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
2022-04-03 10:04:29	ga_s2bm_ard_3-2-1_54JXR_2022-04-03_final.stac-item
2022-04-03 10:04:30	ga_s2bm_ard_3-2-1_55JCK_2022-04-03_final.stac-item
2022-04-03 10:04:33	ga_s2bm_ard_3-2-1_55JBK_2022-04-03_final.stac-item
2022-04-03 10:04:36	ga_s2bm_ard_3-2-1_54JYQ_2022-04-03_final.stac-item
2022-04-03 10:04:40	ga_s2bm_ard_3-2-1_54JXQ_2022-04-03_final.stac-item
2022-04-03 10:04:44	ga_s2bm_ard_3-2-1_55JCJ_2022-04-03_final.stac-item
2022-04-03 10:04:48	ga_s2bm_ard_3-2-1_55JBJ_2022-04-03_final.stac-item
2022-04-03 10:04:51	ga_s2bm_ard_3-2-1_54JYP_2022-04-03_final.stac-item
2022-04-03 10:04:54	ga_s2bm_ard_3-2-1_54JXP_2022-04-03_final.stac-item
2022-04-03 10:04:59	ga_s2bm_ard_3-2-1_55JCH_2022-04-03_final.stac-item
2022-04-03 10:05:02	ga_s2bm_ard_3-2-1_55JBH_2022-04-03_final.stac-item
2022-04-03 10:05:05	ga_s2bm_ard_3-2-1_54JYN_2022-04-03_final.stac-item
2022-04-03 10:05:09	ga_s2bm_ard_3-2-1_54JXN_2022-04-03_final.stac-item
2022-04-03 10:05:13	ga_s2bm_ard_3-2-1_55JCG_2022-04-03_final.stac-item
2022-04-03 10:05:17	ga_s2bm_ard_3-2-1_55JBG_2022-04-03_final.stac-item
2022-04-03 10:05:20	ga_s2bm_ard_3-2-1_54JYM_2022-04-03_final.stac-item
2022-04-03 10:05:23	ga_s2bm_ard_3-2-1_54JXM_2022-04-03_final.stac-item
2022-04-03 10:05:26	ga_s2bm_ard_3-2-1_55JCF_2022-04-03_final.stac-item
2022-04-03 10:05:30	ga_s2bm_ard_3-2-1_54JWM_2022-04-03_final.stac-item
2022-04-03 10:05:31	ga_s2bm_ard_3-2-1_55JBF_2022-04-03_final.stac-item
2022-04-03 10:05:34	ga_s2bm_ard_3-2-1_54JYL_2022-04-03_final.stac-item
2022-04-03 10:05:36	ga_s2bm_ard_3-2-1_55HCE_2022-04-03_final.stac-item
2022-04-03 10:05:38	ga_s2bm_ard_3-2-1_54JXL_2022-04-03_final.stac-item
2022-04-03 10:05:41	ga_s2bm_ard_3-2-1_54JWL_2022-04-03_final.stac-item
2022-04-03 10:05:46	ga_s2bm_ard_3-2-1_55HBE_2022-04-03_final.stac-item
2022-04-03 10:05:48	ga_s2bm_ard_3-2-1_54HYK_2022-04-03_final.stac-item
2022-04-03 10:05:52	ga_s2bm_ard_3-2-1_54HXK_2022-04-03_final.stac-item
2022-04-03 10:05:56	ga_s2bm_ard_3-2-1_54HWK_2022-04-03_final.stac-item
2022-04-03 10:06:01	ga_s2bm_ard_3-2-1_55HBD_2022-04-03_final.stac-item
2022-04-03 10:06:03	ga_s2bm_ard_3-2-1_54HYJ_2022-04-03_final.stac-item
2022-04-03 10:06:07	ga_s2bm_ard_3-2-1_54HXJ_2022-04-03_final.stac-item
2022-04-03 10:06:10	ga_s2bm_ard_3-2-1_54HWJ_2022-04-03_final.stac-item
2022-04-03 10:06:15	ga_s2bm_ard_3-2-1_55HBC_2022-04-03_final.stac-item
2022-04-03 10:06:17	ga_s2bm_ard_3-2-1_54HYH_2022-04-03_final.stac-item
2022-04-03 10:06:21	ga_s2bm_ard_3-2-1_54HXH_2022-04-03_final.stac-item
2022-04-03 10:06:25	ga_s2bm_ard_3-2-1_54HWH_2022-04-03_final.stac-item
2022-04-03 10:06:27	ga_s2bm_ard_3-2-1_55HBB_2022-04-03_final.stac-item
2022-04-03 10:06:28	ga_s2bm_ard_3-2-1_54HYG_2022-04-03_final.stac-item
2022-04-03 10:06:30	ga_s2bm_ard_3-2-1_54HVH_2022-04-03_final.stac-item
2022-04-03 10:06:31	ga_s2bm_ard_3-2-1_54HXG_2022-04-03_final.stac-item
2022-04-03 10:06:32	ga_s2bm_ard_3-2-1_54HWH_2022-04-03_final.stac-item
2022-04-03 10:06:32	ga_s2bm_ard_3-2-1_54HWG_2022-04-03_final.stac-item
2022-04-03 10:06:34	ga_s2bm_ard_3-2-1_55HBB_2022-04-03_final.stac-item
2022-04-03 10:06:34	ga_s2bm_ard_3-2-1_54HVH_2022-04-03_final.stac-item
2022-04-03 10:06:34	ga_s2bm_ard_3-2-1_54HVG_2022-04-03_final.stac-item
2022-04-03 10:06:35	ga_s2bm_ard_3-2-1_54HYG_2022-04-03_final.stac-item
2022-04-03 10:06:37	ga_s2bm_ard_3-2-1_54HXG_2022-04-03_final.stac-item
2022-04-03 10:06:39	ga_s2bm_ard_3-2-1_54HWG_2022-04-03_final.stac-item
2022-04-03 10:06:42	ga_s2bm_ard_3-2-1_55HBA_2022-04-03_final.stac-item
2022-04-03 10:07:12	ga_s2bm_ard_3-2-1_54HVE_2022-04-03_final.stac-item
2022-04-03 10:07:26	ga_s2bm_ard_3-2-1_54HVD_2022-04-03_final.stac-item
2022-04-03 11:44:24	ga_s2bm_ard_3-2-1_51JUN_2022-04-03_final.stac-item
2022-04-03 11:44:27	ga_s2bm_ard_3-2-1_50JRT_2022-04-03_final.stac-item
2022-04-03 11:44:27	ga_s2bm_ard_3-2-1_51JTN_2022-04-03_final.stac-item
2022-04-03 11:44:31	ga_s2bm_ard_3-2-1_50JQT_2022-04-03_final.stac-item
2022-04-03 11:44:34	ga_s2bm_ard_3-2-1_50JPT_2022-04-03_final.stac-item
2022-04-03 11:44:37	ga_s2bm_ard_3-2-1_51JUM_2022-04-03_final.stac-item
2022-04-03 11:44:42	ga_s2bm_ard_3-2-1_50JRS_2022-04-03_final.stac-item
2022-04-03 11:44:42	ga_s2bm_ard_3-2-1_51JTM_2022-04-03_final.stac-item
2022-04-03 11:44:45	ga_s2bm_ard_3-2-1_50JQS_2022-04-03_final.stac-item
2022-04-03 11:44:48	ga_s2bm_ard_3-2-1_51JUL_2022-04-03_final.stac-item
2022-04-03 11:44:49	ga_s2bm_ard_3-2-1_50JPS_2022-04-03_final.stac-item
2022-04-03 11:44:56	ga_s2bm_ard_3-2-1_51JTL_2022-04-03_final.stac-item
2022-04-03 11:45:00	ga_s2bm_ard_3-2-1_50JQR_2022-04-03_final.stac-item
2022-04-03 11:45:03	ga_s2bm_ard_3-2-1_50JPR_2022-04-03_final.stac-item
2022-04-03 11:45:08	ga_s2bm_ard_3-2-1_50JNR_2022-04-03_final.stac-item
2022-04-03 11:45:11	ga_s2bm_ard_3-2-1_51JTK_2022-04-03_final.stac-item
2022-04-03 11:45:14	ga_s2bm_ard_3-2-1_50JQQ_2022-04-03_final.stac-item
2022-04-03 11:45:18	ga_s2bm_ard_3-2-1_50JPQ_2022-04-03_final.stac-item
2022-04-03 11:45:21	ga_s2bm_ard_3-2-1_50JNQ_2022-04-03_final.stac-item
2022-04-03 11:45:26	ga_s2bm_ard_3-2-1_51JTJ_2022-04-03_final.stac-item
2022-04-03 11:45:29	ga_s2bm_ard_3-2-1_50JQP_2022-04-03_final.stac-item
2022-04-03 11:45:32	ga_s2bm_ard_3-2-1_50JPP_2022-04-03_final.stac-item
2022-04-03 11:45:36	ga_s2bm_ard_3-2-1_50JNP_2022-04-03_final.stac-item
2022-04-03 11:45:40	ga_s2bm_ard_3-2-1_51JTH_2022-04-03_final.stac-item
2022-04-03 11:45:43	ga_s2bm_ard_3-2-1_50JQN_2022-04-03_final.stac-item
2022-04-03 11:45:47	ga_s2bm_ard_3-2-1_50JPN_2022-04-03_final.stac-item
2022-04-03 11:45:51	ga_s2bm_ard_3-2-1_50JNN_2022-04-03_final.stac-item
2022-04-03 11:45:53	ga_s2bm_ard_3-2-1_51JTG_2022-04-03_final.stac-item
2022-04-03 11:45:57	ga_s2bm_ard_3-2-1_50JQM_2022-04-03_final.stac-item
2022-04-03 11:46:01	ga_s2bm_ard_3-2-1_50JPM_2022-04-03_final.stac-item
2022-04-03 11:46:04	ga_s2bm_ard_3-2-1_51JTF_2022-04-03_final.stac-item
2022-04-03 11:46:05	ga_s2bm_ard_3-2-1_50JNM_2022-04-03_final.stac-item
2022-04-03 11:46:09	ga_s2bm_ard_3-2-1_50JMM_2022-04-03_final.stac-item
2022-04-03 11:46:12	ga_s2bm_ard_3-2-1_50JQL_2022-04-03_final.stac-item
2022-04-03 11:46:16	ga_s2bm_ard_3-2-1_50JPL_2022-04-03_final.stac-item
2022-04-03 11:46:19	ga_s2bm_ard_3-2-1_50JNL_2022-04-03_final.stac-item
2022-04-03 11:46:23	ga_s2bm_ard_3-2-1_50JML_2022-04-03_final.stac-item
2022-04-03 11:46:26	ga_s2bm_ard_3-2-1_50HQK_2022-04-03_final.stac-item
2022-04-03 11:46:30	ga_s2bm_ard_3-2-1_50HPK_2022-04-03_final.stac-item
2022-04-03 11:46:34	ga_s2bm_ard_3-2-1_50HNK_2022-04-03_final.stac-item
2022-04-03 11:46:37	ga_s2bm_ard_3-2-1_50HMK_2022-04-03_final.stac-item
2022-04-03 11:46:40	ga_s2bm_ard_3-2-1_50HQJ_2022-04-03_final.stac-item
2022-04-03 11:46:45	ga_s2bm_ard_3-2-1_50HPJ_2022-04-03_final.stac-item
2022-04-03 11:46:48	ga_s2bm_ard_3-2-1_50HNJ_2022-04-03_final.stac-item
2022-04-03 11:46:50	ga_s2bm_ard_3-2-1_50HQH_2022-04-03_final.stac-item
2022-04-03 11:46:52	ga_s2bm_ard_3-2-1_50HMJ_2022-04-03_final.stac-item
2022-04-03 11:46:59	ga_s2bm_ard_3-2-1_50HPH_2022-04-03_final.stac-item
2022-04-03 11:47:03	ga_s2bm_ard_3-2-1_50HNH_2022-04-03_final.stac-item
2022-04-03 11:47:06	ga_s2bm_ard_3-2-1_50HMH_2022-04-03_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