Search ga_s2am_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
2018-11-11 12:04:08	ga_s2am_ard_3-2-1_49KHQ_2018-11-11_final.stac-item
2018-11-11 12:04:13	ga_s2am_ard_3-2-1_49KGQ_2018-11-11_final.stac-item
2018-11-11 12:04:16	ga_s2am_ard_3-2-1_50KMU_2018-11-11_final.stac-item
2018-11-11 12:04:20	ga_s2am_ard_3-2-1_50KLU_2018-11-11_final.stac-item
2018-11-11 12:04:23	ga_s2am_ard_3-2-1_49KHP_2018-11-11_final.stac-item
2018-11-11 12:04:23	ga_s2am_ard_3-2-1_50KKU_2018-11-11_final.stac-item
2018-11-11 12:04:26	ga_s2am_ard_3-2-1_49KGP_2018-11-11_final.stac-item
2018-11-11 12:04:31	ga_s2am_ard_3-2-1_50JMT_2018-11-11_final.stac-item
2018-11-11 12:04:34	ga_s2am_ard_3-2-1_50JLT_2018-11-11_final.stac-item
2018-11-11 12:04:37	ga_s2am_ard_3-2-1_49JHN_2018-11-11_final.stac-item
2018-11-11 12:04:37	ga_s2am_ard_3-2-1_50JKT_2018-11-11_final.stac-item
2018-11-11 12:04:41	ga_s2am_ard_3-2-1_49JGN_2018-11-11_final.stac-item
2018-11-11 12:04:44	ga_s2am_ard_3-2-1_50JMS_2018-11-11_final.stac-item
2018-11-11 12:04:49	ga_s2am_ard_3-2-1_50JLS_2018-11-11_final.stac-item
2018-11-11 12:04:52	ga_s2am_ard_3-2-1_49JHM_2018-11-11_final.stac-item
2018-11-11 12:04:52	ga_s2am_ard_3-2-1_50JKS_2018-11-11_final.stac-item
2018-11-11 12:04:54	ga_s2am_ard_3-2-1_50JMR_2018-11-11_final.stac-item
2018-11-11 12:04:55	ga_s2am_ard_3-2-1_49JGM_2018-11-11_final.stac-item
2018-11-11 12:05:03	ga_s2am_ard_3-2-1_50JLR_2018-11-11_final.stac-item
2018-11-11 12:05:07	ga_s2am_ard_3-2-1_50JKR_2018-11-11_final.stac-item
2018-11-11 12:05:10	ga_s2am_ard_3-2-1_49JGL_2018-11-11_final.stac-item
2018-11-11 12:05:18	ga_s2am_ard_3-2-1_50JLQ_2018-11-11_final.stac-item
2018-11-11 12:05:21	ga_s2am_ard_3-2-1_50JKQ_2018-11-11_final.stac-item
2018-11-11 12:05:24	ga_s2am_ard_3-2-1_49JGK_2018-11-11_final.stac-item
2018-11-11 12:05:33	ga_s2am_ard_3-2-1_50JLP_2018-11-11_final.stac-item
2018-11-11 12:05:36	ga_s2am_ard_3-2-1_50JKP_2018-11-11_final.stac-item
2018-11-11 12:05:39	ga_s2am_ard_3-2-1_49JGJ_2018-11-11_final.stac-item
2018-11-11 12:05:46	ga_s2am_ard_3-2-1_50JLN_2018-11-11_final.stac-item
2018-11-11 12:05:50	ga_s2am_ard_3-2-1_50JKN_2018-11-11_final.stac-item
2018-11-11 12:05:59	ga_s2am_ard_3-2-1_50JLM_2018-11-11_final.stac-item
2018-11-11 12:06:05	ga_s2am_ard_3-2-1_50JKM_2018-11-11_final.stac-item
2018-11-11 12:06:09	ga_s2am_ard_3-2-1_50JLL_2018-11-11_final.stac-item
2018-11-12 09:51:35	ga_s2am_ard_3-2-1_56KKF_2018-11-12_final.stac-item
2018-11-12 09:53:46	ga_s2am_ard_3-2-1_55JDN_2018-11-12_final.stac-item
2018-11-12 09:53:53	ga_s2am_ard_3-2-1_55JCN_2018-11-12_final.stac-item
2018-11-12 09:54:00	ga_s2am_ard_3-2-1_55JDM_2018-11-12_final.stac-item
2018-11-12 09:54:04	ga_s2am_ard_3-2-1_55JCM_2018-11-12_final.stac-item
2018-11-12 09:54:15	ga_s2am_ard_3-2-1_55JDL_2018-11-12_final.stac-item
2018-11-12 09:54:18	ga_s2am_ard_3-2-1_55JCL_2018-11-12_final.stac-item
2018-11-12 09:54:26	ga_s2am_ard_3-2-1_55JEK_2018-11-12_final.stac-item
2018-11-12 09:54:29	ga_s2am_ard_3-2-1_55JDK_2018-11-12_final.stac-item
2018-11-12 09:54:32	ga_s2am_ard_3-2-1_55JCK_2018-11-12_final.stac-item
2018-11-12 09:54:40	ga_s2am_ard_3-2-1_55JEJ_2018-11-12_final.stac-item
2018-11-12 09:54:44	ga_s2am_ard_3-2-1_55JDJ_2018-11-12_final.stac-item
2018-11-12 09:54:47	ga_s2am_ard_3-2-1_55JCJ_2018-11-12_final.stac-item
2018-11-12 09:54:54	ga_s2am_ard_3-2-1_55JEH_2018-11-12_final.stac-item
2018-11-12 09:54:58	ga_s2am_ard_3-2-1_55JDH_2018-11-12_final.stac-item
2018-11-12 09:55:02	ga_s2am_ard_3-2-1_55JCH_2018-11-12_final.stac-item
2018-11-12 09:55:06	ga_s2am_ard_3-2-1_55JBH_2018-11-12_final.stac-item
2018-11-12 09:55:09	ga_s2am_ard_3-2-1_55JEG_2018-11-12_final.stac-item
2018-11-12 09:55:13	ga_s2am_ard_3-2-1_55JDG_2018-11-12_final.stac-item
2018-11-12 09:55:16	ga_s2am_ard_3-2-1_55JCG_2018-11-12_final.stac-item
2018-11-12 11:34:10	ga_s2am_ard_3-2-1_51JXN_2018-11-12_final.stac-item
2018-11-12 11:34:12	ga_s2am_ard_3-2-1_51KUP_2018-11-12_final.stac-item
2018-11-12 11:34:17	ga_s2am_ard_3-2-1_51JWN_2018-11-12_final.stac-item
2018-11-12 11:34:19	ga_s2am_ard_3-2-1_51JVN_2018-11-12_final.stac-item
2018-11-12 11:34:20	ga_s2am_ard_3-2-1_51KUP_2018-11-12_final.stac-item
2018-11-12 11:34:20	ga_s2am_ard_3-2-1_51JUN_2018-11-12_final.stac-item
2018-11-12 11:34:22	ga_s2am_ard_3-2-1_51JTN_2018-11-12_final.stac-item
2018-11-12 11:34:23	ga_s2am_ard_3-2-1_51JWN_2018-11-12_final.stac-item
2018-11-12 11:34:25	ga_s2am_ard_3-2-1_51JVN_2018-11-12_final.stac-item
2018-11-12 11:34:27	ga_s2am_ard_3-2-1_51JUN_2018-11-12_final.stac-item
2018-11-12 11:34:31	ga_s2am_ard_3-2-1_51JTN_2018-11-12_final.stac-item
2018-11-12 11:34:32	ga_s2am_ard_3-2-1_50JRT_2018-11-12_final.stac-item
2018-11-12 11:34:34	ga_s2am_ard_3-2-1_51JWM_2018-11-12_final.stac-item
2018-11-12 11:34:38	ga_s2am_ard_3-2-1_51JVM_2018-11-12_final.stac-item
2018-11-12 11:34:41	ga_s2am_ard_3-2-1_51JUM_2018-11-12_final.stac-item
2018-11-12 11:34:44	ga_s2am_ard_3-2-1_50JRS_2018-11-12_final.stac-item
2018-11-12 11:34:44	ga_s2am_ard_3-2-1_51JTM_2018-11-12_final.stac-item
2018-11-12 11:34:49	ga_s2am_ard_3-2-1_51JWL_2018-11-12_final.stac-item
2018-11-12 11:34:53	ga_s2am_ard_3-2-1_51JVL_2018-11-12_final.stac-item
2018-11-12 11:34:56	ga_s2am_ard_3-2-1_51JUL_2018-11-12_final.stac-item
2018-11-12 11:34:59	ga_s2am_ard_3-2-1_51JTL_2018-11-12_final.stac-item
2018-11-12 11:35:03	ga_s2am_ard_3-2-1_51JWK_2018-11-12_final.stac-item
2018-11-12 11:35:07	ga_s2am_ard_3-2-1_51JVK_2018-11-12_final.stac-item
2018-11-12 11:35:10	ga_s2am_ard_3-2-1_51JUK_2018-11-12_final.stac-item
2018-11-12 11:35:14	ga_s2am_ard_3-2-1_51JTK_2018-11-12_final.stac-item
2018-11-12 11:35:14	ga_s2am_ard_3-2-1_51JWJ_2018-11-12_final.stac-item
2018-11-12 11:35:21	ga_s2am_ard_3-2-1_51JVJ_2018-11-12_final.stac-item
2018-11-12 11:35:25	ga_s2am_ard_3-2-1_51JUJ_2018-11-12_final.stac-item
2018-11-12 11:35:28	ga_s2am_ard_3-2-1_51JTJ_2018-11-12_final.stac-item
2018-11-12 11:35:32	ga_s2am_ard_3-2-1_50JQP_2018-11-12_final.stac-item
2018-11-12 11:35:36	ga_s2am_ard_3-2-1_51JVH_2018-11-12_final.stac-item
2018-11-12 11:35:40	ga_s2am_ard_3-2-1_51JUH_2018-11-12_final.stac-item
2018-11-12 11:35:43	ga_s2am_ard_3-2-1_51JTH_2018-11-12_final.stac-item
2018-11-12 11:35:45	ga_s2am_ard_3-2-1_50JQN_2018-11-12_final.stac-item
2018-11-12 11:35:51	ga_s2am_ard_3-2-1_51JVG_2018-11-12_final.stac-item
2018-11-12 11:35:54	ga_s2am_ard_3-2-1_51JUG_2018-11-12_final.stac-item
2018-11-12 11:35:57	ga_s2am_ard_3-2-1_51JTG_2018-11-12_final.stac-item
2018-11-12 11:36:00	ga_s2am_ard_3-2-1_50JQM_2018-11-12_final.stac-item
2018-11-12 11:36:05	ga_s2am_ard_3-2-1_51JVF_2018-11-12_final.stac-item
2018-11-12 11:36:09	ga_s2am_ard_3-2-1_51JUF_2018-11-12_final.stac-item
2018-11-12 11:36:12	ga_s2am_ard_3-2-1_51JTF_2018-11-12_final.stac-item
2018-11-12 11:36:14	ga_s2am_ard_3-2-1_50JQL_2018-11-12_final.stac-item
2018-11-12 11:36:18	ga_s2am_ard_3-2-1_51HVE_2018-11-12_final.stac-item
2018-11-12 11:36:21	ga_s2am_ard_3-2-1_50JPL_2018-11-12_final.stac-item
2018-11-12 11:36:23	ga_s2am_ard_3-2-1_51HUE_2018-11-12_final.stac-item
2018-11-12 11:36:26	ga_s2am_ard_3-2-1_51HTE_2018-11-12_final.stac-item
2018-11-12 11:36:28	ga_s2am_ard_3-2-1_51HVD_2018-11-12_final.stac-item
2018-11-12 11:36:29	ga_s2am_ard_3-2-1_50HQK_2018-11-12_final.stac-item

Return to ga_s2am_ard_3 whole collection overview

ga_s2am_ard_3: Geoscience Australia Sentinel 2A MSI Analysis Ready Data Collection 3

Baseline satellite data

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

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