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
2023-11-10 10:22:29	ga_s2bm_ard_3-2-1_54KWD_2023-11-10_final
2023-11-10 10:22:33	ga_s2bm_ard_3-2-1_54KVD_2023-11-10_final
2023-11-10 10:22:36	ga_s2bm_ard_3-2-1_54KUD_2023-11-10_final
2023-11-11 11:32:38	ga_s2bm_ard_3-2-1_51KYV_2023-11-11_final
2023-11-11 11:32:42	ga_s2bm_ard_3-2-1_51KXV_2023-11-11_final
2023-11-11 11:32:45	ga_s2bm_ard_3-2-1_51KWV_2023-11-11_final
2023-11-11 11:32:48	ga_s2bm_ard_3-2-1_51KVV_2023-11-11_final
2023-11-11 11:32:52	ga_s2bm_ard_3-2-1_51KYU_2023-11-11_final
2023-11-11 11:32:56	ga_s2bm_ard_3-2-1_51KXU_2023-11-11_final
2023-11-11 11:33:00	ga_s2bm_ard_3-2-1_51KWU_2023-11-11_final
2023-11-14 10:01:55	ga_s2bm_ard_3-2-1_55KFV_2023-11-14_nrt
2023-11-14 10:02:08	ga_s2bm_ard_3-2-1_55KCV_2023-11-14_final
2023-11-14 10:02:22	ga_s2bm_ard_3-2-1_55KCU_2023-11-14_final
2023-11-17 10:12:02	ga_s2bm_ard_3-2-1_55KCV_2023-11-17_final
2023-11-17 10:12:05	ga_s2bm_ard_3-2-1_55KBV_2023-11-17_final
2023-11-17 10:12:06	ga_s2bm_ard_3-2-1_54KZE_2023-11-17_final
2023-11-17 10:12:09	ga_s2bm_ard_3-2-1_54KYE_2023-11-17_final
2023-11-17 10:12:13	ga_s2bm_ard_3-2-1_54KXE_2023-11-17_final
2023-11-17 10:12:15	ga_s2bm_ard_3-2-1_55KCU_2023-11-17_final
2023-11-17 10:12:20	ga_s2bm_ard_3-2-1_55KBU_2023-11-17_final
2023-11-17 10:12:20	ga_s2bm_ard_3-2-1_54KZD_2023-11-17_final
2023-11-17 10:12:24	ga_s2bm_ard_3-2-1_54KYD_2023-11-17_final
2023-11-17 10:12:27	ga_s2bm_ard_3-2-1_54KXD_2023-11-17_final
2023-11-18 11:22:32	ga_s2bm_ard_3-2-1_52KCE_2023-11-18_final
2023-11-18 11:22:35	ga_s2bm_ard_3-2-1_52KBE_2023-11-18_final
2023-11-18 11:22:36	ga_s2bm_ard_3-2-1_51KZV_2023-11-18_final
2023-11-18 11:22:40	ga_s2bm_ard_3-2-1_51KYV_2023-11-18_final
2023-11-18 11:22:46	ga_s2bm_ard_3-2-1_52KCD_2023-11-18_final
2023-11-18 11:22:50	ga_s2bm_ard_3-2-1_52KBD_2023-11-18_final
2023-11-18 11:22:51	ga_s2bm_ard_3-2-1_51KZU_2023-11-18_final
2023-11-18 11:22:54	ga_s2bm_ard_3-2-1_51KYU_2023-11-18_final
2023-11-18 11:22:59	ga_s2bm_ard_3-2-1_51KXU_2023-11-18_final
2023-11-19 10:52:24	ga_s2bm_ard_3-2-1_53KLV_2023-11-19_final
2023-11-19 10:52:27	ga_s2bm_ard_3-2-1_53KKV_2023-11-19_final
2023-11-19 10:52:29	ga_s2bm_ard_3-2-1_52KHE_2023-11-19_final
2023-11-19 10:52:35	ga_s2bm_ard_3-2-1_53KMU_2023-11-19_final
2023-11-19 10:52:39	ga_s2bm_ard_3-2-1_53KLU_2023-11-19_final
2023-11-19 10:52:42	ga_s2bm_ard_3-2-1_53KKU_2023-11-19_final
2023-11-19 10:52:42	ga_s2bm_ard_3-2-1_52KHD_2023-11-19_final
2023-11-20 10:22:01	ga_s2bm_ard_3-2-1_54KYE_2023-11-20_final
2023-11-20 10:22:06	ga_s2bm_ard_3-2-1_54KXE_2023-11-20_final
2023-11-26 10:42:08	ga_s2bm_ard_3-2-1_53KRV_2023-11-26_final
2023-11-26 10:42:13	ga_s2bm_ard_3-2-1_53KQV_2023-11-26_final
2023-11-26 10:42:17	ga_s2bm_ard_3-2-1_53KPV_2023-11-26_final
2023-11-26 10:42:18	ga_s2bm_ard_3-2-1_53KRU_2023-11-26_final
2023-11-26 10:42:21	ga_s2bm_ard_3-2-1_53KNV_2023-11-26_final
2023-11-26 10:42:28	ga_s2bm_ard_3-2-1_53KQU_2023-11-26_final
2023-11-26 10:42:32	ga_s2bm_ard_3-2-1_53KPU_2023-11-26_final
2023-11-26 10:42:35	ga_s2bm_ard_3-2-1_53KNU_2023-11-26_final
2023-11-28 11:22:33	ga_s2bm_ard_3-2-1_52KCE_2023-11-28_final
2023-11-28 11:22:35	ga_s2bm_ard_3-2-1_52KBE_2023-11-28_final
2023-11-28 11:22:36	ga_s2bm_ard_3-2-1_51KZV_2023-11-28_final
2023-11-28 11:22:38	ga_s2bm_ard_3-2-1_51KYV_2023-11-28_final
2023-11-28 11:22:45	ga_s2bm_ard_3-2-1_52KCD_2023-11-28_final
2023-11-28 11:22:48	ga_s2bm_ard_3-2-1_52KBD_2023-11-28_final
2023-11-28 11:22:49	ga_s2bm_ard_3-2-1_51KZU_2023-11-28_final
2023-11-28 11:22:52	ga_s2bm_ard_3-2-1_51KYU_2023-11-28_final
2023-11-28 11:22:57	ga_s2bm_ard_3-2-1_51KXU_2023-11-28_final
2023-11-30 12:02:52	ga_s2bm_ard_3-2-1_50KNE_2023-11-30_nrt
2023-11-30 12:02:54	ga_s2bm_ard_3-2-1_50KME_2023-11-30_nrt
2023-11-30 12:02:55	ga_s2bm_ard_3-2-1_50KLE_2023-11-30_nrt
2023-11-30 12:02:58	ga_s2bm_ard_3-2-1_50KKE_2023-11-30_nrt
2023-11-30 12:03:06	ga_s2bm_ard_3-2-1_50KMD_2023-11-30_nrt
2023-11-30 12:03:09	ga_s2bm_ard_3-2-1_50KLD_2023-11-30_nrt
2023-11-30 12:03:12	ga_s2bm_ard_3-2-1_50KKD_2023-11-30_nrt
2023-11-30 12:03:14	ga_s2bm_ard_3-2-1_49KHU_2023-11-30_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 09:52:17	ga_s2bm_ard_3-2-1_55KEU_2023-12-01_final
2024-01-27 11:22:32	ga_s2bm_ard_3-2-1_52KCE_2024-01-27_final
2024-01-27 11:22:35	ga_s2bm_ard_3-2-1_52KBE_2024-01-27_final
2024-01-27 11:22:36	ga_s2bm_ard_3-2-1_51KZV_2024-01-27_final
2024-01-27 11:22:40	ga_s2bm_ard_3-2-1_51KYV_2024-01-27_final
2024-01-27 11:22:47	ga_s2bm_ard_3-2-1_52KCD_2024-01-27_final
2024-01-27 11:22:50	ga_s2bm_ard_3-2-1_52KBD_2024-01-27_final
2024-01-27 11:22:51	ga_s2bm_ard_3-2-1_51KZU_2024-01-27_final
2024-01-27 11:22:54	ga_s2bm_ard_3-2-1_51KYU_2024-01-27_final
2024-01-27 11:22:59	ga_s2bm_ard_3-2-1_51KXU_2024-01-27_final
2024-01-28 10:52:18	ga_s2bm_ard_3-2-1_53KNV_2024-01-28_final
2024-01-28 10:52:22	ga_s2bm_ard_3-2-1_53KMV_2024-01-28_final
2024-01-28 10:52:25	ga_s2bm_ard_3-2-1_53KLV_2024-01-28_final
2024-01-28 10:52:28	ga_s2bm_ard_3-2-1_53KKV_2024-01-28_final
2024-01-28 10:52:29	ga_s2bm_ard_3-2-1_52KHE_2024-01-28_final
2024-01-28 10:52:36	ga_s2bm_ard_3-2-1_53KMU_2024-01-28_final
2024-01-28 10:52:39	ga_s2bm_ard_3-2-1_53KLU_2024-01-28_final
2024-01-28 10:52:43	ga_s2bm_ard_3-2-1_53KKU_2024-01-28_final
2024-01-28 10:52:43	ga_s2bm_ard_3-2-1_52KHD_2024-01-28_final
2024-01-30 11:32:34	ga_s2bm_ard_3-2-1_51KYV_2024-01-30_final
2024-01-30 11:32:38	ga_s2bm_ard_3-2-1_51KXV_2024-01-30_final
2024-01-30 11:32:41	ga_s2bm_ard_3-2-1_51KWV_2024-01-30_final
2024-01-30 11:32:44	ga_s2bm_ard_3-2-1_51KVV_2024-01-30_final
2024-01-30 11:32:48	ga_s2bm_ard_3-2-1_51KYU_2024-01-30_final
2024-01-30 11:32:52	ga_s2bm_ard_3-2-1_51KXU_2024-01-30_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