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
2018-10-04 11:52:44	ga_s2bm_ard_3-2-1_50JKP_2018-10-04_final.stac-item
2018-10-04 11:52:44	ga_s2bm_ard_3-2-1_50JLT_2018-10-04_final.stac-item
2018-10-04 11:52:44	ga_s2bm_ard_3-2-1_50JNT_2018-10-04_final.stac-item
2018-10-07 12:02:45	ga_s2bm_ard_3-2-1_49KHQ_2018-10-07_final.stac-item
2018-10-07 12:02:45	ga_s2bm_ard_3-2-1_50JLT_2018-10-07_final.stac-item
2018-10-07 12:02:45	ga_s2bm_ard_3-2-1_49JGN_2018-10-07_final.stac-item
2018-10-07 12:02:45	ga_s2bm_ard_3-2-1_49KGQ_2018-10-07_final.stac-item
2018-10-07 12:04:33	ga_s2bm_ard_3-2-1_50JKN_2018-10-07_final.stac-item
2018-10-07 12:04:33	ga_s2bm_ard_3-2-1_49JGK_2018-10-07_final.stac-item
2018-10-07 12:04:33	ga_s2bm_ard_3-2-1_50JKR_2018-10-07_final.stac-item
2018-10-10 12:13:39	ga_s2bm_ard_3-2-1_49JFN_2018-10-10_final.stac-item
2018-10-10 12:13:39	ga_s2bm_ard_3-2-1_49JGK_2018-10-10_final.stac-item
2018-10-10 12:13:39	ga_s2bm_ard_3-2-1_49JGL_2018-10-10_final.stac-item
2018-10-11 11:41:47	ga_s2bm_ard_3-2-1_50JQN_2018-10-11_final.stac-item
2018-10-14 11:52:46	ga_s2bm_ard_3-2-1_50JLT_2018-10-14_final.stac-item
2018-10-14 11:52:46	ga_s2bm_ard_3-2-1_50JNT_2018-10-14_final.stac-item
2018-10-17 12:03:15	ga_s2bm_ard_3-2-1_50JKP_2018-10-17_final.stac-item
2018-10-17 12:03:15	ga_s2bm_ard_3-2-1_50JLT_2018-10-17_final.stac-item
2018-10-17 12:03:15	ga_s2bm_ard_3-2-1_49JFM_2018-10-17_final.stac-item
2018-10-17 12:03:15	ga_s2bm_ard_3-2-1_49JGK_2018-10-17_final.stac-item
2018-10-17 12:03:15	ga_s2bm_ard_3-2-1_49JGL_2018-10-17_final.stac-item
2018-10-17 12:03:15	ga_s2bm_ard_3-2-1_49JHM_2018-10-17_final.stac-item
2018-10-17 12:03:15	ga_s2bm_ard_3-2-1_49KGQ_2018-10-17_final.stac-item
2018-10-17 12:03:15	ga_s2bm_ard_3-2-1_50JKS_2018-10-17_final.stac-item
2018-10-20 12:13:18	ga_s2bm_ard_3-2-1_49JFN_2018-10-20_final.stac-item
2018-10-20 12:13:18	ga_s2bm_ard_3-2-1_49JGL_2018-10-20_final.stac-item
2018-10-20 12:14:55	ga_s2bm_ard_3-2-1_49JFM_2018-10-20_final.stac-item
2018-10-24 11:53:29	ga_s2bm_ard_3-2-1_50JKN_2018-10-24_final.stac-item
2018-10-24 11:53:29	ga_s2bm_ard_3-2-1_50JLT_2018-10-24_final.stac-item
2018-10-24 11:53:29	ga_s2bm_ard_3-2-1_50JNT_2018-10-24_final.stac-item
2018-10-24 11:53:29	ga_s2bm_ard_3-2-1_50JMQ_2018-10-24_final.stac-item
2018-10-27 12:02:47	ga_s2bm_ard_3-2-1_50JLT_2018-10-27_final.stac-item
2018-10-27 12:02:47	ga_s2bm_ard_3-2-1_49JFM_2018-10-27_final.stac-item
2018-10-27 12:02:47	ga_s2bm_ard_3-2-1_49JGK_2018-10-27_final.stac-item
2018-10-27 12:02:47	ga_s2bm_ard_3-2-1_49JGN_2018-10-27_final.stac-item
2018-10-27 12:02:47	ga_s2bm_ard_3-2-1_50JKS_2018-10-27_final.stac-item
2018-10-27 12:02:47	ga_s2bm_ard_3-2-1_50JLM_2018-10-27_final.stac-item
2018-10-30 12:13:26	ga_s2bm_ard_3-2-1_49JFM_2018-10-30_final.stac-item
2018-10-30 12:13:26	ga_s2bm_ard_3-2-1_49JFN_2018-10-30_final.stac-item
2018-10-30 12:13:26	ga_s2bm_ard_3-2-1_49KGP_2018-10-30_final.stac-item
2018-10-30 12:13:26	ga_s2bm_ard_3-2-1_49KGQ_2018-10-30_final.stac-item
2018-10-31 11:46:25	ga_s2bm_ard_3-2-1_50HMH_2018-10-31_final.stac-item
2018-11-03 11:54:10	ga_s2bm_ard_3-2-1_50JKM_2018-11-03_final.stac-item
2018-11-06 12:06:02	ga_s2bm_ard_3-2-1_50JLM_2018-11-06_final.stac-item
2018-11-06 12:06:07	ga_s2bm_ard_3-2-1_50JKM_2018-11-06_final.stac-item
2018-11-16 12:06:01	ga_s2bm_ard_3-2-1_50JLM_2018-11-16_final.stac-item
2018-11-16 12:06:07	ga_s2bm_ard_3-2-1_50JKM_2018-11-16_final.stac-item
2018-11-23 11:54:54	ga_s2bm_ard_3-2-1_50JLS_2018-11-23_final.stac-item
2018-11-23 11:56:10	ga_s2bm_ard_3-2-1_50JKM_2018-11-23_final.stac-item
2018-11-26 12:06:00	ga_s2bm_ard_3-2-1_50JLM_2018-11-26_final.stac-item
2018-11-26 12:06:06	ga_s2bm_ard_3-2-1_50JKM_2018-11-26_final.stac-item
2018-12-03 11:54:47	ga_s2bm_ard_3-2-1_50JNS_2018-12-03_final.stac-item
2018-12-03 11:55:01	ga_s2bm_ard_3-2-1_50JNR_2018-12-03_final.stac-item
2018-12-03 11:55:34	ga_s2bm_ard_3-2-1_50JMP_2018-12-03_final.stac-item
2018-12-03 11:55:45	ga_s2bm_ard_3-2-1_50JNN_2018-12-03_final.stac-item
2018-12-03 11:55:51	ga_s2bm_ard_3-2-1_50JLN_2018-12-03_final.stac-item
2018-12-06 12:04:48	ga_s2bm_ard_3-2-1_50JLS_2018-12-06_final.stac-item
2018-12-06 12:04:53	ga_s2bm_ard_3-2-1_50JMR_2018-12-06_final.stac-item
2018-12-06 12:05:03	ga_s2bm_ard_3-2-1_50JLR_2018-12-06_final.stac-item
2018-12-06 12:05:46	ga_s2bm_ard_3-2-1_50JLN_2018-12-06_final.stac-item
2018-12-07 11:35:45	ga_s2bm_ard_3-2-1_50JQN_2018-12-07_final.stac-item
2018-12-10 11:45:05	ga_s2bm_ard_3-2-1_50JNR_2018-12-10_final.stac-item
2018-12-10 11:45:40	ga_s2bm_ard_3-2-1_50JQN_2018-12-10_final.stac-item
2018-12-10 11:45:48	ga_s2bm_ard_3-2-1_50JNN_2018-12-10_final.stac-item
2018-12-13 11:54:45	ga_s2bm_ard_3-2-1_50JNS_2018-12-13_final.stac-item
2018-12-13 11:54:51	ga_s2bm_ard_3-2-1_50JLS_2018-12-13_final.stac-item
2018-12-13 11:54:59	ga_s2bm_ard_3-2-1_50JNR_2018-12-13_final.stac-item
2018-12-13 11:55:03	ga_s2bm_ard_3-2-1_50JMR_2018-12-13_final.stac-item
2018-12-13 11:55:06	ga_s2bm_ard_3-2-1_50JLR_2018-12-13_final.stac-item
2018-12-13 11:55:17	ga_s2bm_ard_3-2-1_50JMQ_2018-12-13_final.stac-item
2018-12-13 11:55:32	ga_s2bm_ard_3-2-1_50JMP_2018-12-13_final.stac-item
2018-12-13 11:55:43	ga_s2bm_ard_3-2-1_50JNN_2018-12-13_final.stac-item
2018-12-13 11:55:50	ga_s2bm_ard_3-2-1_50JLN_2018-12-13_final.stac-item
2018-12-16 12:04:48	ga_s2bm_ard_3-2-1_50JLS_2018-12-16_final.stac-item
2018-12-16 12:04:53	ga_s2bm_ard_3-2-1_50JMR_2018-12-16_final.stac-item
2018-12-16 12:05:02	ga_s2bm_ard_3-2-1_50JLR_2018-12-16_final.stac-item
2018-12-16 12:05:46	ga_s2bm_ard_3-2-1_50JLN_2018-12-16_final.stac-item
2018-12-17 11:35:45	ga_s2bm_ard_3-2-1_50JQN_2018-12-17_final.stac-item
2018-12-20 11:45:06	ga_s2bm_ard_3-2-1_50JNR_2018-12-20_final.stac-item
2018-12-20 11:45:41	ga_s2bm_ard_3-2-1_50JQN_2018-12-20_final.stac-item
2018-12-20 11:45:45	ga_s2bm_ard_3-2-1_50JPN_2018-12-20_final.stac-item
2018-12-20 11:45:49	ga_s2bm_ard_3-2-1_50JNN_2018-12-20_final.stac-item
2018-12-23 11:54:33	ga_s2bm_ard_3-2-1_50JNT_2018-12-23_final.stac-item
2018-12-23 11:54:47	ga_s2bm_ard_3-2-1_50JNS_2018-12-23_final.stac-item
2018-12-23 11:54:53	ga_s2bm_ard_3-2-1_50JLS_2018-12-23_final.stac-item
2018-12-23 11:55:02	ga_s2bm_ard_3-2-1_50JNR_2018-12-23_final.stac-item
2018-12-23 11:55:05	ga_s2bm_ard_3-2-1_50JMR_2018-12-23_final.stac-item
2018-12-23 11:55:08	ga_s2bm_ard_3-2-1_50JLR_2018-12-23_final.stac-item
2018-12-23 11:55:20	ga_s2bm_ard_3-2-1_50JMQ_2018-12-23_final.stac-item
2018-12-23 11:55:34	ga_s2bm_ard_3-2-1_50JMP_2018-12-23_final.stac-item
2018-12-23 11:55:45	ga_s2bm_ard_3-2-1_50JNN_2018-12-23_final.stac-item
2018-12-23 11:55:52	ga_s2bm_ard_3-2-1_50JLN_2018-12-23_final.stac-item
2018-12-26 12:04:50	ga_s2bm_ard_3-2-1_50JLS_2018-12-26_final.stac-item
2018-12-26 12:04:55	ga_s2bm_ard_3-2-1_50JMR_2018-12-26_final.stac-item
2018-12-26 12:05:48	ga_s2bm_ard_3-2-1_50JLN_2018-12-26_final.stac-item
2018-12-27 11:35:47	ga_s2bm_ard_3-2-1_50JQN_2018-12-27_final.stac-item
2018-12-30 11:45:08	ga_s2bm_ard_3-2-1_50JNR_2018-12-30_final.stac-item
2018-12-30 11:45:29	ga_s2bm_ard_3-2-1_50JQP_2018-12-30_final.stac-item
2018-12-30 11:45:43	ga_s2bm_ard_3-2-1_50JQN_2018-12-30_final.stac-item
2018-12-30 11:45:47	ga_s2bm_ard_3-2-1_50JPN_2018-12-30_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