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
2019-10-26 10:04:01	ga_s2bm_ard_3-2-1_55JDM_2019-10-26_final.stac-item
2019-10-26 10:04:05	ga_s2bm_ard_3-2-1_55JCM_2019-10-26_final.stac-item
2019-10-26 10:04:08	ga_s2bm_ard_3-2-1_54JZS_2019-10-26_final.stac-item
2019-10-26 10:04:08	ga_s2bm_ard_3-2-1_55JBM_2019-10-26_final.stac-item
2019-10-26 10:04:12	ga_s2bm_ard_3-2-1_54JYS_2019-10-26_final.stac-item
2019-10-26 10:04:14	ga_s2bm_ard_3-2-1_55JDL_2019-10-26_final.stac-item
2019-10-26 10:04:20	ga_s2bm_ard_3-2-1_55JCL_2019-10-26_final.stac-item
2019-10-26 10:04:23	ga_s2bm_ard_3-2-1_55JBL_2019-10-26_final.stac-item
2019-10-26 10:04:24	ga_s2bm_ard_3-2-1_55JDK_2019-10-26_final.stac-item
2019-10-26 10:04:26	ga_s2bm_ard_3-2-1_54JYR_2019-10-26_final.stac-item
2019-10-26 10:04:33	ga_s2bm_ard_3-2-1_54JXR_2019-10-26_final.stac-item
2019-10-26 10:04:34	ga_s2bm_ard_3-2-1_55JCK_2019-10-26_final.stac-item
2019-10-26 10:04:38	ga_s2bm_ard_3-2-1_55JBK_2019-10-26_final.stac-item
2019-10-26 10:04:41	ga_s2bm_ard_3-2-1_54JYQ_2019-10-26_final.stac-item
2019-10-26 10:04:45	ga_s2bm_ard_3-2-1_54JXQ_2019-10-26_final.stac-item
2019-10-26 10:04:49	ga_s2bm_ard_3-2-1_55JCJ_2019-10-26_final.stac-item
2019-10-26 10:04:52	ga_s2bm_ard_3-2-1_55JBJ_2019-10-26_final.stac-item
2019-10-26 10:04:55	ga_s2bm_ard_3-2-1_54JYP_2019-10-26_final.stac-item
2019-10-26 10:04:58	ga_s2bm_ard_3-2-1_54JXP_2019-10-26_final.stac-item
2019-10-26 10:05:03	ga_s2bm_ard_3-2-1_55JCH_2019-10-26_final.stac-item
2019-10-26 10:05:07	ga_s2bm_ard_3-2-1_55JBH_2019-10-26_final.stac-item
2019-10-26 10:05:09	ga_s2bm_ard_3-2-1_54JYN_2019-10-26_final.stac-item
2019-10-26 10:05:13	ga_s2bm_ard_3-2-1_54JXN_2019-10-26_final.stac-item
2019-10-26 10:05:17	ga_s2bm_ard_3-2-1_55JCG_2019-10-26_final.stac-item
2019-10-26 10:05:21	ga_s2bm_ard_3-2-1_55JBG_2019-10-26_final.stac-item
2019-10-26 10:05:24	ga_s2bm_ard_3-2-1_54JYM_2019-10-26_final.stac-item
2019-10-26 10:05:28	ga_s2bm_ard_3-2-1_54JXM_2019-10-26_final.stac-item
2019-10-26 10:05:30	ga_s2bm_ard_3-2-1_55JCF_2019-10-26_final.stac-item
2019-10-26 10:05:34	ga_s2bm_ard_3-2-1_54JWM_2019-10-26_final.stac-item
2019-10-26 10:05:36	ga_s2bm_ard_3-2-1_55JBF_2019-10-26_final.stac-item
2019-10-26 10:05:38	ga_s2bm_ard_3-2-1_54JYL_2019-10-26_final.stac-item
2019-10-26 10:05:40	ga_s2bm_ard_3-2-1_55HCE_2019-10-26_final.stac-item
2019-10-26 10:05:42	ga_s2bm_ard_3-2-1_54JXL_2019-10-26_final.stac-item
2019-10-26 10:05:46	ga_s2bm_ard_3-2-1_54JWL_2019-10-26_final.stac-item
2019-10-26 10:05:50	ga_s2bm_ard_3-2-1_55HBE_2019-10-26_final.stac-item
2019-10-26 10:05:53	ga_s2bm_ard_3-2-1_54HYK_2019-10-26_final.stac-item
2019-10-26 10:05:56	ga_s2bm_ard_3-2-1_54HXK_2019-10-26_final.stac-item
2019-10-26 10:06:00	ga_s2bm_ard_3-2-1_54HWK_2019-10-26_final.stac-item
2019-10-26 10:06:05	ga_s2bm_ard_3-2-1_55HBD_2019-10-26_final.stac-item
2019-10-26 10:06:07	ga_s2bm_ard_3-2-1_54HYJ_2019-10-26_final.stac-item
2019-10-26 10:06:11	ga_s2bm_ard_3-2-1_54HXJ_2019-10-26_final.stac-item
2019-10-26 10:06:15	ga_s2bm_ard_3-2-1_54HWJ_2019-10-26_final.stac-item
2019-10-26 10:06:20	ga_s2bm_ard_3-2-1_55HBC_2019-10-26_final.stac-item
2019-10-26 10:06:21	ga_s2bm_ard_3-2-1_54HYH_2019-10-26_final.stac-item
2019-10-26 10:06:25	ga_s2bm_ard_3-2-1_54HXH_2019-10-26_final.stac-item
2019-10-26 10:06:29	ga_s2bm_ard_3-2-1_54HWH_2019-10-26_final.stac-item
2019-10-26 10:06:34	ga_s2bm_ard_3-2-1_55HBB_2019-10-26_final.stac-item
2019-10-26 10:06:35	ga_s2bm_ard_3-2-1_54HVH_2019-10-26_final.stac-item
2019-10-26 10:06:36	ga_s2bm_ard_3-2-1_54HYG_2019-10-26_final.stac-item
2019-10-26 10:07:16	ga_s2bm_ard_3-2-1_54HVE_2019-10-26_final.stac-item
2019-10-26 10:07:31	ga_s2bm_ard_3-2-1_54HVD_2019-10-26_final.stac-item
2019-10-26 11:44:28	ga_s2bm_ard_3-2-1_51JUN_2019-10-26_final.stac-item
2019-10-26 11:44:32	ga_s2bm_ard_3-2-1_50JRT_2019-10-26_final.stac-item
2019-10-26 11:44:32	ga_s2bm_ard_3-2-1_51JTN_2019-10-26_final.stac-item
2019-10-26 11:44:35	ga_s2bm_ard_3-2-1_50JQT_2019-10-26_final.stac-item
2019-10-26 11:44:39	ga_s2bm_ard_3-2-1_50JPT_2019-10-26_final.stac-item
2019-10-26 11:44:42	ga_s2bm_ard_3-2-1_51JUM_2019-10-26_final.stac-item
2019-10-26 11:44:46	ga_s2bm_ard_3-2-1_50JRS_2019-10-26_final.stac-item
2019-10-26 11:44:46	ga_s2bm_ard_3-2-1_51JTM_2019-10-26_final.stac-item
2019-10-26 11:44:50	ga_s2bm_ard_3-2-1_50JQS_2019-10-26_final.stac-item
2019-10-26 11:44:52	ga_s2bm_ard_3-2-1_51JUL_2019-10-26_final.stac-item
2019-10-26 11:44:53	ga_s2bm_ard_3-2-1_50JPS_2019-10-26_final.stac-item
2019-10-26 11:45:01	ga_s2bm_ard_3-2-1_51JTL_2019-10-26_final.stac-item
2019-10-26 11:45:04	ga_s2bm_ard_3-2-1_50JQR_2019-10-26_final.stac-item
2019-10-26 11:45:08	ga_s2bm_ard_3-2-1_50JPR_2019-10-26_final.stac-item
2019-10-26 11:45:12	ga_s2bm_ard_3-2-1_50JNR_2019-10-26_final.stac-item
2019-10-26 11:45:15	ga_s2bm_ard_3-2-1_51JTK_2019-10-26_final.stac-item
2019-10-26 11:45:19	ga_s2bm_ard_3-2-1_50JQQ_2019-10-26_final.stac-item
2019-10-26 11:45:22	ga_s2bm_ard_3-2-1_50JPQ_2019-10-26_final.stac-item
2019-10-26 11:45:25	ga_s2bm_ard_3-2-1_50JNQ_2019-10-26_final.stac-item
2019-10-26 11:45:30	ga_s2bm_ard_3-2-1_51JTJ_2019-10-26_final.stac-item
2019-10-26 11:45:33	ga_s2bm_ard_3-2-1_50JQP_2019-10-26_final.stac-item
2019-10-26 11:45:37	ga_s2bm_ard_3-2-1_50JPP_2019-10-26_final.stac-item
2019-10-26 11:45:40	ga_s2bm_ard_3-2-1_50JNP_2019-10-26_final.stac-item
2019-10-26 11:45:44	ga_s2bm_ard_3-2-1_51JTH_2019-10-26_final.stac-item
2019-10-26 11:45:47	ga_s2bm_ard_3-2-1_50JQN_2019-10-26_final.stac-item
2019-10-26 11:45:51	ga_s2bm_ard_3-2-1_50JPN_2019-10-26_final.stac-item
2019-10-26 11:45:55	ga_s2bm_ard_3-2-1_50JNN_2019-10-26_final.stac-item
2019-10-26 11:45:58	ga_s2bm_ard_3-2-1_51JTG_2019-10-26_final.stac-item
2019-10-26 11:46:02	ga_s2bm_ard_3-2-1_50JQM_2019-10-26_final.stac-item
2019-10-26 11:46:06	ga_s2bm_ard_3-2-1_50JPM_2019-10-26_final.stac-item
2019-10-26 11:46:09	ga_s2bm_ard_3-2-1_51JTF_2019-10-26_final.stac-item
2019-10-26 11:46:09	ga_s2bm_ard_3-2-1_50JNM_2019-10-26_final.stac-item
2019-10-26 11:46:14	ga_s2bm_ard_3-2-1_50JMM_2019-10-26_final.stac-item
2019-10-26 11:46:16	ga_s2bm_ard_3-2-1_50JQL_2019-10-26_final.stac-item
2019-10-26 11:46:20	ga_s2bm_ard_3-2-1_50JPL_2019-10-26_final.stac-item
2019-10-26 11:46:24	ga_s2bm_ard_3-2-1_50JNL_2019-10-26_final.stac-item
2019-10-26 11:46:27	ga_s2bm_ard_3-2-1_50JML_2019-10-26_final.stac-item
2019-10-26 11:46:31	ga_s2bm_ard_3-2-1_50HQK_2019-10-26_final.stac-item
2019-10-26 11:46:35	ga_s2bm_ard_3-2-1_50HPK_2019-10-26_final.stac-item
2019-10-26 11:46:38	ga_s2bm_ard_3-2-1_50HNK_2019-10-26_final.stac-item
2019-10-26 11:46:42	ga_s2bm_ard_3-2-1_50HMK_2019-10-26_final.stac-item
2019-10-26 11:46:44	ga_s2bm_ard_3-2-1_50HQJ_2019-10-26_final.stac-item
2019-10-26 11:46:49	ga_s2bm_ard_3-2-1_50HPJ_2019-10-26_final.stac-item
2019-10-26 11:46:53	ga_s2bm_ard_3-2-1_50HNJ_2019-10-26_final.stac-item
2019-10-26 11:46:54	ga_s2bm_ard_3-2-1_50HQH_2019-10-26_final.stac-item
2019-10-26 11:46:56	ga_s2bm_ard_3-2-1_50HMJ_2019-10-26_final.stac-item
2019-10-26 11:47:03	ga_s2bm_ard_3-2-1_50HPH_2019-10-26_final.stac-item
2019-10-26 11:47:07	ga_s2bm_ard_3-2-1_50HNH_2019-10-26_final.stac-item
2019-10-26 11:47:11	ga_s2bm_ard_3-2-1_50HMH_2019-10-26_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