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
2023-11-24 10:07:17	ga_s2bm_ard_3-2-1_54HXD_2023-11-24_final
2023-11-25 09:34:36	ga_s2bm_ard_3-2-1_56JLP_2023-11-25_final
2023-11-25 11:13:24	ga_s2bm_ard_3-2-1_51KZS_2023-11-25_final
2023-11-25 11:16:36	ga_s2bm_ard_3-2-1_51HXD_2023-11-25_final
2023-11-27 10:12:50	ga_s2bm_ard_3-2-1_54KYB_2023-11-27_final
2023-11-27 10:15:04	ga_s2bm_ard_3-2-1_54JXN_2023-11-27_final
2023-11-27 11:53:21	ga_s2bm_ard_3-2-1_50KNC_2023-11-27_final
2023-11-27 11:54:41	ga_s2bm_ard_3-2-1_50JLT_2023-11-27_final
2023-11-28 09:42:39	ga_s2bm_ard_3-2-1_56KKB_2023-11-28_final
2023-11-28 09:46:02	ga_s2bm_ard_3-2-1_55HDD_2023-11-28_final
2023-11-28 09:47:00	ga_s2bm_ard_3-2-1_55HDV_2023-11-28_final
2023-11-28 11:20:54	ga_s2bm_ard_3-2-1_52LEL_2023-11-28_final
2023-11-28 11:21:55	ga_s2bm_ard_3-2-1_51LYC_2023-11-28_final
2023-11-28 11:24:08	ga_s2bm_ard_3-2-1_51KXP_2023-11-28_final
2023-11-28 11:24:26	ga_s2bm_ard_3-2-1_51JWN_2023-11-28_final
2023-11-28 11:26:22	ga_s2bm_ard_3-2-1_51HWE_2023-11-28_final
2023-11-29 10:52:23	ga_s2bm_ard_3-2-1_53KLV_2023-11-29_final
2023-11-30 10:19:52	ga_s2bm_ard_3-2-1_54LYP_2023-11-30_final
2023-11-30 10:21:08	ga_s2bm_ard_3-2-1_54LXJ_2023-11-30_final
2023-11-30 10:21:18	ga_s2bm_ard_3-2-1_54LVJ_2023-11-30_final
2023-11-30 10:23:22	ga_s2bm_ard_3-2-1_54KWV_2023-11-30_final
2023-11-30 10:24:31	ga_s2bm_ard_3-2-1_54JTR_2023-11-30_final
2023-11-30 10:24:56	ga_s2bm_ard_3-2-1_54JUP_2023-11-30_final
2023-11-30 12:03:41	ga_s2bm_ard_3-2-1_49KHS_2023-11-30_final
2023-11-30 12:03:53	ga_s2bm_ard_3-2-1_50KLA_2023-11-30_final
2023-11-30 12:04:36	ga_s2bm_ard_3-2-1_50JLT_2023-11-30_final
2023-11-30 12:04:54	ga_s2bm_ard_3-2-1_49JHM_2023-11-30_final
2023-11-30 12:04:54	ga_s2bm_ard_3-2-1_50JKS_2023-11-30_final
2023-12-01 09:51:23	ga_s2bm_ard_3-2-1_55KHB_2023-12-01_final
2023-12-01 09:51:27	ga_s2bm_ard_3-2-1_55KGB_2023-12-01_final
2023-12-01 09:52:10	ga_s2bm_ard_3-2-1_55KGU_2023-12-01_final
2023-12-01 09:52:46	ga_s2bm_ard_3-2-1_55KES_2023-12-01_final
2023-12-01 09:53:01	ga_s2bm_ard_3-2-1_55KER_2023-12-01_final
2023-12-01 09:53:18	ga_s2bm_ard_3-2-1_55KDQ_2023-12-01_final
2023-12-01 09:54:15	ga_s2bm_ard_3-2-1_55JFK_2023-12-01_final
2023-12-01 09:54:16	ga_s2bm_ard_3-2-1_55JFL_2023-12-01_final
2023-12-01 09:57:23	ga_s2bm_ard_3-2-1_54HXD_2023-12-01_final
2023-12-01 09:57:44	ga_s2bm_ard_3-2-1_55HCS_2023-12-01_final
2023-12-01 09:58:11	ga_s2bm_ard_3-2-1_55GCQ_2023-12-01_final
2023-12-01 11:31:28	ga_s2bm_ard_3-2-1_51LWE_2023-12-01_final
2023-12-01 11:32:17	ga_s2bm_ard_3-2-1_51KVB_2023-12-01_final
2023-12-01 11:32:23	ga_s2bm_ard_3-2-1_51KXA_2023-12-01_final
2023-12-01 11:32:37	ga_s2bm_ard_3-2-1_51KXV_2023-12-01_final
2023-12-01 11:32:47	ga_s2bm_ard_3-2-1_51KYU_2023-12-01_final
2023-12-01 11:33:13	ga_s2bm_ard_3-2-1_51KVT_2023-12-01_final
2023-12-01 11:33:42	ga_s2bm_ard_3-2-1_51KVR_2023-12-01_final
2023-12-01 11:34:02	ga_s2bm_ard_3-2-1_51KXP_2023-12-01_final
2023-12-01 11:34:11	ga_s2bm_ard_3-2-1_51KVP_2023-12-01_final
2023-12-01 11:34:12	ga_s2bm_ard_3-2-1_51JXN_2023-12-01_final
2023-12-01 11:34:58	ga_s2bm_ard_3-2-1_51JUL_2023-12-01_final
2023-12-01 11:35:09	ga_s2bm_ard_3-2-1_51JVK_2023-12-01_final
2023-12-01 11:35:14	ga_s2bm_ard_3-2-1_51JTK_2023-12-01_final
2023-12-01 11:35:16	ga_s2bm_ard_3-2-1_51JWJ_2023-12-01_final
2023-12-01 11:35:19	ga_s2bm_ard_3-2-1_51JWJ_2023-12-01_final
2023-12-01 11:35:24	ga_s2bm_ard_3-2-1_51JVJ_2023-12-01_final
2023-12-01 11:35:27	ga_s2bm_ard_3-2-1_51JUJ_2023-12-01_final
2023-12-01 11:36:14	ga_s2bm_ard_3-2-1_51JTF_2023-12-01_final
2023-12-01 11:36:20	ga_s2bm_ard_3-2-1_51HVE_2023-12-01_final
2023-12-01 11:37:00	ga_s2bm_ard_3-2-1_50HQH_2023-12-01_final
2023-12-01 11:37:04	ga_s2bm_ard_3-2-1_50HPH_2023-12-01_final
2023-12-01 11:37:18	ga_s2bm_ard_3-2-1_50HPG_2023-12-01_final
2023-12-02 09:25:04	ga_s2bm_ard_3-2-1_56JNM_2023-12-01_final
2023-12-02 09:25:19	ga_s2bm_ard_3-2-1_56JNL_2023-12-01_final
2023-12-02 09:28:28	ga_s2bm_ard_3-2-1_55GFP_2023-12-01_final
2023-12-02 09:28:41	ga_s2bm_ard_3-2-1_55GFN_2023-12-01_final
2023-12-02 09:28:48	ga_s2bm_ard_3-2-1_55GFN_2023-12-01_final
2023-12-02 11:00:11	ga_s2bm_ard_3-2-1_53LKJ_2023-12-02_final
2023-12-02 11:00:33	ga_s2bm_ard_3-2-1_53LMG_2023-12-02_final
2023-12-02 11:01:14	ga_s2bm_ard_3-2-1_52LGK_2023-12-02_final
2023-12-02 11:01:49	ga_s2bm_ard_3-2-1_53KLB_2023-12-02_final
2023-12-02 11:01:53	ga_s2bm_ard_3-2-1_53KKB_2023-12-02_final
2023-12-02 11:02:59	ga_s2bm_ard_3-2-1_52KFC_2023-12-02_final
2023-12-02 11:04:08	ga_s2bm_ard_3-2-1_52JGT_2023-12-02_final
2023-12-02 11:04:30	ga_s2bm_ard_3-2-1_52JES_2023-12-02_final
2023-12-02 11:04:55	ga_s2bm_ard_3-2-1_52JFQ_2023-12-02_final
2023-12-02 11:05:20	ga_s2bm_ard_3-2-1_52JCP_2023-12-02_final
2023-12-02 11:05:31	ga_s2bm_ard_3-2-1_52JDN_2023-12-02_final
2023-12-02 11:05:54	ga_s2bm_ard_3-2-1_52JEL_2023-12-02_final
2023-12-02 11:05:55	ga_s2bm_ard_3-2-1_52JBM_2023-12-02_final
2023-12-02 11:06:15	ga_s2bm_ard_3-2-1_52HDK_2023-12-02_final
2023-12-11 11:31:08	ga_s2bm_ard_3-2-1_51LYF_2023-12-11_nrt
2023-12-12 09:25:29	ga_s2bm_ard_3-2-1_56HPK_2023-12-11_nrt
2023-12-12 09:25:33	ga_s2bm_ard_3-2-1_56HNK_2023-12-11_nrt
2023-12-12 09:25:44	ga_s2bm_ard_3-2-1_56HPJ_2023-12-11_nrt
2023-12-12 09:25:48	ga_s2bm_ard_3-2-1_56HNJ_2023-12-11_nrt
2023-12-12 09:25:58	ga_s2bm_ard_3-2-1_56HPH_2023-12-11_nrt
2023-12-12 09:26:02	ga_s2bm_ard_3-2-1_56HNH_2023-12-11_nrt
2023-12-12 09:26:09	ga_s2bm_ard_3-2-1_56HPG_2023-12-11_nrt
2023-12-12 09:26:16	ga_s2bm_ard_3-2-1_56HNG_2023-12-11_nrt
2023-12-12 09:26:31	ga_s2bm_ard_3-2-1_56HNF_2023-12-11_nrt
2023-12-12 09:27:26	ga_s2bm_ard_3-2-1_55HGT_2023-12-11_nrt
2023-12-12 09:27:40	ga_s2bm_ard_3-2-1_55HGS_2023-12-11_nrt
2023-12-12 09:27:51	ga_s2bm_ard_3-2-1_56GLA_2023-12-11_nrt
2023-12-12 09:27:54	ga_s2bm_ard_3-2-1_56GKA_2023-12-11_nrt
2023-12-12 09:28:09	ga_s2bm_ard_3-2-1_56GKV_2023-12-11_nrt
2023-12-12 09:28:23	ga_s2bm_ard_3-2-1_56GKU_2023-12-11_nrt
2023-12-12 09:28:34	ga_s2bm_ard_3-2-1_56GLT_2023-12-11_nrt
2023-12-12 09:28:49	ga_s2bm_ard_3-2-1_56GLS_2023-12-11_nrt
2023-12-12 09:28:54	ga_s2bm_ard_3-2-1_55GFM_2023-12-11_nrt
2023-12-12 11:00:08	ga_s2bm_ard_3-2-1_53LLJ_2023-12-12_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