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
2023-08-21 10:01:17	ga_s2am_ard_3-2-1_55LCD_2023-08-21_final
2023-08-21 10:01:24	ga_s2am_ard_3-2-1_55LEC_2023-08-21_final
2023-08-21 10:01:42	ga_s2am_ard_3-2-1_55KDB_2023-08-21_final
2023-08-21 10:01:49	ga_s2am_ard_3-2-1_55KFA_2023-08-21_final
2023-08-21 10:02:32	ga_s2am_ard_3-2-1_55KBU_2023-08-21_final
2023-08-21 10:02:36	ga_s2am_ard_3-2-1_55KET_2023-08-21_final
2023-08-21 10:02:40	ga_s2am_ard_3-2-1_55KDT_2023-08-21_final
2023-08-21 10:02:46	ga_s2am_ard_3-2-1_55KBT_2023-08-21_final
2023-08-21 10:02:54	ga_s2am_ard_3-2-1_55KDS_2023-08-21_final
2023-08-21 10:03:01	ga_s2am_ard_3-2-1_54KZB_2023-08-21_final
2023-08-21 10:03:12	ga_s2am_ard_3-2-1_55KCR_2023-08-21_final
2023-08-21 10:03:27	ga_s2am_ard_3-2-1_55KCQ_2023-08-21_final
2023-08-21 10:03:30	ga_s2am_ard_3-2-1_54KZV_2023-08-21_final
2023-08-21 10:03:44	ga_s2am_ard_3-2-1_55KBP_2023-08-21_final
2023-08-21 10:04:07	ga_s2am_ard_3-2-1_55JDM_2023-08-21_final
2023-08-21 10:04:14	ga_s2am_ard_3-2-1_55JBM_2023-08-21_final
2023-08-21 10:04:17	ga_s2am_ard_3-2-1_54JYS_2023-08-21_final
2023-08-21 10:04:25	ga_s2am_ard_3-2-1_55JCL_2023-08-21_final
2023-08-21 10:04:28	ga_s2am_ard_3-2-1_55JBL_2023-08-21_final
2023-08-21 10:04:38	ga_s2am_ard_3-2-1_54JXR_2023-08-21_final
2023-08-21 10:04:54	ga_s2am_ard_3-2-1_55JCJ_2023-08-21_final
2023-08-21 10:05:00	ga_s2am_ard_3-2-1_54JYP_2023-08-21_final
2023-08-21 10:05:04	ga_s2am_ard_3-2-1_54JXP_2023-08-21_final
2023-08-21 10:05:51	ga_s2am_ard_3-2-1_54JWL_2023-08-21_final
2023-08-21 10:05:55	ga_s2am_ard_3-2-1_55HBE_2023-08-21_final
2023-08-21 10:06:12	ga_s2am_ard_3-2-1_54HYJ_2023-08-21_final
2023-08-21 10:07:03	ga_s2am_ard_3-2-1_54HWF_2023-08-21_final
2023-08-21 10:07:28	ga_s2am_ard_3-2-1_54HXD_2023-08-21_final
2023-08-21 10:07:32	ga_s2am_ard_3-2-1_54HWD_2023-08-21_final
2023-08-21 10:07:36	ga_s2am_ard_3-2-1_54HVD_2023-08-21_final
2023-08-21 10:07:47	ga_s2am_ard_3-2-1_54HWC_2023-08-21_final
2023-08-21 11:41:03	ga_s2am_ard_3-2-1_51LWG_2023-08-21_final
2023-08-21 11:41:07	ga_s2am_ard_3-2-1_51LVG_2023-08-21_final
2023-08-21 11:41:21	ga_s2am_ard_3-2-1_51LVF_2023-08-21_final
2023-08-21 11:41:24	ga_s2am_ard_3-2-1_51LUF_2023-08-21_final
2023-08-21 11:41:32	ga_s2am_ard_3-2-1_51LWE_2023-08-21_final
2023-08-21 11:41:36	ga_s2am_ard_3-2-1_51LVE_2023-08-21_final
2023-08-21 11:41:53	ga_s2am_ard_3-2-1_51LUD_2023-08-21_final
2023-08-21 11:42:05	ga_s2am_ard_3-2-1_51LVC_2023-08-21_final
2023-08-21 11:42:19	ga_s2am_ard_3-2-1_51KVB_2023-08-21_final
2023-08-21 11:43:06	ga_s2am_ard_3-2-1_51KUU_2023-08-21_final
2023-08-21 11:43:24	ga_s2am_ard_3-2-1_51KTT_2023-08-21_final
2023-08-21 11:43:24	ga_s2am_ard_3-2-1_50KRC_2023-08-21_final
2023-08-21 11:43:31	ga_s2am_ard_3-2-1_51KVS_2023-08-21_final
2023-08-21 11:43:35	ga_s2am_ard_3-2-1_51KUS_2023-08-21_final
2023-08-21 11:43:38	ga_s2am_ard_3-2-1_51KTS_2023-08-21_final
2023-08-21 11:43:42	ga_s2am_ard_3-2-1_50KQB_2023-08-21_final
2023-08-21 11:43:53	ga_s2am_ard_3-2-1_51KTR_2023-08-21_final
2023-08-21 11:44:04	ga_s2am_ard_3-2-1_51KUQ_2023-08-21_final
2023-08-21 11:44:08	ga_s2am_ard_3-2-1_51KTQ_2023-08-21_final
2023-08-21 11:44:08	ga_s2am_ard_3-2-1_50KRV_2023-08-21_final
2023-08-21 11:44:11	ga_s2am_ard_3-2-1_50KQV_2023-08-21_final
2023-08-21 11:44:19	ga_s2am_ard_3-2-1_51KUP_2023-08-21_final
2023-08-21 11:44:29	ga_s2am_ard_3-2-1_50KPU_2023-08-21_final
2023-08-21 11:44:33	ga_s2am_ard_3-2-1_51JUN_2023-08-21_final
2023-08-21 11:44:36	ga_s2am_ard_3-2-1_50JRT_2023-08-21_final
2023-08-21 11:44:40	ga_s2am_ard_3-2-1_51JUN_2023-08-21_final
2023-08-21 11:44:42	ga_s2am_ard_3-2-1_51JTN_2023-08-21_final
2023-08-21 11:44:44	ga_s2am_ard_3-2-1_50JQT_2023-08-21_final
2023-08-21 11:45:17	ga_s2am_ard_3-2-1_50JNR_2023-08-21_final
2023-08-21 11:45:27	ga_s2am_ard_3-2-1_50JPQ_2023-08-21_final
2023-08-21 11:45:35	ga_s2am_ard_3-2-1_51JTJ_2023-08-21_final
2023-08-21 11:45:38	ga_s2am_ard_3-2-1_50JQP_2023-08-21_final
2023-08-21 11:45:45	ga_s2am_ard_3-2-1_50JNP_2023-08-21_final
2023-08-21 11:45:49	ga_s2am_ard_3-2-1_51JTH_2023-08-21_final
2023-08-21 11:45:52	ga_s2am_ard_3-2-1_50JQN_2023-08-21_final
2023-08-21 11:46:00	ga_s2am_ard_3-2-1_50JNN_2023-08-21_final
2023-08-21 11:46:07	ga_s2am_ard_3-2-1_50JQM_2023-08-21_final
2023-08-21 11:46:25	ga_s2am_ard_3-2-1_50JPL_2023-08-21_final
2023-08-21 11:46:32	ga_s2am_ard_3-2-1_50JML_2023-08-21_final
2023-08-21 11:46:43	ga_s2am_ard_3-2-1_50HNK_2023-08-21_final
2023-08-21 11:46:54	ga_s2am_ard_3-2-1_50HPJ_2023-08-21_final
2023-08-21 11:46:58	ga_s2am_ard_3-2-1_50HNJ_2023-08-21_final
2023-08-21 11:47:02	ga_s2am_ard_3-2-1_50HMJ_2023-08-21_final
2023-08-21 11:47:23	ga_s2am_ard_3-2-1_50HPG_2023-08-21_final
2023-08-31 11:40:54	ga_s2am_ard_3-2-1_51LUH_2023-08-31_nrt
2023-08-31 11:41:49	ga_s2am_ard_3-2-1_51LVD_2023-08-31_nrt
2023-08-31 11:42:10	ga_s2am_ard_3-2-1_51LTC_2023-08-31_nrt
2023-09-01 09:33:15	ga_s2am_ard_3-2-1_56KMV_2023-09-01_nrt
2023-09-01 09:33:35	ga_s2am_ard_3-2-1_56JPT_2023-09-01_nrt
2023-09-01 09:33:45	ga_s2am_ard_3-2-1_56JPS_2023-09-01_nrt
2023-09-01 09:37:30	ga_s2am_ard_3-2-1_55HGT_2023-09-01_nrt
2023-09-01 09:37:44	ga_s2am_ard_3-2-1_55HGS_2023-09-01_nrt
2023-09-01 09:37:59	ga_s2am_ard_3-2-1_56GKA_2023-09-01_nrt
2023-09-01 09:37:59	ga_s2am_ard_3-2-1_55GGR_2023-09-01_nrt
2023-09-01 09:38:13	ga_s2am_ard_3-2-1_56GKV_2023-09-01_nrt
2023-09-01 09:38:13	ga_s2am_ard_3-2-1_55GGQ_2023-09-01_nrt
2023-09-01 09:38:24	ga_s2am_ard_3-2-1_55GGP_2023-09-01_nrt
2023-09-01 09:38:25	ga_s2am_ard_3-2-1_56GKU_2023-09-01_nrt
2023-09-01 09:39:01	ga_s2am_ard_3-2-1_55GFM_2023-09-01_nrt
2023-09-01 09:39:08	ga_s2am_ard_3-2-1_55GFM_2023-09-01_nrt
2023-09-01 11:10:20	ga_s2am_ard_3-2-1_52LGP_2023-09-01_nrt
2023-09-01 11:11:02	ga_s2am_ard_3-2-1_52LDM_2023-09-01_nrt
2023-09-01 11:11:13	ga_s2am_ard_3-2-1_52LDL_2023-09-01_nrt
2023-09-01 11:11:27	ga_s2am_ard_3-2-1_52LDK_2023-09-01_nrt
2023-09-01 11:16:33	ga_s2am_ard_3-2-1_52HCJ_2023-09-01_nrt
2023-09-01 11:16:39	ga_s2am_ard_3-2-1_52HBJ_2023-09-01_nrt
2023-09-01 11:16:54	ga_s2am_ard_3-2-1_52HBH_2023-09-01_nrt
2023-09-01 11:16:56	ga_s2am_ard_3-2-1_51HYC_2023-09-01_nrt
2023-09-01 11:17:07	ga_s2am_ard_3-2-1_52HBG_2023-09-01_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