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
2023-05-14 12:05:00	ga_s2bm_ard_3-2-1_49JHM_2023-05-14_final
2023-05-14 12:05:00	ga_s2bm_ard_3-2-1_50JKS_2023-05-14_final
2023-05-14 12:05:02	ga_s2bm_ard_3-2-1_50JMR_2023-05-14_final
2023-05-14 12:05:04	ga_s2bm_ard_3-2-1_49JGM_2023-05-14_final
2023-05-14 12:05:12	ga_s2bm_ard_3-2-1_50JLR_2023-05-14_final
2023-05-14 12:05:12	ga_s2bm_ard_3-2-1_49JFM_2023-05-14_final
2023-05-14 12:05:15	ga_s2bm_ard_3-2-1_50JKR_2023-05-14_final
2023-05-14 12:05:18	ga_s2bm_ard_3-2-1_49JGL_2023-05-14_final
2023-05-14 12:05:23	ga_s2bm_ard_3-2-1_49JFL_2023-05-14_nrt
2023-05-14 12:05:26	ga_s2bm_ard_3-2-1_50JLQ_2023-05-14_final
2023-05-14 12:05:30	ga_s2bm_ard_3-2-1_50JKQ_2023-05-14_final
2023-05-14 12:05:33	ga_s2bm_ard_3-2-1_49JGK_2023-05-14_final
2023-05-14 12:05:36	ga_s2bm_ard_3-2-1_49JFK_2023-05-14_nrt
2023-05-14 12:05:41	ga_s2bm_ard_3-2-1_50JLP_2023-05-14_final
2023-05-14 12:05:44	ga_s2bm_ard_3-2-1_50JKP_2023-05-14_final
2023-05-14 12:05:47	ga_s2bm_ard_3-2-1_49JGJ_2023-05-14_final
2023-05-14 12:05:51	ga_s2bm_ard_3-2-1_49JFJ_2023-05-14_nrt
2023-05-15 11:32:26	ga_s2bm_ard_3-2-1_51KYA_2023-05-15_final
2023-05-15 11:32:50	ga_s2bm_ard_3-2-1_51KVV_2023-05-15_final
2023-05-15 11:33:05	ga_s2bm_ard_3-2-1_51KVU_2023-05-15_final
2023-05-15 11:33:13	ga_s2bm_ard_3-2-1_51KXT_2023-05-15_final
2023-05-15 11:33:20	ga_s2bm_ard_3-2-1_51KVT_2023-05-15_final
2023-05-15 11:33:26	ga_s2bm_ard_3-2-1_51KUT_2023-05-15_final
2023-05-15 11:33:27	ga_s2bm_ard_3-2-1_51KXS_2023-05-15_final
2023-05-15 11:33:31	ga_s2bm_ard_3-2-1_51KWS_2023-05-15_final
2023-05-15 11:33:34	ga_s2bm_ard_3-2-1_51KVS_2023-05-15_final
2023-05-15 11:33:38	ga_s2bm_ard_3-2-1_51KUS_2023-05-15_final
2023-05-15 11:33:42	ga_s2bm_ard_3-2-1_51KXR_2023-05-15_final
2023-05-15 11:33:45	ga_s2bm_ard_3-2-1_51KWR_2023-05-15_final
2023-05-15 11:33:49	ga_s2bm_ard_3-2-1_51KVR_2023-05-15_final
2023-05-15 11:33:52	ga_s2bm_ard_3-2-1_51KUR_2023-05-15_final
2023-05-15 11:33:56	ga_s2bm_ard_3-2-1_51KXQ_2023-05-15_final
2023-05-15 11:34:00	ga_s2bm_ard_3-2-1_51KWQ_2023-05-15_final
2023-05-15 11:34:03	ga_s2bm_ard_3-2-1_51KVQ_2023-05-15_final
2023-05-15 11:34:07	ga_s2bm_ard_3-2-1_51KUQ_2023-05-15_final
2023-05-15 11:34:09	ga_s2bm_ard_3-2-1_51KXP_2023-05-15_final
2023-05-15 11:34:14	ga_s2bm_ard_3-2-1_51KWP_2023-05-15_final
2023-05-15 11:34:18	ga_s2bm_ard_3-2-1_51KVP_2023-05-15_final
2023-05-15 11:34:19	ga_s2bm_ard_3-2-1_51JXN_2023-05-15_final
2023-05-15 11:34:21	ga_s2bm_ard_3-2-1_51KUP_2023-05-15_final
2023-05-15 11:34:29	ga_s2bm_ard_3-2-1_51JWN_2023-05-15_final
2023-05-15 11:34:33	ga_s2bm_ard_3-2-1_51JVN_2023-05-15_final
2023-05-15 11:34:36	ga_s2bm_ard_3-2-1_51JUN_2023-05-15_final
2023-05-15 11:34:40	ga_s2bm_ard_3-2-1_51JTN_2023-05-15_final
2023-05-15 11:34:40	ga_s2bm_ard_3-2-1_50JRT_2023-05-15_final
2023-05-15 11:34:43	ga_s2bm_ard_3-2-1_51JWM_2023-05-15_final
2023-05-15 11:34:47	ga_s2bm_ard_3-2-1_51JVM_2023-05-15_final
2023-05-15 11:34:50	ga_s2bm_ard_3-2-1_51JUM_2023-05-15_final
2023-05-15 11:34:53	ga_s2bm_ard_3-2-1_50JRS_2023-05-15_final
2023-05-15 11:34:53	ga_s2bm_ard_3-2-1_51JTM_2023-05-15_final
2023-05-15 11:34:58	ga_s2bm_ard_3-2-1_51JWL_2023-05-15_final
2023-05-15 11:35:02	ga_s2bm_ard_3-2-1_51JVL_2023-05-15_final
2023-05-15 11:35:05	ga_s2bm_ard_3-2-1_51JUL_2023-05-15_final
2023-05-15 11:35:08	ga_s2bm_ard_3-2-1_51JTL_2023-05-15_final
2023-05-15 11:35:12	ga_s2bm_ard_3-2-1_51JWK_2023-05-15_final
2023-05-15 11:35:16	ga_s2bm_ard_3-2-1_51JVK_2023-05-15_final
2023-05-15 11:35:19	ga_s2bm_ard_3-2-1_51JUK_2023-05-15_final
2023-05-15 11:35:23	ga_s2bm_ard_3-2-1_51JTK_2023-05-15_final
2023-05-15 11:35:23	ga_s2bm_ard_3-2-1_51JWJ_2023-05-15_final
2023-05-15 11:35:30	ga_s2bm_ard_3-2-1_51JVJ_2023-05-15_final
2023-05-15 11:35:34	ga_s2bm_ard_3-2-1_51JUJ_2023-05-15_final
2023-05-15 11:35:37	ga_s2bm_ard_3-2-1_51JTJ_2023-05-15_final
2023-05-15 11:35:41	ga_s2bm_ard_3-2-1_50JQP_2023-05-15_final
2023-05-15 11:35:45	ga_s2bm_ard_3-2-1_51JVH_2023-05-15_final
2023-05-15 11:35:49	ga_s2bm_ard_3-2-1_51JUH_2023-05-15_final
2023-05-15 11:35:52	ga_s2bm_ard_3-2-1_51JTH_2023-05-15_final
2023-05-15 11:35:54	ga_s2bm_ard_3-2-1_50JQN_2023-05-15_final
2023-05-15 11:36:00	ga_s2bm_ard_3-2-1_51JVG_2023-05-15_final
2023-05-15 11:36:03	ga_s2bm_ard_3-2-1_51JUG_2023-05-15_final
2023-05-15 11:36:06	ga_s2bm_ard_3-2-1_51JTG_2023-05-15_final
2023-05-15 11:36:09	ga_s2bm_ard_3-2-1_50JQM_2023-05-15_final
2023-05-15 11:36:14	ga_s2bm_ard_3-2-1_51JVF_2023-05-15_final
2023-05-15 11:36:18	ga_s2bm_ard_3-2-1_51JUF_2023-05-15_final
2023-05-15 11:36:21	ga_s2bm_ard_3-2-1_51JTF_2023-05-15_final
2023-05-15 11:36:23	ga_s2bm_ard_3-2-1_50JQL_2023-05-15_final
2023-05-15 11:36:27	ga_s2bm_ard_3-2-1_51HVE_2023-05-15_final
2023-05-15 11:36:30	ga_s2bm_ard_3-2-1_50JPL_2023-05-15_final
2023-05-15 11:36:32	ga_s2bm_ard_3-2-1_51HUE_2023-05-15_final
2023-05-15 11:36:35	ga_s2bm_ard_3-2-1_51HTE_2023-05-15_final
2023-05-15 11:36:37	ga_s2bm_ard_3-2-1_51HVD_2023-05-15_final
2023-05-15 11:36:38	ga_s2bm_ard_3-2-1_50HQK_2023-05-15_final
2023-05-15 11:36:42	ga_s2bm_ard_3-2-1_50HPK_2023-05-15_final
2023-05-15 11:36:47	ga_s2bm_ard_3-2-1_51HUD_2023-05-15_final
2023-05-15 11:36:50	ga_s2bm_ard_3-2-1_51HTD_2023-05-15_final
2023-05-15 11:36:52	ga_s2bm_ard_3-2-1_50HQJ_2023-05-15_final
2023-05-15 11:36:56	ga_s2bm_ard_3-2-1_50HPJ_2023-05-15_final
2023-05-15 11:37:01	ga_s2bm_ard_3-2-1_51HUC_2023-05-15_final
2023-05-15 11:37:05	ga_s2bm_ard_3-2-1_51HTC_2023-05-15_final
2023-05-15 11:37:07	ga_s2bm_ard_3-2-1_50HQH_2023-05-15_final
2023-05-15 11:37:10	ga_s2bm_ard_3-2-1_50HPH_2023-05-15_final
2023-05-15 11:37:16	ga_s2bm_ard_3-2-1_51HUB_2023-05-15_final
2023-05-15 11:37:19	ga_s2bm_ard_3-2-1_51HTB_2023-05-15_final
2023-05-15 11:37:21	ga_s2bm_ard_3-2-1_50HQG_2023-05-15_final
2023-05-15 11:37:25	ga_s2bm_ard_3-2-1_50HPG_2023-05-15_final
2023-05-15 11:37:29	ga_s2bm_ard_3-2-1_51HUA_2023-05-15_nrt
2023-05-15 11:37:30	ga_s2bm_ard_3-2-1_50HNG_2023-05-15_final
2023-05-15 11:37:32	ga_s2bm_ard_3-2-1_51HTA_2023-05-15_nrt
2023-05-15 11:37:33	ga_s2bm_ard_3-2-1_50HQF_2023-05-15_nrt
2023-05-15 11:37:35	ga_s2bm_ard_3-2-1_50HPF_2023-05-15_nrt
2023-05-15 11:37:36	ga_s2bm_ard_3-2-1_50HNF_2023-05-15_nrt

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