final
2024-01-09 10:26:06	ga_s2bm_ard_3-2-1_53HPE_2024-01-09_final
2024-01-09 10:26:19	ga_s2bm_ard_3-2-1_53HPD_2024-01-09_final
2024-01-09 10:26:26	ga_s2bm_ard_3-2-1_53HPD_2024-01-09_final
2024-01-09 10:26:35	ga_s2bm_ard_3-2-1_53HPC_2024-01-09_final
2024-01-09 10:26:49	ga_s2bm_ard_3-2-1_53HPB_2024-01-09_final
2024-01-09 10:27:04	ga_s2bm_ard_3-2-1_53HPA_2024-01-09_final
2024-01-09 10:27:13	ga_s2bm_ard_3-2-1_53HPV_2024-01-09_final
2024-01-25 10:40:53	ga_s2bm_ard_3-2-1_53LPF_2024-01-25_final
2024-01-25 10:41:08	ga_s2bm_ard_3-2-1_53LPE_2024-01-25_final
2024-01-25 10:41:22	ga_s2bm_ard_3-2-1_53LPD_2024-01-25_final
2024-01-25 10:41:37	ga_s2bm_ard_3-2-1_53LPC_2024-01-25_final
2024-01-25 10:41:51	ga_s2bm_ard_3-2-1_53KPB_2024-01-25_final
2024-01-25 10:42:06	ga_s2bm_ard_3-2-1_53KPA_2024-01-25_final
2024-01-25 10:42:20	ga_s2bm_ard_3-2-1_53KPV_2024-01-25_final
2024-01-25 10:42:28	ga_s2bm_ard_3-2-1_53KPU_2024-01-25_final
2024-01-25 10:42:28	ga_s2bm_ard_3-2-1_53KPV_2024-01-25_final
2024-01-25 10:42:35	ga_s2bm_ard_3-2-1_53KPU_2024-01-25_final
2024-01-25 10:42:49	ga_s2bm_ard_3-2-1_53KPT_2024-01-25_final
2024-01-25 10:43:04	ga_s2bm_ard_3-2-1_53KPS_2024-01-25_final
2024-01-25 10:43:18	ga_s2bm_ard_3-2-1_53KPR_2024-01-25_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