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
2023-12-01 09:51:50	ga_s2bm_ard_3-2-1_55KEA_2023-12-01_nrt
2023-12-01 09:51:51	ga_s2bm_ard_3-2-1_56KKE_2023-12-01_nrt
2023-12-01 09:51:52	ga_s2bm_ard_3-2-1_55KHV_2023-12-01_nrt
2023-12-01 09:51:56	ga_s2bm_ard_3-2-1_55KGV_2023-12-01_nrt
2023-12-01 09:51:59	ga_s2bm_ard_3-2-1_55KFV_2023-12-01_nrt
2023-12-01 09:52:03	ga_s2bm_ard_3-2-1_55KEV_2023-12-01_final
2023-12-01 09:52:05	ga_s2bm_ard_3-2-1_56KKD_2023-12-01_nrt
2023-12-01 09:52:07	ga_s2bm_ard_3-2-1_55KHU_2023-12-01_nrt
2023-12-01 09:52:10	ga_s2bm_ard_3-2-1_55KGU_2023-12-01_final
2023-12-01 09:52:14	ga_s2bm_ard_3-2-1_55KFU_2023-12-01_final
2023-12-01 09:52:16	ga_s2bm_ard_3-2-1_56KKC_2023-12-01_nrt
2023-12-01 09:52:17	ga_s2bm_ard_3-2-1_55KEU_2023-12-01_final
2023-12-01 09:52:21	ga_s2bm_ard_3-2-1_55KHT_2023-12-01_nrt
2023-12-01 09:52:25	ga_s2bm_ard_3-2-1_55KGT_2023-12-01_final
2023-12-01 09:52:28	ga_s2bm_ard_3-2-1_55KFT_2023-12-01_final
2023-12-01 09:52:32	ga_s2bm_ard_3-2-1_55KET_2023-12-01_final
2023-12-01 09:52:32	ga_s2bm_ard_3-2-1_55KHS_2023-12-01_final
2023-12-01 09:52:39	ga_s2bm_ard_3-2-1_55KGS_2023-12-01_final
2023-12-01 09:52:43	ga_s2bm_ard_3-2-1_55KFS_2023-12-01_final
2023-12-01 09:52:46	ga_s2bm_ard_3-2-1_55KES_2023-12-01_final
2023-12-01 09:54:17	ga_s2bm_ard_3-2-1_55JEL_2023-12-01_final
2023-12-01 09:54:19	ga_s2bm_ard_3-2-1_55JDL_2023-12-01_final
2023-12-01 09:54:21	ga_s2bm_ard_3-2-1_55JCL_2023-12-01_final
2023-12-01 09:54:24	ga_s2bm_ard_3-2-1_55JFK_2023-12-01_final
2023-12-01 09:54:28	ga_s2bm_ard_3-2-1_55JEK_2023-12-01_final
2023-12-01 09:54:31	ga_s2bm_ard_3-2-1_55JDK_2023-12-01_final
2023-12-01 09:54:35	ga_s2bm_ard_3-2-1_55JCK_2023-12-01_final
2023-12-01 09:54:37	ga_s2bm_ard_3-2-1_55JFJ_2023-12-01_final
2023-12-01 09:54:42	ga_s2bm_ard_3-2-1_55JEJ_2023-12-01_final
2023-12-01 09:54:46	ga_s2bm_ard_3-2-1_55JDJ_2023-12-01_final
2023-12-01 09:54:48	ga_s2bm_ard_3-2-1_55JFH_2023-12-01_final
2023-12-01 09:54:49	ga_s2bm_ard_3-2-1_55JCJ_2023-12-01_final
2023-12-01 09:54:57	ga_s2bm_ard_3-2-1_55JEH_2023-12-01_final
2023-12-01 09:55:01	ga_s2bm_ard_3-2-1_55JDH_2023-12-01_final
2023-12-01 09:55:04	ga_s2bm_ard_3-2-1_55JCH_2023-12-01_final
2023-12-01 09:55:08	ga_s2bm_ard_3-2-1_55JBH_2023-12-01_final
2023-12-01 09:55:11	ga_s2bm_ard_3-2-1_55JEG_2023-12-01_final
2023-12-01 09:55:15	ga_s2bm_ard_3-2-1_55JDG_2023-12-01_final
2023-12-01 09:55:18	ga_s2bm_ard_3-2-1_55JCG_2023-12-01_final
2023-12-01 09:55:21	ga_s2bm_ard_3-2-1_55JBG_2023-12-01_final
2023-12-01 09:55:26	ga_s2bm_ard_3-2-1_55JEF_2023-12-01_final
2023-12-01 09:55:29	ga_s2bm_ard_3-2-1_55JDF_2023-12-01_final
2023-12-01 09:55:33	ga_s2bm_ard_3-2-1_55JCF_2023-12-01_final
2023-12-01 09:55:36	ga_s2bm_ard_3-2-1_55JBF_2023-12-01_final
2023-12-01 09:55:40	ga_s2bm_ard_3-2-1_55HEE_2023-12-01_final
2023-12-01 09:55:44	ga_s2bm_ard_3-2-1_55HDE_2023-12-01_final
2023-12-01 09:55:47	ga_s2bm_ard_3-2-1_55HCE_2023-12-01_final
2023-12-02 09:26:09	ga_s2bm_ard_3-2-1_56HPG_2023-12-01_nrt
2023-12-02 09:26:16	ga_s2bm_ard_3-2-1_56HNG_2023-12-01_nrt
2023-12-02 09:26:20	ga_s2bm_ard_3-2-1_56HMG_2023-12-01_nrt
2023-12-02 09:26:24	ga_s2bm_ard_3-2-1_56HLG_2023-12-01_final
2023-12-02 09:26:29	ga_s2bm_ard_3-2-1_56HKG_2023-12-01_final
2023-12-02 09:26:31	ga_s2bm_ard_3-2-1_56HNF_2023-12-01_nrt
2023-12-02 09:26:35	ga_s2bm_ard_3-2-1_56HMF_2023-12-01_nrt
2023-12-02 09:26:38	ga_s2bm_ard_3-2-1_56HLF_2023-12-01_nrt
2023-12-02 09:26:41	ga_s2bm_ard_3-2-1_56HKF_2023-12-01_final
2023-12-02 09:26:46	ga_s2bm_ard_3-2-1_56HNE_2023-12-01_nrt
2023-12-02 09:26:49	ga_s2bm_ard_3-2-1_56HME_2023-12-01_nrt
2023-12-02 09:26:53	ga_s2bm_ard_3-2-1_56HLE_2023-12-01_nrt
2023-12-02 09:26:56	ga_s2bm_ard_3-2-1_56HKE_2023-12-01_nrt
2023-12-02 09:27:00	ga_s2bm_ard_3-2-1_56HND_2023-12-01_nrt
2023-12-02 09:27:04	ga_s2bm_ard_3-2-1_56HMD_2023-12-01_nrt
2023-12-02 09:27:07	ga_s2bm_ard_3-2-1_56HLD_2023-12-01_nrt
2023-12-02 09:27:11	ga_s2bm_ard_3-2-1_56HKD_2023-12-01_nrt
2023-12-02 09:27:12	ga_s2bm_ard_3-2-1_56HNC_2023-12-01_nrt
2023-12-02 09:27:18	ga_s2bm_ard_3-2-1_56HMC_2023-12-01_nrt
2023-12-02 09:27:22	ga_s2bm_ard_3-2-1_56HLC_2023-12-01_nrt
2023-12-02 09:27:25	ga_s2bm_ard_3-2-1_56HKC_2023-12-01_nrt
2023-12-02 09:27:26	ga_s2bm_ard_3-2-1_55HGT_2023-12-01_nrt
2023-12-02 09:27:33	ga_s2bm_ard_3-2-1_56HMB_2023-12-01_nrt
2023-12-02 09:27:36	ga_s2bm_ard_3-2-1_56HLB_2023-12-01_nrt
2023-12-02 09:27:40	ga_s2bm_ard_3-2-1_56HKB_2023-12-01_nrt
2023-12-02 09:27:40	ga_s2bm_ard_3-2-1_55HGS_2023-12-01_nrt
2023-12-02 09:27:46	ga_s2bm_ard_3-2-1_55HFS_2023-12-01_final
2023-12-02 09:27:47	ga_s2bm_ard_3-2-1_56GMA_2023-12-01_nrt
2023-12-02 09:27:51	ga_s2bm_ard_3-2-1_56GLA_2023-12-01_nrt
2023-12-02 09:27:54	ga_s2bm_ard_3-2-1_56GKA_2023-12-01_nrt
2023-12-02 09:27:55	ga_s2bm_ard_3-2-1_55GGR_2023-12-01_nrt
2023-12-02 09:28:02	ga_s2bm_ard_3-2-1_56GMV_2023-12-01_nrt
2023-12-02 09:28:06	ga_s2bm_ard_3-2-1_56GLV_2023-12-01_nrt
2023-12-02 09:28:09	ga_s2bm_ard_3-2-1_56GKV_2023-12-01_nrt
2023-12-02 09:28:09	ga_s2bm_ard_3-2-1_55GGQ_2023-12-01_nrt
2023-12-02 09:28:15	ga_s2bm_ard_3-2-1_56GMU_2023-12-01_nrt
2023-12-02 09:28:20	ga_s2bm_ard_3-2-1_56GLU_2023-12-01_nrt
2023-12-02 09:28:23	ga_s2bm_ard_3-2-1_55GGP_2023-12-01_nrt
2023-12-02 09:28:23	ga_s2bm_ard_3-2-1_56GKU_2023-12-01_nrt
2023-12-02 09:28:26	ga_s2bm_ard_3-2-1_56GMT_2023-12-01_nrt
2023-12-02 09:28:34	ga_s2bm_ard_3-2-1_56GLT_2023-12-01_nrt
2023-12-02 09:28:38	ga_s2bm_ard_3-2-1_55GGN_2023-12-01_nrt
2023-12-02 09:28:41	ga_s2bm_ard_3-2-1_55GFN_2023-12-01_final
2023-12-02 09:28:44	ga_s2bm_ard_3-2-1_55GEN_2023-12-01_final
2023-12-02 09:28:45	ga_s2bm_ard_3-2-1_56GLS_2023-12-01_nrt
2023-12-02 09:28:46	ga_s2bm_ard_3-2-1_55GGM_2023-12-01_nrt
2023-12-02 09:28:46	ga_s2bm_ard_3-2-1_55GGN_2023-12-01_nrt
2023-12-02 09:28:48	ga_s2bm_ard_3-2-1_55GFM_2023-12-01_nrt
2023-12-02 09:28:48	ga_s2bm_ard_3-2-1_55GFN_2023-12-01_final
2023-12-02 09:28:50	ga_s2bm_ard_3-2-1_55GEN_2023-12-01_final
2023-12-02 09:28:52	ga_s2bm_ard_3-2-1_56GLS_2023-12-01_nrt
2023-12-02 09:28:53	ga_s2bm_ard_3-2-1_55GGM_2023-12-01_nrt
2023-12-02 09:28:54	ga_s2bm_ard_3-2-1_55GFM_2023-12-01_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