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
2019-06-27 11:26:26	ga_s2am_ard_3-2-1_51HXE_2019-06-27_final.stac-item
2019-06-27 11:26:30	ga_s2am_ard_3-2-1_51HWE_2019-06-27_final.stac-item
2019-06-27 11:26:34	ga_s2am_ard_3-2-1_51HVE_2019-06-27_final.stac-item
2019-06-27 11:26:37	ga_s2am_ard_3-2-1_51HUE_2019-06-27_final.stac-item
2019-06-29 10:26:02	ga_s2am_ard_3-2-1_54HUK_2019-06-29_final.stac-item
2019-06-29 10:26:06	ga_s2am_ard_3-2-1_54HTK_2019-06-29_final.stac-item
2019-06-29 10:26:08	ga_s2am_ard_3-2-1_53HQE_2019-06-29_final.stac-item
2019-06-29 10:26:12	ga_s2am_ard_3-2-1_53HPE_2019-06-29_final.stac-item
2019-06-29 10:26:17	ga_s2am_ard_3-2-1_54HUJ_2019-06-29_final.stac-item
2019-06-29 10:26:20	ga_s2am_ard_3-2-1_54HTJ_2019-06-29_final.stac-item
2019-06-29 10:26:22	ga_s2am_ard_3-2-1_53HQD_2019-06-29_final.stac-item
2019-06-29 10:26:26	ga_s2am_ard_3-2-1_53HPD_2019-06-29_final.stac-item
2019-06-30 11:36:28	ga_s2am_ard_3-2-1_51HVE_2019-06-30_final.stac-item
2019-06-30 11:36:33	ga_s2am_ard_3-2-1_51HUE_2019-06-30_final.stac-item
2019-06-30 11:36:36	ga_s2am_ard_3-2-1_51HTE_2019-06-30_final.stac-item
2019-06-30 11:36:39	ga_s2am_ard_3-2-1_50HQK_2019-06-30_final.stac-item
2019-06-30 11:36:42	ga_s2am_ard_3-2-1_50HPK_2019-06-30_final.stac-item
2019-06-30 11:36:47	ga_s2am_ard_3-2-1_51HUD_2019-06-30_final.stac-item
2019-06-30 11:36:51	ga_s2am_ard_3-2-1_51HTD_2019-06-30_final.stac-item
2019-06-30 11:36:53	ga_s2am_ard_3-2-1_50HQJ_2019-06-30_final.stac-item
2019-06-30 11:36:57	ga_s2am_ard_3-2-1_50HPJ_2019-06-30_final.stac-item
2019-07-06 10:16:00	ga_s2am_ard_3-2-1_54HWK_2019-07-06_final.stac-item
2019-07-06 10:16:04	ga_s2am_ard_3-2-1_54HVK_2019-07-06_final.stac-item
2019-07-06 10:16:07	ga_s2am_ard_3-2-1_54HUK_2019-07-06_final.stac-item
2019-07-06 10:16:21	ga_s2am_ard_3-2-1_54HUJ_2019-07-06_final.stac-item
2019-07-06 10:16:26	ga_s2am_ard_3-2-1_54HTJ_2019-07-06_final.stac-item
2019-07-07 11:26:27	ga_s2am_ard_3-2-1_51HXE_2019-07-07_final.stac-item
2019-07-07 11:26:31	ga_s2am_ard_3-2-1_51HWE_2019-07-07_final.stac-item
2019-07-07 11:26:34	ga_s2am_ard_3-2-1_51HVE_2019-07-07_final.stac-item
2019-07-07 11:26:37	ga_s2am_ard_3-2-1_51HUE_2019-07-07_final.stac-item
2019-07-07 11:26:52	ga_s2am_ard_3-2-1_51HUD_2019-07-07_final.stac-item
2019-07-09 10:26:21	ga_s2am_ard_3-2-1_54HTJ_2019-07-09_final.stac-item
2019-07-09 10:26:23	ga_s2am_ard_3-2-1_53HQD_2019-07-09_final.stac-item
2019-07-09 10:26:27	ga_s2am_ard_3-2-1_53HPD_2019-07-09_final.stac-item
2019-07-10 11:36:28	ga_s2am_ard_3-2-1_51HVE_2019-07-10_final.stac-item
2019-07-10 11:36:33	ga_s2am_ard_3-2-1_51HUE_2019-07-10_final.stac-item
2019-07-10 11:36:37	ga_s2am_ard_3-2-1_51HTE_2019-07-10_final.stac-item
2019-07-10 11:36:39	ga_s2am_ard_3-2-1_50HQK_2019-07-10_final.stac-item
2019-07-10 11:36:43	ga_s2am_ard_3-2-1_50HPK_2019-07-10_final.stac-item
2019-07-10 11:36:48	ga_s2am_ard_3-2-1_51HUD_2019-07-10_final.stac-item
2019-07-10 11:36:51	ga_s2am_ard_3-2-1_51HTD_2019-07-10_final.stac-item
2024-03-09 11:16:16	ga_s2am_ard_3-2-1_52HCK_2024-03-09_final
2024-03-09 11:16:20	ga_s2am_ard_3-2-1_52HBK_2024-03-09_final
2024-03-09 11:16:23	ga_s2am_ard_3-2-1_51HYE_2024-03-09_final
2024-03-09 11:16:27	ga_s2am_ard_3-2-1_51HXE_2024-03-09_final
2024-03-09 11:16:28	ga_s2am_ard_3-2-1_52HCJ_2024-03-09_nrt
2024-03-09 11:16:31	ga_s2am_ard_3-2-1_51HWE_2024-03-09_final
2024-03-09 11:16:35	ga_s2am_ard_3-2-1_52HBJ_2024-03-09_final
2024-03-09 11:16:37	ga_s2am_ard_3-2-1_51HYD_2024-03-09_final
2024-03-09 11:16:41	ga_s2am_ard_3-2-1_51HXD_2024-03-09_final
2024-03-15 11:36:23	ga_s2am_ard_3-2-1_51HVE_2024-03-15_final
2024-03-15 11:36:28	ga_s2am_ard_3-2-1_51HUE_2024-03-15_final
2024-03-15 11:36:31	ga_s2am_ard_3-2-1_51HTE_2024-03-15_final
2024-03-15 11:36:34	ga_s2am_ard_3-2-1_50HQK_2024-03-15_final
2024-03-15 11:36:37	ga_s2am_ard_3-2-1_50HPK_2024-03-15_final
2024-03-15 11:36:42	ga_s2am_ard_3-2-1_51HUD_2024-03-15_final
2024-03-15 11:36:46	ga_s2am_ard_3-2-1_51HTD_2024-03-15_final
2024-03-15 11:36:48	ga_s2am_ard_3-2-1_50HQJ_2024-03-15_final
2024-03-15 11:36:52	ga_s2am_ard_3-2-1_50HPJ_2024-03-15_final
2024-04-08 09:35:34	ga_s2am_ard_3-2-1_56HMK_2024-04-08_final
2024-04-08 09:35:38	ga_s2am_ard_3-2-1_56HLK_2024-04-08_final
2024-04-08 09:35:41	ga_s2am_ard_3-2-1_56HKK_2024-04-08_final
2024-04-08 09:35:43	ga_s2am_ard_3-2-1_55HGE_2024-04-08_final
2024-04-08 09:35:49	ga_s2am_ard_3-2-1_55HFE_2024-04-08_final
2024-04-08 09:35:52	ga_s2am_ard_3-2-1_56HLJ_2024-04-08_final
2024-04-08 09:35:56	ga_s2am_ard_3-2-1_56HKJ_2024-04-08_final
2024-04-08 09:35:58	ga_s2am_ard_3-2-1_55HGD_2024-04-08_final
2024-04-19 10:46:09	ga_s2am_ard_3-2-1_53HME_2024-04-19_final
2024-04-19 10:46:13	ga_s2am_ard_3-2-1_53HLE_2024-04-19_final
2024-04-19 10:46:16	ga_s2am_ard_3-2-1_53HKE_2024-04-19_final
2024-04-19 10:46:18	ga_s2am_ard_3-2-1_52HGK_2024-04-19_final
2024-04-19 10:46:27	ga_s2am_ard_3-2-1_53HLD_2024-04-19_final
2024-04-19 10:46:30	ga_s2am_ard_3-2-1_53HKD_2024-04-19_nrt
2024-04-19 10:46:31	ga_s2am_ard_3-2-1_52HGJ_2024-04-19_nrt
2024-04-20 11:56:40	ga_s2am_ard_3-2-1_50HMK_2024-04-20_final
2024-04-20 11:56:43	ga_s2am_ard_3-2-1_50HLK_2024-04-20_final
2024-04-20 11:56:47	ga_s2am_ard_3-2-1_50HKK_2024-04-20_nrt
2024-04-20 11:56:49	ga_s2am_ard_3-2-1_49HGE_2024-04-20_nrt
2024-04-20 11:56:58	ga_s2am_ard_3-2-1_50HLJ_2024-04-20_final
2024-04-20 11:57:01	ga_s2am_ard_3-2-1_50HKJ_2024-04-20_nrt
2024-04-20 11:57:03	ga_s2am_ard_3-2-1_49HGD_2024-04-20_nrt
2024-04-22 10:56:11	ga_s2am_ard_3-2-1_53HKE_2024-04-22_final
2024-04-22 10:56:14	ga_s2am_ard_3-2-1_52HGK_2024-04-22_final
2024-04-22 10:56:18	ga_s2am_ard_3-2-1_52HFK_2024-04-22_nrt
2024-04-22 10:56:21	ga_s2am_ard_3-2-1_52HEK_2024-04-22_nrt
2024-04-22 10:56:23	ga_s2am_ard_3-2-1_53HKD_2024-04-22_nrt
2024-04-22 10:56:25	ga_s2am_ard_3-2-1_52HGJ_2024-04-22_nrt
2024-04-22 10:56:26	ga_s2am_ard_3-2-1_52HDK_2024-04-22_final
2024-04-22 10:56:27	ga_s2am_ard_3-2-1_52HFJ_2024-04-22_nrt
2024-04-28 09:35:47	ga_s2am_ard_3-2-1_55HGE_2024-04-28_final
2024-04-28 09:35:52	ga_s2am_ard_3-2-1_55HFE_2024-04-28_final
2024-04-28 09:35:56	ga_s2am_ard_3-2-1_56HLJ_2024-04-28_final
2024-04-28 09:35:59	ga_s2am_ard_3-2-1_56HKJ_2024-04-28_final
2024-04-28 09:36:01	ga_s2am_ard_3-2-1_55HGD_2024-04-28_final
2024-04-28 09:36:05	ga_s2am_ard_3-2-1_55HFD_2024-04-28_final
2024-05-17 11:46:32	ga_s2am_ard_3-2-1_50HQK_2024-05-17_nrt
2024-05-17 11:46:36	ga_s2am_ard_3-2-1_50HPK_2024-05-17_nrt
2024-05-17 11:46:40	ga_s2am_ard_3-2-1_50HNK_2024-05-17_nrt
2024-05-17 11:46:43	ga_s2am_ard_3-2-1_50HMK_2024-05-17_nrt
2024-05-17 11:46:45	ga_s2am_ard_3-2-1_50HQJ_2024-05-17_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

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