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
2019-06-29 12:05:19	ga_s2am_ard_3-2-1_49JGL_2019-06-29_final.stac-item
2019-06-29 12:05:27	ga_s2am_ard_3-2-1_50JLQ_2019-06-29_final.stac-item
2019-06-29 12:05:31	ga_s2am_ard_3-2-1_50JKQ_2019-06-29_final.stac-item
2019-06-29 12:05:34	ga_s2am_ard_3-2-1_49JGK_2019-06-29_final.stac-item
2019-06-29 12:05:42	ga_s2am_ard_3-2-1_50JLP_2019-06-29_final.stac-item
2019-06-29 12:05:45	ga_s2am_ard_3-2-1_50JKP_2019-06-29_final.stac-item
2019-06-29 12:05:47	ga_s2am_ard_3-2-1_49JGJ_2019-06-29_final.stac-item
2019-06-29 12:05:51	ga_s2am_ard_3-2-1_50JLN_2019-06-29_final.stac-item
2019-06-29 12:05:53	ga_s2am_ard_3-2-1_50JKP_2019-06-29_final.stac-item
2019-06-29 12:05:53	ga_s2am_ard_3-2-1_50JKN_2019-06-29_final.stac-item
2019-06-29 12:05:54	ga_s2am_ard_3-2-1_49JGJ_2019-06-29_final.stac-item
2019-06-29 12:05:57	ga_s2am_ard_3-2-1_50JLN_2019-06-29_final.stac-item
2019-06-29 12:06:00	ga_s2am_ard_3-2-1_50JKN_2019-06-29_final.stac-item
2019-06-29 12:06:09	ga_s2am_ard_3-2-1_50JLM_2019-06-29_final.stac-item
2019-06-29 12:06:14	ga_s2am_ard_3-2-1_50JKM_2019-06-29_final.stac-item
2019-06-29 12:06:19	ga_s2am_ard_3-2-1_50JLL_2019-06-29_final.stac-item
2019-06-30 09:51:44	ga_s2am_ard_3-2-1_56KKF_2019-06-30_final.stac-item
2019-06-30 09:53:52	ga_s2am_ard_3-2-1_55JEN_2019-06-30_final.stac-item
2019-06-30 09:53:55	ga_s2am_ard_3-2-1_55JDN_2019-06-30_final.stac-item
2019-06-30 09:54:02	ga_s2am_ard_3-2-1_55JCN_2019-06-30_final.stac-item
2019-06-30 09:54:07	ga_s2am_ard_3-2-1_55JEM_2019-06-30_final.stac-item
2019-06-30 09:54:10	ga_s2am_ard_3-2-1_55JDM_2019-06-30_final.stac-item
2019-06-30 09:54:14	ga_s2am_ard_3-2-1_55JCM_2019-06-30_final.stac-item
2019-06-30 09:54:21	ga_s2am_ard_3-2-1_55JEL_2019-06-30_final.stac-item
2019-06-30 09:54:24	ga_s2am_ard_3-2-1_55JDL_2019-06-30_final.stac-item
2019-06-30 09:54:27	ga_s2am_ard_3-2-1_55JCL_2019-06-30_final.stac-item
2019-06-30 09:54:36	ga_s2am_ard_3-2-1_55JEK_2019-06-30_final.stac-item
2019-06-30 09:54:39	ga_s2am_ard_3-2-1_55JDK_2019-06-30_final.stac-item
2019-06-30 09:54:42	ga_s2am_ard_3-2-1_55JCK_2019-06-30_final.stac-item
2019-06-30 09:54:50	ga_s2am_ard_3-2-1_55JEJ_2019-06-30_final.stac-item
2019-06-30 09:54:53	ga_s2am_ard_3-2-1_55JDJ_2019-06-30_final.stac-item
2019-06-30 09:54:55	ga_s2am_ard_3-2-1_55JFH_2019-06-30_final.stac-item
2019-06-30 09:54:57	ga_s2am_ard_3-2-1_55JCJ_2019-06-30_final.stac-item
2019-06-30 09:55:04	ga_s2am_ard_3-2-1_55JEH_2019-06-30_final.stac-item
2019-06-30 09:55:08	ga_s2am_ard_3-2-1_55JDH_2019-06-30_final.stac-item
2019-06-30 09:55:11	ga_s2am_ard_3-2-1_55JCH_2019-06-30_final.stac-item
2019-06-30 09:55:16	ga_s2am_ard_3-2-1_55JBH_2019-06-30_final.stac-item
2019-06-30 09:55:19	ga_s2am_ard_3-2-1_55JEG_2019-06-30_final.stac-item
2019-06-30 09:55:23	ga_s2am_ard_3-2-1_55JDG_2019-06-30_final.stac-item
2019-06-30 09:55:26	ga_s2am_ard_3-2-1_55JCG_2019-06-30_final.stac-item
2019-06-30 09:55:29	ga_s2am_ard_3-2-1_55JBG_2019-06-30_final.stac-item
2019-06-30 09:55:34	ga_s2am_ard_3-2-1_55JEF_2019-06-30_final.stac-item
2019-06-30 09:55:37	ga_s2am_ard_3-2-1_55JDF_2019-06-30_final.stac-item
2019-06-30 09:55:41	ga_s2am_ard_3-2-1_55JCF_2019-06-30_final.stac-item
2019-06-30 09:55:43	ga_s2am_ard_3-2-1_55JBF_2019-06-30_final.stac-item
2019-06-30 09:55:47	ga_s2am_ard_3-2-1_55HEE_2019-06-30_final.stac-item
2019-06-30 09:55:52	ga_s2am_ard_3-2-1_55HDE_2019-06-30_final.stac-item
2019-06-30 09:55:55	ga_s2am_ard_3-2-1_55HCE_2019-06-30_final.stac-item
2019-06-30 09:55:58	ga_s2am_ard_3-2-1_55HBE_2019-06-30_final.stac-item
2019-06-30 11:34:20	ga_s2am_ard_3-2-1_51JXN_2019-06-30_final.stac-item
2019-06-30 11:34:22	ga_s2am_ard_3-2-1_51KUP_2019-06-30_final.stac-item
2019-06-30 11:34:30	ga_s2am_ard_3-2-1_51JWN_2019-06-30_final.stac-item
2019-06-30 11:34:33	ga_s2am_ard_3-2-1_51JVN_2019-06-30_final.stac-item
2019-06-30 11:34:37	ga_s2am_ard_3-2-1_51JUN_2019-06-30_final.stac-item
2019-06-30 11:34:41	ga_s2am_ard_3-2-1_51JTN_2019-06-30_final.stac-item
2019-06-30 11:34:41	ga_s2am_ard_3-2-1_50JRT_2019-06-30_final.stac-item
2019-06-30 11:34:44	ga_s2am_ard_3-2-1_51JWM_2019-06-30_final.stac-item
2019-06-30 11:34:48	ga_s2am_ard_3-2-1_51JVM_2019-06-30_final.stac-item
2019-06-30 11:34:51	ga_s2am_ard_3-2-1_51JUM_2019-06-30_final.stac-item
2019-06-30 11:34:54	ga_s2am_ard_3-2-1_50JRS_2019-06-30_final.stac-item
2019-06-30 11:34:54	ga_s2am_ard_3-2-1_51JTM_2019-06-30_final.stac-item
2019-06-30 11:34:59	ga_s2am_ard_3-2-1_51JWL_2019-06-30_final.stac-item
2019-06-30 11:35:02	ga_s2am_ard_3-2-1_51JVL_2019-06-30_final.stac-item
2019-06-30 11:35:06	ga_s2am_ard_3-2-1_51JUL_2019-06-30_final.stac-item
2019-06-30 11:35:09	ga_s2am_ard_3-2-1_51JTL_2019-06-30_final.stac-item
2019-06-30 11:35:13	ga_s2am_ard_3-2-1_51JWK_2019-06-30_final.stac-item
2019-06-30 11:35:17	ga_s2am_ard_3-2-1_51JVK_2019-06-30_final.stac-item
2019-06-30 11:35:20	ga_s2am_ard_3-2-1_51JUK_2019-06-30_final.stac-item
2019-06-30 11:35:23	ga_s2am_ard_3-2-1_51JTK_2019-06-30_final.stac-item
2019-06-30 11:35:24	ga_s2am_ard_3-2-1_51JWJ_2019-06-30_final.stac-item
2019-06-30 11:35:31	ga_s2am_ard_3-2-1_51JVJ_2019-06-30_final.stac-item
2019-06-30 11:35:35	ga_s2am_ard_3-2-1_51JUJ_2019-06-30_final.stac-item
2019-06-30 11:35:38	ga_s2am_ard_3-2-1_51JTJ_2019-06-30_final.stac-item
2019-06-30 11:35:42	ga_s2am_ard_3-2-1_50JQP_2019-06-30_final.stac-item
2019-06-30 11:35:46	ga_s2am_ard_3-2-1_51JVH_2019-06-30_final.stac-item
2019-06-30 11:35:49	ga_s2am_ard_3-2-1_51JUH_2019-06-30_final.stac-item
2019-06-30 11:35:52	ga_s2am_ard_3-2-1_51JTH_2019-06-30_final.stac-item
2019-06-30 11:35:55	ga_s2am_ard_3-2-1_50JQN_2019-06-30_final.stac-item
2019-06-30 11:36:01	ga_s2am_ard_3-2-1_51JVG_2019-06-30_final.stac-item
2019-06-30 11:36:04	ga_s2am_ard_3-2-1_51JUG_2019-06-30_final.stac-item
2019-06-30 11:36:07	ga_s2am_ard_3-2-1_51JTG_2019-06-30_final.stac-item
2019-06-30 11:36:10	ga_s2am_ard_3-2-1_50JQM_2019-06-30_final.stac-item
2019-06-30 11:36:15	ga_s2am_ard_3-2-1_51JVF_2019-06-30_final.stac-item
2019-06-30 11:36:19	ga_s2am_ard_3-2-1_51JUF_2019-06-30_final.stac-item
2019-06-30 11:36:22	ga_s2am_ard_3-2-1_51JTF_2019-06-30_final.stac-item
2019-06-30 11:36:24	ga_s2am_ard_3-2-1_50JQL_2019-06-30_final.stac-item
2019-06-30 11:36:28	ga_s2am_ard_3-2-1_51HVE_2019-06-30_final.stac-item
2019-06-30 11:36:31	ga_s2am_ard_3-2-1_50JPL_2019-06-30_final.stac-item
2019-06-30 11:36:33	ga_s2am_ard_3-2-1_51HUE_2019-06-30_final.stac-item
2019-06-30 11:36:36	ga_s2am_ard_3-2-1_51HTE_2019-06-30_final.stac-item
2019-06-30 11:36:38	ga_s2am_ard_3-2-1_51HVD_2019-06-30_final.stac-item
2019-06-30 11:36:39	ga_s2am_ard_3-2-1_50HQK_2019-06-30_final.stac-item
2019-06-30 11:36:42	ga_s2am_ard_3-2-1_50HPK_2019-06-30_final.stac-item
2019-06-30 11:36:47	ga_s2am_ard_3-2-1_51HUD_2019-06-30_final.stac-item
2019-06-30 11:36:51	ga_s2am_ard_3-2-1_51HTD_2019-06-30_final.stac-item
2019-06-30 11:36:53	ga_s2am_ard_3-2-1_50HQJ_2019-06-30_final.stac-item
2019-06-30 11:36:57	ga_s2am_ard_3-2-1_50HPJ_2019-06-30_final.stac-item
2019-06-30 11:37:02	ga_s2am_ard_3-2-1_51HUC_2019-06-30_final.stac-item
2019-06-30 11:37:05	ga_s2am_ard_3-2-1_51HTC_2019-06-30_final.stac-item
2019-06-30 11:37:07	ga_s2am_ard_3-2-1_50HQH_2019-06-30_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

Other products

All years