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
2020-10-26 12:05:04	ga_s2bm_ard_3-2-1_49JGM_2020-10-26_final.stac-item
2020-10-26 12:05:11	ga_s2bm_ard_3-2-1_50JLR_2020-10-26_final.stac-item
2020-10-26 12:05:15	ga_s2bm_ard_3-2-1_50JKR_2020-10-26_final.stac-item
2020-10-26 12:05:18	ga_s2bm_ard_3-2-1_49JGL_2020-10-26_final.stac-item
2020-10-26 12:05:26	ga_s2bm_ard_3-2-1_50JLQ_2020-10-26_final.stac-item
2020-10-26 12:05:29	ga_s2bm_ard_3-2-1_50JKQ_2020-10-26_final.stac-item
2020-10-26 12:05:32	ga_s2bm_ard_3-2-1_49JGK_2020-10-26_final.stac-item
2020-10-26 12:05:41	ga_s2bm_ard_3-2-1_50JLP_2020-10-26_final.stac-item
2020-10-26 12:05:44	ga_s2bm_ard_3-2-1_50JKP_2020-10-26_final.stac-item
2020-10-26 12:05:47	ga_s2bm_ard_3-2-1_49JGJ_2020-10-26_final.stac-item
2020-10-26 12:05:55	ga_s2bm_ard_3-2-1_50JLN_2020-10-26_final.stac-item
2020-10-26 12:05:59	ga_s2bm_ard_3-2-1_50JKN_2020-10-26_final.stac-item
2020-10-26 12:06:01	ga_s2bm_ard_3-2-1_49JGH_2020-10-26_final
2020-10-26 12:06:07	ga_s2bm_ard_3-2-1_50JLM_2020-10-26_final.stac-item
2020-10-26 12:06:13	ga_s2bm_ard_3-2-1_50JKM_2020-10-26_final.stac-item
2020-10-26 12:06:17	ga_s2bm_ard_3-2-1_50JLL_2020-10-26_final.stac-item
2020-10-27 09:51:15	ga_s2bm_ard_3-2-1_55LHC_2020-10-27_final
2020-10-27 09:51:19	ga_s2bm_ard_3-2-1_55LGC_2020-10-27_final.stac-item
2020-10-27 09:51:22	ga_s2bm_ard_3-2-1_55LFC_2020-10-27_final.stac-item
2020-10-27 09:51:28	ga_s2bm_ard_3-2-1_56KKG_2020-10-27_final
2020-10-27 09:51:29	ga_s2bm_ard_3-2-1_55KHB_2020-10-27_final
2020-10-27 09:51:33	ga_s2bm_ard_3-2-1_55KGB_2020-10-27_final.stac-item
2020-10-27 09:51:37	ga_s2bm_ard_3-2-1_55KFB_2020-10-27_final.stac-item
2020-10-27 09:51:43	ga_s2bm_ard_3-2-1_56KKF_2020-10-27_final.stac-item
2020-10-27 09:51:51	ga_s2bm_ard_3-2-1_55KFA_2020-10-27_final.stac-item
2020-10-27 09:52:09	ga_s2bm_ard_3-2-1_55KEV_2020-10-27_final.stac-item
2020-10-27 09:52:17	ga_s2bm_ard_3-2-1_55KGU_2020-10-27_final.stac-item
2020-10-27 09:52:20	ga_s2bm_ard_3-2-1_55KFU_2020-10-27_final.stac-item
2020-10-27 09:52:23	ga_s2bm_ard_3-2-1_55KEU_2020-10-27_final.stac-item
2020-10-27 09:52:31	ga_s2bm_ard_3-2-1_55KGT_2020-10-27_final.stac-item
2020-10-27 09:52:35	ga_s2bm_ard_3-2-1_55KFT_2020-10-27_final.stac-item
2020-10-27 09:52:38	ga_s2bm_ard_3-2-1_55KET_2020-10-27_final.stac-item
2020-10-27 09:52:38	ga_s2bm_ard_3-2-1_55KHS_2020-10-27_final.stac-item
2020-10-27 09:52:45	ga_s2bm_ard_3-2-1_55KGS_2020-10-27_final.stac-item
2020-10-27 09:52:49	ga_s2bm_ard_3-2-1_55KFS_2020-10-27_final.stac-item
2020-10-27 09:52:52	ga_s2bm_ard_3-2-1_55KES_2020-10-27_final.stac-item
2020-10-27 09:52:59	ga_s2bm_ard_3-2-1_55KDS_2020-10-27_final.stac-item
2020-10-27 09:53:00	ga_s2bm_ard_3-2-1_55KGR_2020-10-27_final.stac-item
2020-10-27 09:53:04	ga_s2bm_ard_3-2-1_55KFR_2020-10-27_final.stac-item
2020-10-27 09:53:07	ga_s2bm_ard_3-2-1_55KER_2020-10-27_final.stac-item
2020-10-27 09:53:10	ga_s2bm_ard_3-2-1_55KDR_2020-10-27_final.stac-item
2020-10-27 09:53:14	ga_s2bm_ard_3-2-1_55KGQ_2020-10-27_final.stac-item
2020-10-27 09:53:18	ga_s2bm_ard_3-2-1_55KFQ_2020-10-27_final.stac-item
2020-10-27 09:53:21	ga_s2bm_ard_3-2-1_55KEQ_2020-10-27_final.stac-item
2020-10-27 09:53:24	ga_s2bm_ard_3-2-1_55KDQ_2020-10-27_final.stac-item
2020-10-27 09:53:28	ga_s2bm_ard_3-2-1_55KGP_2020-10-27_final.stac-item
2020-10-27 09:53:32	ga_s2bm_ard_3-2-1_55KFP_2020-10-27_final.stac-item
2020-10-27 09:53:36	ga_s2bm_ard_3-2-1_55KEP_2020-10-27_final.stac-item
2020-10-27 09:53:39	ga_s2bm_ard_3-2-1_55KDP_2020-10-27_final.stac-item
2020-10-27 09:53:41	ga_s2bm_ard_3-2-1_55JGN_2020-10-27_final.stac-item
2020-10-27 09:53:47	ga_s2bm_ard_3-2-1_55JFN_2020-10-27_final.stac-item
2020-10-27 09:53:51	ga_s2bm_ard_3-2-1_55JEN_2020-10-27_final.stac-item
2020-10-27 09:53:51	ga_s2bm_ard_3-2-1_55JGM_2020-10-27_final.stac-item
2020-10-27 09:53:54	ga_s2bm_ard_3-2-1_55JDN_2020-10-27_final.stac-item
2020-10-27 09:54:01	ga_s2bm_ard_3-2-1_55JCN_2020-10-27_final.stac-item
2020-10-27 09:54:01	ga_s2bm_ard_3-2-1_55JFM_2020-10-27_final.stac-item
2020-10-27 09:54:05	ga_s2bm_ard_3-2-1_55JEM_2020-10-27_final.stac-item
2020-10-27 09:54:08	ga_s2bm_ard_3-2-1_55JDM_2020-10-27_final.stac-item
2020-10-27 09:54:12	ga_s2bm_ard_3-2-1_55JCM_2020-10-27_final.stac-item
2020-10-27 09:54:16	ga_s2bm_ard_3-2-1_55JFL_2020-10-27_final.stac-item
2020-10-27 09:54:20	ga_s2bm_ard_3-2-1_55JEL_2020-10-27_final.stac-item
2020-10-27 09:54:23	ga_s2bm_ard_3-2-1_55JDL_2020-10-27_final.stac-item
2020-10-27 09:54:26	ga_s2bm_ard_3-2-1_55JCL_2020-10-27_final.stac-item
2020-10-27 09:54:30	ga_s2bm_ard_3-2-1_55JFK_2020-10-27_final.stac-item
2020-10-27 09:54:34	ga_s2bm_ard_3-2-1_55JEK_2020-10-27_final.stac-item
2020-10-27 09:54:38	ga_s2bm_ard_3-2-1_55JDK_2020-10-27_final.stac-item
2020-10-27 09:54:41	ga_s2bm_ard_3-2-1_55JCK_2020-10-27_final.stac-item
2020-10-27 09:54:43	ga_s2bm_ard_3-2-1_55JFJ_2020-10-27_final.stac-item
2020-10-27 09:54:48	ga_s2bm_ard_3-2-1_55JEJ_2020-10-27_final.stac-item
2020-10-27 09:54:52	ga_s2bm_ard_3-2-1_55JDJ_2020-10-27_final.stac-item
2020-10-27 09:54:54	ga_s2bm_ard_3-2-1_55JFH_2020-10-27_final.stac-item
2020-10-27 09:54:55	ga_s2bm_ard_3-2-1_55JCJ_2020-10-27_final.stac-item
2020-10-27 09:55:03	ga_s2bm_ard_3-2-1_55JEH_2020-10-27_final.stac-item
2020-10-27 09:55:07	ga_s2bm_ard_3-2-1_55JDH_2020-10-27_final.stac-item
2020-10-27 09:55:10	ga_s2bm_ard_3-2-1_55JCH_2020-10-27_final.stac-item
2020-10-27 09:55:14	ga_s2bm_ard_3-2-1_55JBH_2020-10-27_final.stac-item
2020-10-27 09:55:17	ga_s2bm_ard_3-2-1_55JEG_2020-10-27_final.stac-item
2020-10-27 09:55:21	ga_s2bm_ard_3-2-1_55JDG_2020-10-27_final.stac-item
2020-10-27 09:57:50	ga_s2bm_ard_3-2-1_55HCS_2020-10-27_final.stac-item
2020-10-27 09:57:53	ga_s2bm_ard_3-2-1_55HBS_2020-10-27_final.stac-item
2020-10-27 09:57:54	ga_s2bm_ard_3-2-1_54HYB_2020-10-27_final.stac-item
2020-10-27 09:58:04	ga_s2bm_ard_3-2-1_55GCR_2020-10-27_final.stac-item
2020-10-27 09:58:08	ga_s2bm_ard_3-2-1_55GBR_2020-10-27_final.stac-item
2020-10-27 09:58:08	ga_s2bm_ard_3-2-1_54GYA_2020-10-27_final.stac-item
2020-10-27 09:58:17	ga_s2bm_ard_3-2-1_55GCQ_2020-10-27_final.stac-item
2020-10-27 09:58:27	ga_s2bm_ard_3-2-1_55GCP_2020-10-27_final.stac-item
2020-10-27 11:32:18	ga_s2bm_ard_3-2-1_51KWB_2020-10-27_final.stac-item
2020-10-27 11:32:23	ga_s2bm_ard_3-2-1_51KVB_2020-10-27_final.stac-item
2020-10-27 11:32:32	ga_s2bm_ard_3-2-1_51KWA_2020-10-27_final.stac-item
2020-10-27 11:32:35	ga_s2bm_ard_3-2-1_51KVA_2020-10-27_final.stac-item
2020-10-27 11:32:50	ga_s2bm_ard_3-2-1_51KVV_2020-10-27_final.stac-item
2020-10-27 11:33:01	ga_s2bm_ard_3-2-1_51KWU_2020-10-27_final.stac-item
2020-10-27 11:33:05	ga_s2bm_ard_3-2-1_51KVU_2020-10-27_final.stac-item
2020-10-27 11:33:16	ga_s2bm_ard_3-2-1_51KWT_2020-10-27_final.stac-item
2020-10-27 11:33:19	ga_s2bm_ard_3-2-1_51KVT_2020-10-27_final.stac-item
2020-10-27 11:33:25	ga_s2bm_ard_3-2-1_51KUT_2020-10-27_final.stac-item
2020-10-27 11:33:30	ga_s2bm_ard_3-2-1_51KWS_2020-10-27_final.stac-item
2020-10-27 11:33:34	ga_s2bm_ard_3-2-1_51KVS_2020-10-27_final.stac-item
2020-10-27 11:33:37	ga_s2bm_ard_3-2-1_51KUS_2020-10-27_final.stac-item
2020-10-27 11:33:45	ga_s2bm_ard_3-2-1_51KWR_2020-10-27_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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