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

77 results

Time (local)	Label
2024-04-05 09:22:50	ga_s2am_ard_3-2-1_56KPA_2024-04-04_nrt
2024-04-05 09:23:05	ga_s2am_ard_3-2-1_56KPV_2024-04-04_nrt
2024-04-05 09:23:19	ga_s2am_ard_3-2-1_56KPU_2024-04-04_nrt
2024-04-05 09:23:48	ga_s2am_ard_3-2-1_56JPS_2024-04-04_nrt
2024-04-05 09:24:03	ga_s2am_ard_3-2-1_56JPR_2024-04-04_nrt
2024-04-05 09:24:17	ga_s2am_ard_3-2-1_56JPQ_2024-04-04_nrt
2024-04-05 09:24:32	ga_s2am_ard_3-2-1_56JPP_2024-04-04_nrt
2024-04-05 09:25:01	ga_s2am_ard_3-2-1_56JPM_2024-04-04_nrt
2024-04-05 09:25:15	ga_s2am_ard_3-2-1_56JPL_2024-04-04_nrt
2024-04-05 09:25:29	ga_s2am_ard_3-2-1_56HPK_2024-04-04_nrt
2024-04-05 09:25:33	ga_s2am_ard_3-2-1_56HNK_2024-04-04_nrt
2024-04-05 09:25:48	ga_s2am_ard_3-2-1_56HNJ_2024-04-04_nrt
2024-04-05 09:25:58	ga_s2am_ard_3-2-1_56HPH_2024-04-04_nrt
2024-04-05 09:26:02	ga_s2am_ard_3-2-1_56HNH_2024-04-04_nrt
2024-04-05 09:26:06	ga_s2am_ard_3-2-1_56HMH_2024-04-04_nrt
2024-04-05 09:26:16	ga_s2am_ard_3-2-1_56HNG_2024-04-04_nrt
2024-04-05 09:26:20	ga_s2am_ard_3-2-1_56HMG_2024-04-04_nrt
2024-04-05 09:26:31	ga_s2am_ard_3-2-1_56HNF_2024-04-04_nrt
2024-04-05 09:26:35	ga_s2am_ard_3-2-1_56HMF_2024-04-04_nrt
2024-04-05 09:26:44	ga_s2am_ard_3-2-1_56HNE_2024-04-04_nrt
2024-04-05 09:26:51	ga_s2am_ard_3-2-1_56HNE_2024-04-04_nrt
2024-04-05 09:27:04	ga_s2am_ard_3-2-1_56HMD_2024-04-04_nrt
2024-04-05 09:27:12	ga_s2am_ard_3-2-1_56HNC_2024-04-04_nrt
2024-04-05 09:27:18	ga_s2am_ard_3-2-1_56HMC_2024-04-04_nrt
2024-04-05 09:27:22	ga_s2am_ard_3-2-1_56HLC_2024-04-04_nrt
2024-04-05 09:27:33	ga_s2am_ard_3-2-1_56HMB_2024-04-04_nrt
2024-04-05 09:27:37	ga_s2am_ard_3-2-1_56HLB_2024-04-04_nrt
2024-04-05 09:27:40	ga_s2am_ard_3-2-1_55HGS_2024-04-04_nrt
2024-04-05 09:27:48	ga_s2am_ard_3-2-1_56GMA_2024-04-04_nrt
2024-04-05 09:27:51	ga_s2am_ard_3-2-1_56GLA_2024-04-04_nrt
2024-04-05 09:27:54	ga_s2am_ard_3-2-1_56GKA_2024-04-04_nrt
2024-04-05 09:27:55	ga_s2am_ard_3-2-1_55GGR_2024-04-04_nrt
2024-04-05 09:28:06	ga_s2am_ard_3-2-1_56GLV_2024-04-04_nrt
2024-04-05 09:28:09	ga_s2am_ard_3-2-1_55GGQ_2024-04-04_nrt
2024-04-05 09:28:20	ga_s2am_ard_3-2-1_56GLU_2024-04-04_nrt
2024-04-05 09:28:23	ga_s2am_ard_3-2-1_55GGP_2024-04-04_nrt
2024-04-05 09:28:23	ga_s2am_ard_3-2-1_56GKU_2024-04-04_nrt
2024-04-05 09:28:26	ga_s2am_ard_3-2-1_56GMT_2024-04-04_nrt
2024-04-05 09:28:34	ga_s2am_ard_3-2-1_56GLT_2024-04-04_nrt
2024-04-05 09:28:38	ga_s2am_ard_3-2-1_55GGN_2024-04-04_nrt
2024-04-05 09:28:49	ga_s2am_ard_3-2-1_56GLS_2024-04-04_nrt
2024-04-05 09:28:52	ga_s2am_ard_3-2-1_55GGM_2024-04-04_nrt
2024-04-05 11:00:05	ga_s2am_ard_3-2-1_53LMJ_2024-04-05_nrt
2024-04-05 11:06:25	ga_s2am_ard_3-2-1_52HEJ_2024-04-05_nrt
2024-04-05 11:06:27	ga_s2am_ard_3-2-1_52HDJ_2024-04-05_nrt
2024-04-05 11:06:29	ga_s2am_ard_3-2-1_52HCJ_2024-04-05_nrt
2024-04-05 11:06:32	ga_s2am_ard_3-2-1_52HEH_2024-04-05_nrt
2024-04-06 10:29:59	ga_s2am_ard_3-2-1_54LVP_2024-04-06_nrt
2024-04-06 10:30:02	ga_s2am_ard_3-2-1_54LUP_2024-04-06_nrt
2024-04-06 10:30:13	ga_s2am_ard_3-2-1_54LVN_2024-04-06_nrt
2024-04-06 10:30:16	ga_s2am_ard_3-2-1_54LUN_2024-04-06_nrt
2024-04-06 10:30:30	ga_s2am_ard_3-2-1_54LUM_2024-04-06_nrt
2024-04-06 10:30:33	ga_s2am_ard_3-2-1_54LTM_2024-04-06_nrt
2024-04-06 10:30:36	ga_s2am_ard_3-2-1_54LUM_2024-04-06_nrt
2024-04-06 10:30:37	ga_s2am_ard_3-2-1_54LUL_2024-04-06_nrt
2024-04-06 10:30:45	ga_s2am_ard_3-2-1_54LUL_2024-04-06_nrt
2024-04-06 10:30:49	ga_s2am_ard_3-2-1_54LTL_2024-04-06_nrt
2024-04-06 10:31:00	ga_s2am_ard_3-2-1_54LUK_2024-04-06_nrt
2024-04-06 10:31:03	ga_s2am_ard_3-2-1_54LTK_2024-04-06_nrt
2024-04-06 10:31:18	ga_s2am_ard_3-2-1_54LTJ_2024-04-06_nrt
2024-04-06 10:31:19	ga_s2am_ard_3-2-1_53LRD_2024-04-06_nrt
2024-04-06 10:31:32	ga_s2am_ard_3-2-1_54LTH_2024-04-06_nrt
2024-04-06 10:31:33	ga_s2am_ard_3-2-1_53LRC_2024-04-06_nrt
2024-04-06 10:36:40	ga_s2am_ard_3-2-1_53HLC_2024-04-06_nrt
2024-04-06 10:36:55	ga_s2am_ard_3-2-1_53HLB_2024-04-06_nrt
2024-04-06 10:37:00	ga_s2am_ard_3-2-1_53HNA_2024-04-06_nrt
2024-04-06 10:37:02	ga_s2am_ard_3-2-1_53HMA_2024-04-06_nrt
2024-04-06 10:37:04	ga_s2am_ard_3-2-1_53HLA_2024-04-06_nrt
2024-04-06 12:10:25	ga_s2am_ard_3-2-1_50LNP_2024-04-06_nrt
2024-04-06 12:10:26	ga_s2am_ard_3-2-1_50LMP_2024-04-06_nrt
2024-04-06 12:13:21	ga_s2am_ard_3-2-1_49KGU_2024-04-06_nrt
2024-04-06 12:13:26	ga_s2am_ard_3-2-1_49KHT_2024-04-06_nrt
2024-04-06 12:13:28	ga_s2am_ard_3-2-1_49KGT_2024-04-06_nrt
2024-04-06 12:13:42	ga_s2am_ard_3-2-1_49KGS_2024-04-06_nrt
2024-04-06 12:14:00	ga_s2am_ard_3-2-1_49KFR_2024-04-06_nrt
2024-04-06 12:14:29	ga_s2am_ard_3-2-1_49KFP_2024-04-06_nrt
2024-04-06 12:15:18	ga_s2am_ard_3-2-1_49JFK_2024-04-06_nrt

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