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
2022-11-25 12:04:17	ga_s2bm_ard_3-2-1_49KGQ_2022-11-25_final.stac-item
2022-11-25 12:04:21	ga_s2bm_ard_3-2-1_50KMU_2022-11-25_final.stac-item
2022-11-25 12:04:24	ga_s2bm_ard_3-2-1_50KLU_2022-11-25_final.stac-item
2022-11-25 12:04:27	ga_s2bm_ard_3-2-1_49KHP_2022-11-25_final.stac-item
2022-11-25 12:04:27	ga_s2bm_ard_3-2-1_50KKU_2022-11-25_final.stac-item
2022-11-25 12:04:30	ga_s2bm_ard_3-2-1_49KGP_2022-11-25_final.stac-item
2022-11-26 09:52:05	ga_s2bm_ard_3-2-1_55KEV_2022-11-26_final.stac-item
2022-11-26 09:52:13	ga_s2bm_ard_3-2-1_55KGU_2022-11-26_final.stac-item
2022-11-26 09:52:16	ga_s2bm_ard_3-2-1_55KFU_2022-11-26_final.stac-item
2022-11-26 09:52:19	ga_s2bm_ard_3-2-1_55KEU_2022-11-26_final.stac-item
2022-11-26 09:52:27	ga_s2bm_ard_3-2-1_55KGT_2022-11-26_final.stac-item
2022-11-26 09:52:31	ga_s2bm_ard_3-2-1_55KFT_2022-11-26_final.stac-item
2022-11-26 09:52:34	ga_s2bm_ard_3-2-1_55KET_2022-11-26_final.stac-item
2022-11-26 09:52:34	ga_s2bm_ard_3-2-1_55KHS_2022-11-26_final.stac-item
2022-11-26 09:52:41	ga_s2bm_ard_3-2-1_55KGS_2022-11-26_final.stac-item
2022-11-26 09:52:45	ga_s2bm_ard_3-2-1_55KFS_2022-11-26_final.stac-item
2022-11-26 09:52:49	ga_s2bm_ard_3-2-1_55KES_2022-11-26_final.stac-item
2022-11-26 09:52:54	ga_s2bm_ard_3-2-1_55KDS_2022-11-26_final.stac-item
2022-11-26 09:52:56	ga_s2bm_ard_3-2-1_55KGR_2022-11-26_final.stac-item
2022-11-26 09:53:00	ga_s2bm_ard_3-2-1_55KFR_2022-11-26_final.stac-item
2022-11-26 09:53:03	ga_s2bm_ard_3-2-1_55KER_2022-11-26_final.stac-item
2022-11-26 09:53:06	ga_s2bm_ard_3-2-1_55KDR_2022-11-26_final.stac-item
2022-11-26 09:53:10	ga_s2bm_ard_3-2-1_55KGQ_2022-11-26_final.stac-item
2022-11-26 09:53:14	ga_s2bm_ard_3-2-1_55KFQ_2022-11-26_final.stac-item
2022-11-26 09:53:17	ga_s2bm_ard_3-2-1_55KEQ_2022-11-26_final.stac-item
2022-11-26 09:53:20	ga_s2bm_ard_3-2-1_55KDQ_2022-11-26_final.stac-item
2022-11-26 09:53:24	ga_s2bm_ard_3-2-1_55KGP_2022-11-26_final.stac-item
2022-11-26 09:53:29	ga_s2bm_ard_3-2-1_55KFP_2022-11-26_final.stac-item
2022-11-26 09:53:32	ga_s2bm_ard_3-2-1_55KEP_2022-11-26_final.stac-item
2022-11-26 09:53:35	ga_s2bm_ard_3-2-1_55KDP_2022-11-26_final.stac-item
2022-11-26 09:53:37	ga_s2bm_ard_3-2-1_55JGN_2022-11-26_final.stac-item
2022-11-26 09:53:43	ga_s2bm_ard_3-2-1_55JFN_2022-11-26_final.stac-item
2022-11-26 09:53:47	ga_s2bm_ard_3-2-1_55JEN_2022-11-26_final.stac-item
2022-11-26 09:53:50	ga_s2bm_ard_3-2-1_55JDN_2022-11-26_final.stac-item
2022-11-26 09:53:57	ga_s2bm_ard_3-2-1_55JCN_2022-11-26_final.stac-item
2022-11-26 09:53:57	ga_s2bm_ard_3-2-1_55JFM_2022-11-26_final.stac-item
2022-11-26 09:54:01	ga_s2bm_ard_3-2-1_55JEM_2022-11-26_final.stac-item
2022-11-26 09:54:04	ga_s2bm_ard_3-2-1_55JDM_2022-11-26_final.stac-item
2022-11-26 09:54:08	ga_s2bm_ard_3-2-1_55JCM_2022-11-26_final.stac-item
2022-11-26 09:54:12	ga_s2bm_ard_3-2-1_55JFL_2022-11-26_final.stac-item
2022-11-26 09:54:16	ga_s2bm_ard_3-2-1_55JEL_2022-11-26_final.stac-item
2022-11-26 09:54:19	ga_s2bm_ard_3-2-1_55JDL_2022-11-26_final.stac-item
2022-11-26 09:54:22	ga_s2bm_ard_3-2-1_55JCL_2022-11-26_final.stac-item
2022-11-26 09:55:23	ga_s2bm_ard_3-2-1_55JBG_2022-11-26_final.stac-item
2022-11-26 09:55:38	ga_s2bm_ard_3-2-1_55JBF_2022-11-26_final.stac-item
2022-11-26 09:55:41	ga_s2bm_ard_3-2-1_55HEE_2022-11-26_final.stac-item
2022-11-26 09:55:43	ga_s2bm_ard_3-2-1_55HDE_2022-11-26_final.stac-item
2022-11-26 09:55:45	ga_s2bm_ard_3-2-1_55HCE_2022-11-26_final.stac-item
2022-11-26 09:55:47	ga_s2bm_ard_3-2-1_55HBE_2022-11-26_final.stac-item
2022-11-26 09:55:48	ga_s2bm_ard_3-2-1_55HEE_2022-11-26_final.stac-item
2022-11-26 09:55:48	ga_s2bm_ard_3-2-1_54HYK_2022-11-26_final.stac-item
2022-11-26 09:55:50	ga_s2bm_ard_3-2-1_55HDE_2022-11-26_final.stac-item
2022-11-26 09:55:52	ga_s2bm_ard_3-2-1_55HCE_2022-11-26_final.stac-item
2022-11-26 09:55:53	ga_s2bm_ard_3-2-1_55HED_2022-11-26_final.stac-item
2022-11-26 09:55:53	ga_s2bm_ard_3-2-1_55HBE_2022-11-26_final.stac-item
2022-11-26 09:55:56	ga_s2bm_ard_3-2-1_54HYK_2022-11-26_final.stac-item
2022-11-26 09:56:00	ga_s2bm_ard_3-2-1_55HDD_2022-11-26_final.stac-item
2022-11-26 09:56:04	ga_s2bm_ard_3-2-1_55HCD_2022-11-26_final.stac-item
2022-11-26 09:56:07	ga_s2bm_ard_3-2-1_55HBD_2022-11-26_final.stac-item
2022-11-26 09:56:09	ga_s2bm_ard_3-2-1_54HYJ_2022-11-26_final.stac-item
2022-11-26 09:56:15	ga_s2bm_ard_3-2-1_55HDC_2022-11-26_final.stac-item
2022-11-26 09:56:19	ga_s2bm_ard_3-2-1_55HCC_2022-11-26_final.stac-item
2022-11-26 09:56:22	ga_s2bm_ard_3-2-1_55HBC_2022-11-26_final.stac-item
2022-11-26 09:56:24	ga_s2bm_ard_3-2-1_54HYH_2022-11-26_final.stac-item
2022-11-26 09:56:30	ga_s2bm_ard_3-2-1_55HDB_2022-11-26_final.stac-item
2022-11-26 09:56:33	ga_s2bm_ard_3-2-1_55HCB_2022-11-26_final.stac-item
2022-11-26 09:56:36	ga_s2bm_ard_3-2-1_55HBB_2022-11-26_final.stac-item
2022-11-26 09:56:38	ga_s2bm_ard_3-2-1_54HYG_2022-11-26_final.stac-item
2022-11-26 11:35:11	ga_s2bm_ard_3-2-1_51JVK_2022-11-26_final.stac-item
2022-11-26 11:35:15	ga_s2bm_ard_3-2-1_51JUK_2022-11-26_final.stac-item
2022-11-26 11:35:18	ga_s2bm_ard_3-2-1_51JTK_2022-11-26_final.stac-item
2022-11-26 11:35:18	ga_s2bm_ard_3-2-1_51JWJ_2022-11-26_final.stac-item
2022-11-26 11:35:26	ga_s2bm_ard_3-2-1_51JVJ_2022-11-26_final.stac-item
2022-11-26 11:35:29	ga_s2bm_ard_3-2-1_51JUJ_2022-11-26_final.stac-item
2022-11-26 11:35:33	ga_s2bm_ard_3-2-1_51JTJ_2022-11-26_final.stac-item
2022-11-26 11:35:36	ga_s2bm_ard_3-2-1_50JQP_2022-11-26_final.stac-item
2022-11-26 11:35:40	ga_s2bm_ard_3-2-1_51JVH_2022-11-26_final.stac-item
2022-11-26 11:35:44	ga_s2bm_ard_3-2-1_51JUH_2022-11-26_final.stac-item
2022-11-26 11:35:47	ga_s2bm_ard_3-2-1_51JTH_2022-11-26_final.stac-item
2022-11-26 11:35:50	ga_s2bm_ard_3-2-1_50JQN_2022-11-26_final.stac-item
2022-11-26 11:35:55	ga_s2bm_ard_3-2-1_51JVG_2022-11-26_final.stac-item
2022-11-26 11:35:58	ga_s2bm_ard_3-2-1_51JUG_2022-11-26_final.stac-item
2022-11-26 11:36:02	ga_s2bm_ard_3-2-1_51JTG_2022-11-26_final.stac-item
2022-11-26 11:36:04	ga_s2bm_ard_3-2-1_50JQM_2022-11-26_final.stac-item
2022-11-26 11:36:09	ga_s2bm_ard_3-2-1_51JVF_2022-11-26_final.stac-item
2022-11-26 11:36:13	ga_s2bm_ard_3-2-1_51JUF_2022-11-26_final.stac-item
2022-11-26 11:36:16	ga_s2bm_ard_3-2-1_51JTF_2022-11-26_final.stac-item
2022-11-26 11:36:19	ga_s2bm_ard_3-2-1_50JQL_2022-11-26_final.stac-item
2022-11-26 11:36:23	ga_s2bm_ard_3-2-1_51HVE_2022-11-26_final.stac-item
2022-11-26 11:36:26	ga_s2bm_ard_3-2-1_50JPL_2022-11-26_final.stac-item
2022-11-26 11:36:27	ga_s2bm_ard_3-2-1_51HUE_2022-11-26_final.stac-item
2022-11-26 11:36:31	ga_s2bm_ard_3-2-1_51HTE_2022-11-26_final.stac-item
2022-11-26 11:36:33	ga_s2bm_ard_3-2-1_51HVD_2022-11-26_final.stac-item
2022-11-26 11:36:33	ga_s2bm_ard_3-2-1_50HQK_2022-11-26_final.stac-item
2022-11-26 11:36:37	ga_s2bm_ard_3-2-1_50HPK_2022-11-26_final.stac-item
2022-11-26 11:36:42	ga_s2bm_ard_3-2-1_51HUD_2022-11-26_final.stac-item
2022-11-26 11:36:46	ga_s2bm_ard_3-2-1_51HTD_2022-11-26_final.stac-item
2022-11-26 11:36:48	ga_s2bm_ard_3-2-1_50HQJ_2022-11-26_final.stac-item
2022-11-26 11:36:51	ga_s2bm_ard_3-2-1_50HPJ_2022-11-26_final.stac-item
2022-11-26 11:36:57	ga_s2bm_ard_3-2-1_51HUC_2022-11-26_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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