Search ga_s2bm_ard_3 on 11th December 2023

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
2023-12-11 09:49:33	ga_s2bm_ard_3-2-1_56LMP_2023-12-11_nrt
2023-12-11 09:49:37	ga_s2bm_ard_3-2-1_56LLP_2023-12-11_nrt
2023-12-11 09:49:40	ga_s2bm_ard_3-2-1_56LKP_2023-12-11_nrt
2023-12-11 09:49:42	ga_s2bm_ard_3-2-1_55LHJ_2023-12-11_nrt
2023-12-11 09:49:46	ga_s2bm_ard_3-2-1_56LMN_2023-12-11_nrt
2023-12-11 09:49:46	ga_s2bm_ard_3-2-1_55LGJ_2023-12-11_nrt
2023-12-11 09:49:51	ga_s2bm_ard_3-2-1_56LLN_2023-12-11_nrt
2023-12-11 09:49:54	ga_s2bm_ard_3-2-1_56LKN_2023-12-11_nrt
2023-12-11 09:49:55	ga_s2bm_ard_3-2-1_55LHH_2023-12-11_nrt
2023-12-11 09:49:56	ga_s2bm_ard_3-2-1_56LMM_2023-12-11_nrt
2023-12-11 09:49:56	ga_s2bm_ard_3-2-1_55LGH_2023-12-11_nrt
2023-12-11 09:49:59	ga_s2bm_ard_3-2-1_56LLM_2023-12-11_nrt
2023-12-11 09:50:01	ga_s2bm_ard_3-2-1_56LKM_2023-12-11_nrt
2023-12-11 09:50:01	ga_s2bm_ard_3-2-1_55LHG_2023-12-11_nrt
2023-12-11 09:50:56	ga_s2bm_ard_3-2-1_56LLJ_2023-12-11_nrt
2023-12-11 09:50:58	ga_s2bm_ard_3-2-1_56LKJ_2023-12-11_nrt
2023-12-11 09:50:59	ga_s2bm_ard_3-2-1_55LHD_2023-12-11_nrt
2023-12-11 09:51:00	ga_s2bm_ard_3-2-1_55LGD_2023-12-11_nrt
2023-12-11 09:51:01	ga_s2bm_ard_3-2-1_56LLH_2023-12-11_nrt
2023-12-11 09:51:02	ga_s2bm_ard_3-2-1_55LFD_2023-12-11_nrt
2023-12-11 09:51:07	ga_s2bm_ard_3-2-1_56LKH_2023-12-11_nrt
2023-12-11 09:51:09	ga_s2bm_ard_3-2-1_55LHC_2023-12-11_final
2023-12-11 09:51:12	ga_s2bm_ard_3-2-1_55LGC_2023-12-11_final
2023-12-11 09:51:15	ga_s2bm_ard_3-2-1_55LFC_2023-12-11_final
2023-12-11 09:51:22	ga_s2bm_ard_3-2-1_56KKG_2023-12-11_final
2023-12-11 09:51:23	ga_s2bm_ard_3-2-1_55KHB_2023-12-11_final
2023-12-11 09:51:27	ga_s2bm_ard_3-2-1_55KGB_2023-12-11_final
2023-12-11 09:51:30	ga_s2bm_ard_3-2-1_55KFB_2023-12-11_final
2023-12-11 09:51:36	ga_s2bm_ard_3-2-1_56KKF_2023-12-11_final
2023-12-11 09:51:37	ga_s2bm_ard_3-2-1_55KHA_2023-12-11_nrt
2023-12-11 09:51:41	ga_s2bm_ard_3-2-1_55KGA_2023-12-11_nrt
2023-12-11 09:51:45	ga_s2bm_ard_3-2-1_55KFA_2023-12-11_final
2023-12-11 09:51:50	ga_s2bm_ard_3-2-1_55KEA_2023-12-11_nrt
2023-12-11 09:51:51	ga_s2bm_ard_3-2-1_56KKE_2023-12-11_nrt
2023-12-11 09:51:52	ga_s2bm_ard_3-2-1_55KHV_2023-12-11_nrt
2023-12-11 09:53:59	ga_s2bm_ard_3-2-1_55JEM_2023-12-11_final
2023-12-11 09:54:02	ga_s2bm_ard_3-2-1_55JDM_2023-12-11_final
2023-12-11 09:54:06	ga_s2bm_ard_3-2-1_55JCM_2023-12-11_final
2023-12-11 09:54:09	ga_s2bm_ard_3-2-1_55JFL_2023-12-11_final
2023-12-11 09:54:13	ga_s2bm_ard_3-2-1_55JEL_2023-12-11_final
2023-12-11 09:54:16	ga_s2bm_ard_3-2-1_55JDL_2023-12-11_final
2023-12-11 09:54:19	ga_s2bm_ard_3-2-1_55JCL_2023-12-11_final
2023-12-11 09:54:24	ga_s2bm_ard_3-2-1_55JFK_2023-12-11_final
2023-12-11 09:54:28	ga_s2bm_ard_3-2-1_55JEK_2023-12-11_final
2023-12-11 09:54:31	ga_s2bm_ard_3-2-1_55JDK_2023-12-11_final
2023-12-11 09:54:34	ga_s2bm_ard_3-2-1_55JCK_2023-12-11_final
2023-12-11 09:54:35	ga_s2bm_ard_3-2-1_55JFJ_2023-12-11_final
2023-12-11 09:54:38	ga_s2bm_ard_3-2-1_55JEJ_2023-12-11_final
2023-12-11 09:54:39	ga_s2bm_ard_3-2-1_55JDK_2023-12-11_final
2023-12-11 09:54:39	ga_s2bm_ard_3-2-1_55JDJ_2023-12-11_final
2023-12-11 09:54:40	ga_s2bm_ard_3-2-1_55JCK_2023-12-11_final
2023-12-11 09:54:41	ga_s2bm_ard_3-2-1_55JCJ_2023-12-11_final
2023-12-11 09:54:41	ga_s2bm_ard_3-2-1_55JFJ_2023-12-11_final
2023-12-11 09:54:44	ga_s2bm_ard_3-2-1_55JEJ_2023-12-11_final
2023-12-11 09:54:46	ga_s2bm_ard_3-2-1_55JDJ_2023-12-11_final
2023-12-11 09:54:47	ga_s2bm_ard_3-2-1_55JFH_2023-12-11_final
2023-12-11 09:54:49	ga_s2bm_ard_3-2-1_55JCJ_2023-12-11_final
2023-12-11 09:54:56	ga_s2bm_ard_3-2-1_55JEH_2023-12-11_final
2023-12-11 09:55:00	ga_s2bm_ard_3-2-1_55JDH_2023-12-11_final
2023-12-11 09:55:03	ga_s2bm_ard_3-2-1_55JCH_2023-12-11_final
2023-12-11 09:55:08	ga_s2bm_ard_3-2-1_55JBH_2023-12-11_final
2023-12-11 09:55:11	ga_s2bm_ard_3-2-1_55JEG_2023-12-11_final
2023-12-11 09:55:15	ga_s2bm_ard_3-2-1_55JDG_2023-12-11_final
2023-12-11 09:55:18	ga_s2bm_ard_3-2-1_55JCG_2023-12-11_final
2023-12-11 09:55:21	ga_s2bm_ard_3-2-1_55JBG_2023-12-11_final
2023-12-11 09:57:08	ga_s2bm_ard_3-2-1_54HXE_2023-12-11_final
2023-12-11 09:57:51	ga_s2bm_ard_3-2-1_54HXB_2023-12-11_nrt
2023-12-11 09:57:55	ga_s2bm_ard_3-2-1_54HWB_2023-12-11_nrt
2023-12-11 09:58:06	ga_s2bm_ard_3-2-1_54GXA_2023-12-11_nrt
2023-12-11 09:58:10	ga_s2bm_ard_3-2-1_54GWA_2023-12-11_nrt
2023-12-11 09:58:20	ga_s2bm_ard_3-2-1_54GXV_2023-12-11_nrt
2023-12-11 09:58:23	ga_s2bm_ard_3-2-1_54GWV_2023-12-11_nrt
2023-12-11 09:58:25	ga_s2bm_ard_3-2-1_54GYU_2023-12-11_nrt
2023-12-11 09:58:26	ga_s2bm_ard_3-2-1_55GBP_2023-12-11_nrt
2023-12-11 09:58:27	ga_s2bm_ard_3-2-1_54GXU_2023-12-11_nrt
2023-12-11 11:30:11	ga_s2bm_ard_3-2-1_52LCP_2023-12-11_nrt
2023-12-11 11:30:18	ga_s2bm_ard_3-2-1_52LBP_2023-12-11_nrt
2023-12-11 11:30:20	ga_s2bm_ard_3-2-1_51LZJ_2023-12-11_nrt
2023-12-11 11:30:23	ga_s2bm_ard_3-2-1_51LYJ_2023-12-11_nrt
2023-12-11 11:30:26	ga_s2bm_ard_3-2-1_51LXJ_2023-12-11_nrt
2023-12-11 11:30:32	ga_s2bm_ard_3-2-1_52LBN_2023-12-11_nrt
2023-12-11 11:30:34	ga_s2bm_ard_3-2-1_51LZH_2023-12-11_nrt
2023-12-11 11:36:35	ga_s2bm_ard_3-2-1_50HPK_2023-12-11_final
2023-12-11 11:36:39	ga_s2bm_ard_3-2-1_51HUD_2023-12-11_final
2023-12-11 11:36:43	ga_s2bm_ard_3-2-1_51HTD_2023-12-11_final
2023-12-11 11:36:45	ga_s2bm_ard_3-2-1_50HQJ_2023-12-11_final
2023-12-11 11:36:49	ga_s2bm_ard_3-2-1_50HPJ_2023-12-11_final
2023-12-11 11:36:54	ga_s2bm_ard_3-2-1_51HUC_2023-12-11_final
2023-12-11 11:36:57	ga_s2bm_ard_3-2-1_51HTC_2023-12-11_final
2023-12-11 11:36:59	ga_s2bm_ard_3-2-1_50HQH_2023-12-11_final
2023-12-11 11:37:03	ga_s2bm_ard_3-2-1_50HPH_2023-12-11_final
2023-12-11 11:37:09	ga_s2bm_ard_3-2-1_51HUB_2023-12-11_final
2023-12-11 11:37:12	ga_s2bm_ard_3-2-1_51HTB_2023-12-11_final
2023-12-11 11:37:14	ga_s2bm_ard_3-2-1_50HQG_2023-12-11_final
2023-12-11 11:37:18	ga_s2bm_ard_3-2-1_50HPG_2023-12-11_final
2023-12-11 11:37:22	ga_s2bm_ard_3-2-1_51HUA_2023-12-11_nrt
2023-12-11 11:37:23	ga_s2bm_ard_3-2-1_50HNG_2023-12-11_final
2023-12-11 11:37:25	ga_s2bm_ard_3-2-1_51HTA_2023-12-11_nrt
2023-12-11 11:37:25	ga_s2bm_ard_3-2-1_50HQF_2023-12-11_nrt
2023-12-11 11:37:27	ga_s2bm_ard_3-2-1_50HPF_2023-12-11_nrt

Return to ga_s2bm_ard_3 on 11th December 2023 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

2023

December

11th