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
2018-11-22 09:52:48	ga_s2am_ard_3-2-1_55KDS_2018-11-22_final.stac-item
2018-11-22 09:53:00	ga_s2am_ard_3-2-1_55KDR_2018-11-22_final.stac-item
2018-11-22 09:53:14	ga_s2am_ard_3-2-1_55KDQ_2018-11-22_final.stac-item
2018-11-22 09:53:29	ga_s2am_ard_3-2-1_55KDP_2018-11-22_final.stac-item
2018-11-22 09:53:44	ga_s2am_ard_3-2-1_55JDN_2018-11-22_final.stac-item
2018-11-22 09:53:58	ga_s2am_ard_3-2-1_55JDM_2018-11-22_final.stac-item
2018-11-22 09:54:13	ga_s2am_ard_3-2-1_55JDL_2018-11-22_final.stac-item
2018-11-22 09:54:27	ga_s2am_ard_3-2-1_55JDK_2018-11-22_final.stac-item
2018-11-22 09:54:38	ga_s2am_ard_3-2-1_55JEJ_2018-11-22_final.stac-item
2018-11-22 09:54:42	ga_s2am_ard_3-2-1_55JDJ_2018-11-22_final.stac-item
2018-11-22 09:54:53	ga_s2am_ard_3-2-1_55JEH_2018-11-22_final.stac-item
2018-11-22 09:54:56	ga_s2am_ard_3-2-1_55JDH_2018-11-22_final.stac-item
2018-11-22 09:55:07	ga_s2am_ard_3-2-1_55JEG_2018-11-22_final.stac-item
2018-11-22 09:55:11	ga_s2am_ard_3-2-1_55JDG_2018-11-22_final.stac-item
2018-11-22 09:55:22	ga_s2am_ard_3-2-1_55JEF_2018-11-22_final.stac-item
2018-11-22 09:55:25	ga_s2am_ard_3-2-1_55JDF_2018-11-22_final.stac-item
2018-11-22 09:55:36	ga_s2am_ard_3-2-1_55HEE_2018-11-22_final.stac-item
2018-11-22 09:55:40	ga_s2am_ard_3-2-1_55HDE_2018-11-22_final.stac-item
2018-11-22 09:55:47	ga_s2am_ard_3-2-1_55HED_2018-11-22_final.stac-item
2018-11-22 09:55:54	ga_s2am_ard_3-2-1_55HDD_2018-11-22_final.stac-item
2018-12-16 09:37:24	ga_s2am_ard_3-2-1_55HET_2018-12-16_final.stac-item
2018-12-16 09:37:31	ga_s2am_ard_3-2-1_55HDT_2018-12-16_final.stac-item
2018-12-16 09:37:39	ga_s2am_ard_3-2-1_55HES_2018-12-16_final.stac-item
2018-12-16 09:37:43	ga_s2am_ard_3-2-1_55HDS_2018-12-16_final.stac-item
2018-12-16 09:37:53	ga_s2am_ard_3-2-1_55GER_2018-12-16_final.stac-item
2018-12-16 09:37:57	ga_s2am_ard_3-2-1_55GDR_2018-12-16_final.stac-item
2018-12-19 09:45:10	ga_s2am_ard_3-2-1_55JEG_2018-12-19_final.stac-item
2018-12-19 09:45:17	ga_s2am_ard_3-2-1_55JDG_2018-12-19_final.stac-item
2018-12-19 09:45:24	ga_s2am_ard_3-2-1_55JEF_2018-12-19_final.stac-item
2018-12-19 09:45:28	ga_s2am_ard_3-2-1_55JDF_2018-12-19_final.stac-item
2018-12-19 09:45:39	ga_s2am_ard_3-2-1_55HEE_2018-12-19_final.stac-item
2018-12-19 09:45:42	ga_s2am_ard_3-2-1_55HDE_2018-12-19_final.stac-item
2018-12-19 09:45:53	ga_s2am_ard_3-2-1_55HED_2018-12-19_final.stac-item
2018-12-19 09:45:57	ga_s2am_ard_3-2-1_55HDD_2018-12-19_final.stac-item
2018-12-19 09:46:08	ga_s2am_ard_3-2-1_55HEC_2018-12-19_final.stac-item
2018-12-19 09:46:11	ga_s2am_ard_3-2-1_55HDC_2018-12-19_final.stac-item
2018-12-19 09:46:22	ga_s2am_ard_3-2-1_55HEB_2018-12-19_final.stac-item
2018-12-19 09:46:26	ga_s2am_ard_3-2-1_55HDB_2018-12-19_final.stac-item
2018-12-19 09:46:37	ga_s2am_ard_3-2-1_55HEA_2018-12-19_final.stac-item
2018-12-19 09:46:40	ga_s2am_ard_3-2-1_55HDA_2018-12-19_final.stac-item
2018-12-19 09:46:51	ga_s2am_ard_3-2-1_55HEV_2018-12-19_final.stac-item
2018-12-19 09:46:55	ga_s2am_ard_3-2-1_55HDV_2018-12-19_final.stac-item
2018-12-19 09:47:06	ga_s2am_ard_3-2-1_55HEU_2018-12-19_final.stac-item
2018-12-19 09:47:09	ga_s2am_ard_3-2-1_55HDU_2018-12-19_final.stac-item
2018-12-19 09:47:20	ga_s2am_ard_3-2-1_55HET_2018-12-19_final.stac-item
2018-12-19 09:47:24	ga_s2am_ard_3-2-1_55HDT_2018-12-19_final.stac-item
2018-12-19 09:47:35	ga_s2am_ard_3-2-1_55HES_2018-12-19_final.stac-item
2018-12-19 09:47:38	ga_s2am_ard_3-2-1_55HDS_2018-12-19_final.stac-item
2019-03-19 09:45:16	ga_s2am_ard_3-2-1_55JEG_2019-03-19_final.stac-item
2019-03-19 09:45:24	ga_s2am_ard_3-2-1_55JDG_2019-03-19_final.stac-item
2019-03-19 09:45:30	ga_s2am_ard_3-2-1_55JEF_2019-03-19_final.stac-item
2019-03-19 09:45:34	ga_s2am_ard_3-2-1_55JDF_2019-03-19_final.stac-item
2019-03-19 09:45:45	ga_s2am_ard_3-2-1_55HEE_2019-03-19_final.stac-item
2019-03-19 09:45:48	ga_s2am_ard_3-2-1_55HDE_2019-03-19_final.stac-item
2019-03-19 09:46:00	ga_s2am_ard_3-2-1_55HED_2019-03-19_final.stac-item
2019-03-19 09:46:03	ga_s2am_ard_3-2-1_55HDD_2019-03-19_final.stac-item
2019-03-19 09:46:14	ga_s2am_ard_3-2-1_55HEC_2019-03-19_final.stac-item
2019-03-19 09:46:18	ga_s2am_ard_3-2-1_55HDC_2019-03-19_final.stac-item
2019-03-19 09:46:29	ga_s2am_ard_3-2-1_55HEB_2019-03-19_final.stac-item
2019-03-19 09:46:32	ga_s2am_ard_3-2-1_55HDB_2019-03-19_final.stac-item
2019-03-19 09:46:43	ga_s2am_ard_3-2-1_55HEA_2019-03-19_final.stac-item
2019-03-19 09:46:46	ga_s2am_ard_3-2-1_55HDA_2019-03-19_final.stac-item
2019-03-19 09:46:57	ga_s2am_ard_3-2-1_55HEV_2019-03-19_final.stac-item
2019-03-19 09:47:01	ga_s2am_ard_3-2-1_55HDV_2019-03-19_final.stac-item
2019-03-19 09:47:12	ga_s2am_ard_3-2-1_55HEU_2019-03-19_final.stac-item
2019-03-19 09:47:16	ga_s2am_ard_3-2-1_55HDU_2019-03-19_final.stac-item
2019-03-19 09:47:26	ga_s2am_ard_3-2-1_55HET_2019-03-19_final.stac-item
2019-03-19 09:47:30	ga_s2am_ard_3-2-1_55HDT_2019-03-19_final.stac-item
2019-03-19 09:47:41	ga_s2am_ard_3-2-1_55HES_2019-03-19_final.stac-item
2019-03-19 09:47:45	ga_s2am_ard_3-2-1_55HDS_2019-03-19_final.stac-item
2019-03-19 09:47:55	ga_s2am_ard_3-2-1_55GER_2019-03-19_final.stac-item
2019-03-19 09:47:59	ga_s2am_ard_3-2-1_55GDR_2019-03-19_final.stac-item
2020-11-18 09:48:05	ga_s2am_ard_3-2-1_55GDR_2020-11-18_final.stac-item
2020-11-24 10:01:37	ga_s2am_ard_3-2-1_55KDB_2020-11-24_final.stac-item
2020-11-24 10:01:52	ga_s2am_ard_3-2-1_55KDA_2020-11-24_final.stac-item
2020-11-24 10:02:06	ga_s2am_ard_3-2-1_55KDV_2020-11-24_final.stac-item
2020-11-24 10:02:21	ga_s2am_ard_3-2-1_55KDU_2020-11-24_final.stac-item
2020-11-24 10:02:35	ga_s2am_ard_3-2-1_55KDT_2020-11-24_final.stac-item
2020-11-24 10:02:50	ga_s2am_ard_3-2-1_55KDS_2020-11-24_final.stac-item
2020-11-24 10:03:04	ga_s2am_ard_3-2-1_55KDR_2020-11-24_final.stac-item
2020-11-24 10:03:18	ga_s2am_ard_3-2-1_55KDQ_2020-11-24_final.stac-item
2020-12-04 10:01:34	ga_s2am_ard_3-2-1_55KDB_2020-12-04_final.stac-item
2020-12-04 10:01:49	ga_s2am_ard_3-2-1_55KDA_2020-12-04_final.stac-item
2020-12-04 10:02:03	ga_s2am_ard_3-2-1_55KDV_2020-12-04_final.stac-item
2020-12-04 10:02:18	ga_s2am_ard_3-2-1_55KDU_2020-12-04_final.stac-item
2020-12-04 10:02:32	ga_s2am_ard_3-2-1_55KDT_2020-12-04_final.stac-item
2020-12-04 10:02:47	ga_s2am_ard_3-2-1_55KDS_2020-12-04_final.stac-item
2020-12-04 10:03:01	ga_s2am_ard_3-2-1_55KDR_2020-12-04_final.stac-item
2020-12-04 10:03:16	ga_s2am_ard_3-2-1_55KDQ_2020-12-04_final.stac-item
2020-12-05 09:37:31	ga_s2am_ard_3-2-1_55HET_2020-12-05_final.stac-item
2020-12-05 09:37:38	ga_s2am_ard_3-2-1_55HDT_2020-12-05_final.stac-item
2020-12-05 09:37:46	ga_s2am_ard_3-2-1_55HES_2020-12-05_final.stac-item
2020-12-05 09:37:50	ga_s2am_ard_3-2-1_55HDS_2020-12-05_final.stac-item
2020-12-05 09:38:00	ga_s2am_ard_3-2-1_55GER_2020-12-05_final.stac-item
2020-12-05 09:38:04	ga_s2am_ard_3-2-1_55GDR_2020-12-05_final.stac-item
2020-12-05 09:38:15	ga_s2am_ard_3-2-1_55GEQ_2020-12-05_final.stac-item
2020-12-05 09:38:18	ga_s2am_ard_3-2-1_55GDQ_2020-12-05_final.stac-item
2020-12-05 09:38:29	ga_s2am_ard_3-2-1_55GEP_2020-12-05_final.stac-item
2020-12-05 09:38:33	ga_s2am_ard_3-2-1_55GDP_2020-12-05_final.stac-item
2020-12-05 09:38:44	ga_s2am_ard_3-2-1_55GEN_2020-12-05_final.stac-item

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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