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
2023-04-01 09:27:56	ga_s2am_ard_3-2-1_56GKA_2023-03-31_nrt
2023-04-01 09:27:56	ga_s2am_ard_3-2-1_55GGR_2023-03-31_nrt
2023-04-01 09:28:10	ga_s2am_ard_3-2-1_56GKV_2023-03-31_nrt
2023-04-01 09:28:11	ga_s2am_ard_3-2-1_55GGQ_2023-03-31_nrt
2023-04-01 09:28:25	ga_s2am_ard_3-2-1_55GGP_2023-03-31_nrt
2023-04-01 09:28:25	ga_s2am_ard_3-2-1_56GKU_2023-03-31_nrt
2023-04-01 09:28:39	ga_s2am_ard_3-2-1_55GGN_2023-03-31_nrt
2023-04-01 09:28:52	ga_s2am_ard_3-2-1_55GGM_2023-03-31_nrt
2023-04-01 09:28:59	ga_s2am_ard_3-2-1_55GGM_2023-03-31_nrt
2023-05-17 09:42:15	ga_s2am_ard_3-2-1_56KKD_2023-05-17_nrt
2023-05-17 09:42:16	ga_s2am_ard_3-2-1_55KHU_2023-05-17_nrt
2023-05-17 09:42:29	ga_s2am_ard_3-2-1_56KKC_2023-05-17_nrt
2023-05-17 09:42:30	ga_s2am_ard_3-2-1_55KHT_2023-05-17_nrt
2023-05-17 09:42:44	ga_s2am_ard_3-2-1_56KKB_2023-05-17_final
2023-05-17 09:42:44	ga_s2am_ard_3-2-1_55KHS_2023-05-17_final
2023-05-17 09:42:58	ga_s2am_ard_3-2-1_56KKA_2023-05-17_final
2023-05-17 09:42:59	ga_s2am_ard_3-2-1_55KHR_2023-05-17_final
2023-05-17 09:43:05	ga_s2am_ard_3-2-1_56KKA_2023-05-17_final
2023-05-17 09:43:05	ga_s2am_ard_3-2-1_55KHR_2023-05-17_final
2023-05-17 09:43:13	ga_s2am_ard_3-2-1_56KKV_2023-05-17_final
2023-05-17 09:43:13	ga_s2am_ard_3-2-1_55KHQ_2023-05-17_final
2023-05-17 09:43:28	ga_s2am_ard_3-2-1_56KKU_2023-05-17_final
2023-05-17 09:43:28	ga_s2am_ard_3-2-1_55KHP_2023-05-17_final
2023-05-17 09:43:42	ga_s2am_ard_3-2-1_55JHN_2023-05-17_final
2023-05-17 09:43:42	ga_s2am_ard_3-2-1_56JKT_2023-05-17_final
2023-05-17 09:43:57	ga_s2am_ard_3-2-1_55JHM_2023-05-17_final
2023-05-17 09:43:57	ga_s2am_ard_3-2-1_56JKS_2023-05-17_final
2023-05-17 09:44:11	ga_s2am_ard_3-2-1_56JKR_2023-05-17_final
2023-05-17 09:44:26	ga_s2am_ard_3-2-1_56JKQ_2023-05-17_final
2023-05-17 09:44:40	ga_s2am_ard_3-2-1_56JKP_2023-05-17_final
2023-05-17 09:44:44	ga_s2am_ard_3-2-1_55JGJ_2023-05-17_final
2023-05-17 09:44:55	ga_s2am_ard_3-2-1_56JKN_2023-05-17_final
2023-05-17 09:44:58	ga_s2am_ard_3-2-1_55JGH_2023-05-17_final
2023-05-17 09:45:10	ga_s2am_ard_3-2-1_56JKM_2023-05-17_final
2023-05-17 09:45:12	ga_s2am_ard_3-2-1_55JGG_2023-05-17_final
2023-05-20 09:49:47	ga_s2am_ard_3-2-1_55LHJ_2023-05-20_nrt
2023-05-20 09:50:01	ga_s2am_ard_3-2-1_55LHH_2023-05-20_nrt
2023-05-20 09:51:04	ga_s2am_ard_3-2-1_55LHD_2023-05-20_nrt
2023-05-20 09:51:14	ga_s2am_ard_3-2-1_55LHC_2023-05-20_final
2023-05-20 09:51:29	ga_s2am_ard_3-2-1_55KHB_2023-05-20_final
2023-05-20 09:51:42	ga_s2am_ard_3-2-1_56KKF_2023-05-20_final
2023-05-20 09:51:43	ga_s2am_ard_3-2-1_55KHA_2023-05-20_final
2023-05-20 09:51:57	ga_s2am_ard_3-2-1_56KKE_2023-05-20_nrt
2023-05-20 09:51:57	ga_s2am_ard_3-2-1_55KHV_2023-05-20_nrt
2023-05-20 09:52:10	ga_s2am_ard_3-2-1_56KKD_2023-05-20_nrt
2023-05-20 09:52:12	ga_s2am_ard_3-2-1_55KHU_2023-05-20_final
2023-05-20 09:52:21	ga_s2am_ard_3-2-1_56KKC_2023-05-20_final
2023-05-20 09:52:26	ga_s2am_ard_3-2-1_55KHT_2023-05-20_final
2023-07-16 09:44:15	ga_s2am_ard_3-2-1_56JKR_2023-07-16_final
2023-07-16 09:44:29	ga_s2am_ard_3-2-1_56JKQ_2023-07-16_final
2023-07-16 09:44:44	ga_s2am_ard_3-2-1_56JKP_2023-07-16_final
2023-07-16 09:44:47	ga_s2am_ard_3-2-1_55JGJ_2023-07-16_final
2023-07-16 09:44:59	ga_s2am_ard_3-2-1_56JKN_2023-07-16_final
2023-07-16 09:45:02	ga_s2am_ard_3-2-1_55JGH_2023-07-16_final
2023-07-16 09:45:11	ga_s2am_ard_3-2-1_56JKM_2023-07-16_final
2023-07-16 09:45:12	ga_s2am_ard_3-2-1_55JGG_2023-07-16_final
2023-07-16 09:45:17	ga_s2am_ard_3-2-1_56JKM_2023-07-16_final
2023-07-16 09:45:19	ga_s2am_ard_3-2-1_55JGG_2023-07-16_final
2023-07-16 09:45:30	ga_s2am_ard_3-2-1_55JGF_2023-07-16_final
2023-09-04 09:42:04	ga_s2am_ard_3-2-1_56KKE_2023-09-04_nrt
2023-09-04 09:42:05	ga_s2am_ard_3-2-1_55KHV_2023-09-04_nrt
2023-09-04 09:42:19	ga_s2am_ard_3-2-1_56KKD_2023-09-04_nrt
2023-09-04 09:42:20	ga_s2am_ard_3-2-1_55KHU_2023-09-04_nrt
2023-09-04 09:42:33	ga_s2am_ard_3-2-1_56KKC_2023-09-04_nrt
2023-09-04 09:42:34	ga_s2am_ard_3-2-1_55KHT_2023-09-04_nrt
2023-09-04 09:42:48	ga_s2am_ard_3-2-1_56KKB_2023-09-04_final
2023-09-04 09:42:48	ga_s2am_ard_3-2-1_55KHS_2023-09-04_final
2023-09-04 09:43:03	ga_s2am_ard_3-2-1_56KKA_2023-09-04_final
2023-09-04 09:43:03	ga_s2am_ard_3-2-1_55KHR_2023-09-04_final
2023-09-04 09:43:17	ga_s2am_ard_3-2-1_56KKV_2023-09-04_final
2023-09-04 09:43:17	ga_s2am_ard_3-2-1_55KHQ_2023-09-04_final
2023-09-04 09:43:32	ga_s2am_ard_3-2-1_56KKU_2023-09-04_final
2023-09-04 09:43:32	ga_s2am_ard_3-2-1_55KHP_2023-09-04_final
2023-09-04 09:43:46	ga_s2am_ard_3-2-1_55JHN_2023-09-04_final
2023-09-04 09:43:46	ga_s2am_ard_3-2-1_56JKT_2023-09-04_final
2023-09-04 09:44:01	ga_s2am_ard_3-2-1_55JHM_2023-09-04_final
2023-09-04 09:44:01	ga_s2am_ard_3-2-1_56JKS_2023-09-04_final
2023-09-04 09:44:15	ga_s2am_ard_3-2-1_56JKR_2023-09-04_final
2023-09-04 09:44:30	ga_s2am_ard_3-2-1_56JKQ_2023-09-04_final
2023-09-04 09:44:44	ga_s2am_ard_3-2-1_56JKP_2023-09-04_final
2023-09-04 09:44:48	ga_s2am_ard_3-2-1_55JGJ_2023-09-04_final
2023-09-11 09:34:49	ga_s2am_ard_3-2-1_56JKP_2023-09-11_final
2023-09-11 09:34:55	ga_s2am_ard_3-2-1_55JGJ_2023-09-11_final
2023-09-11 09:36:18	ga_s2am_ard_3-2-1_55HGC_2023-09-11_final
2023-09-11 09:36:31	ga_s2am_ard_3-2-1_56HKG_2023-09-11_final
2023-09-11 09:36:32	ga_s2am_ard_3-2-1_55HGB_2023-09-11_final
2023-09-11 09:36:47	ga_s2am_ard_3-2-1_55HGA_2023-09-11_final
2023-09-11 09:37:01	ga_s2am_ard_3-2-1_55HGV_2023-09-11_final
2023-09-11 09:37:16	ga_s2am_ard_3-2-1_55HGU_2023-09-11_final
2023-09-11 09:37:29	ga_s2am_ard_3-2-1_56HKC_2023-09-11_nrt
2023-09-11 09:37:30	ga_s2am_ard_3-2-1_55HGT_2023-09-11_nrt
2023-09-11 09:37:44	ga_s2am_ard_3-2-1_56HKB_2023-09-11_nrt
2023-09-11 09:37:44	ga_s2am_ard_3-2-1_55HGS_2023-09-11_nrt
2023-09-11 09:37:58	ga_s2am_ard_3-2-1_56GKA_2023-09-11_nrt
2023-09-11 09:37:59	ga_s2am_ard_3-2-1_55GGR_2023-09-11_nrt
2023-09-14 09:44:43	ga_s2am_ard_3-2-1_56JKP_2023-09-14_final
2023-09-14 09:44:47	ga_s2am_ard_3-2-1_55JGJ_2023-09-14_final
2023-09-14 09:44:58	ga_s2am_ard_3-2-1_56JKN_2023-09-14_final
2023-09-14 09:45:01	ga_s2am_ard_3-2-1_55JGH_2023-09-14_final
2023-09-14 09:45:13	ga_s2am_ard_3-2-1_56JKM_2023-09-14_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