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
2018-11-29 12:14:04	ga_s2bm_ard_3-2-1_49KHQ_2018-11-29_final.stac-item
2018-11-29 12:14:08	ga_s2bm_ard_3-2-1_49KGQ_2018-11-29_final.stac-item
2018-11-29 12:14:14	ga_s2bm_ard_3-2-1_50KKU_2018-11-29_final.stac-item
2018-11-29 12:14:17	ga_s2bm_ard_3-2-1_49KHP_2018-11-29_final.stac-item
2018-11-29 12:14:23	ga_s2bm_ard_3-2-1_49KGP_2018-11-29_final.stac-item
2018-11-29 12:14:27	ga_s2bm_ard_3-2-1_49JHN_2018-11-29_final.stac-item
2018-11-29 12:14:37	ga_s2bm_ard_3-2-1_49JGN_2018-11-29_final.stac-item
2018-11-29 12:14:41	ga_s2bm_ard_3-2-1_49JFN_2018-11-29_final.stac-item
2018-11-29 12:14:52	ga_s2bm_ard_3-2-1_49JGM_2018-11-29_final.stac-item
2018-11-29 12:14:56	ga_s2bm_ard_3-2-1_49JFM_2018-11-29_final.stac-item
2018-11-29 12:15:06	ga_s2bm_ard_3-2-1_49JGL_2018-11-29_final.stac-item
2018-11-29 12:15:16	ga_s2bm_ard_3-2-1_49JGK_2018-11-29_final.stac-item
2018-11-30 10:05:32	ga_s2bm_ard_3-2-1_55JCF_2018-11-30_final.stac-item
2018-11-30 10:05:34	ga_s2bm_ard_3-2-1_55HCE_2018-11-30_final.stac-item
2018-11-30 10:05:35	ga_s2bm_ard_3-2-1_55JBF_2018-11-30_final.stac-item
2018-11-30 10:05:36	ga_s2bm_ard_3-2-1_54JYL_2018-11-30_final.stac-item
2018-11-30 10:05:38	ga_s2bm_ard_3-2-1_54JXL_2018-11-30_final.stac-item
2018-11-30 10:05:41	ga_s2bm_ard_3-2-1_54JWL_2018-11-30_final.stac-item
2018-11-30 10:05:45	ga_s2bm_ard_3-2-1_55HBE_2018-11-30_final.stac-item
2018-11-30 10:05:47	ga_s2bm_ard_3-2-1_54HYK_2018-11-30_final.stac-item
2018-11-30 10:05:51	ga_s2bm_ard_3-2-1_54HXK_2018-11-30_final.stac-item
2018-11-30 10:05:55	ga_s2bm_ard_3-2-1_54HWK_2018-11-30_final.stac-item
2018-11-30 10:06:00	ga_s2bm_ard_3-2-1_55HBD_2018-11-30_final.stac-item
2018-11-30 10:06:02	ga_s2bm_ard_3-2-1_54HYJ_2018-11-30_final.stac-item
2018-11-30 10:06:06	ga_s2bm_ard_3-2-1_54HXJ_2018-11-30_final.stac-item
2018-11-30 10:06:09	ga_s2bm_ard_3-2-1_54HWJ_2018-11-30_final.stac-item
2018-11-30 10:06:14	ga_s2bm_ard_3-2-1_55HBC_2018-11-30_final.stac-item
2018-11-30 10:06:16	ga_s2bm_ard_3-2-1_54HYH_2018-11-30_final.stac-item
2018-11-30 10:06:20	ga_s2bm_ard_3-2-1_54HXH_2018-11-30_final.stac-item
2018-11-30 10:06:24	ga_s2bm_ard_3-2-1_54HWH_2018-11-30_final.stac-item
2018-11-30 10:06:28	ga_s2bm_ard_3-2-1_55HBB_2018-11-30_final.stac-item
2018-11-30 10:06:29	ga_s2bm_ard_3-2-1_54HVH_2018-11-30_final.stac-item
2018-11-30 10:06:30	ga_s2bm_ard_3-2-1_54HYG_2018-11-30_final.stac-item
2018-11-30 10:06:35	ga_s2bm_ard_3-2-1_54HXG_2018-11-30_final.stac-item
2018-11-30 10:06:38	ga_s2bm_ard_3-2-1_54HWG_2018-11-30_final.stac-item
2018-11-30 10:06:41	ga_s2bm_ard_3-2-1_55HBA_2018-11-30_final.stac-item
2018-11-30 10:06:42	ga_s2bm_ard_3-2-1_54HVG_2018-11-30_final.stac-item
2018-11-30 10:06:45	ga_s2bm_ard_3-2-1_54HYF_2018-11-30_final.stac-item
2018-11-30 10:06:49	ga_s2bm_ard_3-2-1_54HXF_2018-11-30_final.stac-item
2018-11-30 10:06:51	ga_s2bm_ard_3-2-1_55HBV_2018-11-30_final.stac-item
2018-11-30 10:06:53	ga_s2bm_ard_3-2-1_54HWF_2018-11-30_final.stac-item
2018-11-30 10:06:56	ga_s2bm_ard_3-2-1_54HVF_2018-11-30_final.stac-item
2018-11-30 10:06:59	ga_s2bm_ard_3-2-1_54HYE_2018-11-30_final.stac-item
2018-11-30 10:07:03	ga_s2bm_ard_3-2-1_54HXE_2018-11-30_final.stac-item
2018-11-30 10:07:07	ga_s2bm_ard_3-2-1_54HWE_2018-11-30_final.stac-item
2018-11-30 10:07:10	ga_s2bm_ard_3-2-1_54HYD_2018-11-30_final.stac-item
2018-11-30 10:07:11	ga_s2bm_ard_3-2-1_54HVE_2018-11-30_final.stac-item
2018-11-30 10:07:18	ga_s2bm_ard_3-2-1_54HXD_2018-11-30_final.stac-item
2018-11-30 10:07:22	ga_s2bm_ard_3-2-1_54HWD_2018-11-30_final.stac-item
2018-11-30 10:07:25	ga_s2bm_ard_3-2-1_54HVD_2018-11-30_final.stac-item
2018-11-30 10:07:32	ga_s2bm_ard_3-2-1_54HXC_2018-11-30_final.stac-item
2018-11-30 10:07:36	ga_s2bm_ard_3-2-1_54HWC_2018-11-30_final.stac-item
2018-11-30 11:44:23	ga_s2bm_ard_3-2-1_51JUN_2018-11-30_final.stac-item
2018-11-30 11:44:26	ga_s2bm_ard_3-2-1_51JTN_2018-11-30_final.stac-item
2018-11-30 11:44:30	ga_s2bm_ard_3-2-1_50JQT_2018-11-30_final.stac-item
2018-11-30 11:44:33	ga_s2bm_ard_3-2-1_50JPT_2018-11-30_final.stac-item
2018-11-30 11:44:36	ga_s2bm_ard_3-2-1_51JUM_2018-11-30_final.stac-item
2018-11-30 11:44:41	ga_s2bm_ard_3-2-1_50JRS_2018-11-30_final.stac-item
2018-11-30 11:44:41	ga_s2bm_ard_3-2-1_51JTM_2018-11-30_final.stac-item
2018-11-30 11:44:44	ga_s2bm_ard_3-2-1_50JQS_2018-11-30_final.stac-item
2018-11-30 11:44:47	ga_s2bm_ard_3-2-1_51JUL_2018-11-30_final.stac-item
2018-11-30 11:44:48	ga_s2bm_ard_3-2-1_50JPS_2018-11-30_final.stac-item
2018-11-30 11:44:55	ga_s2bm_ard_3-2-1_51JTL_2018-11-30_final.stac-item
2018-11-30 11:44:59	ga_s2bm_ard_3-2-1_50JQR_2018-11-30_final.stac-item
2018-11-30 11:45:02	ga_s2bm_ard_3-2-1_50JPR_2018-11-30_final.stac-item
2018-11-30 11:45:07	ga_s2bm_ard_3-2-1_50JNR_2018-11-30_final.stac-item
2018-11-30 11:45:10	ga_s2bm_ard_3-2-1_51JTK_2018-11-30_final.stac-item
2018-11-30 11:45:13	ga_s2bm_ard_3-2-1_50JQQ_2018-11-30_final.stac-item
2018-11-30 11:45:17	ga_s2bm_ard_3-2-1_50JPQ_2018-11-30_final.stac-item
2018-11-30 11:45:20	ga_s2bm_ard_3-2-1_50JNQ_2018-11-30_final.stac-item
2018-11-30 11:45:25	ga_s2bm_ard_3-2-1_51JTJ_2018-11-30_final.stac-item
2018-11-30 11:45:28	ga_s2bm_ard_3-2-1_50JQP_2018-11-30_final.stac-item
2018-11-30 11:45:32	ga_s2bm_ard_3-2-1_50JPP_2018-11-30_final.stac-item
2018-11-30 11:45:35	ga_s2bm_ard_3-2-1_50JNP_2018-11-30_final.stac-item
2018-11-30 11:45:39	ga_s2bm_ard_3-2-1_51JTH_2018-11-30_final.stac-item
2018-11-30 11:45:42	ga_s2bm_ard_3-2-1_50JQN_2018-11-30_final.stac-item
2018-11-30 11:45:46	ga_s2bm_ard_3-2-1_50JPN_2018-11-30_final.stac-item
2018-11-30 11:45:50	ga_s2bm_ard_3-2-1_50JNN_2018-11-30_final.stac-item
2018-11-30 11:45:52	ga_s2bm_ard_3-2-1_51JTG_2018-11-30_final.stac-item
2018-11-30 11:45:56	ga_s2bm_ard_3-2-1_50JQM_2018-11-30_final.stac-item
2018-11-30 11:46:00	ga_s2bm_ard_3-2-1_50JPM_2018-11-30_final.stac-item
2018-11-30 11:46:03	ga_s2bm_ard_3-2-1_51JTF_2018-11-30_final.stac-item
2018-11-30 11:46:04	ga_s2bm_ard_3-2-1_50JNM_2018-11-30_final.stac-item
2018-11-30 11:46:08	ga_s2bm_ard_3-2-1_50JMM_2018-11-30_final.stac-item
2018-11-30 11:46:11	ga_s2bm_ard_3-2-1_50JQL_2018-11-30_final.stac-item
2018-11-30 11:46:15	ga_s2bm_ard_3-2-1_50JPL_2018-11-30_final.stac-item
2018-11-30 11:46:18	ga_s2bm_ard_3-2-1_50JNL_2018-11-30_final.stac-item
2018-11-30 11:46:22	ga_s2bm_ard_3-2-1_50JML_2018-11-30_final.stac-item
2018-11-30 11:46:26	ga_s2bm_ard_3-2-1_50HQK_2018-11-30_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 11:46:33	ga_s2bm_ard_3-2-1_50HNK_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 11:46:39	ga_s2bm_ard_3-2-1_50HQJ_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 11:46:47	ga_s2bm_ard_3-2-1_50HNJ_2018-11-30_final.stac-item
2018-11-30 11:46:49	ga_s2bm_ard_3-2-1_50HQH_2018-11-30_final.stac-item
2018-11-30 11:46:51	ga_s2bm_ard_3-2-1_50HMJ_2018-11-30_final.stac-item
2018-11-30 11:46:58	ga_s2bm_ard_3-2-1_50HPH_2018-11-30_final.stac-item
2018-11-30 11:47:02	ga_s2bm_ard_3-2-1_50HNH_2018-11-30_final.stac-item
2018-11-30 11:47:05	ga_s2bm_ard_3-2-1_50HMH_2018-11-30_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

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