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
2022-08-22 12:05:21	ga_s2am_ard_3-2-1_49JFM_2022-08-22_final.stac-item
2022-08-22 12:05:24	ga_s2am_ard_3-2-1_50JKR_2022-08-22_final.stac-item
2022-08-22 12:05:27	ga_s2am_ard_3-2-1_49JGL_2022-08-22_final.stac-item
2022-08-22 12:05:32	ga_s2am_ard_3-2-1_49JFL_2022-08-22_final
2022-08-22 12:05:35	ga_s2am_ard_3-2-1_50JLQ_2022-08-22_final.stac-item
2022-08-22 12:05:39	ga_s2am_ard_3-2-1_50JKQ_2022-08-22_final.stac-item
2022-08-22 12:05:42	ga_s2am_ard_3-2-1_49JGK_2022-08-22_final.stac-item
2022-08-22 12:05:50	ga_s2am_ard_3-2-1_50JLP_2022-08-22_final.stac-item
2022-08-22 12:05:53	ga_s2am_ard_3-2-1_50JKP_2022-08-22_final.stac-item
2022-08-22 12:05:56	ga_s2am_ard_3-2-1_49JGJ_2022-08-22_final.stac-item
2022-08-22 12:06:04	ga_s2am_ard_3-2-1_50JLN_2022-08-22_final.stac-item
2022-08-22 12:06:08	ga_s2am_ard_3-2-1_50JKN_2022-08-22_final.stac-item
2022-08-22 12:06:17	ga_s2am_ard_3-2-1_50JLM_2022-08-22_final.stac-item
2022-08-22 12:06:22	ga_s2am_ard_3-2-1_50JKM_2022-08-22_final.stac-item
2022-08-22 12:06:35	ga_s2am_ard_3-2-1_50JKL_2022-08-22_final
2022-08-23 09:51:23	ga_s2am_ard_3-2-1_56LKH_2022-08-23_final
2022-08-23 09:51:28	ga_s2am_ard_3-2-1_55LGC_2022-08-23_final.stac-item
2022-08-23 09:51:31	ga_s2am_ard_3-2-1_55LFC_2022-08-23_final.stac-item
2022-08-23 09:51:43	ga_s2am_ard_3-2-1_55KGB_2022-08-23_final.stac-item
2022-08-23 09:51:46	ga_s2am_ard_3-2-1_55KFB_2022-08-23_final.stac-item
2022-08-23 09:51:52	ga_s2am_ard_3-2-1_56KKF_2022-08-23_final.stac-item
2022-08-23 09:51:53	ga_s2am_ard_3-2-1_55KHA_2022-08-23_final
2022-08-23 09:51:57	ga_s2am_ard_3-2-1_55KGA_2022-08-23_final
2022-08-23 09:52:00	ga_s2am_ard_3-2-1_55KFA_2022-08-23_final.stac-item
2022-08-23 09:52:05	ga_s2am_ard_3-2-1_55KEA_2022-08-23_final
2022-08-23 09:52:15	ga_s2am_ard_3-2-1_55KFV_2022-08-23_final
2022-08-23 09:52:18	ga_s2am_ard_3-2-1_55KEV_2022-08-23_final.stac-item
2022-08-23 09:52:22	ga_s2am_ard_3-2-1_55KHU_2022-08-23_final
2022-08-23 09:52:26	ga_s2am_ard_3-2-1_55KGU_2022-08-23_final.stac-item
2022-08-23 09:52:30	ga_s2am_ard_3-2-1_55KFU_2022-08-23_final.stac-item
2022-08-23 09:52:32	ga_s2am_ard_3-2-1_56KKC_2022-08-23_final
2022-08-23 09:52:33	ga_s2am_ard_3-2-1_55KEU_2022-08-23_final.stac-item
2022-08-23 09:52:36	ga_s2am_ard_3-2-1_55KHT_2022-08-23_final
2022-08-23 09:52:40	ga_s2am_ard_3-2-1_55KGT_2022-08-23_final.stac-item
2022-08-23 09:52:44	ga_s2am_ard_3-2-1_55KFT_2022-08-23_final.stac-item
2022-08-23 09:52:47	ga_s2am_ard_3-2-1_55KET_2022-08-23_final.stac-item
2022-08-23 09:52:47	ga_s2am_ard_3-2-1_55KHS_2022-08-23_final.stac-item
2022-08-23 09:52:55	ga_s2am_ard_3-2-1_55KGS_2022-08-23_final.stac-item
2022-08-23 09:52:59	ga_s2am_ard_3-2-1_55KFS_2022-08-23_final.stac-item
2022-08-23 09:53:02	ga_s2am_ard_3-2-1_55KES_2022-08-23_final.stac-item
2022-08-23 09:53:08	ga_s2am_ard_3-2-1_55KDS_2022-08-23_final.stac-item
2022-08-23 09:53:09	ga_s2am_ard_3-2-1_55KGR_2022-08-23_final.stac-item
2022-08-23 09:53:13	ga_s2am_ard_3-2-1_55KFR_2022-08-23_final.stac-item
2022-08-23 09:53:16	ga_s2am_ard_3-2-1_55KER_2022-08-23_final.stac-item
2022-08-23 09:53:20	ga_s2am_ard_3-2-1_55KDR_2022-08-23_final.stac-item
2022-08-23 09:53:24	ga_s2am_ard_3-2-1_55KGQ_2022-08-23_final.stac-item
2022-08-23 09:53:27	ga_s2am_ard_3-2-1_55KFQ_2022-08-23_final.stac-item
2022-08-23 09:53:31	ga_s2am_ard_3-2-1_55KEQ_2022-08-23_final.stac-item
2022-08-23 09:53:34	ga_s2am_ard_3-2-1_55KDQ_2022-08-23_final.stac-item
2022-08-23 09:53:38	ga_s2am_ard_3-2-1_55KGP_2022-08-23_final.stac-item
2022-08-23 09:53:42	ga_s2am_ard_3-2-1_55KFP_2022-08-23_final.stac-item
2022-08-23 09:53:45	ga_s2am_ard_3-2-1_55KEP_2022-08-23_final.stac-item
2022-08-23 09:53:49	ga_s2am_ard_3-2-1_55KDP_2022-08-23_final.stac-item
2022-08-23 09:53:50	ga_s2am_ard_3-2-1_55JGN_2022-08-23_final.stac-item
2022-08-23 09:53:56	ga_s2am_ard_3-2-1_55JFN_2022-08-23_final.stac-item
2022-08-23 09:54:00	ga_s2am_ard_3-2-1_55JEN_2022-08-23_final.stac-item
2022-08-23 09:54:03	ga_s2am_ard_3-2-1_55JDN_2022-08-23_final.stac-item
2022-08-23 09:54:10	ga_s2am_ard_3-2-1_55JCN_2022-08-23_final.stac-item
2022-08-23 09:54:11	ga_s2am_ard_3-2-1_55JFM_2022-08-23_final.stac-item
2022-08-23 09:54:15	ga_s2am_ard_3-2-1_55JEM_2022-08-23_final.stac-item
2022-08-23 09:54:18	ga_s2am_ard_3-2-1_55JDM_2022-08-23_final.stac-item
2022-08-23 09:54:22	ga_s2am_ard_3-2-1_55JCM_2022-08-23_final.stac-item
2022-08-23 09:54:25	ga_s2am_ard_3-2-1_55JFL_2022-08-23_final.stac-item
2022-08-23 09:54:29	ga_s2am_ard_3-2-1_55JEL_2022-08-23_final.stac-item
2022-08-23 09:54:32	ga_s2am_ard_3-2-1_55JDL_2022-08-23_final.stac-item
2022-08-23 09:54:35	ga_s2am_ard_3-2-1_55JCL_2022-08-23_final.stac-item
2022-08-23 09:54:40	ga_s2am_ard_3-2-1_55JFK_2022-08-23_final.stac-item
2022-08-23 09:54:44	ga_s2am_ard_3-2-1_55JEK_2022-08-23_final.stac-item
2022-08-23 09:54:47	ga_s2am_ard_3-2-1_55JDK_2022-08-23_final.stac-item
2022-08-23 09:54:50	ga_s2am_ard_3-2-1_55JCK_2022-08-23_final.stac-item
2022-08-23 09:54:53	ga_s2am_ard_3-2-1_55JFJ_2022-08-23_final.stac-item
2022-08-23 09:54:58	ga_s2am_ard_3-2-1_55JEJ_2022-08-23_final.stac-item
2022-08-23 09:55:01	ga_s2am_ard_3-2-1_55JDJ_2022-08-23_final.stac-item
2022-08-23 09:55:03	ga_s2am_ard_3-2-1_55JFH_2022-08-23_final.stac-item
2022-08-23 09:55:05	ga_s2am_ard_3-2-1_55JCJ_2022-08-23_final.stac-item
2022-08-23 09:55:12	ga_s2am_ard_3-2-1_55JEH_2022-08-23_final.stac-item
2022-08-23 09:55:16	ga_s2am_ard_3-2-1_55JDH_2022-08-23_final.stac-item
2022-08-23 09:55:19	ga_s2am_ard_3-2-1_55JCH_2022-08-23_final.stac-item
2022-08-23 09:55:23	ga_s2am_ard_3-2-1_55JBH_2022-08-23_final.stac-item
2022-08-23 09:55:27	ga_s2am_ard_3-2-1_55JEG_2022-08-23_final.stac-item
2022-08-23 09:55:31	ga_s2am_ard_3-2-1_55JDG_2022-08-23_final.stac-item
2022-08-23 09:55:34	ga_s2am_ard_3-2-1_55JCG_2022-08-23_final.stac-item
2022-08-23 09:55:37	ga_s2am_ard_3-2-1_55JBG_2022-08-23_final.stac-item
2022-08-23 09:55:42	ga_s2am_ard_3-2-1_55JEF_2022-08-23_final.stac-item
2022-08-23 09:55:45	ga_s2am_ard_3-2-1_55JDF_2022-08-23_final.stac-item
2022-08-23 09:55:49	ga_s2am_ard_3-2-1_55JCF_2022-08-23_final.stac-item
2022-08-23 11:34:56	ga_s2am_ard_3-2-1_51JVM_2022-08-23_final.stac-item
2022-08-23 11:34:59	ga_s2am_ard_3-2-1_51JUM_2022-08-23_final.stac-item
2022-08-23 11:35:02	ga_s2am_ard_3-2-1_50JRS_2022-08-23_final.stac-item
2022-08-23 11:35:02	ga_s2am_ard_3-2-1_51JTM_2022-08-23_final.stac-item
2022-08-23 11:35:10	ga_s2am_ard_3-2-1_51JVL_2022-08-23_final.stac-item
2022-08-23 11:35:43	ga_s2am_ard_3-2-1_51JUJ_2022-08-23_final.stac-item
2022-08-23 11:35:46	ga_s2am_ard_3-2-1_51JTJ_2022-08-23_final.stac-item
2022-08-23 11:35:50	ga_s2am_ard_3-2-1_50JQP_2022-08-23_final.stac-item
2022-08-23 11:36:00	ga_s2am_ard_3-2-1_51JTH_2022-08-23_final.stac-item
2022-08-23 11:36:09	ga_s2am_ard_3-2-1_51JVG_2022-08-23_final.stac-item
2022-08-23 11:36:23	ga_s2am_ard_3-2-1_51JVF_2022-08-23_final.stac-item
2022-08-23 11:36:27	ga_s2am_ard_3-2-1_51JUF_2022-08-23_final.stac-item
2022-08-23 11:36:30	ga_s2am_ard_3-2-1_51JTF_2022-08-23_final.stac-item
2022-08-23 11:36:44	ga_s2am_ard_3-2-1_51HTE_2022-08-23_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