Search ga_s2bm_ard_3 on 31st 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
2023-12-31 09:49:37	ga_s2bm_ard_3-2-1_56LMP_2023-12-31_nrt
2023-12-31 09:49:41	ga_s2bm_ard_3-2-1_56LLP_2023-12-31_nrt
2023-12-31 09:49:45	ga_s2bm_ard_3-2-1_56LKP_2023-12-31_nrt
2023-12-31 09:49:46	ga_s2bm_ard_3-2-1_55LHJ_2023-12-31_nrt
2023-12-31 09:49:50	ga_s2bm_ard_3-2-1_56LMN_2023-12-31_nrt
2023-12-31 09:49:50	ga_s2bm_ard_3-2-1_55LGJ_2023-12-31_nrt
2023-12-31 09:49:56	ga_s2bm_ard_3-2-1_56LLN_2023-12-31_nrt
2023-12-31 09:49:59	ga_s2bm_ard_3-2-1_56LKN_2023-12-31_nrt
2023-12-31 09:50:00	ga_s2bm_ard_3-2-1_56LMM_2023-12-31_nrt
2023-12-31 09:50:00	ga_s2bm_ard_3-2-1_55LHH_2023-12-31_nrt
2023-12-31 09:50:03	ga_s2bm_ard_3-2-1_55LGH_2023-12-31_nrt
2023-12-31 09:50:06	ga_s2bm_ard_3-2-1_56LLM_2023-12-31_nrt
2023-12-31 09:50:07	ga_s2bm_ard_3-2-1_56LKM_2023-12-31_nrt
2023-12-31 09:50:08	ga_s2bm_ard_3-2-1_55LHG_2023-12-31_nrt
2023-12-31 09:50:09	ga_s2bm_ard_3-2-1_55LGG_2023-12-31_nrt
2023-12-31 09:51:00	ga_s2bm_ard_3-2-1_56LLJ_2023-12-31_nrt
2023-12-31 09:51:02	ga_s2bm_ard_3-2-1_56LKJ_2023-12-31_nrt
2023-12-31 09:51:03	ga_s2bm_ard_3-2-1_55LHD_2023-12-31_nrt
2023-12-31 09:51:04	ga_s2bm_ard_3-2-1_55LGD_2023-12-31_nrt
2023-12-31 09:51:05	ga_s2bm_ard_3-2-1_56LLH_2023-12-31_nrt
2023-12-31 09:51:06	ga_s2bm_ard_3-2-1_55LFD_2023-12-31_nrt
2023-12-31 09:51:11	ga_s2bm_ard_3-2-1_56LKH_2023-12-31_nrt
2023-12-31 09:51:17	ga_s2bm_ard_3-2-1_55LGC_2023-12-31_final
2023-12-31 09:51:20	ga_s2bm_ard_3-2-1_55LFC_2023-12-31_final
2023-12-31 09:51:27	ga_s2bm_ard_3-2-1_55KHB_2023-12-31_final
2023-12-31 09:51:31	ga_s2bm_ard_3-2-1_55KGB_2023-12-31_final
2023-12-31 09:51:34	ga_s2bm_ard_3-2-1_55KFB_2023-12-31_final
2023-12-31 09:51:41	ga_s2bm_ard_3-2-1_56KKF_2023-12-31_final
2023-12-31 09:51:42	ga_s2bm_ard_3-2-1_55KHA_2023-12-31_nrt
2023-12-31 09:51:46	ga_s2bm_ard_3-2-1_55KGA_2023-12-31_nrt
2023-12-31 09:51:54	ga_s2bm_ard_3-2-1_55KEA_2023-12-31_nrt
2023-12-31 09:51:55	ga_s2bm_ard_3-2-1_56KKE_2023-12-31_nrt
2023-12-31 09:51:56	ga_s2bm_ard_3-2-1_55KHV_2023-12-31_nrt
2023-12-31 09:52:00	ga_s2bm_ard_3-2-1_55KGV_2023-12-31_nrt
2023-12-31 09:52:03	ga_s2bm_ard_3-2-1_55KFV_2023-12-31_nrt
2023-12-31 09:52:09	ga_s2bm_ard_3-2-1_56KKD_2023-12-31_nrt
2023-12-31 09:52:11	ga_s2bm_ard_3-2-1_55KHU_2023-12-31_nrt
2023-12-31 09:52:14	ga_s2bm_ard_3-2-1_55KGU_2023-12-31_final
2023-12-31 09:52:20	ga_s2bm_ard_3-2-1_56KKC_2023-12-31_nrt
2023-12-31 09:52:21	ga_s2bm_ard_3-2-1_55KEU_2023-12-31_final
2023-12-31 09:52:24	ga_s2bm_ard_3-2-1_55KHT_2023-12-31_nrt
2023-12-31 09:52:29	ga_s2bm_ard_3-2-1_55KGT_2023-12-31_final
2023-12-31 09:52:32	ga_s2bm_ard_3-2-1_55KFT_2023-12-31_final
2023-12-31 09:52:36	ga_s2bm_ard_3-2-1_55KET_2023-12-31_final
2023-12-31 09:52:36	ga_s2bm_ard_3-2-1_55KHS_2023-12-31_final
2023-12-31 09:52:43	ga_s2bm_ard_3-2-1_55KGS_2023-12-31_final
2023-12-31 09:52:47	ga_s2bm_ard_3-2-1_55KFS_2023-12-31_final
2023-12-31 09:52:50	ga_s2bm_ard_3-2-1_55KES_2023-12-31_final
2023-12-31 09:52:56	ga_s2bm_ard_3-2-1_55KDS_2023-12-31_final
2023-12-31 09:52:58	ga_s2bm_ard_3-2-1_55KGR_2023-12-31_final
2023-12-31 09:53:01	ga_s2bm_ard_3-2-1_55KFR_2023-12-31_final
2023-12-31 09:55:51	ga_s2bm_ard_3-2-1_55HCE_2023-12-31_final
2023-12-31 09:55:55	ga_s2bm_ard_3-2-1_55HBE_2023-12-31_final
2023-12-31 09:55:55	ga_s2bm_ard_3-2-1_55HED_2023-12-31_final
2023-12-31 09:55:58	ga_s2bm_ard_3-2-1_54HYK_2023-12-31_final
2023-12-31 09:56:02	ga_s2bm_ard_3-2-1_55HDD_2023-12-31_final
2023-12-31 09:56:06	ga_s2bm_ard_3-2-1_55HCD_2023-12-31_final
2023-12-31 09:56:09	ga_s2bm_ard_3-2-1_55HBD_2023-12-31_final
2023-12-31 09:56:11	ga_s2bm_ard_3-2-1_54HYJ_2023-12-31_final
2023-12-31 09:56:17	ga_s2bm_ard_3-2-1_55HDC_2023-12-31_final
2023-12-31 09:56:21	ga_s2bm_ard_3-2-1_55HCC_2023-12-31_final
2023-12-31 09:56:24	ga_s2bm_ard_3-2-1_55HBC_2023-12-31_final
2023-12-31 09:56:26	ga_s2bm_ard_3-2-1_54HYH_2023-12-31_final
2023-12-31 09:56:32	ga_s2bm_ard_3-2-1_55HDB_2023-12-31_final
2023-12-31 09:56:35	ga_s2bm_ard_3-2-1_55HCB_2023-12-31_final
2023-12-31 09:56:38	ga_s2bm_ard_3-2-1_55HBB_2023-12-31_final
2023-12-31 09:56:40	ga_s2bm_ard_3-2-1_54HYG_2023-12-31_final
2023-12-31 09:56:46	ga_s2bm_ard_3-2-1_55HDA_2023-12-31_final
2023-12-31 09:56:47	ga_s2bm_ard_3-2-1_54HXG_2023-12-31_final
2023-12-31 09:56:50	ga_s2bm_ard_3-2-1_55HCA_2023-12-31_final
2023-12-31 09:56:53	ga_s2bm_ard_3-2-1_55HBA_2023-12-31_final
2023-12-31 09:56:54	ga_s2bm_ard_3-2-1_54HYF_2023-12-31_final
2023-12-31 09:56:58	ga_s2bm_ard_3-2-1_54HXF_2023-12-31_final
2023-12-31 09:56:59	ga_s2bm_ard_3-2-1_55HDV_2023-12-31_final
2023-12-31 09:57:04	ga_s2bm_ard_3-2-1_55HCV_2023-12-31_final
2023-12-31 09:57:07	ga_s2bm_ard_3-2-1_55HBV_2023-12-31_final
2023-12-31 09:57:09	ga_s2bm_ard_3-2-1_54HYE_2023-12-31_final
2023-12-31 09:57:09	ga_s2bm_ard_3-2-1_55HDU_2023-12-31_final
2023-12-31 09:57:12	ga_s2bm_ard_3-2-1_54HXE_2023-12-31_final
2023-12-31 09:57:19	ga_s2bm_ard_3-2-1_55HCU_2023-12-31_final
2023-12-31 09:57:22	ga_s2bm_ard_3-2-1_55HBU_2023-12-31_final
2023-12-31 09:57:23	ga_s2bm_ard_3-2-1_54HYD_2023-12-31_final
2023-12-31 09:57:27	ga_s2bm_ard_3-2-1_54HXD_2023-12-31_final
2023-12-31 09:57:33	ga_s2bm_ard_3-2-1_55HCT_2023-12-31_final
2023-12-31 09:57:37	ga_s2bm_ard_3-2-1_55HBT_2023-12-31_final
2023-12-31 09:57:38	ga_s2bm_ard_3-2-1_54HYC_2023-12-31_final
2023-12-31 09:57:41	ga_s2bm_ard_3-2-1_54HXC_2023-12-31_final
2023-12-31 09:57:46	ga_s2bm_ard_3-2-1_54HWC_2023-12-31_final
2023-12-31 09:57:48	ga_s2bm_ard_3-2-1_55HCS_2023-12-31_final
2023-12-31 09:57:51	ga_s2bm_ard_3-2-1_55HBS_2023-12-31_final
2023-12-31 09:57:52	ga_s2bm_ard_3-2-1_54HYB_2023-12-31_final
2023-12-31 09:57:56	ga_s2bm_ard_3-2-1_54HXB_2023-12-31_nrt
2023-12-31 09:57:59	ga_s2bm_ard_3-2-1_54HWB_2023-12-31_nrt
2023-12-31 09:58:02	ga_s2bm_ard_3-2-1_55GCR_2023-12-31_final
2023-12-31 09:58:06	ga_s2bm_ard_3-2-1_55GBR_2023-12-31_final
2023-12-31 09:58:06	ga_s2bm_ard_3-2-1_54GYA_2023-12-31_final
2023-12-31 09:58:10	ga_s2bm_ard_3-2-1_54GXA_2023-12-31_nrt
2023-12-31 09:58:14	ga_s2bm_ard_3-2-1_54GWA_2023-12-31_nrt
2023-12-31 09:58:14	ga_s2bm_ard_3-2-1_55GCQ_2023-12-31_final
2023-12-31 09:58:20	ga_s2bm_ard_3-2-1_55GBQ_2023-12-31_final

Return to ga_s2bm_ard_3 on 31st 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

31st