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
2022-10-21 12:05:21	ga_s2am_ard_3-2-1_49JFL_2022-10-21_final
2022-11-10 12:05:23	ga_s2am_ard_3-2-1_49JFL_2022-11-10_final
2022-12-20 12:05:18	ga_s2am_ard_3-2-1_49JFL_2022-12-20_final
2022-12-30 12:05:18	ga_s2am_ard_3-2-1_49JFL_2022-12-30_final
2023-02-08 12:05:18	ga_s2am_ard_3-2-1_49JFL_2023-02-08_final
2023-02-28 12:05:17	ga_s2am_ard_3-2-1_49JFL_2023-02-28_final
2023-03-30 12:05:17	ga_s2am_ard_3-2-1_49JFL_2023-03-30_final
2023-04-09 12:05:19	ga_s2am_ard_3-2-1_49JFL_2023-04-09_final
2023-04-29 12:05:19	ga_s2am_ard_3-2-1_49JFL_2023-04-29_final
2023-05-19 12:05:21	ga_s2am_ard_3-2-1_49JFL_2023-05-19_final
2023-06-08 12:05:23	ga_s2am_ard_3-2-1_49JFL_2023-06-08_final
2023-06-28 12:05:23	ga_s2am_ard_3-2-1_49JFL_2023-06-28_final
2023-07-08 12:05:24	ga_s2am_ard_3-2-1_49JFL_2023-07-08_final
2023-07-18 12:05:24	ga_s2am_ard_3-2-1_49JFL_2023-07-18_final
2023-07-28 12:05:24	ga_s2am_ard_3-2-1_49JFL_2023-07-28_final
2023-08-17 12:05:25	ga_s2am_ard_3-2-1_49JFL_2023-08-17_final
2023-08-27 12:05:25	ga_s2am_ard_3-2-1_49JFL_2023-08-27_final
2023-09-06 12:05:24	ga_s2am_ard_3-2-1_49JFL_2023-09-06_final
2023-10-26 12:05:19	ga_s2am_ard_3-2-1_49JFL_2023-10-26_final
2023-11-28 12:13:37	ga_s2am_ard_3-2-1_49KGS_2023-11-28_final
2023-11-28 12:15:06	ga_s2am_ard_3-2-1_49JFL_2023-11-28_final
2023-12-02 11:57:16	ga_s2am_ard_3-2-1_50HKG_2023-12-02_final
2023-12-02 11:57:19	ga_s2am_ard_3-2-1_50HMF_2023-12-02_final
2023-12-05 12:05:12	ga_s2am_ard_3-2-1_49JFL_2023-12-05_final
2023-12-08 12:13:38	ga_s2am_ard_3-2-1_49KGS_2023-12-08_final
2023-12-08 12:15:08	ga_s2am_ard_3-2-1_49JFL_2023-12-08_final
2023-12-09 11:47:26	ga_s2am_ard_3-2-1_50HMF_2023-12-09_final
2023-12-12 11:57:19	ga_s2am_ard_3-2-1_50HKG_2023-12-12_final
2023-12-12 11:57:22	ga_s2am_ard_3-2-1_50HMF_2023-12-12_final
2023-12-18 12:13:40	ga_s2am_ard_3-2-1_49KGS_2023-12-18_final
2023-12-18 12:15:10	ga_s2am_ard_3-2-1_49JFL_2023-12-18_final
2023-12-19 11:47:28	ga_s2am_ard_3-2-1_50HMF_2023-12-19_final
2023-12-22 11:57:20	ga_s2am_ard_3-2-1_50HKG_2023-12-22_final
2023-12-22 11:57:23	ga_s2am_ard_3-2-1_50HMF_2023-12-22_final
2023-12-25 12:05:16	ga_s2am_ard_3-2-1_49JFL_2023-12-25_final
2023-12-28 12:13:41	ga_s2am_ard_3-2-1_49KGS_2023-12-28_final
2023-12-28 12:15:11	ga_s2am_ard_3-2-1_49JFL_2023-12-28_final
2023-12-29 11:47:30	ga_s2am_ard_3-2-1_50HMF_2023-12-29_final
2024-01-01 11:57:21	ga_s2am_ard_3-2-1_50HKG_2024-01-01_final
2024-01-07 12:13:40	ga_s2am_ard_3-2-1_49KGS_2024-01-07_final
2024-01-07 12:15:10	ga_s2am_ard_3-2-1_49JFL_2024-01-07_final
2024-01-11 11:57:19	ga_s2am_ard_3-2-1_50HKG_2024-01-11_final
2024-01-11 11:57:22	ga_s2am_ard_3-2-1_50HMF_2024-01-11_final
2024-01-14 12:05:13	ga_s2am_ard_3-2-1_49JFL_2024-01-14_final
2024-01-17 12:13:36	ga_s2am_ard_3-2-1_49KGS_2024-01-17_final
2024-01-17 12:15:06	ga_s2am_ard_3-2-1_49JFL_2024-01-17_final
2024-01-21 11:57:16	ga_s2am_ard_3-2-1_50HKG_2024-01-21_final
2024-01-21 11:57:19	ga_s2am_ard_3-2-1_50HMF_2024-01-21_final
2024-01-27 12:13:38	ga_s2am_ard_3-2-1_49KGS_2024-01-27_final
2024-01-27 12:15:08	ga_s2am_ard_3-2-1_49JFL_2024-01-27_final
2024-01-28 11:47:26	ga_s2am_ard_3-2-1_50HMF_2024-01-28_final
2024-01-31 11:57:19	ga_s2am_ard_3-2-1_50HKG_2024-01-31_final
2024-02-06 12:13:40	ga_s2am_ard_3-2-1_49KGS_2024-02-06_final
2024-02-06 12:15:10	ga_s2am_ard_3-2-1_49JFL_2024-02-06_final
2024-02-10 11:57:20	ga_s2am_ard_3-2-1_50HKG_2024-02-10_final
2024-02-16 12:13:42	ga_s2am_ard_3-2-1_49KGS_2024-02-16_final
2024-02-16 12:15:12	ga_s2am_ard_3-2-1_49JFL_2024-02-16_final
2024-02-20 11:57:22	ga_s2am_ard_3-2-1_50HKG_2024-02-20_final
2024-02-26 12:13:43	ga_s2am_ard_3-2-1_49KGS_2024-02-26_final
2024-02-26 12:15:13	ga_s2am_ard_3-2-1_49JFL_2024-02-26_final
2024-03-01 11:57:24	ga_s2am_ard_3-2-1_50HKG_2024-03-01_final
2024-03-04 12:05:19	ga_s2am_ard_3-2-1_49JFL_2024-03-04_final
2024-03-07 12:13:44	ga_s2am_ard_3-2-1_49KGS_2024-03-07_final
2024-03-07 12:15:14	ga_s2am_ard_3-2-1_49JFL_2024-03-07_final
2024-03-11 11:57:24	ga_s2am_ard_3-2-1_50HKG_2024-03-11_final
2024-03-14 12:05:19	ga_s2am_ard_3-2-1_49JFL_2024-03-14_final
2024-03-17 12:13:44	ga_s2am_ard_3-2-1_49KGS_2024-03-17_final
2024-03-17 12:15:14	ga_s2am_ard_3-2-1_49JFL_2024-03-17_final
2024-03-21 11:57:25	ga_s2am_ard_3-2-1_50HKG_2024-03-21_final
2024-03-21 11:57:28	ga_s2am_ard_3-2-1_50HMF_2024-03-21_final
2024-03-24 12:05:20	ga_s2am_ard_3-2-1_49JFL_2024-03-24_final
2024-03-27 12:13:40	ga_s2am_ard_3-2-1_49KHS_2024-03-27_final
2024-03-27 12:13:44	ga_s2am_ard_3-2-1_49KGS_2024-03-27_final
2024-03-27 12:13:59	ga_s2am_ard_3-2-1_49KGR_2024-03-27_final
2024-03-27 12:14:09	ga_s2am_ard_3-2-1_49KHQ_2024-03-27_final
2024-03-27 12:14:21	ga_s2am_ard_3-2-1_49KHP_2024-03-27_final
2024-03-27 12:14:31	ga_s2am_ard_3-2-1_49JHN_2024-03-27_final
2024-03-27 12:14:42	ga_s2am_ard_3-2-1_49JGN_2024-03-27_final
2024-03-27 12:15:11	ga_s2am_ard_3-2-1_49JGL_2024-03-27_final
2024-03-27 12:15:14	ga_s2am_ard_3-2-1_49JFL_2024-03-27_final
2024-03-27 12:15:19	ga_s2am_ard_3-2-1_49JGK_2024-03-27_final
2024-03-28 11:47:14	ga_s2am_ard_3-2-1_50HLH_2024-03-28_final
2024-03-28 11:47:32	ga_s2am_ard_3-2-1_50HMF_2024-03-28_final
2024-03-31 11:56:39	ga_s2am_ard_3-2-1_50HLK_2024-03-31_final
2024-03-31 11:56:54	ga_s2am_ard_3-2-1_50HLJ_2024-03-31_final
2024-03-31 11:57:08	ga_s2am_ard_3-2-1_50HLH_2024-03-31_final
2024-03-31 11:57:23	ga_s2am_ard_3-2-1_50HKG_2024-03-31_final
2024-03-31 11:57:26	ga_s2am_ard_3-2-1_50HMF_2024-03-31_final
2024-04-03 12:03:49	ga_s2am_ard_3-2-1_49KHS_2024-04-03_final
2024-04-03 12:05:17	ga_s2am_ard_3-2-1_49JFL_2024-04-03_final
2024-04-16 12:13:28	ga_s2am_ard_3-2-1_49KFU_2024-04-16_nrt
2024-04-16 12:13:31	ga_s2am_ard_3-2-1_49KHT_2024-04-16_nrt
2024-04-16 12:13:33	ga_s2am_ard_3-2-1_49KGT_2024-04-16_nrt
2024-04-16 12:13:36	ga_s2am_ard_3-2-1_49KFT_2024-04-16_nrt
2024-04-16 12:13:46	ga_s2am_ard_3-2-1_49KGS_2024-04-16_nrt
2024-04-16 12:13:50	ga_s2am_ard_3-2-1_49KFS_2024-04-16_nrt
2024-04-16 12:14:04	ga_s2am_ard_3-2-1_49KFR_2024-04-16_nrt
2024-04-16 12:14:19	ga_s2am_ard_3-2-1_49KFQ_2024-04-16_nrt
2024-04-16 12:14:33	ga_s2am_ard_3-2-1_49KFP_2024-04-16_nrt
2024-04-16 12:15:17	ga_s2am_ard_3-2-1_49JFL_2024-04-16_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