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
2023-09-04 10:32:16	ga_s2bm_ard_3-2-1_54KVE_2023-09-04_final
2023-09-04 10:32:20	ga_s2bm_ard_3-2-1_54KUE_2023-09-04_final
2023-09-04 10:32:23	ga_s2bm_ard_3-2-1_54KTE_2023-09-04_final
2023-09-04 10:32:23	ga_s2bm_ard_3-2-1_53KRV_2023-09-04_final
2023-09-04 10:32:27	ga_s2bm_ard_3-2-1_53KQV_2023-09-04_final
2023-09-04 10:32:34	ga_s2bm_ard_3-2-1_54KUD_2023-09-04_final
2023-09-04 10:32:37	ga_s2bm_ard_3-2-1_54KTD_2023-09-04_final
2023-09-04 10:32:38	ga_s2bm_ard_3-2-1_53KRU_2023-09-04_final
2023-09-04 10:32:41	ga_s2bm_ard_3-2-1_53KQU_2023-09-04_final
2023-09-05 10:02:05	ga_s2bm_ard_3-2-1_55KEV_2023-09-05_final
2023-09-05 10:02:09	ga_s2bm_ard_3-2-1_55KDV_2023-09-05_final
2023-09-05 10:02:12	ga_s2bm_ard_3-2-1_55KCV_2023-09-05_final
2023-09-05 10:02:19	ga_s2bm_ard_3-2-1_55KBV_2023-09-05_final
2023-09-05 10:02:27	ga_s2bm_ard_3-2-1_55KCU_2023-09-05_final
2023-09-05 10:02:31	ga_s2bm_ard_3-2-1_55KBU_2023-09-05_final
2023-09-05 11:42:47	ga_s2bm_ard_3-2-1_51KVV_2023-09-05_final
2023-09-05 11:42:50	ga_s2bm_ard_3-2-1_51KUV_2023-09-05_final
2023-09-05 11:42:53	ga_s2bm_ard_3-2-1_51KTV_2023-09-05_nrt
2023-09-05 11:42:54	ga_s2bm_ard_3-2-1_50KRE_2023-09-05_nrt
2023-09-05 11:43:05	ga_s2bm_ard_3-2-1_51KUU_2023-09-05_final
2023-09-05 11:43:07	ga_s2bm_ard_3-2-1_51KTU_2023-09-05_final
2023-09-05 11:43:07	ga_s2bm_ard_3-2-1_50KRD_2023-09-05_final
2023-09-05 11:43:10	ga_s2bm_ard_3-2-1_50KQD_2023-09-05_final
2023-10-01 12:02:57	ga_s2bm_ard_3-2-1_50KNE_2023-10-01_nrt
2023-10-01 12:02:59	ga_s2bm_ard_3-2-1_50KME_2023-10-01_nrt
2023-10-01 12:03:00	ga_s2bm_ard_3-2-1_50KLE_2023-10-01_nrt
2023-10-01 12:03:03	ga_s2bm_ard_3-2-1_50KKE_2023-10-01_nrt
2023-10-01 12:03:14	ga_s2bm_ard_3-2-1_50KLD_2023-10-01_nrt
2023-10-01 12:03:17	ga_s2bm_ard_3-2-1_50KKD_2023-10-01_nrt
2023-10-01 12:03:19	ga_s2bm_ard_3-2-1_49KHU_2023-10-01_nrt
2023-10-03 11:02:26	ga_s2bm_ard_3-2-1_53KKV_2023-10-03_final
2023-10-03 11:02:27	ga_s2bm_ard_3-2-1_52KHE_2023-10-03_final
2023-10-03 11:02:30	ga_s2bm_ard_3-2-1_52KGE_2023-10-03_final
2023-10-03 11:02:33	ga_s2bm_ard_3-2-1_52KFE_2023-10-03_final
2023-10-03 11:02:36	ga_s2bm_ard_3-2-1_53KKU_2023-10-03_final
2023-10-03 11:02:36	ga_s2bm_ard_3-2-1_52KHD_2023-10-03_final
2023-10-03 11:02:38	ga_s2bm_ard_3-2-1_52KGE_2023-10-03_final
2023-10-03 11:02:38	ga_s2bm_ard_3-2-1_52KGD_2023-10-03_final
2023-10-03 11:02:39	ga_s2bm_ard_3-2-1_52KFD_2023-10-03_final
2023-10-03 11:02:39	ga_s2bm_ard_3-2-1_52KFE_2023-10-03_final
2023-10-03 11:02:45	ga_s2bm_ard_3-2-1_52KGD_2023-10-03_final
2023-10-03 11:02:48	ga_s2bm_ard_3-2-1_52KFD_2023-10-03_final
2023-10-03 11:02:53	ga_s2bm_ard_3-2-1_52KED_2023-10-03_final
2023-10-04 10:32:12	ga_s2bm_ard_3-2-1_54KVE_2023-10-04_final
2023-10-04 10:32:15	ga_s2bm_ard_3-2-1_54KUE_2023-10-04_final
2023-10-04 10:32:19	ga_s2bm_ard_3-2-1_54KTE_2023-10-04_final
2023-10-04 10:32:19	ga_s2bm_ard_3-2-1_53KRV_2023-10-04_final
2023-10-04 10:32:23	ga_s2bm_ard_3-2-1_53KQV_2023-10-04_final
2023-10-04 10:32:30	ga_s2bm_ard_3-2-1_54KUD_2023-10-04_final
2023-10-04 10:32:33	ga_s2bm_ard_3-2-1_54KTD_2023-10-04_final
2023-10-04 10:32:33	ga_s2bm_ard_3-2-1_53KRU_2023-10-04_final
2023-10-04 10:32:35	ga_s2bm_ard_3-2-1_53KQU_2023-10-04_final
2023-10-12 11:32:39	ga_s2bm_ard_3-2-1_51KYV_2023-10-12_final
2023-10-12 11:32:42	ga_s2bm_ard_3-2-1_51KXV_2023-10-12_final
2023-10-12 11:32:46	ga_s2bm_ard_3-2-1_51KWV_2023-10-12_final
2023-10-12 11:32:48	ga_s2bm_ard_3-2-1_51KVV_2023-10-12_final
2023-10-12 11:32:52	ga_s2bm_ard_3-2-1_51KYU_2023-10-12_final
2023-10-12 11:32:57	ga_s2bm_ard_3-2-1_51KXU_2023-10-12_final
2023-10-12 11:33:00	ga_s2bm_ard_3-2-1_51KWU_2023-10-12_final
2023-10-13 11:02:27	ga_s2bm_ard_3-2-1_53KKV_2023-10-13_final
2023-10-13 11:02:28	ga_s2bm_ard_3-2-1_52KHE_2023-10-13_final
2023-10-13 11:02:31	ga_s2bm_ard_3-2-1_52KGE_2023-10-13_final
2023-10-13 11:02:34	ga_s2bm_ard_3-2-1_52KFE_2023-10-13_final
2023-10-13 11:02:37	ga_s2bm_ard_3-2-1_53KKU_2023-10-13_final
2023-10-13 11:02:37	ga_s2bm_ard_3-2-1_52KHD_2023-10-13_final
2023-10-13 11:02:39	ga_s2bm_ard_3-2-1_52KGE_2023-10-13_final
2023-10-13 11:02:39	ga_s2bm_ard_3-2-1_52KGD_2023-10-13_final
2023-10-13 11:02:40	ga_s2bm_ard_3-2-1_52KFD_2023-10-13_final
2023-10-13 11:02:40	ga_s2bm_ard_3-2-1_52KFE_2023-10-13_final
2023-10-13 11:02:46	ga_s2bm_ard_3-2-1_52KGD_2023-10-13_final
2023-10-13 11:02:50	ga_s2bm_ard_3-2-1_52KFD_2023-10-13_final
2023-10-13 11:02:54	ga_s2bm_ard_3-2-1_52KED_2023-10-13_final
2023-10-15 10:01:57	ga_s2bm_ard_3-2-1_55KFV_2023-10-15_nrt
2023-10-15 10:02:03	ga_s2bm_ard_3-2-1_55KEV_2023-10-15_final
2023-10-15 10:02:07	ga_s2bm_ard_3-2-1_55KDV_2023-10-15_final
2023-10-15 10:02:10	ga_s2bm_ard_3-2-1_55KCV_2023-10-15_final
2023-10-15 10:02:17	ga_s2bm_ard_3-2-1_55KBV_2023-10-15_final
2023-10-15 10:02:24	ga_s2bm_ard_3-2-1_55KCU_2023-10-15_final
2023-10-15 10:02:28	ga_s2bm_ard_3-2-1_55KBU_2023-10-15_final
2023-10-16 11:12:49	ga_s2bm_ard_3-2-1_52KED_2023-10-16_final
2023-10-16 11:12:55	ga_s2bm_ard_3-2-1_52KCD_2023-10-16_final
2023-10-17 10:42:15	ga_s2bm_ard_3-2-1_53KRV_2023-10-17_final
2023-10-17 10:42:20	ga_s2bm_ard_3-2-1_53KQV_2023-10-17_final
2023-10-17 10:42:24	ga_s2bm_ard_3-2-1_53KPV_2023-10-17_final
2023-10-17 10:42:24	ga_s2bm_ard_3-2-1_53KRU_2023-10-17_final
2023-10-17 10:42:27	ga_s2bm_ard_3-2-1_53KNV_2023-10-17_final
2023-10-17 10:42:34	ga_s2bm_ard_3-2-1_53KQU_2023-10-17_final
2023-10-17 10:42:38	ga_s2bm_ard_3-2-1_53KPU_2023-10-17_final
2023-10-17 10:42:41	ga_s2bm_ard_3-2-1_53KNU_2023-10-17_final
2023-10-20 10:52:22	ga_s2bm_ard_3-2-1_53KNV_2023-10-20_final
2023-10-20 10:52:25	ga_s2bm_ard_3-2-1_53KMV_2023-10-20_final
2023-10-20 10:52:29	ga_s2bm_ard_3-2-1_53KLV_2023-10-20_final
2023-10-20 10:52:31	ga_s2bm_ard_3-2-1_53KKV_2023-10-20_final
2023-10-20 10:52:33	ga_s2bm_ard_3-2-1_52KHE_2023-10-20_final
2023-10-21 10:22:06	ga_s2bm_ard_3-2-1_54KYE_2023-10-21_final
2023-10-21 10:22:11	ga_s2bm_ard_3-2-1_54KXE_2023-10-21_final
2023-10-21 10:22:15	ga_s2bm_ard_3-2-1_54KWE_2023-10-21_final
2023-10-21 10:22:15	ga_s2bm_ard_3-2-1_54KYD_2023-10-21_final
2023-10-21 10:22:18	ga_s2bm_ard_3-2-1_54KVE_2023-10-21_final
2023-11-07 10:12:23	ga_s2bm_ard_3-2-1_55KBU_2023-11-07_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