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
2019-05-31 10:44:56	ga_s2bm_ard_3-2-1_53JKL_2019-05-31_final.stac-item
2019-05-31 10:45:08	ga_s2bm_ard_3-2-1_53JKK_2019-05-31_final.stac-item
2019-05-31 10:45:19	ga_s2bm_ard_3-2-1_53JLJ_2019-05-31_final.stac-item
2019-05-31 10:45:22	ga_s2bm_ard_3-2-1_53JKJ_2019-05-31_final.stac-item
2019-05-31 10:45:34	ga_s2bm_ard_3-2-1_53JLH_2019-05-31_final.stac-item
2019-05-31 10:45:37	ga_s2bm_ard_3-2-1_53JKH_2019-05-31_final.stac-item
2019-05-31 10:45:49	ga_s2bm_ard_3-2-1_53JLG_2019-05-31_final.stac-item
2019-05-31 10:45:52	ga_s2bm_ard_3-2-1_53JKG_2019-05-31_final.stac-item
2019-05-31 10:46:03	ga_s2bm_ard_3-2-1_53JLF_2019-05-31_final.stac-item
2019-05-31 10:46:06	ga_s2bm_ard_3-2-1_53JKF_2019-05-31_final.stac-item
2019-06-06 11:00:37	ga_s2bm_ard_3-2-1_53LKH_2019-06-06_final.stac-item
2019-06-06 11:00:50	ga_s2bm_ard_3-2-1_53LKG_2019-06-06_final.stac-item
2019-06-06 11:00:56	ga_s2bm_ard_3-2-1_53LKG_2019-06-06_final.stac-item
2019-06-06 11:01:06	ga_s2bm_ard_3-2-1_53LKF_2019-06-06_final.stac-item
2019-06-06 11:01:20	ga_s2bm_ard_3-2-1_53LKE_2019-06-06_final.stac-item
2019-06-06 11:01:35	ga_s2bm_ard_3-2-1_53LKD_2019-06-06_final.stac-item
2019-06-06 11:01:49	ga_s2bm_ard_3-2-1_53LKC_2019-06-06_final.stac-item
2019-06-06 11:02:04	ga_s2bm_ard_3-2-1_53KKB_2019-06-06_final.stac-item
2019-06-06 11:02:18	ga_s2bm_ard_3-2-1_53KKA_2019-06-06_final.stac-item
2019-06-06 11:02:33	ga_s2bm_ard_3-2-1_53KKV_2019-06-06_final.stac-item
2019-06-10 10:44:56	ga_s2bm_ard_3-2-1_53JKL_2019-06-10_final.stac-item
2019-06-10 10:45:08	ga_s2bm_ard_3-2-1_53JKK_2019-06-10_final.stac-item
2019-06-10 10:45:19	ga_s2bm_ard_3-2-1_53JLJ_2019-06-10_final.stac-item
2019-06-10 10:45:22	ga_s2bm_ard_3-2-1_53JKJ_2019-06-10_final.stac-item
2019-06-10 10:45:33	ga_s2bm_ard_3-2-1_53JLH_2019-06-10_final.stac-item
2019-06-10 10:45:36	ga_s2bm_ard_3-2-1_53JKH_2019-06-10_final.stac-item
2019-06-10 10:45:48	ga_s2bm_ard_3-2-1_53JLG_2019-06-10_final.stac-item
2019-06-10 10:45:51	ga_s2bm_ard_3-2-1_53JKG_2019-06-10_final.stac-item
2019-06-10 10:46:03	ga_s2bm_ard_3-2-1_53JLF_2019-06-10_final.stac-item
2019-06-10 10:46:06	ga_s2bm_ard_3-2-1_53JKF_2019-06-10_final.stac-item
2019-06-16 11:00:36	ga_s2bm_ard_3-2-1_53LKH_2019-06-16_final.stac-item
2019-06-16 11:00:51	ga_s2bm_ard_3-2-1_53LKG_2019-06-16_final.stac-item
2019-06-16 11:01:02	ga_s2bm_ard_3-2-1_53LKF_2019-06-16_final.stac-item
2019-06-16 11:01:08	ga_s2bm_ard_3-2-1_53LKF_2019-06-16_final.stac-item
2019-06-16 11:01:20	ga_s2bm_ard_3-2-1_53LKE_2019-06-16_final.stac-item
2019-06-16 11:01:34	ga_s2bm_ard_3-2-1_53LKD_2019-06-16_final.stac-item
2019-06-16 11:01:49	ga_s2bm_ard_3-2-1_53LKC_2019-06-16_final.stac-item
2019-06-16 11:02:03	ga_s2bm_ard_3-2-1_53KKB_2019-06-16_final.stac-item
2019-06-16 11:02:18	ga_s2bm_ard_3-2-1_53KKA_2019-06-16_final.stac-item
2019-06-16 11:02:32	ga_s2bm_ard_3-2-1_53KKV_2019-06-16_final.stac-item
2019-06-20 10:44:56	ga_s2bm_ard_3-2-1_53JKL_2019-06-20_final.stac-item
2019-06-20 10:45:08	ga_s2bm_ard_3-2-1_53JKK_2019-06-20_final.stac-item
2019-06-20 10:45:19	ga_s2bm_ard_3-2-1_53JLJ_2019-06-20_final.stac-item
2019-06-20 10:45:22	ga_s2bm_ard_3-2-1_53JKJ_2019-06-20_final.stac-item
2019-06-20 10:45:34	ga_s2bm_ard_3-2-1_53JLH_2019-06-20_final.stac-item
2019-06-20 10:45:37	ga_s2bm_ard_3-2-1_53JKH_2019-06-20_final.stac-item
2019-06-20 10:45:48	ga_s2bm_ard_3-2-1_53JLG_2019-06-20_final.stac-item
2019-06-20 10:45:51	ga_s2bm_ard_3-2-1_53JKG_2019-06-20_final.stac-item
2019-06-20 10:46:03	ga_s2bm_ard_3-2-1_53JLF_2019-06-20_final.stac-item
2019-06-20 10:46:06	ga_s2bm_ard_3-2-1_53JKF_2019-06-20_final.stac-item
2019-06-20 10:46:17	ga_s2bm_ard_3-2-1_53HLE_2019-06-20_final.stac-item
2019-06-26 11:00:37	ga_s2bm_ard_3-2-1_53LKH_2019-06-26_final.stac-item
2019-06-26 11:00:51	ga_s2bm_ard_3-2-1_53LKG_2019-06-26_final.stac-item
2019-06-26 11:01:03	ga_s2bm_ard_3-2-1_53LKF_2019-06-26_final.stac-item
2019-06-26 11:01:09	ga_s2bm_ard_3-2-1_53LKF_2019-06-26_final.stac-item
2019-06-26 11:01:21	ga_s2bm_ard_3-2-1_53LKE_2019-06-26_final.stac-item
2019-06-26 11:01:35	ga_s2bm_ard_3-2-1_53LKD_2019-06-26_final.stac-item
2019-06-26 11:01:50	ga_s2bm_ard_3-2-1_53LKC_2019-06-26_final.stac-item
2019-06-26 11:02:04	ga_s2bm_ard_3-2-1_53KKB_2019-06-26_final.stac-item
2019-06-26 11:02:18	ga_s2bm_ard_3-2-1_53KKA_2019-06-26_final.stac-item
2019-06-26 11:02:33	ga_s2bm_ard_3-2-1_53KKV_2019-06-26_final.stac-item
2019-06-30 10:46:18	ga_s2bm_ard_3-2-1_53HLE_2019-06-30_final.stac-item
2019-06-30 10:46:32	ga_s2bm_ard_3-2-1_53HLD_2019-06-30_final.stac-item
2019-07-03 10:55:14	ga_s2bm_ard_3-2-1_53JLJ_2019-07-03_final.stac-item
2019-07-03 10:55:19	ga_s2bm_ard_3-2-1_53JKJ_2019-07-03_final.stac-item
2019-07-03 10:55:24	ga_s2bm_ard_3-2-1_53JLH_2019-07-03_final.stac-item
2019-07-03 10:55:33	ga_s2bm_ard_3-2-1_53JKH_2019-07-03_final.stac-item
2019-07-10 10:46:18	ga_s2bm_ard_3-2-1_53HLE_2019-07-10_final.stac-item
2019-07-10 10:46:33	ga_s2bm_ard_3-2-1_53HLD_2019-07-10_final.stac-item
2019-07-20 10:45:52	ga_s2bm_ard_3-2-1_53JKG_2019-07-20_final.stac-item
2019-07-20 10:46:04	ga_s2bm_ard_3-2-1_53JLF_2019-07-20_final.stac-item
2019-07-20 10:46:07	ga_s2bm_ard_3-2-1_53JKF_2019-07-20_final.stac-item
2019-07-20 10:46:33	ga_s2bm_ard_3-2-1_53HLD_2019-07-20_final.stac-item
2019-09-21 10:54:40	ga_s2bm_ard_3-2-1_53JKL_2019-09-21_final.stac-item
2019-09-21 10:54:55	ga_s2bm_ard_3-2-1_53JKK_2019-09-21_final.stac-item
2019-09-21 10:55:04	ga_s2bm_ard_3-2-1_53JLJ_2019-09-21_final.stac-item
2019-09-21 10:55:09	ga_s2bm_ard_3-2-1_53JKJ_2019-09-21_final.stac-item
2019-09-21 10:55:15	ga_s2bm_ard_3-2-1_53JLH_2019-09-21_final.stac-item
2019-09-21 10:55:24	ga_s2bm_ard_3-2-1_53JKH_2019-09-21_final.stac-item
2019-09-28 10:45:00	ga_s2bm_ard_3-2-1_53JKK_2019-09-28_final.stac-item
2019-09-28 10:45:14	ga_s2bm_ard_3-2-1_53JKJ_2019-09-28_final.stac-item
2019-09-28 10:45:29	ga_s2bm_ard_3-2-1_53JKH_2019-09-28_final.stac-item
2019-09-28 10:45:44	ga_s2bm_ard_3-2-1_53JKG_2019-09-28_final.stac-item
2019-09-28 10:45:58	ga_s2bm_ard_3-2-1_53JKF_2019-09-28_final.stac-item
2019-10-11 10:52:45	ga_s2bm_ard_3-2-1_53KKU_2019-10-11_final.stac-item
2019-10-11 10:53:00	ga_s2bm_ard_3-2-1_53KKT_2019-10-11_final.stac-item
2019-10-11 10:53:14	ga_s2bm_ard_3-2-1_53KKS_2019-10-11_final.stac-item
2019-10-11 10:53:15	ga_s2bm_ard_3-2-1_52KHB_2019-10-11_final.stac-item
2019-10-11 10:53:29	ga_s2bm_ard_3-2-1_53KKR_2019-10-11_final.stac-item
2019-10-11 10:53:29	ga_s2bm_ard_3-2-1_52KHA_2019-10-11_final.stac-item
2019-10-11 10:53:44	ga_s2bm_ard_3-2-1_53KKQ_2019-10-11_final.stac-item
2019-10-11 10:53:44	ga_s2bm_ard_3-2-1_52KHV_2019-10-11_final.stac-item
2019-10-11 10:53:58	ga_s2bm_ard_3-2-1_53KKP_2019-10-11_final.stac-item
2019-10-11 10:53:58	ga_s2bm_ard_3-2-1_52KHU_2019-10-11_final.stac-item
2019-10-11 10:54:13	ga_s2bm_ard_3-2-1_52JHT_2019-10-11_final.stac-item
2019-10-11 10:54:13	ga_s2bm_ard_3-2-1_53JKN_2019-10-11_final.stac-item
2019-10-11 10:54:27	ga_s2bm_ard_3-2-1_52JHS_2019-10-11_final.stac-item
2019-10-11 10:54:27	ga_s2bm_ard_3-2-1_53JKM_2019-10-11_final.stac-item
2019-10-11 10:54:42	ga_s2bm_ard_3-2-1_53JKL_2019-10-11_final.stac-item
2019-10-11 10:54:57	ga_s2bm_ard_3-2-1_53JKK_2019-10-11_final.stac-item

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