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
2019-12-11 12:04:37	ga_s2bm_ard_3-2-1_49JHN_2019-12-11_final.stac-item
2019-12-11 12:04:37	ga_s2bm_ard_3-2-1_50JKT_2019-12-11_final.stac-item
2019-12-11 12:04:40	ga_s2bm_ard_3-2-1_49JGN_2019-12-11_final.stac-item
2019-12-11 12:04:43	ga_s2bm_ard_3-2-1_50JMS_2019-12-11_final.stac-item
2019-12-11 12:04:48	ga_s2bm_ard_3-2-1_50JLS_2019-12-11_final.stac-item
2019-12-11 12:04:51	ga_s2bm_ard_3-2-1_49JHM_2019-12-11_final.stac-item
2019-12-11 12:04:51	ga_s2bm_ard_3-2-1_50JKS_2019-12-11_final.stac-item
2019-12-11 12:04:53	ga_s2bm_ard_3-2-1_50JMR_2019-12-11_final.stac-item
2019-12-11 12:04:55	ga_s2bm_ard_3-2-1_49JGM_2019-12-11_final.stac-item
2019-12-11 12:05:02	ga_s2bm_ard_3-2-1_50JLR_2019-12-11_final.stac-item
2019-12-11 12:05:06	ga_s2bm_ard_3-2-1_50JKR_2019-12-11_final.stac-item
2019-12-11 12:05:09	ga_s2bm_ard_3-2-1_49JGL_2019-12-11_final.stac-item
2019-12-11 12:05:17	ga_s2bm_ard_3-2-1_50JLQ_2019-12-11_final.stac-item
2019-12-11 12:05:20	ga_s2bm_ard_3-2-1_50JKQ_2019-12-11_final.stac-item
2019-12-11 12:05:23	ga_s2bm_ard_3-2-1_49JGK_2019-12-11_final.stac-item
2019-12-11 12:05:32	ga_s2bm_ard_3-2-1_50JLP_2019-12-11_final.stac-item
2019-12-12 09:55:37	ga_s2bm_ard_3-2-1_55HEE_2019-12-12_final.stac-item
2019-12-12 09:55:41	ga_s2bm_ard_3-2-1_55HDE_2019-12-12_final.stac-item
2019-12-12 09:55:45	ga_s2bm_ard_3-2-1_55HCE_2019-12-12_final.stac-item
2019-12-12 09:55:48	ga_s2bm_ard_3-2-1_55HBE_2019-12-12_final.stac-item
2019-12-12 09:55:49	ga_s2bm_ard_3-2-1_55HED_2019-12-12_final.stac-item
2019-12-12 09:55:51	ga_s2bm_ard_3-2-1_54HYK_2019-12-12_final.stac-item
2019-12-12 09:55:56	ga_s2bm_ard_3-2-1_55HDD_2019-12-12_final.stac-item
2019-12-12 09:55:59	ga_s2bm_ard_3-2-1_55HCD_2019-12-12_final.stac-item
2019-12-12 09:56:02	ga_s2bm_ard_3-2-1_55HBD_2019-12-12_final.stac-item
2019-12-12 09:56:04	ga_s2bm_ard_3-2-1_54HYJ_2019-12-12_final.stac-item
2019-12-12 09:56:10	ga_s2bm_ard_3-2-1_55HDC_2019-12-12_final.stac-item
2019-12-12 09:56:14	ga_s2bm_ard_3-2-1_55HCC_2019-12-12_final.stac-item
2019-12-12 09:56:17	ga_s2bm_ard_3-2-1_55HBC_2019-12-12_final.stac-item
2019-12-12 09:56:19	ga_s2bm_ard_3-2-1_54HYH_2019-12-12_final.stac-item
2019-12-12 09:56:25	ga_s2bm_ard_3-2-1_55HDB_2019-12-12_final.stac-item
2019-12-12 09:56:28	ga_s2bm_ard_3-2-1_55HCB_2019-12-12_final.stac-item
2019-12-12 09:56:32	ga_s2bm_ard_3-2-1_55HBB_2019-12-12_final.stac-item
2019-12-12 09:56:33	ga_s2bm_ard_3-2-1_54HYG_2019-12-12_final.stac-item
2019-12-12 09:56:39	ga_s2bm_ard_3-2-1_55HDA_2019-12-12_final.stac-item
2019-12-12 09:56:40	ga_s2bm_ard_3-2-1_54HXG_2019-12-12_final.stac-item
2019-12-12 09:56:43	ga_s2bm_ard_3-2-1_55HCA_2019-12-12_final.stac-item
2019-12-12 09:56:45	ga_s2bm_ard_3-2-1_55HBA_2019-12-12_final.stac-item
2019-12-12 09:56:46	ga_s2bm_ard_3-2-1_54HYF_2019-12-12_final.stac-item
2019-12-12 09:56:48	ga_s2bm_ard_3-2-1_54HXF_2019-12-12_final.stac-item
2019-12-12 09:56:49	ga_s2bm_ard_3-2-1_55HDV_2019-12-12_final.stac-item
2019-12-12 09:56:50	ga_s2bm_ard_3-2-1_55HCA_2019-12-12_final.stac-item
2019-12-12 09:56:50	ga_s2bm_ard_3-2-1_55HCV_2019-12-12_final.stac-item
2019-12-12 09:56:52	ga_s2bm_ard_3-2-1_55HBV_2019-12-12_final.stac-item
2019-12-12 09:56:52	ga_s2bm_ard_3-2-1_55HBA_2019-12-12_final.stac-item
2019-12-12 09:56:52	ga_s2bm_ard_3-2-1_54HYF_2019-12-12_final.stac-item
2019-12-12 09:56:54	ga_s2bm_ard_3-2-1_55HDV_2019-12-12_final.stac-item
2019-12-12 09:56:54	ga_s2bm_ard_3-2-1_54HXF_2019-12-12_final.stac-item
2019-12-12 09:56:58	ga_s2bm_ard_3-2-1_55HCV_2019-12-12_final.stac-item
2019-12-12 09:57:01	ga_s2bm_ard_3-2-1_55HBV_2019-12-12_final.stac-item
2019-12-12 09:57:02	ga_s2bm_ard_3-2-1_54HYE_2019-12-12_final.stac-item
2019-12-12 09:57:03	ga_s2bm_ard_3-2-1_55HDU_2019-12-12_final.stac-item
2019-12-12 11:34:19	ga_s2bm_ard_3-2-1_51JWN_2019-12-12_final.stac-item
2019-12-12 11:34:23	ga_s2bm_ard_3-2-1_51JVN_2019-12-12_final.stac-item
2019-12-12 11:34:26	ga_s2bm_ard_3-2-1_51JUN_2019-12-12_final.stac-item
2019-12-12 11:34:30	ga_s2bm_ard_3-2-1_51JTN_2019-12-12_final.stac-item
2019-12-12 11:34:31	ga_s2bm_ard_3-2-1_50JRT_2019-12-12_final.stac-item
2019-12-12 11:34:34	ga_s2bm_ard_3-2-1_51JWM_2019-12-12_final.stac-item
2019-12-12 11:34:37	ga_s2bm_ard_3-2-1_51JVM_2019-12-12_final.stac-item
2019-12-12 11:34:41	ga_s2bm_ard_3-2-1_51JUM_2019-12-12_final.stac-item
2019-12-12 11:34:43	ga_s2bm_ard_3-2-1_50JRS_2019-12-12_final.stac-item
2019-12-12 11:34:44	ga_s2bm_ard_3-2-1_51JTM_2019-12-12_final.stac-item
2019-12-12 11:34:49	ga_s2bm_ard_3-2-1_51JWL_2019-12-12_final.stac-item
2019-12-12 11:34:52	ga_s2bm_ard_3-2-1_51JVL_2019-12-12_final.stac-item
2019-12-12 11:34:55	ga_s2bm_ard_3-2-1_51JUL_2019-12-12_final.stac-item
2019-12-12 11:34:58	ga_s2bm_ard_3-2-1_51JTL_2019-12-12_final.stac-item
2019-12-12 11:35:02	ga_s2bm_ard_3-2-1_51JWK_2019-12-12_final.stac-item
2019-12-12 11:35:06	ga_s2bm_ard_3-2-1_51JVK_2019-12-12_final.stac-item
2019-12-12 11:35:10	ga_s2bm_ard_3-2-1_51JUK_2019-12-12_final.stac-item
2019-12-12 11:35:13	ga_s2bm_ard_3-2-1_51JTK_2019-12-12_final.stac-item
2019-12-12 11:35:14	ga_s2bm_ard_3-2-1_51JWJ_2019-12-12_final.stac-item
2019-12-12 11:35:21	ga_s2bm_ard_3-2-1_51JVJ_2019-12-12_final.stac-item
2019-12-12 11:35:25	ga_s2bm_ard_3-2-1_51JUJ_2019-12-12_final.stac-item
2019-12-12 11:35:28	ga_s2bm_ard_3-2-1_51JTJ_2019-12-12_final.stac-item
2019-12-12 11:35:31	ga_s2bm_ard_3-2-1_50JQP_2019-12-12_final.stac-item
2019-12-12 11:35:35	ga_s2bm_ard_3-2-1_51JVH_2019-12-12_final.stac-item
2019-12-12 11:35:39	ga_s2bm_ard_3-2-1_51JUH_2019-12-12_final.stac-item
2019-12-12 11:35:42	ga_s2bm_ard_3-2-1_51JTH_2019-12-12_final.stac-item
2019-12-12 11:35:45	ga_s2bm_ard_3-2-1_50JQN_2019-12-12_final.stac-item
2019-12-12 11:35:50	ga_s2bm_ard_3-2-1_51JVG_2019-12-12_final.stac-item
2019-12-12 11:35:54	ga_s2bm_ard_3-2-1_51JUG_2019-12-12_final.stac-item
2019-12-12 11:35:57	ga_s2bm_ard_3-2-1_51JTG_2019-12-12_final.stac-item
2019-12-12 11:35:59	ga_s2bm_ard_3-2-1_50JQM_2019-12-12_final.stac-item
2019-12-12 11:36:05	ga_s2bm_ard_3-2-1_51JVF_2019-12-12_final.stac-item
2019-12-12 11:36:08	ga_s2bm_ard_3-2-1_51JUF_2019-12-12_final.stac-item
2019-12-12 11:36:11	ga_s2bm_ard_3-2-1_51JTF_2019-12-12_final.stac-item
2019-12-12 11:36:14	ga_s2bm_ard_3-2-1_50JQL_2019-12-12_final.stac-item
2019-12-12 11:36:18	ga_s2bm_ard_3-2-1_51HVE_2019-12-12_final.stac-item
2019-12-12 11:36:21	ga_s2bm_ard_3-2-1_50JPL_2019-12-12_final.stac-item
2019-12-12 11:36:23	ga_s2bm_ard_3-2-1_51HUE_2019-12-12_final.stac-item
2019-12-12 11:36:26	ga_s2bm_ard_3-2-1_51HTE_2019-12-12_final.stac-item
2019-12-12 11:36:28	ga_s2bm_ard_3-2-1_51HVD_2019-12-12_final.stac-item
2019-12-12 11:36:28	ga_s2bm_ard_3-2-1_50HQK_2019-12-12_final.stac-item
2019-12-12 11:36:32	ga_s2bm_ard_3-2-1_50HPK_2019-12-12_final.stac-item
2019-12-12 11:36:34	ga_s2bm_ard_3-2-1_51HUD_2019-12-12_final.stac-item
2019-12-12 11:36:36	ga_s2bm_ard_3-2-1_51HTD_2019-12-12_final.stac-item
2019-12-12 11:36:36	ga_s2bm_ard_3-2-1_50HQK_2019-12-12_final.stac-item
2019-12-12 11:36:36	ga_s2bm_ard_3-2-1_50HQJ_2019-12-12_final.stac-item
2019-12-12 11:36:38	ga_s2bm_ard_3-2-1_50HPK_2019-12-12_final.stac-item
2019-12-12 11:36:38	ga_s2bm_ard_3-2-1_50HPJ_2019-12-12_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

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