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_50JKN_2018-10-04_final.stac-item
2018-10-04 11:52:44	ga_s2bm_ard_3-2-1_50JKP_2018-10-04_final.stac-item
2018-10-07 12:02:45	ga_s2bm_ard_3-2-1_49JHN_2018-10-07_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_50JKT_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 12:04:33	ga_s2bm_ard_3-2-1_49JHN_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_50JKP_2018-10-07_final.stac-item
2018-10-07 12:04:33	ga_s2bm_ard_3-2-1_49JGJ_2018-10-07_final.stac-item
2018-10-07 12:04:33	ga_s2bm_ard_3-2-1_49JGM_2018-10-07_final.stac-item
2018-10-07 12:04:33	ga_s2bm_ard_3-2-1_49JGN_2018-10-07_final.stac-item
2018-10-10 12:13:39	ga_s2bm_ard_3-2-1_49JHN_2018-10-10_final.stac-item
2018-10-10 12:13:39	ga_s2bm_ard_3-2-1_49KHQ_2018-10-10_final.stac-item
2018-10-10 12:13:39	ga_s2bm_ard_3-2-1_49JGM_2018-10-10_final.stac-item
2018-10-14 11:52:46	ga_s2bm_ard_3-2-1_50JKN_2018-10-14_final.stac-item
2018-10-17 12:03:15	ga_s2bm_ard_3-2-1_49JHN_2018-10-17_final.stac-item
2018-10-17 12:03:15	ga_s2bm_ard_3-2-1_49KHQ_2018-10-17_final.stac-item
2018-10-17 12:03:15	ga_s2bm_ard_3-2-1_50JKN_2018-10-17_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_49JGJ_2018-10-17_final.stac-item
2018-10-17 12:03:15	ga_s2bm_ard_3-2-1_49JGM_2018-10-17_final.stac-item
2018-10-20 12:13:18	ga_s2bm_ard_3-2-1_49JHN_2018-10-20_final.stac-item
2018-10-20 12:13:18	ga_s2bm_ard_3-2-1_49KHQ_2018-10-20_final.stac-item
2018-10-20 12:13:18	ga_s2bm_ard_3-2-1_49JGN_2018-10-20_final.stac-item
2018-10-20 12:14:55	ga_s2bm_ard_3-2-1_49JGM_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_50JKP_2018-10-24_final.stac-item
2018-10-27 12:02:47	ga_s2bm_ard_3-2-1_49JHN_2018-10-27_final.stac-item
2018-10-27 12:02:47	ga_s2bm_ard_3-2-1_49KHQ_2018-10-27_final.stac-item
2018-10-27 12:02:47	ga_s2bm_ard_3-2-1_50JKN_2018-10-27_final.stac-item
2018-10-27 12:02:47	ga_s2bm_ard_3-2-1_49JGJ_2018-10-27_final.stac-item
2018-10-27 12:02:47	ga_s2bm_ard_3-2-1_49JGM_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
2018-10-30 12:13:26	ga_s2bm_ard_3-2-1_49JHN_2018-10-30_final.stac-item
2018-10-30 12:13:26	ga_s2bm_ard_3-2-1_49KHQ_2018-10-30_final.stac-item
2018-10-30 12:13:26	ga_s2bm_ard_3-2-1_49JGM_2018-10-30_final.stac-item
2018-10-30 12:13:26	ga_s2bm_ard_3-2-1_49JGN_2018-10-30_final.stac-item
2018-11-03 11:54:10	ga_s2bm_ard_3-2-1_50HLH_2018-11-03_final.stac-item
2018-11-03 11:54:10	ga_s2bm_ard_3-2-1_50HLJ_2018-11-03_final.stac-item
2018-11-03 11:54:10	ga_s2bm_ard_3-2-1_50HMK_2018-11-03_final.stac-item
2018-11-03 11:54:10	ga_s2bm_ard_3-2-1_50JKN_2018-11-03_final.stac-item
2018-11-06 12:05:38	ga_s2bm_ard_3-2-1_50JKP_2018-11-06_final.stac-item
2018-11-07 11:36:35	ga_s2bm_ard_3-2-1_50HPK_2018-11-07_final.stac-item
2018-11-07 11:36:49	ga_s2bm_ard_3-2-1_50HPJ_2018-11-07_final.stac-item
2018-11-10 11:46:31	ga_s2bm_ard_3-2-1_50HPK_2018-11-10_final.stac-item
2018-11-10 11:46:38	ga_s2bm_ard_3-2-1_50HMK_2018-11-10_final.stac-item
2018-11-10 11:46:45	ga_s2bm_ard_3-2-1_50HPJ_2018-11-10_final.stac-item
2018-11-10 11:47:12	ga_s2bm_ard_3-2-1_50HLH_2018-11-10_final.stac-item
2018-11-16 12:04:58	ga_s2bm_ard_3-2-1_49JGM_2018-11-16_final.stac-item
2018-11-16 12:05:38	ga_s2bm_ard_3-2-1_50JKP_2018-11-16_final.stac-item
2018-11-16 12:05:53	ga_s2bm_ard_3-2-1_50JKN_2018-11-16_final.stac-item
2018-11-17 11:36:35	ga_s2bm_ard_3-2-1_50HPK_2018-11-17_final.stac-item
2018-11-17 11:36:49	ga_s2bm_ard_3-2-1_50HPJ_2018-11-17_final.stac-item
2018-11-20 11:46:31	ga_s2bm_ard_3-2-1_50HPK_2018-11-20_final.stac-item
2018-11-20 11:46:38	ga_s2bm_ard_3-2-1_50HMK_2018-11-20_final.stac-item
2018-11-20 11:46:45	ga_s2bm_ard_3-2-1_50HPJ_2018-11-20_final.stac-item
2018-11-20 11:47:11	ga_s2bm_ard_3-2-1_50HLH_2018-11-20_final.stac-item
2018-11-23 11:56:33	ga_s2bm_ard_3-2-1_50HMK_2018-11-23_final.stac-item
2018-11-23 11:56:51	ga_s2bm_ard_3-2-1_50HLJ_2018-11-23_final.stac-item
2018-11-23 11:57:06	ga_s2bm_ard_3-2-1_50HLH_2018-11-23_final.stac-item
2018-11-27 11:36:34	ga_s2bm_ard_3-2-1_50HPK_2018-11-27_final.stac-item
2018-11-27 11:36:48	ga_s2bm_ard_3-2-1_50HPJ_2018-11-27_final.stac-item
2018-11-29 12:14:52	ga_s2bm_ard_3-2-1_49JGM_2018-11-29_final.stac-item
2018-11-30 11:46:29	ga_s2bm_ard_3-2-1_50HPK_2018-11-30_final.stac-item
2018-11-30 11:46:36	ga_s2bm_ard_3-2-1_50HMK_2018-11-30_final.stac-item
2018-11-30 11:46:44	ga_s2bm_ard_3-2-1_50HPJ_2018-11-30_final.stac-item
2018-11-30 11:47:10	ga_s2bm_ard_3-2-1_50HLH_2018-11-30_final.stac-item
2018-12-03 11:55:55	ga_s2bm_ard_3-2-1_50JKN_2018-12-03_final.stac-item
2018-12-06 12:04:08	ga_s2bm_ard_3-2-1_49KHQ_2018-12-06_final.stac-item
2018-12-06 12:04:37	ga_s2bm_ard_3-2-1_49JHN_2018-12-06_final.stac-item
2018-12-06 12:04:55	ga_s2bm_ard_3-2-1_49JGM_2018-12-06_final.stac-item
2018-12-06 12:05:35	ga_s2bm_ard_3-2-1_50JKP_2018-12-06_final.stac-item
2018-12-06 12:05:38	ga_s2bm_ard_3-2-1_49JGJ_2018-12-06_final.stac-item
2018-12-06 12:05:50	ga_s2bm_ard_3-2-1_50JKN_2018-12-06_final.stac-item
2018-12-09 12:14:03	ga_s2bm_ard_3-2-1_49KHQ_2018-12-09_final.stac-item
2018-12-09 12:14:25	ga_s2bm_ard_3-2-1_49JHN_2018-12-09_final.stac-item
2018-12-09 12:14:35	ga_s2bm_ard_3-2-1_49JGN_2018-12-09_final.stac-item
2018-12-09 12:14:50	ga_s2bm_ard_3-2-1_49JGM_2018-12-09_final.stac-item
2018-12-13 11:55:40	ga_s2bm_ard_3-2-1_50JKP_2018-12-13_final.stac-item
2018-12-13 11:55:53	ga_s2bm_ard_3-2-1_50JKN_2018-12-13_final.stac-item
2018-12-16 12:04:08	ga_s2bm_ard_3-2-1_49KHQ_2018-12-16_final.stac-item
2018-12-16 12:04:36	ga_s2bm_ard_3-2-1_49JHN_2018-12-16_final.stac-item
2018-12-16 12:04:55	ga_s2bm_ard_3-2-1_49JGM_2018-12-16_final.stac-item
2018-12-16 12:05:35	ga_s2bm_ard_3-2-1_50JKP_2018-12-16_final.stac-item
2018-12-16 12:05:38	ga_s2bm_ard_3-2-1_49JGJ_2018-12-16_final.stac-item
2018-12-16 12:05:49	ga_s2bm_ard_3-2-1_50JKN_2018-12-16_final.stac-item
2018-12-19 12:14:03	ga_s2bm_ard_3-2-1_49KHQ_2018-12-19_final.stac-item
2018-12-19 12:14:26	ga_s2bm_ard_3-2-1_49JHN_2018-12-19_final.stac-item
2018-12-19 12:14:51	ga_s2bm_ard_3-2-1_49JGM_2018-12-19_final.stac-item
2018-12-23 11:55:42	ga_s2bm_ard_3-2-1_50JKP_2018-12-23_final.stac-item
2018-12-23 11:55:55	ga_s2bm_ard_3-2-1_50JKN_2018-12-23_final.stac-item
2018-12-26 12:04:10	ga_s2bm_ard_3-2-1_49KHQ_2018-12-26_final.stac-item
2018-12-26 12:04:39	ga_s2bm_ard_3-2-1_49JHN_2018-12-26_final.stac-item
2018-12-26 12:04:57	ga_s2bm_ard_3-2-1_49JGM_2018-12-26_final.stac-item
2018-12-26 12:05:37	ga_s2bm_ard_3-2-1_50JKP_2018-12-26_final.stac-item
2018-12-26 12:05:40	ga_s2bm_ard_3-2-1_49JGJ_2018-12-26_final.stac-item
2018-12-26 12:05:52	ga_s2bm_ard_3-2-1_50JKN_2018-12-26_final.stac-item
2018-12-29 12:14:06	ga_s2bm_ard_3-2-1_49KHQ_2018-12-29_final.stac-item
2018-12-29 12:14:28	ga_s2bm_ard_3-2-1_49JHN_2018-12-29_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