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
2023-08-10 11:22:43	ga_s2bm_ard_3-2-1_51KZV_2023-08-10_final
2023-08-10 11:22:58	ga_s2bm_ard_3-2-1_51KZU_2023-08-10_final
2023-08-10 11:23:30	ga_s2bm_ard_3-2-1_51KYS_2023-08-10_final
2023-08-10 11:23:33	ga_s2bm_ard_3-2-1_51KXS_2023-08-10_final
2023-08-10 11:23:45	ga_s2bm_ard_3-2-1_51KYR_2023-08-10_final
2023-08-10 11:23:48	ga_s2bm_ard_3-2-1_51KXR_2023-08-10_final
2023-08-10 11:23:59	ga_s2bm_ard_3-2-1_51KYQ_2023-08-10_final
2023-08-10 11:24:10	ga_s2bm_ard_3-2-1_51KZP_2023-08-10_final
2023-08-10 11:24:57	ga_s2bm_ard_3-2-1_51JYL_2023-08-10_final
2023-08-10 11:25:11	ga_s2bm_ard_3-2-1_51JYK_2023-08-10_final
2023-08-10 11:25:18	ga_s2bm_ard_3-2-1_51JWK_2023-08-10_final
2023-08-10 11:25:33	ga_s2bm_ard_3-2-1_51JWJ_2023-08-10_final
2023-08-10 11:25:36	ga_s2bm_ard_3-2-1_51JVJ_2023-08-10_final
2023-08-10 11:25:44	ga_s2bm_ard_3-2-1_51JXH_2023-08-10_final
2023-08-10 11:25:50	ga_s2bm_ard_3-2-1_51JYG_2023-08-10_final
2023-08-10 11:25:51	ga_s2bm_ard_3-2-1_51JVH_2023-08-10_final
2023-08-10 11:25:58	ga_s2bm_ard_3-2-1_51JXG_2023-08-10_final
2023-08-10 11:26:31	ga_s2bm_ard_3-2-1_51HWE_2023-08-10_final
2023-08-10 11:26:49	ga_s2bm_ard_3-2-1_51HVD_2023-08-10_final
2023-08-10 11:27:04	ga_s2bm_ard_3-2-1_51HVC_2023-08-10_final
2023-08-10 11:27:18	ga_s2bm_ard_3-2-1_51HUB_2023-08-10_final
2023-08-12 12:03:32	ga_s2bm_ard_3-2-1_50KLC_2023-08-12_final
2023-08-12 12:03:39	ga_s2bm_ard_3-2-1_50KNB_2023-08-12_final
2023-08-12 12:03:47	ga_s2bm_ard_3-2-1_50KLB_2023-08-12_final
2023-08-12 12:03:50	ga_s2bm_ard_3-2-1_50KNA_2023-08-12_final
2023-08-12 12:03:50	ga_s2bm_ard_3-2-1_50KKB_2023-08-12_final
2023-08-12 12:03:58	ga_s2bm_ard_3-2-1_50KMA_2023-08-12_final
2023-08-12 12:04:01	ga_s2bm_ard_3-2-1_50KLA_2023-08-12_final
2023-08-12 12:04:19	ga_s2bm_ard_3-2-1_49KHQ_2023-08-12_final
2023-08-12 12:04:41	ga_s2bm_ard_3-2-1_50JMT_2023-08-12_final
2023-08-12 12:04:45	ga_s2bm_ard_3-2-1_50JLT_2023-08-12_final
2023-08-12 12:04:47	ga_s2bm_ard_3-2-1_49JHN_2023-08-12_final
2023-08-12 12:04:48	ga_s2bm_ard_3-2-1_50JKT_2023-08-12_final
2023-08-12 12:04:49	ga_s2bm_ard_3-2-1_49JGN_2023-08-12_final
2023-08-12 12:04:53	ga_s2bm_ard_3-2-1_50JLT_2023-08-12_final
2023-08-12 12:04:53	ga_s2bm_ard_3-2-1_50JLS_2023-08-12_final
2023-08-12 12:04:54	ga_s2bm_ard_3-2-1_50JKT_2023-08-12_final
2023-08-12 12:04:54	ga_s2bm_ard_3-2-1_49JHN_2023-08-12_final
2023-08-12 12:04:54	ga_s2bm_ard_3-2-1_49JHM_2023-08-12_final
2023-08-12 12:04:54	ga_s2bm_ard_3-2-1_50JKS_2023-08-12_final
2023-08-12 12:04:56	ga_s2bm_ard_3-2-1_49JGN_2023-08-12_final
2023-08-12 12:05:00	ga_s2bm_ard_3-2-1_50JLS_2023-08-12_final
2023-08-12 12:05:02	ga_s2bm_ard_3-2-1_49JHM_2023-08-12_final
2023-08-12 12:05:03	ga_s2bm_ard_3-2-1_50JKS_2023-08-12_final
2023-08-12 12:05:04	ga_s2bm_ard_3-2-1_50JMR_2023-08-12_final
2023-08-12 12:05:06	ga_s2bm_ard_3-2-1_49JGM_2023-08-12_final
2023-08-12 12:05:14	ga_s2bm_ard_3-2-1_50JLR_2023-08-12_final
2023-08-12 12:05:17	ga_s2bm_ard_3-2-1_50JKR_2023-08-12_final
2023-08-12 12:05:32	ga_s2bm_ard_3-2-1_50JKQ_2023-08-12_final
2023-08-12 12:05:46	ga_s2bm_ard_3-2-1_50JKP_2023-08-12_final
2023-08-12 12:05:49	ga_s2bm_ard_3-2-1_49JGJ_2023-08-12_final
2023-08-12 12:05:57	ga_s2bm_ard_3-2-1_50JLN_2023-08-12_final
2023-08-12 12:06:01	ga_s2bm_ard_3-2-1_50JKN_2023-08-12_final
2023-08-12 12:06:04	ga_s2bm_ard_3-2-1_49JGH_2023-08-12_final
2023-08-12 12:06:10	ga_s2bm_ard_3-2-1_50JLM_2023-08-12_final
2023-08-12 12:06:19	ga_s2bm_ard_3-2-1_50JLL_2023-08-12_final
2023-08-13 11:31:48	ga_s2bm_ard_3-2-1_51LXD_2023-08-13_final
2023-08-13 11:32:02	ga_s2bm_ard_3-2-1_51LXC_2023-08-13_final
2023-08-13 11:32:05	ga_s2bm_ard_3-2-1_51KZB_2023-08-13_final
2023-08-13 11:32:17	ga_s2bm_ard_3-2-1_51KXB_2023-08-13_final
2023-08-13 11:32:20	ga_s2bm_ard_3-2-1_51KWB_2023-08-13_final
2023-08-13 11:32:31	ga_s2bm_ard_3-2-1_51KXA_2023-08-13_final
2023-08-13 11:32:34	ga_s2bm_ard_3-2-1_51KWA_2023-08-13_final
2023-08-13 11:32:49	ga_s2bm_ard_3-2-1_51KWV_2023-08-13_final
2023-08-13 11:33:28	ga_s2bm_ard_3-2-1_51KUT_2023-08-13_final
2023-08-13 11:33:40	ga_s2bm_ard_3-2-1_51KUS_2023-08-13_final
2023-08-13 11:33:44	ga_s2bm_ard_3-2-1_51KXR_2023-08-13_final
2023-08-13 11:33:51	ga_s2bm_ard_3-2-1_51KVR_2023-08-13_final
2023-08-13 11:34:05	ga_s2bm_ard_3-2-1_51KVQ_2023-08-13_final
2023-08-13 11:34:55	ga_s2bm_ard_3-2-1_51JTM_2023-08-13_final
2023-08-13 11:35:07	ga_s2bm_ard_3-2-1_51JUL_2023-08-13_final
2023-08-13 11:35:10	ga_s2bm_ard_3-2-1_51JTL_2023-08-13_final
2023-08-13 11:35:13	ga_s2bm_ard_3-2-1_51JWK_2023-08-13_final
2023-08-13 11:35:21	ga_s2bm_ard_3-2-1_51JUK_2023-08-13_final
2023-08-13 11:35:25	ga_s2bm_ard_3-2-1_51JWJ_2023-08-13_final
2023-08-13 11:35:32	ga_s2bm_ard_3-2-1_51JVJ_2023-08-13_final
2023-08-13 11:35:36	ga_s2bm_ard_3-2-1_51JUJ_2023-08-13_final
2023-08-13 11:35:43	ga_s2bm_ard_3-2-1_50JQP_2023-08-13_final
2023-08-13 11:35:47	ga_s2bm_ard_3-2-1_51JVH_2023-08-13_final
2023-08-13 11:36:31	ga_s2bm_ard_3-2-1_51JTF_2023-08-13_final
2023-08-13 11:36:31	ga_s2bm_ard_3-2-1_51HTE_2023-08-13_final
2023-08-13 11:36:32	ga_s2bm_ard_3-2-1_50JQL_2023-08-13_final
2023-08-13 11:36:38	ga_s2bm_ard_3-2-1_51HTE_2023-08-13_final
2023-08-13 11:36:39	ga_s2bm_ard_3-2-1_51HVD_2023-08-13_final
2023-08-13 11:36:43	ga_s2bm_ard_3-2-1_50HPK_2023-08-13_final
2023-08-13 11:36:52	ga_s2bm_ard_3-2-1_51HTD_2023-08-13_final
2023-08-13 11:36:54	ga_s2bm_ard_3-2-1_50HQJ_2023-08-13_final
2023-08-13 11:36:57	ga_s2bm_ard_3-2-1_50HPJ_2023-08-13_final
2023-08-13 11:37:18	ga_s2bm_ard_3-2-1_51HUB_2023-08-13_final
2023-08-13 11:37:27	ga_s2bm_ard_3-2-1_50HPG_2023-08-13_final
2023-08-13 11:37:32	ga_s2bm_ard_3-2-1_50HNG_2023-08-13_final
2023-08-14 11:04:41	ga_s2bm_ard_3-2-1_52JDS_2023-08-14_final
2023-08-14 11:05:57	ga_s2bm_ard_3-2-1_52JCM_2023-08-14_final
2023-08-14 11:06:09	ga_s2bm_ard_3-2-1_52JDL_2023-08-14_final
2023-08-14 11:06:29	ga_s2bm_ard_3-2-1_52HBK_2023-08-14_final
2023-08-15 12:14:04	ga_s2bm_ard_3-2-1_49KGR_2023-08-15_final
2023-08-15 12:14:14	ga_s2bm_ard_3-2-1_49KHQ_2023-08-15_final
2023-08-15 12:14:26	ga_s2bm_ard_3-2-1_49KHP_2023-08-15_final
2023-08-15 12:14:36	ga_s2bm_ard_3-2-1_49JHN_2023-08-15_final
2023-08-15 12:15:02	ga_s2bm_ard_3-2-1_49JGM_2023-08-15_final

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