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
2019-08-16 10:34:20	ga_s2bm_ard_3-2-1_53JNN_2019-08-16_final.stac-item
2019-08-16 10:34:20	ga_s2bm_ard_3-2-1_53JRM_2019-08-16_final.stac-item
2019-08-16 10:34:21	ga_s2bm_ard_3-2-1_54JTS_2019-08-16_final.stac-item
2019-08-16 10:34:23	ga_s2bm_ard_3-2-1_53JQM_2019-08-16_final.stac-item
2019-08-16 10:34:25	ga_s2bm_ard_3-2-1_53JPM_2019-08-16_final.stac-item
2019-08-16 10:34:27	ga_s2bm_ard_3-2-1_53JNM_2019-08-16_final.stac-item
2019-08-16 10:34:28	ga_s2bm_ard_3-2-1_53JRM_2019-08-16_final.stac-item
2019-08-16 10:34:28	ga_s2bm_ard_3-2-1_54JTS_2019-08-16_final.stac-item
2019-08-16 10:34:29	ga_s2bm_ard_3-2-1_54JTR_2019-08-16_final.stac-item
2019-08-16 10:34:29	ga_s2bm_ard_3-2-1_53JQL_2019-08-16_final.stac-item
2019-08-16 10:34:30	ga_s2bm_ard_3-2-1_53JQM_2019-08-16_final.stac-item
2019-08-16 10:34:31	ga_s2bm_ard_3-2-1_53JPM_2019-08-16_final.stac-item
2019-08-16 10:34:33	ga_s2bm_ard_3-2-1_53JNM_2019-08-16_final.stac-item
2019-08-16 10:34:35	ga_s2bm_ard_3-2-1_54JTR_2019-08-16_final.stac-item
2019-08-16 10:34:39	ga_s2bm_ard_3-2-1_53JQL_2019-08-16_final.stac-item
2019-08-16 10:34:42	ga_s2bm_ard_3-2-1_53JPL_2019-08-16_final.stac-item
2019-08-16 10:34:46	ga_s2bm_ard_3-2-1_53JNL_2019-08-16_final.stac-item
2019-08-16 10:34:50	ga_s2bm_ard_3-2-1_54JTQ_2019-08-16_final.stac-item
2019-08-16 10:34:53	ga_s2bm_ard_3-2-1_53JQK_2019-08-16_final.stac-item
2019-08-16 10:34:57	ga_s2bm_ard_3-2-1_53JPK_2019-08-16_final.stac-item
2019-08-16 10:35:00	ga_s2bm_ard_3-2-1_53JNK_2019-08-16_final.stac-item
2019-08-16 10:35:03	ga_s2bm_ard_3-2-1_54JTP_2019-08-16_final.stac-item
2019-08-16 10:35:07	ga_s2bm_ard_3-2-1_53JQJ_2019-08-16_final.stac-item
2019-08-16 10:35:11	ga_s2bm_ard_3-2-1_53JPJ_2019-08-16_final.stac-item
2019-08-16 10:35:14	ga_s2bm_ard_3-2-1_54JTN_2019-08-16_final.stac-item
2019-08-16 10:35:15	ga_s2bm_ard_3-2-1_53JNJ_2019-08-16_final.stac-item
2019-08-16 10:35:21	ga_s2bm_ard_3-2-1_53JMJ_2019-08-16_final.stac-item
2019-08-16 10:35:22	ga_s2bm_ard_3-2-1_53JQH_2019-08-16_final.stac-item
2019-08-16 10:35:26	ga_s2bm_ard_3-2-1_53JPH_2019-08-16_final.stac-item
2019-08-16 10:35:29	ga_s2bm_ard_3-2-1_53JNH_2019-08-16_final.stac-item
2019-08-16 10:35:33	ga_s2bm_ard_3-2-1_53JMH_2019-08-16_final.stac-item
2019-08-16 10:35:37	ga_s2bm_ard_3-2-1_53JQG_2019-08-16_final.stac-item
2019-08-16 10:35:40	ga_s2bm_ard_3-2-1_53JPG_2019-08-16_final.stac-item
2019-08-16 10:35:44	ga_s2bm_ard_3-2-1_53JNG_2019-08-16_final.stac-item
2019-08-16 10:35:47	ga_s2bm_ard_3-2-1_53JMG_2019-08-16_final.stac-item
2019-08-16 10:35:51	ga_s2bm_ard_3-2-1_53JQF_2019-08-16_final.stac-item
2019-08-16 10:35:55	ga_s2bm_ard_3-2-1_53JPF_2019-08-16_final.stac-item
2019-08-16 10:35:58	ga_s2bm_ard_3-2-1_53JNF_2019-08-16_final.stac-item
2019-08-16 10:36:02	ga_s2bm_ard_3-2-1_53JMF_2019-08-16_final.stac-item
2019-08-16 10:36:03	ga_s2bm_ard_3-2-1_53HQE_2019-08-16_final.stac-item
2019-08-16 10:36:09	ga_s2bm_ard_3-2-1_53HPE_2019-08-16_final.stac-item
2019-08-16 10:36:13	ga_s2bm_ard_3-2-1_53HNE_2019-08-16_final.stac-item
2019-08-16 10:36:16	ga_s2bm_ard_3-2-1_53HME_2019-08-16_final.stac-item
2019-08-16 10:36:23	ga_s2bm_ard_3-2-1_53HLE_2019-08-16_final.stac-item
2019-08-16 10:36:23	ga_s2bm_ard_3-2-1_53HPD_2019-08-16_final.stac-item
2019-08-16 10:36:27	ga_s2bm_ard_3-2-1_53HND_2019-08-16_final.stac-item
2019-08-16 12:14:52	ga_s2bm_ard_3-2-1_49JFN_2019-08-16_final.stac-item
2019-08-16 12:15:06	ga_s2bm_ard_3-2-1_49JFM_2019-08-16_final.stac-item
2019-08-17 10:04:54	ga_s2bm_ard_3-2-1_55JCJ_2019-08-17_final.stac-item
2019-08-17 10:04:57	ga_s2bm_ard_3-2-1_55JBJ_2019-08-17_final.stac-item
2019-08-17 10:05:00	ga_s2bm_ard_3-2-1_54JYP_2019-08-17_final.stac-item
2019-08-17 10:05:03	ga_s2bm_ard_3-2-1_54JXP_2019-08-17_final.stac-item
2019-08-17 10:05:09	ga_s2bm_ard_3-2-1_55JCH_2019-08-17_final.stac-item
2019-08-17 10:05:12	ga_s2bm_ard_3-2-1_55JBH_2019-08-17_final.stac-item
2019-08-17 10:05:15	ga_s2bm_ard_3-2-1_54JYN_2019-08-17_final.stac-item
2019-08-17 10:05:18	ga_s2bm_ard_3-2-1_54JXN_2019-08-17_final.stac-item
2019-08-17 10:05:22	ga_s2bm_ard_3-2-1_55JCG_2019-08-17_final.stac-item
2019-08-17 10:05:26	ga_s2bm_ard_3-2-1_55JBG_2019-08-17_final.stac-item
2019-08-17 10:05:29	ga_s2bm_ard_3-2-1_54JYM_2019-08-17_final.stac-item
2019-08-17 10:05:33	ga_s2bm_ard_3-2-1_54JXM_2019-08-17_final.stac-item
2019-08-17 10:05:35	ga_s2bm_ard_3-2-1_55JCF_2019-08-17_final.stac-item
2019-08-17 10:05:39	ga_s2bm_ard_3-2-1_54JWM_2019-08-17_final.stac-item
2019-08-17 10:05:41	ga_s2bm_ard_3-2-1_55JBF_2019-08-17_final.stac-item
2019-08-17 10:05:43	ga_s2bm_ard_3-2-1_54JYL_2019-08-17_final.stac-item
2019-08-17 10:05:45	ga_s2bm_ard_3-2-1_55HCE_2019-08-17_final.stac-item
2019-08-17 10:05:47	ga_s2bm_ard_3-2-1_54JXL_2019-08-17_final.stac-item
2019-08-17 10:05:51	ga_s2bm_ard_3-2-1_54JWL_2019-08-17_final.stac-item
2019-08-17 10:05:55	ga_s2bm_ard_3-2-1_55HBE_2019-08-17_final.stac-item
2019-08-17 10:05:58	ga_s2bm_ard_3-2-1_54HYK_2019-08-17_final.stac-item
2019-08-17 10:06:02	ga_s2bm_ard_3-2-1_54HXK_2019-08-17_final.stac-item
2019-08-17 10:06:05	ga_s2bm_ard_3-2-1_54HWK_2019-08-17_final.stac-item
2019-08-17 10:06:10	ga_s2bm_ard_3-2-1_55HBD_2019-08-17_final.stac-item
2019-08-17 10:06:12	ga_s2bm_ard_3-2-1_54HYJ_2019-08-17_final.stac-item
2019-08-17 10:06:16	ga_s2bm_ard_3-2-1_54HXJ_2019-08-17_final.stac-item
2019-08-17 10:06:20	ga_s2bm_ard_3-2-1_54HWJ_2019-08-17_final.stac-item
2019-08-17 10:06:25	ga_s2bm_ard_3-2-1_55HBC_2019-08-17_final.stac-item
2019-08-17 10:06:26	ga_s2bm_ard_3-2-1_54HYH_2019-08-17_final.stac-item
2019-08-17 10:06:31	ga_s2bm_ard_3-2-1_54HXH_2019-08-17_final.stac-item
2019-08-17 10:06:34	ga_s2bm_ard_3-2-1_54HWH_2019-08-17_final.stac-item
2019-08-17 10:06:39	ga_s2bm_ard_3-2-1_55HBB_2019-08-17_final.stac-item
2019-08-17 10:06:40	ga_s2bm_ard_3-2-1_54HVH_2019-08-17_final.stac-item
2019-08-17 10:06:41	ga_s2bm_ard_3-2-1_54HYG_2019-08-17_final.stac-item
2019-08-17 10:06:45	ga_s2bm_ard_3-2-1_54HXG_2019-08-17_final.stac-item
2019-08-17 10:06:49	ga_s2bm_ard_3-2-1_54HWG_2019-08-17_final.stac-item
2019-08-17 10:06:52	ga_s2bm_ard_3-2-1_55HBA_2019-08-17_final.stac-item
2019-08-17 10:06:52	ga_s2bm_ard_3-2-1_54HVG_2019-08-17_final.stac-item
2019-08-17 10:06:56	ga_s2bm_ard_3-2-1_54HYF_2019-08-17_final.stac-item
2019-08-17 10:06:59	ga_s2bm_ard_3-2-1_54HXF_2019-08-17_final.stac-item
2019-08-17 10:07:02	ga_s2bm_ard_3-2-1_55HBV_2019-08-17_final.stac-item
2019-08-17 10:07:03	ga_s2bm_ard_3-2-1_54HWF_2019-08-17_final.stac-item
2019-08-17 10:07:06	ga_s2bm_ard_3-2-1_54HVF_2019-08-17_final.stac-item
2019-08-17 10:07:09	ga_s2bm_ard_3-2-1_54HYE_2019-08-17_final.stac-item
2019-08-17 10:07:14	ga_s2bm_ard_3-2-1_54HXE_2019-08-17_final.stac-item
2019-08-17 10:07:18	ga_s2bm_ard_3-2-1_54HWE_2019-08-17_final.stac-item
2019-08-17 10:07:20	ga_s2bm_ard_3-2-1_54HYD_2019-08-17_final.stac-item
2019-08-17 10:07:21	ga_s2bm_ard_3-2-1_54HVE_2019-08-17_final.stac-item
2019-08-17 10:07:28	ga_s2bm_ard_3-2-1_54HXD_2019-08-17_final.stac-item
2019-08-17 10:07:32	ga_s2bm_ard_3-2-1_54HWD_2019-08-17_final.stac-item
2019-08-17 10:07:36	ga_s2bm_ard_3-2-1_54HVD_2019-08-17_final.stac-item
2019-08-17 10:07:43	ga_s2bm_ard_3-2-1_54HXC_2019-08-17_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