Search ga_s2bm_ard_3 on 14th June 2019

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
2019-06-14 10:24:08	ga_s2bm_ard_3-2-1_54JUT_2019-06-14_final.stac-item
2019-06-14 10:24:11	ga_s2bm_ard_3-2-1_53JRN_2019-06-14_final.stac-item
2019-06-14 10:24:11	ga_s2bm_ard_3-2-1_54JTT_2019-06-14_final.stac-item
2019-06-14 10:24:23	ga_s2bm_ard_3-2-1_54JUS_2019-06-14_final.stac-item
2019-06-14 10:24:26	ga_s2bm_ard_3-2-1_53JRM_2019-06-14_final.stac-item
2019-06-14 10:24:26	ga_s2bm_ard_3-2-1_54JTS_2019-06-14_final.stac-item
2019-06-14 10:24:38	ga_s2bm_ard_3-2-1_54JUR_2019-06-14_final.stac-item
2019-06-14 10:24:41	ga_s2bm_ard_3-2-1_54JTR_2019-06-14_final.stac-item
2019-06-14 10:24:47	ga_s2bm_ard_3-2-1_53JQL_2019-06-14_final.stac-item
2019-06-14 10:24:52	ga_s2bm_ard_3-2-1_54JUQ_2019-06-14_final.stac-item
2019-06-14 10:24:55	ga_s2bm_ard_3-2-1_54JTQ_2019-06-14_final.stac-item
2019-06-14 10:24:59	ga_s2bm_ard_3-2-1_53JQK_2019-06-14_final.stac-item
2019-06-14 10:25:07	ga_s2bm_ard_3-2-1_54JUP_2019-06-14_final.stac-item
2019-06-14 10:25:10	ga_s2bm_ard_3-2-1_54JTP_2019-06-14_final.stac-item
2019-06-14 10:25:13	ga_s2bm_ard_3-2-1_53JQJ_2019-06-14_final.stac-item
2019-06-14 10:25:21	ga_s2bm_ard_3-2-1_54JUN_2019-06-14_final.stac-item
2019-06-14 10:25:25	ga_s2bm_ard_3-2-1_54JTN_2019-06-14_final.stac-item
2019-06-14 10:25:27	ga_s2bm_ard_3-2-1_53JQH_2019-06-14_final.stac-item
2019-06-14 10:25:36	ga_s2bm_ard_3-2-1_54JUM_2019-06-14_final.stac-item
2019-06-14 10:25:39	ga_s2bm_ard_3-2-1_54JTM_2019-06-14_final.stac-item
2019-06-14 10:25:42	ga_s2bm_ard_3-2-1_53JQG_2019-06-14_final.stac-item
2019-06-14 10:25:43	ga_s2bm_ard_3-2-1_54JVL_2019-06-14_final.stac-item
2019-06-14 10:25:47	ga_s2bm_ard_3-2-1_53JPG_2019-06-14_final.stac-item
2019-06-14 10:25:50	ga_s2bm_ard_3-2-1_54JUL_2019-06-14_final.stac-item
2019-06-14 10:25:54	ga_s2bm_ard_3-2-1_54JTL_2019-06-14_final.stac-item
2019-06-14 10:25:56	ga_s2bm_ard_3-2-1_53JQF_2019-06-14_final.stac-item
2019-06-14 10:26:00	ga_s2bm_ard_3-2-1_53JPF_2019-06-14_final.stac-item
2019-06-14 10:26:05	ga_s2bm_ard_3-2-1_54HUK_2019-06-14_final.stac-item
2019-06-14 10:26:08	ga_s2bm_ard_3-2-1_54HTK_2019-06-14_final.stac-item
2019-06-14 10:26:11	ga_s2bm_ard_3-2-1_53HQE_2019-06-14_final.stac-item
2019-06-14 10:26:14	ga_s2bm_ard_3-2-1_53HPE_2019-06-14_final.stac-item
2019-06-14 10:26:20	ga_s2bm_ard_3-2-1_54HUJ_2019-06-14_final.stac-item
2019-06-14 10:26:23	ga_s2bm_ard_3-2-1_54HTJ_2019-06-14_final.stac-item
2019-06-14 10:26:25	ga_s2bm_ard_3-2-1_53HQD_2019-06-14_final.stac-item
2019-06-14 10:26:29	ga_s2bm_ard_3-2-1_53HPD_2019-06-14_final.stac-item
2019-06-14 10:26:34	ga_s2bm_ard_3-2-1_54HUH_2019-06-14_final.stac-item
2019-06-14 10:26:37	ga_s2bm_ard_3-2-1_54HTH_2019-06-14_final.stac-item
2019-06-14 10:26:39	ga_s2bm_ard_3-2-1_53HQC_2019-06-14_final.stac-item
2019-06-14 10:26:43	ga_s2bm_ard_3-2-1_53HPC_2019-06-14_final.stac-item
2019-06-14 10:26:47	ga_s2bm_ard_3-2-1_54HUG_2019-06-14_final.stac-item
2019-06-14 10:26:48	ga_s2bm_ard_3-2-1_53HNC_2019-06-14_final.stac-item
2019-06-14 10:26:52	ga_s2bm_ard_3-2-1_54HTG_2019-06-14_final.stac-item
2019-06-14 10:26:54	ga_s2bm_ard_3-2-1_53HQB_2019-06-14_final.stac-item
2019-06-14 10:26:58	ga_s2bm_ard_3-2-1_53HPB_2019-06-14_final.stac-item
2019-06-14 10:26:58	ga_s2bm_ard_3-2-1_54HUF_2019-06-14_final.stac-item
2019-06-14 10:27:01	ga_s2bm_ard_3-2-1_53HNB_2019-06-14_final.stac-item
2019-06-14 10:27:06	ga_s2bm_ard_3-2-1_54HTF_2019-06-14_final.stac-item
2019-06-14 10:27:08	ga_s2bm_ard_3-2-1_53HQA_2019-06-14_final.stac-item
2019-06-14 10:27:12	ga_s2bm_ard_3-2-1_53HPA_2019-06-14_final.stac-item
2019-06-14 12:03:27	ga_s2bm_ard_3-2-1_50KNC_2019-06-14_final.stac-item
2019-06-14 12:03:30	ga_s2bm_ard_3-2-1_50KMC_2019-06-14_final.stac-item
2019-06-14 12:03:34	ga_s2bm_ard_3-2-1_50KLC_2019-06-14_final.stac-item
2019-06-14 12:03:40	ga_s2bm_ard_3-2-1_50KNB_2019-06-14_final.stac-item
2019-06-14 12:03:45	ga_s2bm_ard_3-2-1_50KMB_2019-06-14_final.stac-item
2019-06-14 12:03:48	ga_s2bm_ard_3-2-1_50KLB_2019-06-14_final.stac-item
2019-06-14 12:03:51	ga_s2bm_ard_3-2-1_50KNA_2019-06-14_final.stac-item
2019-06-14 12:03:51	ga_s2bm_ard_3-2-1_50KKB_2019-06-14_final.stac-item
2019-06-14 12:03:59	ga_s2bm_ard_3-2-1_50KMA_2019-06-14_final.stac-item
2019-06-14 12:04:03	ga_s2bm_ard_3-2-1_50KLA_2019-06-14_final.stac-item
2019-06-14 12:04:06	ga_s2bm_ard_3-2-1_50KKA_2019-06-14_final.stac-item
2019-06-14 12:04:06	ga_s2bm_ard_3-2-1_49KHR_2019-06-14_final.stac-item
2019-06-14 12:04:14	ga_s2bm_ard_3-2-1_50KMV_2019-06-14_final.stac-item
2019-06-14 12:04:17	ga_s2bm_ard_3-2-1_50KLV_2019-06-14_final.stac-item
2019-06-14 12:04:20	ga_s2bm_ard_3-2-1_50KKV_2019-06-14_final.stac-item
2019-06-14 12:04:21	ga_s2bm_ard_3-2-1_49KHQ_2019-06-14_final.stac-item
2019-06-14 12:04:25	ga_s2bm_ard_3-2-1_49KGQ_2019-06-14_final.stac-item
2019-06-14 12:04:29	ga_s2bm_ard_3-2-1_50KMU_2019-06-14_final.stac-item
2019-06-14 12:04:32	ga_s2bm_ard_3-2-1_50KLU_2019-06-14_final.stac-item
2019-06-14 12:04:35	ga_s2bm_ard_3-2-1_49KHP_2019-06-14_final.stac-item
2019-06-14 12:04:35	ga_s2bm_ard_3-2-1_50KKU_2019-06-14_final.stac-item
2019-06-14 12:04:38	ga_s2bm_ard_3-2-1_49KGP_2019-06-14_final.stac-item
2019-06-14 12:04:43	ga_s2bm_ard_3-2-1_50JMT_2019-06-14_final.stac-item
2019-06-14 12:04:46	ga_s2bm_ard_3-2-1_50JLT_2019-06-14_final.stac-item
2019-06-14 12:04:50	ga_s2bm_ard_3-2-1_49JHN_2019-06-14_final.stac-item
2019-06-14 12:04:50	ga_s2bm_ard_3-2-1_50JKT_2019-06-14_final.stac-item
2019-06-14 12:04:53	ga_s2bm_ard_3-2-1_49JGN_2019-06-14_final.stac-item
2019-06-14 12:04:56	ga_s2bm_ard_3-2-1_50JMS_2019-06-14_final.stac-item
2019-06-14 12:05:01	ga_s2bm_ard_3-2-1_50JLS_2019-06-14_final.stac-item
2019-06-14 12:05:04	ga_s2bm_ard_3-2-1_49JHM_2019-06-14_final.stac-item
2019-06-14 12:05:04	ga_s2bm_ard_3-2-1_50JKS_2019-06-14_final.stac-item
2019-06-14 12:05:06	ga_s2bm_ard_3-2-1_50JMR_2019-06-14_final.stac-item
2019-06-14 12:05:08	ga_s2bm_ard_3-2-1_49JGM_2019-06-14_final.stac-item
2019-06-14 12:05:15	ga_s2bm_ard_3-2-1_50JLR_2019-06-14_final.stac-item
2019-06-14 12:05:19	ga_s2bm_ard_3-2-1_50JKR_2019-06-14_final.stac-item
2019-06-14 12:05:21	ga_s2bm_ard_3-2-1_49JGL_2019-06-14_final.stac-item
2019-06-14 12:05:24	ga_s2bm_ard_3-2-1_50JLQ_2019-06-14_final.stac-item
2019-06-14 12:05:26	ga_s2bm_ard_3-2-1_50JKR_2019-06-14_final.stac-item
2019-06-14 12:05:26	ga_s2bm_ard_3-2-1_50JKQ_2019-06-14_final.stac-item
2019-06-14 12:05:27	ga_s2bm_ard_3-2-1_49JGK_2019-06-14_final.stac-item
2019-06-14 12:05:27	ga_s2bm_ard_3-2-1_49JGL_2019-06-14_final.stac-item
2019-06-14 12:05:31	ga_s2bm_ard_3-2-1_50JLQ_2019-06-14_final.stac-item
2019-06-14 12:05:33	ga_s2bm_ard_3-2-1_50JKQ_2019-06-14_final.stac-item
2019-06-14 12:05:36	ga_s2bm_ard_3-2-1_49JGK_2019-06-14_final.stac-item
2019-06-14 12:05:45	ga_s2bm_ard_3-2-1_50JLP_2019-06-14_final.stac-item
2019-06-14 12:05:48	ga_s2bm_ard_3-2-1_50JKP_2019-06-14_final.stac-item
2019-06-14 12:05:51	ga_s2bm_ard_3-2-1_49JGJ_2019-06-14_final.stac-item
2019-06-14 12:05:59	ga_s2bm_ard_3-2-1_50JLN_2019-06-14_final.stac-item
2019-06-14 12:06:03	ga_s2bm_ard_3-2-1_50JKN_2019-06-14_final.stac-item
2019-06-14 12:06:11	ga_s2bm_ard_3-2-1_50JLM_2019-06-14_final.stac-item
2019-06-14 12:06:17	ga_s2bm_ard_3-2-1_50JKM_2019-06-14_final.stac-item

Return to ga_s2bm_ard_3 on 14th June 2019 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

2019

June

14th