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
2023-08-08 10:41:11	ga_s2bm_ard_3-2-1_53LQE_2023-08-08_final
2023-08-08 10:41:43	ga_s2bm_ard_3-2-1_53LPC_2023-08-08_final
2023-08-08 10:41:47	ga_s2bm_ard_3-2-1_53LNC_2023-08-08_final
2023-08-08 10:41:48	ga_s2bm_ard_3-2-1_54KTG_2023-08-08_final
2023-08-08 10:41:54	ga_s2bm_ard_3-2-1_53KQB_2023-08-08_final
2023-08-08 10:42:00	ga_s2bm_ard_3-2-1_53KNB_2023-08-08_final
2023-08-08 10:42:17	ga_s2bm_ard_3-2-1_53KRV_2023-08-08_final
2023-08-08 10:42:30	ga_s2bm_ard_3-2-1_53KNV_2023-08-08_final
2023-08-08 10:42:44	ga_s2bm_ard_3-2-1_53KNU_2023-08-08_final
2023-08-08 10:43:00	ga_s2bm_ard_3-2-1_53KQS_2023-08-08_final
2023-09-01 10:20:26	ga_s2bm_ard_3-2-1_54LZM_2023-09-01_final
2023-09-01 10:20:40	ga_s2bm_ard_3-2-1_54LZL_2023-09-01_final
2023-09-01 10:20:47	ga_s2bm_ard_3-2-1_54LXL_2023-09-01_final
2023-09-01 10:21:02	ga_s2bm_ard_3-2-1_54LXK_2023-09-01_final
2023-09-01 10:21:37	ga_s2bm_ard_3-2-1_54LVH_2023-09-01_final
2023-09-01 10:22:00	ga_s2bm_ard_3-2-1_54KXF_2023-09-01_final
2023-09-01 10:22:25	ga_s2bm_ard_3-2-1_54KWE_2023-09-01_final
2023-09-01 10:22:32	ga_s2bm_ard_3-2-1_54KWD_2023-09-01_final
2023-09-01 10:24:09	ga_s2bm_ard_3-2-1_53JRN_2023-09-01_final
2023-09-01 10:24:13	ga_s2bm_ard_3-2-1_54JWS_2023-09-01_final
2023-09-01 10:24:24	ga_s2bm_ard_3-2-1_54JTS_2023-09-01_final
2023-09-01 10:24:38	ga_s2bm_ard_3-2-1_54JTR_2023-09-01_final
2023-09-01 10:24:44	ga_s2bm_ard_3-2-1_53JQL_2023-09-01_final
2023-09-01 10:24:50	ga_s2bm_ard_3-2-1_54JUQ_2023-09-01_final
2023-09-01 10:25:04	ga_s2bm_ard_3-2-1_54JUP_2023-09-01_final
2023-09-01 10:25:15	ga_s2bm_ard_3-2-1_54JVN_2023-09-01_final
2023-09-01 10:25:54	ga_s2bm_ard_3-2-1_53JQF_2023-09-01_final
2023-09-01 10:26:41	ga_s2bm_ard_3-2-1_53HPC_2023-09-01_final
2023-09-01 10:26:51	ga_s2bm_ard_3-2-1_53HQB_2023-09-01_final
2023-09-01 10:26:55	ga_s2bm_ard_3-2-1_53HPB_2023-09-01_final
2023-09-01 12:03:24	ga_s2bm_ard_3-2-1_50KNC_2023-09-01_final
2023-09-01 12:04:11	ga_s2bm_ard_3-2-1_50KMV_2023-09-01_final
2023-09-01 12:04:15	ga_s2bm_ard_3-2-1_50KLV_2023-09-01_final
2023-09-01 12:04:18	ga_s2bm_ard_3-2-1_49KHQ_2023-09-01_final
2023-09-01 12:04:26	ga_s2bm_ard_3-2-1_50KMU_2023-09-01_final
2023-09-01 12:04:47	ga_s2bm_ard_3-2-1_50JKT_2023-09-01_final
2023-09-01 12:04:58	ga_s2bm_ard_3-2-1_50JLS_2023-09-01_final
2023-09-01 12:05:13	ga_s2bm_ard_3-2-1_50JLR_2023-09-01_final
2023-09-01 12:05:46	ga_s2bm_ard_3-2-1_50JKP_2023-09-01_final
2023-09-01 12:06:19	ga_s2bm_ard_3-2-1_50JLL_2023-09-01_final
2023-09-02 09:52:30	ga_s2bm_ard_3-2-1_55KFT_2023-09-02_final
2023-09-02 09:52:37	ga_s2bm_ard_3-2-1_55KFT_2023-09-02_final
2023-09-02 09:53:12	ga_s2bm_ard_3-2-1_55KDR_2023-09-02_final
2023-09-02 09:54:02	ga_s2bm_ard_3-2-1_55JCN_2023-09-02_final
2023-09-02 09:54:03	ga_s2bm_ard_3-2-1_55JFM_2023-09-02_final
2023-09-02 09:54:07	ga_s2bm_ard_3-2-1_55JEM_2023-09-02_final
2023-09-02 09:54:14	ga_s2bm_ard_3-2-1_55JCM_2023-09-02_final
2023-09-02 09:54:45	ga_s2bm_ard_3-2-1_55JFJ_2023-09-02_final
2023-09-02 09:54:55	ga_s2bm_ard_3-2-1_55JFH_2023-09-02_final
2023-09-02 09:55:26	ga_s2bm_ard_3-2-1_55JCG_2023-09-02_final
2023-09-02 09:56:15	ga_s2bm_ard_3-2-1_54HYJ_2023-09-02_final
2023-09-02 09:56:29	ga_s2bm_ard_3-2-1_54HYH_2023-09-02_final
2023-09-02 09:56:39	ga_s2bm_ard_3-2-1_55HCB_2023-09-02_final
2023-09-02 09:56:50	ga_s2bm_ard_3-2-1_54HXG_2023-09-02_final
2023-09-02 09:57:13	ga_s2bm_ard_3-2-1_55HDU_2023-09-02_final
2023-09-02 11:31:53	ga_s2bm_ard_3-2-1_51LZC_2023-09-02_final
2023-09-02 11:32:12	ga_s2bm_ard_3-2-1_51KYB_2023-09-02_final
2023-09-02 11:32:24	ga_s2bm_ard_3-2-1_51KVB_2023-09-02_final
2023-09-02 11:32:41	ga_s2bm_ard_3-2-1_51KYV_2023-09-02_final
2023-09-02 11:33:28	ga_s2bm_ard_3-2-1_51KXS_2023-09-02_final
2023-09-02 11:33:53	ga_s2bm_ard_3-2-1_51KUR_2023-09-02_final
2023-09-02 11:34:08	ga_s2bm_ard_3-2-1_51KUQ_2023-09-02_final
2023-09-02 11:34:19	ga_s2bm_ard_3-2-1_51KVP_2023-09-02_final
2023-09-02 11:34:41	ga_s2bm_ard_3-2-1_51JTN_2023-09-02_final
2023-09-02 11:34:41	ga_s2bm_ard_3-2-1_50JRT_2023-09-02_final
2023-09-02 11:35:55	ga_s2bm_ard_3-2-1_50JQN_2023-09-02_final
2023-09-02 11:36:23	ga_s2bm_ard_3-2-1_51JVF_2023-09-02_final
2023-09-02 11:36:38	ga_s2bm_ard_3-2-1_51HVD_2023-09-02_final
2023-09-02 11:36:57	ga_s2bm_ard_3-2-1_50HPJ_2023-09-02_final
2023-09-11 12:00:44	ga_s2bm_ard_3-2-1_50LNP_2023-09-11_nrt
2023-09-11 12:00:48	ga_s2bm_ard_3-2-1_50LMP_2023-09-11_nrt
2023-09-11 12:00:58	ga_s2bm_ard_3-2-1_50LNN_2023-09-11_nrt
2023-09-11 12:01:01	ga_s2bm_ard_3-2-1_50LMN_2023-09-11_nrt
2023-09-11 12:01:13	ga_s2bm_ard_3-2-1_50LNM_2023-09-11_nrt
2023-09-11 12:01:16	ga_s2bm_ard_3-2-1_50LMM_2023-09-11_nrt
2023-09-11 12:01:27	ga_s2bm_ard_3-2-1_50LNL_2023-09-11_nrt
2023-09-11 12:01:31	ga_s2bm_ard_3-2-1_50LML_2023-09-11_nrt
2023-09-11 12:01:36	ga_s2bm_ard_3-2-1_50LPK_2023-09-11_nrt
2023-09-11 12:01:38	ga_s2bm_ard_3-2-1_50LNK_2023-09-11_nrt
2023-09-11 12:01:40	ga_s2bm_ard_3-2-1_50LMK_2023-09-11_nrt
2023-09-11 12:02:59	ga_s2bm_ard_3-2-1_50KNE_2023-09-11_nrt
2023-09-11 12:03:00	ga_s2bm_ard_3-2-1_50KME_2023-09-11_nrt
2023-09-11 12:03:02	ga_s2bm_ard_3-2-1_50KLE_2023-09-11_nrt
2023-09-11 12:03:09	ga_s2bm_ard_3-2-1_50KND_2023-09-11_nrt
2023-09-11 12:05:21	ga_s2bm_ard_3-2-1_49JFL_2023-09-11_nrt
2023-09-11 12:05:26	ga_s2bm_ard_3-2-1_49JFL_2023-09-11_nrt
2023-09-11 12:05:36	ga_s2bm_ard_3-2-1_49JFK_2023-09-11_nrt
2023-09-11 12:05:51	ga_s2bm_ard_3-2-1_49JFJ_2023-09-11_nrt
2023-09-11 12:06:06	ga_s2bm_ard_3-2-1_49JFH_2023-09-11_nrt
2023-09-11 12:06:20	ga_s2bm_ard_3-2-1_49JFG_2023-09-11_nrt
2023-09-11 12:06:28	ga_s2bm_ard_3-2-1_49JFF_2023-09-11_nrt
2023-09-12 09:50:02	ga_s2bm_ard_3-2-1_55LHH_2023-09-12_nrt
2023-09-12 09:50:08	ga_s2bm_ard_3-2-1_55LHG_2023-09-12_nrt
2023-09-12 09:51:44	ga_s2bm_ard_3-2-1_55KHA_2023-09-12_nrt
2023-09-12 09:51:48	ga_s2bm_ard_3-2-1_55KGA_2023-09-12_nrt
2023-09-12 09:51:59	ga_s2bm_ard_3-2-1_55KHV_2023-09-12_nrt
2023-09-12 09:52:02	ga_s2bm_ard_3-2-1_55KGV_2023-09-12_nrt
2023-09-12 09:52:13	ga_s2bm_ard_3-2-1_55KHU_2023-09-12_nrt
2023-09-12 09:52:27	ga_s2bm_ard_3-2-1_55KHT_2023-09-12_nrt
2023-09-12 09:52:35	ga_s2bm_ard_3-2-1_55KHT_2023-09-12_nrt

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