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
2023-06-11 09:41:22	ga_s2bm_ard_3-2-1_56LLH_2023-06-11_nrt
2023-06-11 09:41:32	ga_s2bm_ard_3-2-1_56KLG_2023-06-11_final
2023-06-11 09:41:46	ga_s2bm_ard_3-2-1_56KLF_2023-06-11_final
2023-06-11 09:42:01	ga_s2bm_ard_3-2-1_56KLE_2023-06-11_final
2023-06-14 09:49:45	ga_s2bm_ard_3-2-1_56LLP_2023-06-14_nrt
2023-06-14 09:49:48	ga_s2bm_ard_3-2-1_56LKP_2023-06-14_nrt
2023-06-14 09:50:00	ga_s2bm_ard_3-2-1_56LLN_2023-06-14_nrt
2023-06-14 09:50:03	ga_s2bm_ard_3-2-1_56LKN_2023-06-14_nrt
2023-06-14 09:50:10	ga_s2bm_ard_3-2-1_56LLM_2023-06-14_nrt
2023-06-14 09:50:11	ga_s2bm_ard_3-2-1_56LKM_2023-06-14_nrt
2023-06-14 09:51:04	ga_s2bm_ard_3-2-1_56LLJ_2023-06-14_nrt
2023-06-14 09:51:09	ga_s2bm_ard_3-2-1_56LLH_2023-06-14_nrt
2023-06-18 09:33:32	ga_s2bm_ard_3-2-1_56KLU_2023-06-18_final
2023-06-18 09:33:47	ga_s2bm_ard_3-2-1_56JLT_2023-06-18_final
2023-06-18 09:34:01	ga_s2bm_ard_3-2-1_56JLS_2023-06-18_final
2023-06-18 09:34:16	ga_s2bm_ard_3-2-1_56JLR_2023-06-18_final
2023-06-18 09:34:31	ga_s2bm_ard_3-2-1_56JLQ_2023-06-18_final
2023-06-18 09:34:45	ga_s2bm_ard_3-2-1_56JLP_2023-06-18_final
2023-06-18 09:35:00	ga_s2bm_ard_3-2-1_56JLN_2023-06-18_final
2023-06-18 09:35:14	ga_s2bm_ard_3-2-1_56JLM_2023-06-18_final
2023-06-18 09:35:29	ga_s2bm_ard_3-2-1_56JLL_2023-06-18_final
2023-06-18 09:35:43	ga_s2bm_ard_3-2-1_56HLK_2023-06-18_final
2023-06-18 09:35:58	ga_s2bm_ard_3-2-1_56HLJ_2023-06-18_final
2023-06-18 09:36:12	ga_s2bm_ard_3-2-1_56HLH_2023-06-18_final
2023-06-18 09:36:27	ga_s2bm_ard_3-2-1_56HLG_2023-06-18_final
2023-06-18 09:36:42	ga_s2bm_ard_3-2-1_56HLF_2023-06-18_nrt
2023-06-21 09:41:46	ga_s2bm_ard_3-2-1_56KLF_2023-06-21_final
2023-06-21 09:42:00	ga_s2bm_ard_3-2-1_56KLE_2023-06-21_final
2023-06-21 09:42:15	ga_s2bm_ard_3-2-1_56KLD_2023-06-21_final
2023-06-21 09:42:29	ga_s2bm_ard_3-2-1_56KLC_2023-06-21_nrt
2023-06-21 09:42:44	ga_s2bm_ard_3-2-1_56KLB_2023-06-21_final
2023-06-21 09:42:58	ga_s2bm_ard_3-2-1_56KLA_2023-06-21_final
2023-06-21 09:43:13	ga_s2bm_ard_3-2-1_56KLV_2023-06-21_final
2023-06-21 09:43:27	ga_s2bm_ard_3-2-1_56KLU_2023-06-21_final
2023-06-24 09:49:59	ga_s2bm_ard_3-2-1_56LLN_2023-06-24_nrt
2023-06-24 09:50:02	ga_s2bm_ard_3-2-1_56LKN_2023-06-24_nrt
2023-06-24 09:50:09	ga_s2bm_ard_3-2-1_56LLM_2023-06-24_nrt
2023-06-24 09:50:10	ga_s2bm_ard_3-2-1_56LKM_2023-06-24_nrt
2023-06-24 09:51:03	ga_s2bm_ard_3-2-1_56LLJ_2023-06-24_nrt
2023-06-24 09:51:08	ga_s2bm_ard_3-2-1_56LLH_2023-06-24_nrt
2023-06-25 09:26:02	ga_s2bm_ard_3-2-1_56HLJ_2023-06-24_final
2023-06-25 09:28:44	ga_s2bm_ard_3-2-1_56GLT_2023-06-24_nrt
2023-06-25 09:28:56	ga_s2bm_ard_3-2-1_56GLS_2023-06-24_nrt
2023-09-19 09:43:41	ga_s2bm_ard_3-2-1_56JLT_2023-09-19_final
2023-09-19 09:43:56	ga_s2bm_ard_3-2-1_56JLS_2023-09-19_final
2023-09-19 09:44:09	ga_s2bm_ard_3-2-1_56JLR_2023-09-19_final
2023-09-22 09:49:44	ga_s2bm_ard_3-2-1_56LLP_2023-09-22_nrt
2023-09-22 09:49:47	ga_s2bm_ard_3-2-1_56LKP_2023-09-22_nrt
2023-09-22 09:49:58	ga_s2bm_ard_3-2-1_56LLN_2023-09-22_nrt
2023-09-22 09:50:01	ga_s2bm_ard_3-2-1_56LKN_2023-09-22_nrt
2023-09-22 09:50:06	ga_s2bm_ard_3-2-1_56LLM_2023-09-22_nrt
2023-09-22 09:50:08	ga_s2bm_ard_3-2-1_56LKM_2023-09-22_nrt
2023-09-22 09:51:03	ga_s2bm_ard_3-2-1_56LLJ_2023-09-22_nrt
2023-09-22 09:51:07	ga_s2bm_ard_3-2-1_56LLH_2023-09-22_nrt
2023-09-23 09:26:45	ga_s2bm_ard_3-2-1_56HLF_2023-09-22_nrt
2023-09-23 09:26:59	ga_s2bm_ard_3-2-1_56HLE_2023-09-22_nrt
2023-09-23 09:27:14	ga_s2bm_ard_3-2-1_56HLD_2023-09-22_nrt
2023-09-23 09:27:28	ga_s2bm_ard_3-2-1_56HLC_2023-09-22_nrt
2023-09-23 09:27:43	ga_s2bm_ard_3-2-1_56HLB_2023-09-22_nrt
2023-09-23 09:27:57	ga_s2bm_ard_3-2-1_56GLA_2023-09-22_nrt
2023-09-23 09:28:12	ga_s2bm_ard_3-2-1_56GLV_2023-09-22_nrt
2023-09-23 09:28:26	ga_s2bm_ard_3-2-1_56GLU_2023-09-22_nrt
2023-09-23 09:28:35	ga_s2bm_ard_3-2-1_56GLT_2023-09-22_nrt
2023-09-23 09:28:35	ga_s2bm_ard_3-2-1_56GLU_2023-09-22_nrt
2023-09-23 09:28:41	ga_s2bm_ard_3-2-1_56GLT_2023-09-22_nrt
2023-10-06 09:36:51	ga_s2bm_ard_3-2-1_56HLE_2023-10-06_nrt
2023-10-09 09:43:09	ga_s2bm_ard_3-2-1_56KLV_2023-10-09_final
2023-10-09 09:43:24	ga_s2bm_ard_3-2-1_56KLU_2023-10-09_final
2023-10-09 09:43:39	ga_s2bm_ard_3-2-1_56JLT_2023-10-09_final
2023-10-12 09:49:42	ga_s2bm_ard_3-2-1_56LLP_2023-10-12_nrt
2023-10-12 09:49:45	ga_s2bm_ard_3-2-1_56LKP_2023-10-12_nrt
2023-10-12 09:49:56	ga_s2bm_ard_3-2-1_56LLN_2023-10-12_nrt
2023-10-12 09:49:59	ga_s2bm_ard_3-2-1_56LKN_2023-10-12_nrt
2023-10-12 09:50:05	ga_s2bm_ard_3-2-1_56LLM_2023-10-12_nrt
2023-10-12 09:50:06	ga_s2bm_ard_3-2-1_56LKM_2023-10-12_nrt
2023-10-12 09:51:01	ga_s2bm_ard_3-2-1_56LLJ_2023-10-12_nrt
2023-10-12 09:51:06	ga_s2bm_ard_3-2-1_56LLH_2023-10-12_nrt
2023-11-18 09:41:15	ga_s2bm_ard_3-2-1_56LLH_2023-11-18_nrt
2023-11-18 09:41:25	ga_s2bm_ard_3-2-1_56KLG_2023-11-18_final
2023-11-18 09:41:40	ga_s2bm_ard_3-2-1_56KLF_2023-11-18_final
2023-11-18 09:41:54	ga_s2bm_ard_3-2-1_56KLE_2023-11-18_final
2023-11-18 09:42:09	ga_s2bm_ard_3-2-1_56KLD_2023-11-18_final
2023-11-18 09:42:23	ga_s2bm_ard_3-2-1_56KLC_2023-11-18_nrt
2023-11-18 09:42:38	ga_s2bm_ard_3-2-1_56KLB_2023-11-18_final
2023-11-18 09:42:52	ga_s2bm_ard_3-2-1_56KLA_2023-11-18_final
2023-11-18 09:43:07	ga_s2bm_ard_3-2-1_56KLV_2023-11-18_final
2023-11-18 09:43:21	ga_s2bm_ard_3-2-1_56KLU_2023-11-18_final
2023-11-18 09:43:36	ga_s2bm_ard_3-2-1_56JLT_2023-11-18_final
2023-11-18 09:43:51	ga_s2bm_ard_3-2-1_56JLS_2023-11-18_final
2023-12-28 09:41:18	ga_s2bm_ard_3-2-1_56LLH_2023-12-28_nrt
2023-12-28 09:41:28	ga_s2bm_ard_3-2-1_56KLG_2023-12-28_final
2023-12-28 09:41:43	ga_s2bm_ard_3-2-1_56KLF_2023-12-28_final
2023-12-28 09:41:57	ga_s2bm_ard_3-2-1_56KLE_2023-12-28_final
2023-12-28 09:42:12	ga_s2bm_ard_3-2-1_56KLD_2023-12-28_final
2023-12-28 09:42:26	ga_s2bm_ard_3-2-1_56KLC_2023-12-28_nrt
2023-12-28 09:42:41	ga_s2bm_ard_3-2-1_56KLB_2023-12-28_final
2023-12-28 09:42:55	ga_s2bm_ard_3-2-1_56KLA_2023-12-28_final
2023-12-28 09:43:10	ga_s2bm_ard_3-2-1_56KLV_2023-12-28_final
2023-12-28 09:43:24	ga_s2bm_ard_3-2-1_56KLU_2023-12-28_final
2023-12-28 09:43:39	ga_s2bm_ard_3-2-1_56JLT_2023-12-28_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