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
2023-02-28 12:04:40	ga_s2am_ard_3-2-1_49JHN_2023-02-28_final
2023-02-28 12:04:40	ga_s2am_ard_3-2-1_50JKT_2023-02-28_final
2023-02-28 12:04:43	ga_s2am_ard_3-2-1_49JGN_2023-02-28_final
2023-02-28 12:04:46	ga_s2am_ard_3-2-1_50JMS_2023-02-28_final
2023-02-28 12:04:51	ga_s2am_ard_3-2-1_50JLS_2023-02-28_final
2023-03-01 09:53:27	ga_s2am_ard_3-2-1_55KFP_2023-03-01_final
2023-03-01 09:53:30	ga_s2am_ard_3-2-1_55KEP_2023-03-01_final
2023-03-01 09:53:34	ga_s2am_ard_3-2-1_55KDP_2023-03-01_final
2023-03-01 09:53:35	ga_s2am_ard_3-2-1_55JGN_2023-03-01_final
2023-03-01 09:53:41	ga_s2am_ard_3-2-1_55JFN_2023-03-01_final
2023-03-01 09:53:45	ga_s2am_ard_3-2-1_55JEN_2023-03-01_final
2023-03-01 09:53:45	ga_s2am_ard_3-2-1_55JGM_2023-03-01_final
2023-03-01 09:53:55	ga_s2am_ard_3-2-1_55JCN_2023-03-01_final
2023-03-01 09:53:55	ga_s2am_ard_3-2-1_55JFM_2023-03-01_final
2023-03-01 09:53:59	ga_s2am_ard_3-2-1_55JEM_2023-03-01_final
2023-03-01 09:54:03	ga_s2am_ard_3-2-1_55JDM_2023-03-01_final
2023-03-01 09:54:06	ga_s2am_ard_3-2-1_55JCM_2023-03-01_final
2023-03-01 09:54:10	ga_s2am_ard_3-2-1_55JFL_2023-03-01_final
2023-03-01 09:54:14	ga_s2am_ard_3-2-1_55JEL_2023-03-01_final
2023-03-01 09:54:17	ga_s2am_ard_3-2-1_55JDL_2023-03-01_final
2023-03-01 09:54:20	ga_s2am_ard_3-2-1_55JCL_2023-03-01_final
2023-03-01 09:54:25	ga_s2am_ard_3-2-1_55JFK_2023-03-01_final
2023-03-01 09:54:28	ga_s2am_ard_3-2-1_55JEK_2023-03-01_final
2023-03-01 09:54:32	ga_s2am_ard_3-2-1_55JDK_2023-03-01_final
2023-03-01 09:54:35	ga_s2am_ard_3-2-1_55JCK_2023-03-01_final
2023-03-01 09:54:38	ga_s2am_ard_3-2-1_55JFJ_2023-03-01_final
2023-03-01 09:54:43	ga_s2am_ard_3-2-1_55JEJ_2023-03-01_final
2023-03-01 09:54:46	ga_s2am_ard_3-2-1_55JDJ_2023-03-01_final
2023-03-01 09:54:48	ga_s2am_ard_3-2-1_55JFH_2023-03-01_final
2023-03-01 09:54:50	ga_s2am_ard_3-2-1_55JCJ_2023-03-01_final
2023-03-01 09:54:57	ga_s2am_ard_3-2-1_55JEH_2023-03-01_final
2023-03-01 09:55:01	ga_s2am_ard_3-2-1_55JDH_2023-03-01_final
2023-03-01 09:55:04	ga_s2am_ard_3-2-1_55JCH_2023-03-01_final
2023-03-01 09:55:08	ga_s2am_ard_3-2-1_55JBH_2023-03-01_final
2023-03-01 09:55:12	ga_s2am_ard_3-2-1_55JEG_2023-03-01_final
2023-03-01 09:55:15	ga_s2am_ard_3-2-1_55JDG_2023-03-01_final
2023-03-01 09:55:18	ga_s2am_ard_3-2-1_55JCG_2023-03-01_final
2023-03-01 09:55:22	ga_s2am_ard_3-2-1_55JBG_2023-03-01_final
2023-03-01 09:55:26	ga_s2am_ard_3-2-1_55JEF_2023-03-01_final
2023-03-01 09:55:30	ga_s2am_ard_3-2-1_55JDF_2023-03-01_final
2023-03-01 09:55:33	ga_s2am_ard_3-2-1_55JCF_2023-03-01_final
2023-03-01 09:55:36	ga_s2am_ard_3-2-1_55JBF_2023-03-01_final
2023-03-01 09:55:40	ga_s2am_ard_3-2-1_55HEE_2023-03-01_final
2023-03-01 09:55:44	ga_s2am_ard_3-2-1_55HDE_2023-03-01_final
2023-03-01 09:55:48	ga_s2am_ard_3-2-1_55HCE_2023-03-01_final
2023-03-01 09:55:51	ga_s2am_ard_3-2-1_55HBE_2023-03-01_final
2023-03-01 09:55:51	ga_s2am_ard_3-2-1_55HED_2023-03-01_final
2023-03-01 09:55:54	ga_s2am_ard_3-2-1_54HYK_2023-03-01_final
2023-03-01 09:55:59	ga_s2am_ard_3-2-1_55HDD_2023-03-01_final
2023-03-01 09:56:02	ga_s2am_ard_3-2-1_55HCD_2023-03-01_final
2023-03-01 09:56:06	ga_s2am_ard_3-2-1_55HBD_2023-03-01_final
2023-03-01 09:56:07	ga_s2am_ard_3-2-1_54HYJ_2023-03-01_final
2023-03-01 09:56:13	ga_s2am_ard_3-2-1_55HDC_2023-03-01_final
2023-03-01 09:56:17	ga_s2am_ard_3-2-1_55HCC_2023-03-01_final
2023-03-01 09:56:20	ga_s2am_ard_3-2-1_55HBC_2023-03-01_final
2023-03-01 09:56:22	ga_s2am_ard_3-2-1_54HYH_2023-03-01_final
2023-03-01 09:56:28	ga_s2am_ard_3-2-1_55HDB_2023-03-01_final
2023-03-01 09:56:31	ga_s2am_ard_3-2-1_55HCB_2023-03-01_final
2023-03-01 09:57:48	ga_s2am_ard_3-2-1_54HYB_2023-03-01_final
2023-03-01 09:57:52	ga_s2am_ard_3-2-1_54HXB_2023-03-01_final
2023-03-01 09:57:56	ga_s2am_ard_3-2-1_54HWB_2023-03-01_nrt
2023-03-01 09:57:58	ga_s2am_ard_3-2-1_55GCR_2023-03-01_final
2023-03-01 09:58:02	ga_s2am_ard_3-2-1_55GBR_2023-03-01_final
2023-03-01 09:58:03	ga_s2am_ard_3-2-1_54GYA_2023-03-01_final
2023-03-01 09:58:07	ga_s2am_ard_3-2-1_54GXA_2023-03-01_nrt
2023-03-01 09:58:11	ga_s2am_ard_3-2-1_54GWA_2023-03-01_nrt
2023-03-01 09:58:11	ga_s2am_ard_3-2-1_55GCQ_2023-03-01_final
2023-03-01 09:58:17	ga_s2am_ard_3-2-1_55GBQ_2023-03-01_final
2023-03-01 09:58:17	ga_s2am_ard_3-2-1_54GYV_2023-03-01_final
2023-03-01 09:58:21	ga_s2am_ard_3-2-1_54GXV_2023-03-01_nrt
2023-03-01 09:58:21	ga_s2am_ard_3-2-1_55GCP_2023-03-01_final
2023-03-01 09:58:23	ga_s2am_ard_3-2-1_54GWV_2023-03-01_nrt
2023-03-01 09:58:26	ga_s2am_ard_3-2-1_54GYU_2023-03-01_nrt
2023-03-01 09:58:26	ga_s2am_ard_3-2-1_55GBP_2023-03-01_final
2023-03-01 09:58:28	ga_s2am_ard_3-2-1_54GXU_2023-03-01_nrt
2023-03-01 09:58:29	ga_s2am_ard_3-2-1_54GVV_2023-03-01_nrt
2023-03-01 09:58:31	ga_s2am_ard_3-2-1_54GWU_2023-03-01_nrt
2023-03-01 11:30:11	ga_s2am_ard_3-2-1_52LCP_2023-03-01_nrt
2023-03-01 11:30:18	ga_s2am_ard_3-2-1_52LBP_2023-03-01_nrt
2023-03-01 11:30:20	ga_s2am_ard_3-2-1_51LZJ_2023-03-01_nrt
2023-03-01 11:30:24	ga_s2am_ard_3-2-1_51LYJ_2023-03-01_nrt
2023-03-01 11:30:27	ga_s2am_ard_3-2-1_51LXJ_2023-03-01_nrt
2023-03-01 11:30:33	ga_s2am_ard_3-2-1_52LBN_2023-03-01_nrt
2023-03-01 11:30:35	ga_s2am_ard_3-2-1_51LZH_2023-03-01_nrt
2023-03-01 11:30:38	ga_s2am_ard_3-2-1_51LYH_2023-03-01_nrt
2023-03-01 11:30:41	ga_s2am_ard_3-2-1_51LXH_2023-03-01_nrt
2023-03-01 11:30:47	ga_s2am_ard_3-2-1_52LBM_2023-03-01_nrt
2023-03-01 11:30:49	ga_s2am_ard_3-2-1_51LZG_2023-03-01_nrt
2023-03-01 11:30:56	ga_s2am_ard_3-2-1_51LXG_2023-03-01_nrt
2023-03-01 11:31:02	ga_s2am_ard_3-2-1_52LBL_2023-03-01_final
2023-03-01 11:31:03	ga_s2am_ard_3-2-1_51LZF_2023-03-01_final
2023-03-01 11:31:07	ga_s2am_ard_3-2-1_51LYF_2023-03-01_final
2023-03-01 11:31:10	ga_s2am_ard_3-2-1_51LXF_2023-03-01_nrt
2023-03-01 11:31:15	ga_s2am_ard_3-2-1_51LWF_2023-03-01_final
2023-03-01 11:31:15	ga_s2am_ard_3-2-1_52LBK_2023-03-01_final
2023-03-01 11:31:18	ga_s2am_ard_3-2-1_51LZE_2023-03-01_final
2023-03-01 11:31:22	ga_s2am_ard_3-2-1_51LYE_2023-03-01_final
2023-03-01 11:31:25	ga_s2am_ard_3-2-1_51LXE_2023-03-01_final
2023-03-01 11:31:26	ga_s2am_ard_3-2-1_52LBJ_2023-03-01_final
2023-03-01 11:31:28	ga_s2am_ard_3-2-1_51LWE_2023-03-01_final

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