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
2023-05-21 11:56:45	ga_s2bm_ard_3-2-1_50HLK_2023-05-21_final
2023-05-21 11:56:48	ga_s2bm_ard_3-2-1_50HKK_2023-05-21_nrt
2023-05-21 11:57:00	ga_s2bm_ard_3-2-1_50HLJ_2023-05-21_final
2023-05-21 11:57:14	ga_s2bm_ard_3-2-1_50HLH_2023-05-21_final
2023-05-21 11:57:27	ga_s2bm_ard_3-2-1_50HLG_2023-05-21_final
2023-05-24 12:03:06	ga_s2bm_ard_3-2-1_50KKE_2023-05-24_nrt
2023-05-24 12:03:20	ga_s2bm_ard_3-2-1_50KKD_2023-05-24_nrt
2023-05-24 12:03:34	ga_s2bm_ard_3-2-1_50KKC_2023-05-24_nrt
2023-05-24 12:03:49	ga_s2bm_ard_3-2-1_50KKB_2023-05-24_final
2023-05-24 12:04:18	ga_s2bm_ard_3-2-1_50KKV_2023-05-24_final
2023-05-24 12:04:30	ga_s2bm_ard_3-2-1_50KKU_2023-05-24_final
2023-05-24 12:04:37	ga_s2bm_ard_3-2-1_50KKU_2023-05-24_final
2023-05-24 12:04:47	ga_s2bm_ard_3-2-1_49JHN_2023-05-24_final
2023-05-24 12:04:47	ga_s2bm_ard_3-2-1_50JKT_2023-05-24_final
2023-05-24 12:05:02	ga_s2bm_ard_3-2-1_49JHM_2023-05-24_final
2023-05-24 12:05:02	ga_s2bm_ard_3-2-1_50JKS_2023-05-24_final
2023-05-24 12:05:13	ga_s2bm_ard_3-2-1_50JLR_2023-05-24_final
2023-05-24 12:05:17	ga_s2bm_ard_3-2-1_50JKR_2023-05-24_final
2023-05-24 12:05:28	ga_s2bm_ard_3-2-1_50JLQ_2023-05-24_final
2023-05-24 12:05:31	ga_s2bm_ard_3-2-1_50JKQ_2023-05-24_final
2023-05-24 12:05:42	ga_s2bm_ard_3-2-1_50JLP_2023-05-24_final
2023-05-24 12:05:46	ga_s2bm_ard_3-2-1_50JKP_2023-05-24_final
2023-05-24 12:05:56	ga_s2bm_ard_3-2-1_50JLN_2023-05-24_final
2023-05-24 12:06:00	ga_s2bm_ard_3-2-1_50JKN_2023-05-24_final
2023-05-24 12:06:09	ga_s2bm_ard_3-2-1_50JLM_2023-05-24_final
2023-05-24 12:06:15	ga_s2bm_ard_3-2-1_50JKM_2023-05-24_final
2023-06-10 11:55:47	ga_s2bm_ard_3-2-1_50JLP_2023-06-10_final
2023-06-10 11:55:51	ga_s2bm_ard_3-2-1_50JKP_2023-06-10_final
2023-08-09 11:55:47	ga_s2bm_ard_3-2-1_50JLP_2023-08-09_final
2023-08-09 11:55:52	ga_s2bm_ard_3-2-1_50JKP_2023-08-09_final
2023-08-09 11:56:02	ga_s2bm_ard_3-2-1_50JLN_2023-08-09_final
2023-08-09 11:56:05	ga_s2bm_ard_3-2-1_50JKN_2023-08-09_final
2023-08-09 11:56:16	ga_s2bm_ard_3-2-1_50JLM_2023-08-09_final
2023-08-09 11:56:19	ga_s2bm_ard_3-2-1_50JKM_2023-08-09_final
2023-08-09 11:56:31	ga_s2bm_ard_3-2-1_50JLL_2023-08-09_final
2023-08-09 11:56:45	ga_s2bm_ard_3-2-1_50HLK_2023-08-09_final
2023-08-09 11:57:00	ga_s2bm_ard_3-2-1_50HLJ_2023-08-09_final
2023-08-09 11:57:15	ga_s2bm_ard_3-2-1_50HLH_2023-08-09_final
2023-08-09 11:57:28	ga_s2bm_ard_3-2-1_50HLG_2023-08-09_final
2023-08-12 12:03:07	ga_s2bm_ard_3-2-1_50KKE_2023-08-12_nrt
2023-08-12 12:03:20	ga_s2bm_ard_3-2-1_50KKD_2023-08-12_nrt
2023-08-12 12:03:35	ga_s2bm_ard_3-2-1_50KKC_2023-08-12_nrt
2023-08-12 12:03:50	ga_s2bm_ard_3-2-1_50KKB_2023-08-12_final
2023-08-12 12:04:04	ga_s2bm_ard_3-2-1_50KKA_2023-08-12_final
2023-08-12 12:04:05	ga_s2bm_ard_3-2-1_49KHR_2023-08-12_final
2023-08-12 12:04:19	ga_s2bm_ard_3-2-1_50KKV_2023-08-12_final
2023-08-12 12:04:19	ga_s2bm_ard_3-2-1_49KHQ_2023-08-12_final
2023-08-12 12:04:33	ga_s2bm_ard_3-2-1_49KHP_2023-08-12_final
2023-08-12 12:04:33	ga_s2bm_ard_3-2-1_50KKU_2023-08-12_final
2023-08-12 12:04:47	ga_s2bm_ard_3-2-1_49JHN_2023-08-12_final
2023-08-12 12:04:48	ga_s2bm_ard_3-2-1_50JKT_2023-08-12_final
2023-08-12 12:04:54	ga_s2bm_ard_3-2-1_50JKT_2023-08-12_final
2023-08-12 12:04:54	ga_s2bm_ard_3-2-1_49JHN_2023-08-12_final
2023-08-12 12:04:54	ga_s2bm_ard_3-2-1_49JHM_2023-08-12_final
2023-08-12 12:04:54	ga_s2bm_ard_3-2-1_50JKS_2023-08-12_final
2023-08-12 12:05:02	ga_s2bm_ard_3-2-1_49JHM_2023-08-12_final
2023-08-12 12:05:03	ga_s2bm_ard_3-2-1_50JKS_2023-08-12_final
2023-08-12 12:05:14	ga_s2bm_ard_3-2-1_50JLR_2023-08-12_final
2023-08-12 12:05:17	ga_s2bm_ard_3-2-1_50JKR_2023-08-12_final
2023-08-12 12:05:28	ga_s2bm_ard_3-2-1_50JLQ_2023-08-12_final
2023-08-12 12:05:32	ga_s2bm_ard_3-2-1_50JKQ_2023-08-12_final
2023-08-12 12:05:43	ga_s2bm_ard_3-2-1_50JLP_2023-08-12_final
2023-08-12 12:05:46	ga_s2bm_ard_3-2-1_50JKP_2023-08-12_final
2023-08-12 12:05:57	ga_s2bm_ard_3-2-1_50JLN_2023-08-12_final
2023-08-12 12:06:01	ga_s2bm_ard_3-2-1_50JKN_2023-08-12_final
2023-08-12 12:06:10	ga_s2bm_ard_3-2-1_50JLM_2023-08-12_final
2023-08-12 12:06:15	ga_s2bm_ard_3-2-1_50JKM_2023-08-12_final
2023-10-01 12:03:17	ga_s2bm_ard_3-2-1_50KKD_2023-10-01_nrt
2023-10-01 12:03:31	ga_s2bm_ard_3-2-1_50KKC_2023-10-01_nrt
2023-10-01 12:03:46	ga_s2bm_ard_3-2-1_50KKB_2023-10-01_final
2023-10-01 12:04:01	ga_s2bm_ard_3-2-1_50KKA_2023-10-01_final
2023-10-01 12:04:01	ga_s2bm_ard_3-2-1_49KHR_2023-10-01_final
2023-10-01 12:04:15	ga_s2bm_ard_3-2-1_50KKV_2023-10-01_final
2023-10-01 12:04:15	ga_s2bm_ard_3-2-1_49KHQ_2023-10-01_final
2023-10-01 12:04:27	ga_s2bm_ard_3-2-1_49KHP_2023-10-01_final
2023-10-01 12:04:27	ga_s2bm_ard_3-2-1_50KKU_2023-10-01_final
2023-10-01 12:04:34	ga_s2bm_ard_3-2-1_49KHP_2023-10-01_final
2023-10-01 12:04:34	ga_s2bm_ard_3-2-1_50KKU_2023-10-01_final
2023-10-01 12:04:44	ga_s2bm_ard_3-2-1_49JHN_2023-10-01_final
2023-10-01 12:04:44	ga_s2bm_ard_3-2-1_50JKT_2023-10-01_final
2023-10-01 12:04:59	ga_s2bm_ard_3-2-1_49JHM_2023-10-01_final
2023-10-01 12:04:59	ga_s2bm_ard_3-2-1_50JKS_2023-10-01_final
2023-10-01 12:05:10	ga_s2bm_ard_3-2-1_50JLR_2023-10-01_final
2023-10-01 12:05:14	ga_s2bm_ard_3-2-1_50JKR_2023-10-01_final
2023-10-18 11:55:44	ga_s2bm_ard_3-2-1_50JLP_2023-10-18_final
2023-10-18 11:55:49	ga_s2bm_ard_3-2-1_50JKP_2023-10-18_final
2023-10-18 11:55:58	ga_s2bm_ard_3-2-1_50JLN_2023-10-18_final
2023-10-18 11:56:01	ga_s2bm_ard_3-2-1_50JKN_2023-10-18_final
2023-10-18 11:56:06	ga_s2bm_ard_3-2-1_50JLN_2023-10-18_final
2023-10-18 11:56:06	ga_s2bm_ard_3-2-1_50JLM_2023-10-18_final
2023-10-18 11:56:07	ga_s2bm_ard_3-2-1_50JKM_2023-10-18_final
2023-10-18 11:56:07	ga_s2bm_ard_3-2-1_50JKN_2023-10-18_final
2023-10-18 11:56:13	ga_s2bm_ard_3-2-1_50JLM_2023-10-18_final
2023-10-18 11:56:16	ga_s2bm_ard_3-2-1_50JKM_2023-10-18_final
2023-10-18 11:56:28	ga_s2bm_ard_3-2-1_50JLL_2023-10-18_final
2023-10-18 11:56:31	ga_s2bm_ard_3-2-1_50JKL_2023-10-18_nrt
2023-10-18 11:56:42	ga_s2bm_ard_3-2-1_50HLK_2023-10-18_final
2023-10-18 11:56:46	ga_s2bm_ard_3-2-1_50HKK_2023-10-18_nrt
2023-10-18 11:56:57	ga_s2bm_ard_3-2-1_50HLJ_2023-10-18_final
2023-10-18 11:57:11	ga_s2bm_ard_3-2-1_50HLH_2023-10-18_final

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