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
2023-04-22 10:33:15	ga_s2am_ard_3-2-1_53KRR_2023-04-22_final
2023-04-22 10:33:30	ga_s2am_ard_3-2-1_54KTV_2023-04-22_final
2023-04-22 10:33:44	ga_s2am_ard_3-2-1_54KTU_2023-04-22_final
2023-04-22 10:33:44	ga_s2am_ard_3-2-1_53KRP_2023-04-22_final
2023-04-22 10:33:52	ga_s2am_ard_3-2-1_53KPP_2023-04-22_final
2023-04-22 10:35:00	ga_s2am_ard_3-2-1_53JQJ_2023-04-22_final
2023-04-22 10:35:04	ga_s2am_ard_3-2-1_53JPJ_2023-04-22_final
2023-04-22 10:35:07	ga_s2am_ard_3-2-1_54JTN_2023-04-22_final
2023-04-22 10:35:07	ga_s2am_ard_3-2-1_53JNJ_2023-04-22_final
2023-04-22 10:35:14	ga_s2am_ard_3-2-1_53JMJ_2023-04-22_final
2023-04-22 10:35:14	ga_s2am_ard_3-2-1_53JQH_2023-04-22_final
2023-04-22 10:35:18	ga_s2am_ard_3-2-1_53JPH_2023-04-22_final
2023-04-22 10:35:22	ga_s2am_ard_3-2-1_53JNH_2023-04-22_final
2023-04-22 10:35:25	ga_s2am_ard_3-2-1_53JMH_2023-04-22_final
2023-04-22 10:35:29	ga_s2am_ard_3-2-1_53JQG_2023-04-22_final
2023-04-22 10:35:33	ga_s2am_ard_3-2-1_53JPG_2023-04-22_final
2023-04-22 10:35:36	ga_s2am_ard_3-2-1_53JNG_2023-04-22_final
2023-04-22 10:35:40	ga_s2am_ard_3-2-1_53JMG_2023-04-22_final
2023-04-22 10:35:43	ga_s2am_ard_3-2-1_53JQF_2023-04-22_final
2023-04-22 10:35:47	ga_s2am_ard_3-2-1_53JPF_2023-04-22_final
2023-04-22 10:35:51	ga_s2am_ard_3-2-1_53JNF_2023-04-22_final
2023-04-22 10:35:54	ga_s2am_ard_3-2-1_53JMF_2023-04-22_final
2023-04-22 10:35:55	ga_s2am_ard_3-2-1_53HQE_2023-04-22_final
2023-04-22 10:36:01	ga_s2am_ard_3-2-1_53HPE_2023-04-22_final
2023-04-22 10:36:05	ga_s2am_ard_3-2-1_53HNE_2023-04-22_final
2023-04-22 10:36:09	ga_s2am_ard_3-2-1_53HME_2023-04-22_final
2023-04-22 10:36:15	ga_s2am_ard_3-2-1_53HLE_2023-04-22_final
2023-04-22 10:36:16	ga_s2am_ard_3-2-1_53HPD_2023-04-22_final
2023-04-22 10:36:20	ga_s2am_ard_3-2-1_53HND_2023-04-22_final
2023-04-22 10:36:23	ga_s2am_ard_3-2-1_53HMD_2023-04-22_final
2023-04-22 10:36:27	ga_s2am_ard_3-2-1_53HLD_2023-04-22_final
2023-04-22 10:36:31	ga_s2am_ard_3-2-1_53HPC_2023-04-22_final
2023-04-22 10:36:34	ga_s2am_ard_3-2-1_53HNC_2023-04-22_final
2023-04-22 10:36:38	ga_s2am_ard_3-2-1_53HMC_2023-04-22_final
2023-04-22 10:36:41	ga_s2am_ard_3-2-1_53HLC_2023-04-22_nrt
2023-04-22 10:36:45	ga_s2am_ard_3-2-1_53HPB_2023-04-22_final
2023-04-22 10:36:49	ga_s2am_ard_3-2-1_53HNB_2023-04-22_final
2023-04-22 10:36:53	ga_s2am_ard_3-2-1_53HMB_2023-04-22_final
2023-04-22 10:36:56	ga_s2am_ard_3-2-1_53HLB_2023-04-22_nrt
2023-04-22 10:36:57	ga_s2am_ard_3-2-1_53HPA_2023-04-22_final
2023-04-22 10:37:01	ga_s2am_ard_3-2-1_53HNA_2023-04-22_nrt
2023-04-22 10:37:03	ga_s2am_ard_3-2-1_53HMA_2023-04-22_nrt
2023-04-22 10:37:05	ga_s2am_ard_3-2-1_53HLA_2023-04-22_nrt
2023-04-22 12:10:26	ga_s2am_ard_3-2-1_50LNP_2023-04-22_nrt
2023-04-22 12:10:27	ga_s2am_ard_3-2-1_50LMP_2023-04-22_nrt
2023-04-22 12:13:22	ga_s2am_ard_3-2-1_49KGU_2023-04-22_nrt
2023-04-22 12:13:24	ga_s2am_ard_3-2-1_49KFU_2023-04-22_nrt
2023-04-22 12:13:27	ga_s2am_ard_3-2-1_50KKC_2023-04-22_nrt
2023-04-22 12:13:27	ga_s2am_ard_3-2-1_49KHT_2023-04-22_nrt
2023-04-22 12:13:29	ga_s2am_ard_3-2-1_49KGT_2023-04-22_nrt
2023-04-22 12:13:32	ga_s2am_ard_3-2-1_49KFT_2023-04-22_nrt
2023-04-22 12:13:38	ga_s2am_ard_3-2-1_50KKB_2023-04-22_final
2023-04-22 12:13:39	ga_s2am_ard_3-2-1_49KHS_2023-04-22_final
2023-04-22 12:13:43	ga_s2am_ard_3-2-1_49KGS_2023-04-22_nrt
2023-04-23 10:05:40	ga_s2am_ard_3-2-1_54JWL_2023-04-23_final
2023-04-23 10:05:42	ga_s2am_ard_3-2-1_55HBE_2023-04-23_final
2023-04-23 10:05:42	ga_s2am_ard_3-2-1_55JBF_2023-04-23_final
2023-04-23 10:05:43	ga_s2am_ard_3-2-1_54HYK_2023-04-23_final
2023-04-23 10:05:43	ga_s2am_ard_3-2-1_54JYL_2023-04-23_final
2023-04-23 10:05:45	ga_s2am_ard_3-2-1_54JXL_2023-04-23_final
2023-04-23 10:05:46	ga_s2am_ard_3-2-1_54JWL_2023-04-23_final
2023-04-23 10:05:49	ga_s2am_ard_3-2-1_55HBE_2023-04-23_final
2023-04-23 10:05:51	ga_s2am_ard_3-2-1_54HYK_2023-04-23_final
2023-04-23 10:05:55	ga_s2am_ard_3-2-1_54HXK_2023-04-23_final
2023-04-23 10:05:58	ga_s2am_ard_3-2-1_54HWK_2023-04-23_final
2023-04-23 10:06:03	ga_s2am_ard_3-2-1_55HBD_2023-04-23_final
2023-04-23 10:06:05	ga_s2am_ard_3-2-1_54HYJ_2023-04-23_final
2023-04-23 10:06:09	ga_s2am_ard_3-2-1_54HXJ_2023-04-23_final
2023-04-23 10:06:13	ga_s2am_ard_3-2-1_54HWJ_2023-04-23_final
2023-04-23 10:06:18	ga_s2am_ard_3-2-1_55HBC_2023-04-23_final
2023-04-23 10:06:19	ga_s2am_ard_3-2-1_54HYH_2023-04-23_final
2023-04-23 10:06:24	ga_s2am_ard_3-2-1_54HXH_2023-04-23_final
2023-04-23 10:06:27	ga_s2am_ard_3-2-1_54HWH_2023-04-23_final
2023-04-23 10:06:32	ga_s2am_ard_3-2-1_55HBB_2023-04-23_final
2023-04-23 10:06:33	ga_s2am_ard_3-2-1_54HVH_2023-04-23_final
2023-04-23 10:06:34	ga_s2am_ard_3-2-1_54HYG_2023-04-23_final
2023-04-23 10:06:38	ga_s2am_ard_3-2-1_54HXG_2023-04-23_final
2023-04-23 10:06:42	ga_s2am_ard_3-2-1_54HWG_2023-04-23_final
2023-04-23 10:06:44	ga_s2am_ard_3-2-1_55HBA_2023-04-23_final
2023-04-23 10:06:45	ga_s2am_ard_3-2-1_54HVG_2023-04-23_final
2023-04-23 10:06:49	ga_s2am_ard_3-2-1_54HYF_2023-04-23_final
2023-04-23 10:06:52	ga_s2am_ard_3-2-1_54HXF_2023-04-23_final
2023-04-23 10:06:54	ga_s2am_ard_3-2-1_55HBV_2023-04-23_final
2023-04-23 10:06:56	ga_s2am_ard_3-2-1_54HWF_2023-04-23_final
2023-04-23 10:07:00	ga_s2am_ard_3-2-1_54HVF_2023-04-23_final
2023-04-23 10:07:02	ga_s2am_ard_3-2-1_54HYE_2023-04-23_final
2023-04-23 10:07:07	ga_s2am_ard_3-2-1_54HXE_2023-04-23_final
2023-04-23 10:07:11	ga_s2am_ard_3-2-1_54HWE_2023-04-23_final
2023-04-23 10:07:13	ga_s2am_ard_3-2-1_54HYD_2023-04-23_final
2023-04-23 10:07:14	ga_s2am_ard_3-2-1_54HVE_2023-04-23_final
2023-04-23 10:07:21	ga_s2am_ard_3-2-1_54HXD_2023-04-23_final
2023-04-23 10:07:25	ga_s2am_ard_3-2-1_54HWD_2023-04-23_final
2023-04-23 10:07:29	ga_s2am_ard_3-2-1_54HVD_2023-04-23_final
2023-04-23 10:07:34	ga_s2am_ard_3-2-1_54HUD_2023-04-23_final
2023-04-23 10:07:36	ga_s2am_ard_3-2-1_54HXC_2023-04-23_final
2023-04-23 10:07:40	ga_s2am_ard_3-2-1_54HWC_2023-04-23_final
2023-04-23 10:07:43	ga_s2am_ard_3-2-1_54HVC_2023-04-23_final
2023-04-23 10:07:45	ga_s2am_ard_3-2-1_54HUC_2023-04-23_nrt
2023-04-23 10:07:46	ga_s2am_ard_3-2-1_54HXB_2023-04-23_nrt
2023-04-23 10:07:48	ga_s2am_ard_3-2-1_54HWB_2023-04-23_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