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
2023-06-18 11:10:30	ga_s2bm_ard_3-2-1_52LHN_2023-06-18_final
2023-06-18 11:10:34	ga_s2bm_ard_3-2-1_52LGN_2023-06-18_final
2023-06-18 11:10:37	ga_s2bm_ard_3-2-1_52LFN_2023-06-18_final
2023-06-18 11:10:40	ga_s2bm_ard_3-2-1_52LEN_2023-06-18_nrt
2023-06-23 12:00:51	ga_s2bm_ard_3-2-1_50LQN_2023-06-23_nrt
2023-06-23 12:00:55	ga_s2bm_ard_3-2-1_50LPN_2023-06-23_nrt
2023-06-23 12:00:58	ga_s2bm_ard_3-2-1_50LNN_2023-06-23_nrt
2023-06-23 12:01:01	ga_s2bm_ard_3-2-1_50LMN_2023-06-23_nrt
2023-07-11 11:20:36	ga_s2bm_ard_3-2-1_52LEN_2023-07-11_nrt
2023-07-11 11:20:39	ga_s2bm_ard_3-2-1_52LDN_2023-07-11_nrt
2023-07-11 11:20:42	ga_s2bm_ard_3-2-1_52LCN_2023-07-11_nrt
2023-07-11 11:20:45	ga_s2bm_ard_3-2-1_52LBN_2023-07-11_nrt
2023-07-12 10:50:21	ga_s2bm_ard_3-2-1_53LQH_2023-07-12_nrt
2023-07-12 10:50:25	ga_s2bm_ard_3-2-1_53LPH_2023-07-12_final
2023-07-12 10:50:29	ga_s2bm_ard_3-2-1_53LNH_2023-07-12_final
2023-07-12 10:50:32	ga_s2bm_ard_3-2-1_53LMH_2023-07-12_final
2023-07-13 10:20:09	ga_s2bm_ard_3-2-1_55LBH_2023-07-13_nrt
2023-07-13 10:20:11	ga_s2bm_ard_3-2-1_54LZN_2023-07-13_final
2023-07-13 10:20:15	ga_s2bm_ard_3-2-1_54LYN_2023-07-13_final
2023-07-13 10:20:18	ga_s2bm_ard_3-2-1_54LXN_2023-07-13_final
2023-07-13 10:20:23	ga_s2bm_ard_3-2-1_54LWN_2023-07-13_final
2023-07-14 11:30:40	ga_s2bm_ard_3-2-1_52LBN_2023-07-14_nrt
2023-07-14 11:30:42	ga_s2bm_ard_3-2-1_51LZH_2023-07-14_nrt
2023-07-14 11:30:46	ga_s2bm_ard_3-2-1_51LYH_2023-07-14_nrt
2023-07-14 11:30:49	ga_s2bm_ard_3-2-1_51LXH_2023-07-14_nrt
2023-07-17 11:40:45	ga_s2bm_ard_3-2-1_51LXH_2023-07-17_nrt
2023-07-17 11:40:48	ga_s2bm_ard_3-2-1_51LWH_2023-07-17_nrt
2023-07-17 11:40:51	ga_s2bm_ard_3-2-1_51LVH_2023-07-17_nrt
2023-07-17 11:40:54	ga_s2bm_ard_3-2-1_51LUH_2023-07-17_nrt
2023-07-18 09:30:00	ga_s2bm_ard_3-2-1_56LPN_2023-07-18_nrt
2023-07-20 10:10:04	ga_s2bm_ard_3-2-1_55LEH_2023-07-20_nrt
2023-07-20 10:10:09	ga_s2bm_ard_3-2-1_55LDH_2023-07-20_nrt
2023-07-20 10:10:12	ga_s2bm_ard_3-2-1_55LCH_2023-07-20_nrt
2023-07-20 10:10:16	ga_s2bm_ard_3-2-1_55LBH_2023-07-20_nrt
2023-07-20 10:10:17	ga_s2bm_ard_3-2-1_54LZN_2023-07-20_final
2023-07-20 11:50:50	ga_s2bm_ard_3-2-1_51LUH_2023-07-20_nrt
2023-07-20 11:50:54	ga_s2bm_ard_3-2-1_51LTH_2023-07-20_nrt
2023-07-20 11:50:55	ga_s2bm_ard_3-2-1_50LRN_2023-07-20_nrt
2023-07-20 11:50:58	ga_s2bm_ard_3-2-1_50LQN_2023-07-20_nrt
2023-07-21 09:39:55	ga_s2bm_ard_3-2-1_56LPN_2023-07-21_nrt
2023-07-21 09:39:59	ga_s2bm_ard_3-2-1_56LNN_2023-07-21_nrt
2023-07-21 09:40:02	ga_s2bm_ard_3-2-1_56LMN_2023-07-21_nrt
2023-07-21 09:40:06	ga_s2bm_ard_3-2-1_56LLN_2023-07-21_nrt
2023-07-22 10:50:22	ga_s2bm_ard_3-2-1_53LQH_2023-07-22_nrt
2023-07-22 10:50:26	ga_s2bm_ard_3-2-1_53LPH_2023-07-22_final
2023-07-22 10:50:30	ga_s2bm_ard_3-2-1_53LNH_2023-07-22_final
2023-07-22 10:50:33	ga_s2bm_ard_3-2-1_53LMH_2023-07-22_final
2023-07-31 11:20:36	ga_s2bm_ard_3-2-1_52LEN_2023-07-31_nrt
2023-07-31 11:20:39	ga_s2bm_ard_3-2-1_52LDN_2023-07-31_nrt
2023-07-31 11:20:43	ga_s2bm_ard_3-2-1_52LCN_2023-07-31_nrt
2023-07-31 11:20:45	ga_s2bm_ard_3-2-1_52LBN_2023-07-31_nrt
2023-08-05 10:30:20	ga_s2bm_ard_3-2-1_54LVN_2023-08-05_nrt
2023-08-05 10:30:23	ga_s2bm_ard_3-2-1_54LUN_2023-08-05_nrt
2023-08-15 10:30:13	ga_s2bm_ard_3-2-1_54LXN_2023-08-15_final
2023-08-15 10:30:17	ga_s2bm_ard_3-2-1_54LWN_2023-08-15_final
2023-08-15 10:30:21	ga_s2bm_ard_3-2-1_54LVN_2023-08-15_nrt
2023-08-15 10:30:24	ga_s2bm_ard_3-2-1_54LUN_2023-08-15_nrt
2023-08-20 09:39:54	ga_s2bm_ard_3-2-1_56LPN_2023-08-20_nrt
2023-08-20 09:39:58	ga_s2bm_ard_3-2-1_56LNN_2023-08-20_nrt
2023-08-20 09:40:01	ga_s2bm_ard_3-2-1_56LMN_2023-08-20_nrt
2023-08-20 09:40:05	ga_s2bm_ard_3-2-1_56LLN_2023-08-20_nrt
2023-08-20 11:20:36	ga_s2bm_ard_3-2-1_52LEN_2023-08-20_nrt
2023-08-20 11:20:39	ga_s2bm_ard_3-2-1_52LDN_2023-08-20_nrt
2023-08-20 11:20:42	ga_s2bm_ard_3-2-1_52LCN_2023-08-20_nrt
2023-08-20 11:20:45	ga_s2bm_ard_3-2-1_52LBN_2023-08-20_nrt
2023-08-22 12:00:52	ga_s2bm_ard_3-2-1_50LQN_2023-08-22_nrt
2023-08-22 12:00:56	ga_s2bm_ard_3-2-1_50LPN_2023-08-22_nrt
2023-08-22 12:00:59	ga_s2bm_ard_3-2-1_50LNN_2023-08-22_nrt
2023-08-22 12:01:02	ga_s2bm_ard_3-2-1_50LMN_2023-08-22_nrt
2023-12-11 11:30:38	ga_s2bm_ard_3-2-1_51LYH_2023-12-11_nrt
2023-12-11 11:30:41	ga_s2bm_ard_3-2-1_51LXH_2023-12-11_nrt
2023-12-12 11:00:19	ga_s2bm_ard_3-2-1_53LMH_2023-12-12_final
2023-12-12 11:00:23	ga_s2bm_ard_3-2-1_53LLH_2023-12-12_final
2023-12-12 11:00:26	ga_s2bm_ard_3-2-1_53LKH_2023-12-12_final
2023-12-12 11:00:28	ga_s2bm_ard_3-2-1_52LHN_2023-12-12_final
2023-12-15 11:10:24	ga_s2bm_ard_3-2-1_52LHN_2023-12-15_final
2023-12-15 11:10:28	ga_s2bm_ard_3-2-1_52LGN_2023-12-15_final
2023-12-15 11:10:31	ga_s2bm_ard_3-2-1_52LFN_2023-12-15_final
2023-12-15 11:10:34	ga_s2bm_ard_3-2-1_52LEN_2023-12-15_nrt
2023-12-16 10:40:13	ga_s2bm_ard_3-2-1_54LUN_2023-12-16_nrt
2023-12-16 10:40:16	ga_s2bm_ard_3-2-1_54LTN_2023-12-16_nrt
2023-12-16 10:40:18	ga_s2bm_ard_3-2-1_53LRH_2023-12-16_nrt
2023-12-16 10:40:21	ga_s2bm_ard_3-2-1_53LQH_2023-12-16_nrt
2023-12-16 10:40:27	ga_s2bm_ard_3-2-1_53LPH_2023-12-16_final
2023-12-17 11:50:44	ga_s2bm_ard_3-2-1_51LUH_2023-12-17_nrt
2023-12-17 11:50:47	ga_s2bm_ard_3-2-1_51LTH_2023-12-17_nrt
2023-12-17 11:50:49	ga_s2bm_ard_3-2-1_50LRN_2023-12-17_nrt
2023-12-17 11:50:52	ga_s2bm_ard_3-2-1_50LQN_2023-12-17_nrt
2023-12-18 09:39:49	ga_s2bm_ard_3-2-1_56LPN_2023-12-18_nrt
2023-12-18 09:39:53	ga_s2bm_ard_3-2-1_56LNN_2023-12-18_nrt
2023-12-18 09:39:56	ga_s2bm_ard_3-2-1_56LMN_2023-12-18_nrt
2023-12-18 09:40:00	ga_s2bm_ard_3-2-1_56LLN_2023-12-18_nrt
2023-12-19 10:50:16	ga_s2bm_ard_3-2-1_53LQH_2023-12-19_nrt
2023-12-19 10:50:21	ga_s2bm_ard_3-2-1_53LPH_2023-12-19_final
2023-12-19 10:50:24	ga_s2bm_ard_3-2-1_53LNH_2023-12-19_final
2023-12-19 10:50:27	ga_s2bm_ard_3-2-1_53LMH_2023-12-19_final
2023-12-20 10:20:05	ga_s2bm_ard_3-2-1_55LBH_2023-12-20_nrt
2023-12-20 10:20:07	ga_s2bm_ard_3-2-1_54LZN_2023-12-20_final
2023-12-20 10:20:11	ga_s2bm_ard_3-2-1_54LYN_2023-12-20_final
2023-12-20 10:20:14	ga_s2bm_ard_3-2-1_54LXN_2023-12-20_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