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
2023-08-20 12:14:04	ga_s2am_ard_3-2-1_49KGR_2023-08-20_final
2023-08-20 12:14:08	ga_s2am_ard_3-2-1_49KFR_2023-08-20_nrt
2023-08-20 12:14:14	ga_s2am_ard_3-2-1_50KKV_2023-08-20_final
2023-08-20 12:14:15	ga_s2am_ard_3-2-1_49KHQ_2023-08-20_final
2023-08-20 12:14:19	ga_s2am_ard_3-2-1_49KGQ_2023-08-20_final
2023-08-20 12:14:22	ga_s2am_ard_3-2-1_49KFQ_2023-08-20_nrt
2023-08-20 12:14:25	ga_s2am_ard_3-2-1_50KKU_2023-08-20_final
2023-08-20 12:14:27	ga_s2am_ard_3-2-1_49KHP_2023-08-20_final
2023-08-20 12:14:33	ga_s2am_ard_3-2-1_49KGP_2023-08-20_final
2023-08-20 12:14:37	ga_s2am_ard_3-2-1_49JHN_2023-08-20_final
2023-08-20 12:14:37	ga_s2am_ard_3-2-1_49KFP_2023-08-20_nrt
2023-08-20 12:14:47	ga_s2am_ard_3-2-1_49JGN_2023-08-20_final
2023-08-20 12:14:51	ga_s2am_ard_3-2-1_49JFN_2023-08-20_final
2023-08-20 12:15:02	ga_s2am_ard_3-2-1_49JGM_2023-08-20_final
2023-08-20 12:15:06	ga_s2am_ard_3-2-1_49JFM_2023-08-20_final
2023-08-20 12:15:16	ga_s2am_ard_3-2-1_49JGL_2023-08-20_final
2023-08-20 12:15:20	ga_s2am_ard_3-2-1_49JFL_2023-08-20_nrt
2023-08-20 12:15:25	ga_s2am_ard_3-2-1_49JGK_2023-08-20_final
2023-08-20 12:15:27	ga_s2am_ard_3-2-1_49JFK_2023-08-20_nrt
2023-08-21 08:24:31	ga_s2am_ard_3-2-1_59JKH_2023-08-20_final
2023-08-21 08:24:32	ga_s2am_ard_3-2-1_58JGN_2023-08-20_final
2023-08-21 08:31:48	ga_s2am_ard_3-2-1_57FVV_2023-08-20_final
2023-08-21 09:59:44	ga_s2am_ard_3-2-1_55LHJ_2023-08-21_nrt
2023-08-21 09:59:50	ga_s2am_ard_3-2-1_55LGJ_2023-08-21_nrt
2023-08-21 09:59:53	ga_s2am_ard_3-2-1_55LFJ_2023-08-21_nrt
2023-08-21 09:59:54	ga_s2am_ard_3-2-1_55LHH_2023-08-21_nrt
2023-08-21 09:59:57	ga_s2am_ard_3-2-1_55LEJ_2023-08-21_nrt
2023-08-21 10:00:04	ga_s2am_ard_3-2-1_55LGH_2023-08-21_nrt
2023-08-21 10:00:08	ga_s2am_ard_3-2-1_55LFH_2023-08-21_nrt
2023-08-21 10:00:11	ga_s2am_ard_3-2-1_55LEH_2023-08-21_nrt
2023-08-21 10:00:15	ga_s2am_ard_3-2-1_55LDH_2023-08-21_nrt
2023-08-21 10:00:19	ga_s2am_ard_3-2-1_55LGG_2023-08-21_nrt
2023-08-21 10:00:22	ga_s2am_ard_3-2-1_55LFG_2023-08-21_nrt
2023-08-21 10:00:25	ga_s2am_ard_3-2-1_55LEG_2023-08-21_nrt
2023-08-21 10:00:28	ga_s2am_ard_3-2-1_55LDG_2023-08-21_nrt
2023-08-21 10:00:33	ga_s2am_ard_3-2-1_55LGF_2023-08-21_nrt
2023-08-21 10:00:37	ga_s2am_ard_3-2-1_55LFF_2023-08-21_nrt
2023-08-21 10:00:40	ga_s2am_ard_3-2-1_55LEF_2023-08-21_nrt
2023-08-21 10:00:43	ga_s2am_ard_3-2-1_55LDF_2023-08-21_nrt
2023-08-21 10:00:47	ga_s2am_ard_3-2-1_55LGE_2023-08-21_nrt
2023-08-21 10:00:51	ga_s2am_ard_3-2-1_55LFE_2023-08-21_nrt
2023-08-21 10:00:55	ga_s2am_ard_3-2-1_55LEE_2023-08-21_nrt
2023-08-21 10:00:57	ga_s2am_ard_3-2-1_55LGD_2023-08-21_nrt
2023-08-21 10:00:58	ga_s2am_ard_3-2-1_55LDE_2023-08-21_nrt
2023-08-21 10:01:05	ga_s2am_ard_3-2-1_55LFD_2023-08-21_nrt
2023-08-21 10:01:09	ga_s2am_ard_3-2-1_55LED_2023-08-21_nrt
2023-08-21 10:01:12	ga_s2am_ard_3-2-1_55LDD_2023-08-21_nrt
2023-08-21 10:01:17	ga_s2am_ard_3-2-1_55LCD_2023-08-21_final
2023-08-21 10:01:20	ga_s2am_ard_3-2-1_55LFC_2023-08-21_final
2023-08-21 10:01:24	ga_s2am_ard_3-2-1_55LEC_2023-08-21_final
2023-08-21 10:01:27	ga_s2am_ard_3-2-1_55LDC_2023-08-21_nrt
2023-08-21 10:01:30	ga_s2am_ard_3-2-1_55LCC_2023-08-21_final
2023-08-21 10:01:35	ga_s2am_ard_3-2-1_55KFB_2023-08-21_final
2023-08-21 10:01:38	ga_s2am_ard_3-2-1_55KEB_2023-08-21_final
2023-08-21 10:01:42	ga_s2am_ard_3-2-1_55KDB_2023-08-21_final
2023-08-21 10:01:44	ga_s2am_ard_3-2-1_55KCB_2023-08-21_final
2023-08-21 10:06:02	ga_s2am_ard_3-2-1_54HXK_2023-08-21_final
2023-08-21 10:06:10	ga_s2am_ard_3-2-1_55HBD_2023-08-21_final
2023-08-21 10:06:12	ga_s2am_ard_3-2-1_54HYJ_2023-08-21_final
2023-08-21 10:06:16	ga_s2am_ard_3-2-1_54HXJ_2023-08-21_final
2023-08-21 10:06:26	ga_s2am_ard_3-2-1_54HYH_2023-08-21_final
2023-08-21 10:06:31	ga_s2am_ard_3-2-1_54HXH_2023-08-21_final
2023-08-21 10:06:40	ga_s2am_ard_3-2-1_54HVH_2023-08-21_final
2023-08-21 10:06:41	ga_s2am_ard_3-2-1_54HYG_2023-08-21_final
2023-08-21 10:06:45	ga_s2am_ard_3-2-1_54HXG_2023-08-21_final
2023-08-21 10:06:52	ga_s2am_ard_3-2-1_54HVG_2023-08-21_final
2023-08-21 10:06:56	ga_s2am_ard_3-2-1_54HYF_2023-08-21_final
2023-08-21 10:07:01	ga_s2am_ard_3-2-1_55HBV_2023-08-21_final
2023-08-21 10:07:07	ga_s2am_ard_3-2-1_54HVF_2023-08-21_final
2023-08-21 10:07:09	ga_s2am_ard_3-2-1_54HYE_2023-08-21_final
2023-08-21 10:07:20	ga_s2am_ard_3-2-1_54HYD_2023-08-21_final
2023-08-21 10:07:21	ga_s2am_ard_3-2-1_54HVE_2023-08-21_final
2023-08-21 11:46:11	ga_s2am_ard_3-2-1_50JPM_2023-08-21_final
2023-08-21 11:46:13	ga_s2am_ard_3-2-1_51JTF_2023-08-21_final
2023-08-21 11:46:14	ga_s2am_ard_3-2-1_50JNM_2023-08-21_final
2023-08-21 11:46:19	ga_s2am_ard_3-2-1_50JMM_2023-08-21_final
2023-08-21 11:46:21	ga_s2am_ard_3-2-1_50JQL_2023-08-21_final
2023-08-21 11:46:25	ga_s2am_ard_3-2-1_50JPL_2023-08-21_final
2023-08-21 11:46:29	ga_s2am_ard_3-2-1_50JNL_2023-08-21_final
2023-08-21 11:46:32	ga_s2am_ard_3-2-1_50JML_2023-08-21_final
2023-08-21 11:46:36	ga_s2am_ard_3-2-1_50HQK_2023-08-21_final
2023-08-21 11:46:40	ga_s2am_ard_3-2-1_50HPK_2023-08-21_final
2023-08-21 11:46:43	ga_s2am_ard_3-2-1_50HNK_2023-08-21_final
2023-08-21 11:46:47	ga_s2am_ard_3-2-1_50HMK_2023-08-21_final
2023-08-21 11:46:49	ga_s2am_ard_3-2-1_50HQJ_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 11:46:59	ga_s2am_ard_3-2-1_50HQH_2023-08-21_final
2023-08-21 11:47:02	ga_s2am_ard_3-2-1_50HMJ_2023-08-21_final
2023-08-21 11:47:08	ga_s2am_ard_3-2-1_50HPH_2023-08-21_final
2023-08-21 11:47:12	ga_s2am_ard_3-2-1_50HNH_2023-08-21_final
2023-08-21 11:47:16	ga_s2am_ard_3-2-1_50HMH_2023-08-21_final
2023-08-21 11:47:20	ga_s2am_ard_3-2-1_50HLH_2023-08-21_final
2023-08-21 11:47:23	ga_s2am_ard_3-2-1_50HPG_2023-08-21_final
2023-08-21 11:47:27	ga_s2am_ard_3-2-1_50HNG_2023-08-21_final
2023-08-21 11:47:30	ga_s2am_ard_3-2-1_50HMG_2023-08-21_final
2023-08-21 11:47:33	ga_s2am_ard_3-2-1_50HLG_2023-08-21_final
2023-08-21 11:47:34	ga_s2am_ard_3-2-1_50HPF_2023-08-21_nrt
2023-08-21 11:47:36	ga_s2am_ard_3-2-1_50HNF_2023-08-21_nrt
2023-08-21 11:47:38	ga_s2am_ard_3-2-1_50HMF_2023-08-21_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