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
2024-02-13 10:23:59	ga_s2am_ard_3-2-1_54JUT_2024-02-13_final
2024-02-13 10:24:01	ga_s2am_ard_3-2-1_53JRN_2024-02-13_final
2024-02-13 10:24:06	ga_s2am_ard_3-2-1_54JWS_2024-02-13_final
2024-02-13 10:24:09	ga_s2am_ard_3-2-1_54JVS_2024-02-13_final
2024-02-13 10:24:13	ga_s2am_ard_3-2-1_53JRM_2024-02-13_final
2024-02-13 10:24:13	ga_s2am_ard_3-2-1_54JTS_2024-02-13_final
2024-02-13 10:24:14	ga_s2am_ard_3-2-1_54JWS_2024-02-13_final
2024-02-13 10:24:16	ga_s2am_ard_3-2-1_54JVS_2024-02-13_final
2024-02-13 10:24:18	ga_s2am_ard_3-2-1_54JUS_2024-02-13_final
2024-02-13 10:24:19	ga_s2am_ard_3-2-1_53JRM_2024-02-13_final
2024-02-13 10:24:24	ga_s2am_ard_3-2-1_54JVR_2024-02-13_final
2024-02-13 10:24:28	ga_s2am_ard_3-2-1_54JWQ_2024-02-13_final
2024-02-13 10:24:31	ga_s2am_ard_3-2-1_54JTR_2024-02-13_final
2024-02-13 10:24:37	ga_s2am_ard_3-2-1_53JQL_2024-02-13_final
2024-02-13 10:24:39	ga_s2am_ard_3-2-1_54JVQ_2024-02-13_final
2024-02-13 10:24:45	ga_s2am_ard_3-2-1_54JTQ_2024-02-13_final
2024-02-13 10:24:49	ga_s2am_ard_3-2-1_53JQK_2024-02-13_final
2024-02-13 10:24:53	ga_s2am_ard_3-2-1_54JVP_2024-02-13_final
2024-02-13 10:24:57	ga_s2am_ard_3-2-1_54JUP_2024-02-13_final
2024-02-13 10:25:00	ga_s2am_ard_3-2-1_54JTP_2024-02-13_final
2024-02-13 10:25:03	ga_s2am_ard_3-2-1_53JQJ_2024-02-13_final
2024-02-13 10:25:08	ga_s2am_ard_3-2-1_54JVN_2024-02-13_final
2024-02-13 10:25:11	ga_s2am_ard_3-2-1_54JUN_2024-02-13_final
2024-02-13 10:25:15	ga_s2am_ard_3-2-1_54JTN_2024-02-13_final
2024-02-13 10:25:17	ga_s2am_ard_3-2-1_53JQH_2024-02-13_final
2024-02-13 10:25:21	ga_s2am_ard_3-2-1_54JVM_2024-02-13_final
2024-02-13 10:25:26	ga_s2am_ard_3-2-1_54JUM_2024-02-13_final
2024-02-13 10:25:29	ga_s2am_ard_3-2-1_54JTM_2024-02-13_final
2024-02-13 10:25:32	ga_s2am_ard_3-2-1_53JQG_2024-02-13_final
2024-02-13 10:25:33	ga_s2am_ard_3-2-1_54JVL_2024-02-13_final
2024-02-13 10:25:37	ga_s2am_ard_3-2-1_53JPG_2024-02-13_final
2024-02-13 10:25:40	ga_s2am_ard_3-2-1_54JUL_2024-02-13_final
2024-02-13 10:25:44	ga_s2am_ard_3-2-1_54JTL_2024-02-13_final
2024-02-13 10:25:46	ga_s2am_ard_3-2-1_53JQF_2024-02-13_final
2024-02-13 10:25:50	ga_s2am_ard_3-2-1_53JPF_2024-02-13_final
2024-02-13 10:25:55	ga_s2am_ard_3-2-1_54HUK_2024-02-13_final
2024-02-13 10:25:58	ga_s2am_ard_3-2-1_54HTK_2024-02-13_final
2024-02-13 10:26:01	ga_s2am_ard_3-2-1_53HQE_2024-02-13_final
2024-02-13 10:26:04	ga_s2am_ard_3-2-1_53HPE_2024-02-13_final
2024-02-13 10:26:10	ga_s2am_ard_3-2-1_54HUJ_2024-02-13_final
2024-02-13 10:26:13	ga_s2am_ard_3-2-1_54HTJ_2024-02-13_final
2024-02-13 10:26:15	ga_s2am_ard_3-2-1_53HQD_2024-02-13_final
2024-02-13 10:26:19	ga_s2am_ard_3-2-1_53HPD_2024-02-13_final
2024-02-13 10:26:24	ga_s2am_ard_3-2-1_54HUH_2024-02-13_final
2024-02-13 10:26:28	ga_s2am_ard_3-2-1_54HTH_2024-02-13_final
2024-02-13 10:26:29	ga_s2am_ard_3-2-1_53HQC_2024-02-13_final
2024-02-13 10:26:33	ga_s2am_ard_3-2-1_53HPC_2024-02-13_final
2024-02-13 10:26:37	ga_s2am_ard_3-2-1_54HUG_2024-02-13_final
2024-02-13 10:26:38	ga_s2am_ard_3-2-1_53HNC_2024-02-13_final
2024-02-13 10:26:42	ga_s2am_ard_3-2-1_54HTG_2024-02-13_final
2024-02-13 10:26:44	ga_s2am_ard_3-2-1_53HQB_2024-02-13_final
2024-02-13 10:26:48	ga_s2am_ard_3-2-1_53HPB_2024-02-13_final
2024-02-13 10:26:48	ga_s2am_ard_3-2-1_54HUF_2024-02-13_final
2024-02-13 10:26:51	ga_s2am_ard_3-2-1_53HNB_2024-02-13_final
2024-02-13 10:26:56	ga_s2am_ard_3-2-1_54HTF_2024-02-13_final
2024-02-13 10:26:58	ga_s2am_ard_3-2-1_53HQA_2024-02-13_final
2024-02-13 10:27:02	ga_s2am_ard_3-2-1_53HPA_2024-02-13_final
2024-02-13 10:27:06	ga_s2am_ard_3-2-1_53HNA_2024-02-13_final
2024-02-13 10:27:08	ga_s2am_ard_3-2-1_54HTE_2024-02-13_final
2024-02-13 10:27:09	ga_s2am_ard_3-2-1_53HQV_2024-02-13_final
2024-02-13 10:27:11	ga_s2am_ard_3-2-1_53HPV_2024-02-13_final
2024-02-13 10:27:13	ga_s2am_ard_3-2-1_53HNV_2024-02-13_nrt
2024-02-13 12:00:21	ga_s2am_ard_3-2-1_50LRP_2024-02-13_nrt
2024-02-13 12:00:30	ga_s2am_ard_3-2-1_50LQP_2024-02-13_nrt
2024-02-13 12:00:34	ga_s2am_ard_3-2-1_50LPP_2024-02-13_nrt
2024-02-13 12:00:37	ga_s2am_ard_3-2-1_50LNP_2024-02-13_nrt
2024-02-13 12:00:41	ga_s2am_ard_3-2-1_50LMP_2024-02-13_nrt
2024-02-13 12:00:45	ga_s2am_ard_3-2-1_50LQN_2024-02-13_nrt
2024-02-13 12:00:48	ga_s2am_ard_3-2-1_50LPN_2024-02-13_nrt
2024-02-13 12:00:52	ga_s2am_ard_3-2-1_50LNN_2024-02-13_nrt
2024-02-13 12:00:55	ga_s2am_ard_3-2-1_50LMN_2024-02-13_nrt
2024-02-13 12:01:00	ga_s2am_ard_3-2-1_50LQM_2024-02-13_nrt
2024-02-13 12:01:03	ga_s2am_ard_3-2-1_50LPM_2024-02-13_nrt
2024-02-13 12:01:06	ga_s2am_ard_3-2-1_50LNM_2024-02-13_nrt
2024-02-13 12:01:09	ga_s2am_ard_3-2-1_50LMM_2024-02-13_nrt
2024-02-13 12:01:13	ga_s2am_ard_3-2-1_50LQL_2024-02-13_nrt
2024-02-13 12:01:17	ga_s2am_ard_3-2-1_50LPL_2024-02-13_nrt
2024-02-13 12:01:21	ga_s2am_ard_3-2-1_50LNL_2024-02-13_nrt
2024-02-13 12:01:24	ga_s2am_ard_3-2-1_50LQK_2024-02-13_nrt
2024-02-13 12:01:24	ga_s2am_ard_3-2-1_50LML_2024-02-13_nrt
2024-02-13 12:01:30	ga_s2am_ard_3-2-1_50LPK_2024-02-13_nrt
2024-02-13 12:01:32	ga_s2am_ard_3-2-1_50LNK_2024-02-13_nrt
2024-02-13 12:01:34	ga_s2am_ard_3-2-1_50LMK_2024-02-13_nrt
2024-02-13 12:02:52	ga_s2am_ard_3-2-1_50KNE_2024-02-13_nrt
2024-02-13 12:02:54	ga_s2am_ard_3-2-1_50KME_2024-02-13_nrt
2024-02-13 12:02:56	ga_s2am_ard_3-2-1_50KLE_2024-02-13_nrt
2024-02-13 12:02:59	ga_s2am_ard_3-2-1_50KKE_2024-02-13_nrt
2024-02-13 12:03:02	ga_s2am_ard_3-2-1_50KND_2024-02-13_nrt
2024-02-13 12:03:06	ga_s2am_ard_3-2-1_50KMD_2024-02-13_nrt
2024-02-13 12:03:09	ga_s2am_ard_3-2-1_50KLD_2024-02-13_nrt
2024-02-13 12:03:12	ga_s2am_ard_3-2-1_50KKD_2024-02-13_nrt
2024-02-13 12:03:15	ga_s2am_ard_3-2-1_49KHU_2024-02-13_nrt
2024-02-13 12:03:17	ga_s2am_ard_3-2-1_50KNC_2024-02-13_final
2024-02-13 12:03:21	ga_s2am_ard_3-2-1_50KMC_2024-02-13_final
2024-02-13 12:03:24	ga_s2am_ard_3-2-1_50KLC_2024-02-13_final
2024-02-13 12:03:27	ga_s2am_ard_3-2-1_50KKC_2024-02-13_final
2024-02-13 12:03:27	ga_s2am_ard_3-2-1_49KHT_2024-02-13_nrt
2024-02-13 12:03:30	ga_s2am_ard_3-2-1_50KNB_2024-02-13_final
2024-02-13 12:03:35	ga_s2am_ard_3-2-1_50KMB_2024-02-13_final
2024-02-13 12:03:38	ga_s2am_ard_3-2-1_50KLB_2024-02-13_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