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
2022-02-08 12:04:59	ga_s2bm_ard_3-2-1_49JGM_2022-02-08_final.stac-item
2022-02-08 12:05:03	ga_s2bm_ard_3-2-1_50JLR_2022-02-08_final.stac-item
2022-02-08 12:05:06	ga_s2bm_ard_3-2-1_50JKR_2022-02-08_final.stac-item
2022-02-08 12:05:09	ga_s2bm_ard_3-2-1_49JGL_2022-02-08_final.stac-item
2022-02-08 12:05:17	ga_s2bm_ard_3-2-1_50JLQ_2022-02-08_final.stac-item
2022-02-08 12:05:20	ga_s2bm_ard_3-2-1_50JKQ_2022-02-08_final.stac-item
2022-02-08 12:05:24	ga_s2bm_ard_3-2-1_49JGK_2022-02-08_final.stac-item
2022-02-08 12:05:32	ga_s2bm_ard_3-2-1_50JLP_2022-02-08_final.stac-item
2022-02-08 12:05:35	ga_s2bm_ard_3-2-1_50JKP_2022-02-08_final.stac-item
2022-02-08 12:05:38	ga_s2bm_ard_3-2-1_49JGJ_2022-02-08_final.stac-item
2022-02-08 12:05:46	ga_s2bm_ard_3-2-1_50JLN_2022-02-08_final.stac-item
2022-02-08 12:05:50	ga_s2bm_ard_3-2-1_50JKN_2022-02-08_final.stac-item
2022-02-08 12:05:59	ga_s2bm_ard_3-2-1_50JLM_2022-02-08_final.stac-item
2022-02-08 12:06:04	ga_s2bm_ard_3-2-1_50JKM_2022-02-08_final.stac-item
2022-02-08 12:06:08	ga_s2bm_ard_3-2-1_50JLL_2022-02-08_final.stac-item
2022-02-09 09:51:28	ga_s2bm_ard_3-2-1_55KFB_2022-02-09_final.stac-item
2022-02-09 09:51:34	ga_s2bm_ard_3-2-1_56KKF_2022-02-09_final.stac-item
2022-02-09 09:51:42	ga_s2bm_ard_3-2-1_55KFA_2022-02-09_final.stac-item
2022-02-09 09:52:00	ga_s2bm_ard_3-2-1_55KEV_2022-02-09_final.stac-item
2022-02-09 09:52:14	ga_s2bm_ard_3-2-1_55KEU_2022-02-09_final.stac-item
2022-02-09 09:52:29	ga_s2bm_ard_3-2-1_55KET_2022-02-09_final.stac-item
2022-02-09 09:52:40	ga_s2bm_ard_3-2-1_55KFS_2022-02-09_final.stac-item
2022-02-09 09:52:44	ga_s2bm_ard_3-2-1_55KES_2022-02-09_final.stac-item
2022-02-09 09:52:50	ga_s2bm_ard_3-2-1_55KDS_2022-02-09_final.stac-item
2022-02-09 09:52:55	ga_s2bm_ard_3-2-1_55KFR_2022-02-09_final.stac-item
2022-02-09 09:52:58	ga_s2bm_ard_3-2-1_55KER_2022-02-09_final.stac-item
2022-02-09 09:53:02	ga_s2bm_ard_3-2-1_55KDR_2022-02-09_final.stac-item
2022-02-09 09:53:09	ga_s2bm_ard_3-2-1_55KFQ_2022-02-09_final.stac-item
2022-02-09 09:53:13	ga_s2bm_ard_3-2-1_55KEQ_2022-02-09_final.stac-item
2022-02-09 09:53:16	ga_s2bm_ard_3-2-1_55KDQ_2022-02-09_final.stac-item
2022-02-09 09:53:24	ga_s2bm_ard_3-2-1_55KFP_2022-02-09_final.stac-item
2022-02-09 09:53:27	ga_s2bm_ard_3-2-1_55KEP_2022-02-09_final.stac-item
2022-02-09 09:53:30	ga_s2bm_ard_3-2-1_55KDP_2022-02-09_final.stac-item
2022-02-09 09:53:32	ga_s2bm_ard_3-2-1_55JGN_2022-02-09_final.stac-item
2022-02-09 09:53:38	ga_s2bm_ard_3-2-1_55JFN_2022-02-09_final.stac-item
2022-02-09 09:53:42	ga_s2bm_ard_3-2-1_55JEN_2022-02-09_final.stac-item
2022-02-09 09:53:42	ga_s2bm_ard_3-2-1_55JGM_2022-02-09_final.stac-item
2022-02-09 09:53:45	ga_s2bm_ard_3-2-1_55JDN_2022-02-09_final.stac-item
2022-02-09 09:53:52	ga_s2bm_ard_3-2-1_55JCN_2022-02-09_final.stac-item
2022-02-09 09:53:52	ga_s2bm_ard_3-2-1_55JFM_2022-02-09_final.stac-item
2022-02-09 09:53:56	ga_s2bm_ard_3-2-1_55JEM_2022-02-09_final.stac-item
2022-02-09 09:53:59	ga_s2bm_ard_3-2-1_55JDM_2022-02-09_final.stac-item
2022-02-09 09:54:03	ga_s2bm_ard_3-2-1_55JCM_2022-02-09_final.stac-item
2022-02-09 09:54:07	ga_s2bm_ard_3-2-1_55JFL_2022-02-09_final.stac-item
2022-02-09 09:54:11	ga_s2bm_ard_3-2-1_55JEL_2022-02-09_final.stac-item
2022-02-09 09:54:14	ga_s2bm_ard_3-2-1_55JDL_2022-02-09_final.stac-item
2022-02-09 09:54:17	ga_s2bm_ard_3-2-1_55JCL_2022-02-09_final.stac-item
2022-02-09 09:54:21	ga_s2bm_ard_3-2-1_55JFK_2022-02-09_final.stac-item
2022-02-09 09:54:25	ga_s2bm_ard_3-2-1_55JEK_2022-02-09_final.stac-item
2022-02-09 09:54:29	ga_s2bm_ard_3-2-1_55JDK_2022-02-09_final.stac-item
2022-02-09 09:54:32	ga_s2bm_ard_3-2-1_55JCK_2022-02-09_final.stac-item
2022-02-09 09:54:35	ga_s2bm_ard_3-2-1_55JFJ_2022-02-09_final.stac-item
2022-02-09 09:54:39	ga_s2bm_ard_3-2-1_55JEJ_2022-02-09_final.stac-item
2022-02-09 09:54:43	ga_s2bm_ard_3-2-1_55JDJ_2022-02-09_final.stac-item
2022-02-09 09:54:45	ga_s2bm_ard_3-2-1_55JFH_2022-02-09_final.stac-item
2022-02-09 09:54:46	ga_s2bm_ard_3-2-1_55JCJ_2022-02-09_final.stac-item
2022-02-09 09:54:54	ga_s2bm_ard_3-2-1_55JEH_2022-02-09_final.stac-item
2022-02-09 09:54:58	ga_s2bm_ard_3-2-1_55JDH_2022-02-09_final.stac-item
2022-02-09 09:55:01	ga_s2bm_ard_3-2-1_55JCH_2022-02-09_final.stac-item
2022-02-09 09:55:05	ga_s2bm_ard_3-2-1_55JBH_2022-02-09_final.stac-item
2022-02-09 09:55:08	ga_s2bm_ard_3-2-1_55JEG_2022-02-09_final.stac-item
2022-02-09 09:55:12	ga_s2bm_ard_3-2-1_55JDG_2022-02-09_final.stac-item
2022-02-09 09:55:15	ga_s2bm_ard_3-2-1_55JCG_2022-02-09_final.stac-item
2022-02-09 09:55:18	ga_s2bm_ard_3-2-1_55JBG_2022-02-09_final.stac-item
2022-02-09 09:55:22	ga_s2bm_ard_3-2-1_55JEF_2022-02-09_final.stac-item
2022-02-09 09:55:24	ga_s2bm_ard_3-2-1_55JDF_2022-02-09_final.stac-item
2022-02-09 09:55:25	ga_s2bm_ard_3-2-1_55JCF_2022-02-09_final.stac-item
2022-02-09 09:55:27	ga_s2bm_ard_3-2-1_55JBF_2022-02-09_final.stac-item
2022-02-09 09:55:29	ga_s2bm_ard_3-2-1_55JEF_2022-02-09_final.stac-item
2022-02-09 09:55:31	ga_s2bm_ard_3-2-1_55JDF_2022-02-09_final.stac-item
2022-02-09 09:55:32	ga_s2bm_ard_3-2-1_55JCF_2022-02-09_final.stac-item
2022-02-09 09:55:34	ga_s2bm_ard_3-2-1_55JBF_2022-02-09_final.stac-item
2022-02-09 09:55:37	ga_s2bm_ard_3-2-1_55HEE_2022-02-09_final.stac-item
2022-02-09 09:55:41	ga_s2bm_ard_3-2-1_55HDE_2022-02-09_final.stac-item
2022-02-09 09:55:45	ga_s2bm_ard_3-2-1_55HCE_2022-02-09_final.stac-item
2022-02-09 09:55:48	ga_s2bm_ard_3-2-1_55HBE_2022-02-09_final.stac-item
2022-02-09 09:55:48	ga_s2bm_ard_3-2-1_55HED_2022-02-09_final.stac-item
2022-02-09 09:55:51	ga_s2bm_ard_3-2-1_54HYK_2022-02-09_final.stac-item
2022-02-09 09:55:55	ga_s2bm_ard_3-2-1_55HDD_2022-02-09_final.stac-item
2022-02-09 09:55:59	ga_s2bm_ard_3-2-1_55HCD_2022-02-09_final.stac-item
2022-02-09 09:56:02	ga_s2bm_ard_3-2-1_55HBD_2022-02-09_final.stac-item
2022-02-09 09:56:04	ga_s2bm_ard_3-2-1_54HYJ_2022-02-09_final.stac-item
2022-02-09 09:56:10	ga_s2bm_ard_3-2-1_55HDC_2022-02-09_final.stac-item
2022-02-09 09:56:14	ga_s2bm_ard_3-2-1_55HCC_2022-02-09_final.stac-item
2022-02-09 09:56:17	ga_s2bm_ard_3-2-1_55HBC_2022-02-09_final.stac-item
2022-02-09 09:56:19	ga_s2bm_ard_3-2-1_54HYH_2022-02-09_final.stac-item
2022-02-09 09:56:25	ga_s2bm_ard_3-2-1_55HDB_2022-02-09_final.stac-item
2022-02-09 09:56:28	ga_s2bm_ard_3-2-1_55HCB_2022-02-09_final.stac-item
2022-02-09 09:56:32	ga_s2bm_ard_3-2-1_55HBB_2022-02-09_final.stac-item
2022-02-09 09:56:33	ga_s2bm_ard_3-2-1_54HYG_2022-02-09_final.stac-item
2022-02-09 09:56:39	ga_s2bm_ard_3-2-1_55HDA_2022-02-09_final.stac-item
2022-02-09 09:56:40	ga_s2bm_ard_3-2-1_54HXG_2022-02-09_final.stac-item
2022-02-09 09:56:43	ga_s2bm_ard_3-2-1_55HCA_2022-02-09_final.stac-item
2022-02-09 09:56:46	ga_s2bm_ard_3-2-1_55HBA_2022-02-09_final.stac-item
2022-02-09 09:56:48	ga_s2bm_ard_3-2-1_54HYF_2022-02-09_final.stac-item
2022-02-09 09:56:52	ga_s2bm_ard_3-2-1_54HXF_2022-02-09_final.stac-item
2022-02-09 09:56:52	ga_s2bm_ard_3-2-1_55HDV_2022-02-09_final.stac-item
2022-02-09 09:56:57	ga_s2bm_ard_3-2-1_55HCV_2022-02-09_final.stac-item
2022-02-09 09:57:01	ga_s2bm_ard_3-2-1_55HBV_2022-02-09_final.stac-item
2022-02-09 09:57:02	ga_s2bm_ard_3-2-1_54HYE_2022-02-09_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

All years