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
2017-06-30 09:52:34	ga_s2am_ard_3-2-1_55JBH_2017-06-30_final.stac-item
2017-06-30 09:52:34	ga_s2am_ard_3-2-1_55JCH_2017-06-30_final.stac-item
2017-06-30 09:52:34	ga_s2am_ard_3-2-1_55JCJ_2017-06-30_final.stac-item
2017-06-30 09:52:34	ga_s2am_ard_3-2-1_55JDH_2017-06-30_final.stac-item
2017-06-30 09:52:34	ga_s2am_ard_3-2-1_55JDJ_2017-06-30_final.stac-item
2017-06-30 09:52:34	ga_s2am_ard_3-2-1_55JEH_2017-06-30_final.stac-item
2017-06-30 09:52:34	ga_s2am_ard_3-2-1_55JEJ_2017-06-30_final.stac-item
2017-06-30 09:52:34	ga_s2am_ard_3-2-1_55JFH_2017-06-30_final.stac-item
2017-06-30 09:52:34	ga_s2am_ard_3-2-1_55JFJ_2017-06-30_final.stac-item
2017-07-02 10:30:35	ga_s2am_ard_3-2-1_54JTN_2017-07-02_final.stac-item
2017-07-02 10:30:35	ga_s2am_ard_3-2-1_54JTP_2017-07-02_final.stac-item
2017-07-02 10:30:35	ga_s2am_ard_3-2-1_53JMJ_2017-07-02_final.stac-item
2017-07-02 10:30:35	ga_s2am_ard_3-2-1_53JNJ_2017-07-02_final.stac-item
2017-07-02 10:30:35	ga_s2am_ard_3-2-1_53JQH_2017-07-02_final.stac-item
2017-07-02 10:30:35	ga_s2am_ard_3-2-1_53JQJ_2017-07-02_final.stac-item
2017-07-06 10:11:06	ga_s2am_ard_3-2-1_54JUN_2017-07-06_final.stac-item
2017-07-06 10:11:06	ga_s2am_ard_3-2-1_54JUP_2017-07-06_final.stac-item
2017-07-06 10:11:06	ga_s2am_ard_3-2-1_54JVN_2017-07-06_final.stac-item
2017-07-06 10:11:06	ga_s2am_ard_3-2-1_54JVP_2017-07-06_final.stac-item
2017-07-06 10:11:06	ga_s2am_ard_3-2-1_54JWN_2017-07-06_final.stac-item
2017-07-06 10:11:06	ga_s2am_ard_3-2-1_54JWP_2017-07-06_final.stac-item
2017-07-06 10:11:06	ga_s2am_ard_3-2-1_54JXN_2017-07-06_final.stac-item
2017-07-06 10:11:06	ga_s2am_ard_3-2-1_54JXP_2017-07-06_final.stac-item
2017-07-06 10:11:06	ga_s2am_ard_3-2-1_54JYN_2017-07-06_final.stac-item
2017-07-06 10:11:06	ga_s2am_ard_3-2-1_54JYP_2017-07-06_final.stac-item
2017-07-11 09:24:01	ga_s2am_ard_3-2-1_56JMP_2017-07-10_final.stac-item
2017-07-11 09:24:01	ga_s2am_ard_3-2-1_56JNN_2017-07-10_final.stac-item
2017-07-21 09:22:46	ga_s2am_ard_3-2-1_56JMP_2017-07-20_final.stac-item
2017-07-21 09:22:46	ga_s2am_ard_3-2-1_56JNN_2017-07-20_final.stac-item
2017-07-22 10:32:12	ga_s2am_ard_3-2-1_54JTN_2017-07-22_final.stac-item
2017-07-22 10:32:12	ga_s2am_ard_3-2-1_54JTP_2017-07-22_final.stac-item
2017-07-22 10:32:12	ga_s2am_ard_3-2-1_53JMJ_2017-07-22_final.stac-item
2017-07-22 10:32:12	ga_s2am_ard_3-2-1_53JNH_2017-07-22_final.stac-item
2017-07-22 10:32:12	ga_s2am_ard_3-2-1_53JNJ_2017-07-22_final.stac-item
2017-07-22 10:32:12	ga_s2am_ard_3-2-1_53JPH_2017-07-22_final.stac-item
2017-07-22 10:32:12	ga_s2am_ard_3-2-1_53JPJ_2017-07-22_final.stac-item
2017-07-22 10:32:12	ga_s2am_ard_3-2-1_53JQH_2017-07-22_final.stac-item
2017-07-22 10:32:12	ga_s2am_ard_3-2-1_53JQJ_2017-07-22_final.stac-item
2019-02-02 10:34:54	ga_s2am_ard_3-2-1_54JTP_2019-02-02_final.stac-item
2019-02-02 10:34:58	ga_s2am_ard_3-2-1_53JQJ_2019-02-02_final.stac-item
2019-02-02 10:35:02	ga_s2am_ard_3-2-1_53JPJ_2019-02-02_final.stac-item
2019-02-02 10:35:05	ga_s2am_ard_3-2-1_54JTN_2019-02-02_final.stac-item
2019-02-02 10:35:06	ga_s2am_ard_3-2-1_53JNJ_2019-02-02_final.stac-item
2019-02-02 10:35:12	ga_s2am_ard_3-2-1_53JMJ_2019-02-02_final.stac-item
2019-02-02 10:35:12	ga_s2am_ard_3-2-1_53JQH_2019-02-02_final.stac-item
2019-02-02 10:35:16	ga_s2am_ard_3-2-1_53JPH_2019-02-02_final.stac-item
2019-02-02 10:35:20	ga_s2am_ard_3-2-1_53JNH_2019-02-02_final.stac-item
2019-02-08 10:55:02	ga_s2am_ard_3-2-1_53JLJ_2019-02-08_final.stac-item
2019-02-08 10:55:07	ga_s2am_ard_3-2-1_53JKJ_2019-02-08_final.stac-item
2019-02-08 10:55:10	ga_s2am_ard_3-2-1_52JGP_2019-02-08_final.stac-item
2019-02-08 10:55:12	ga_s2am_ard_3-2-1_53JLH_2019-02-08_final.stac-item
2019-02-08 10:55:14	ga_s2am_ard_3-2-1_52JFP_2019-02-08_final.stac-item
2019-02-08 10:55:19	ga_s2am_ard_3-2-1_52JEP_2019-02-08_final.stac-item
2019-02-08 10:55:21	ga_s2am_ard_3-2-1_53JKH_2019-02-08_final.stac-item
2019-02-08 10:55:24	ga_s2am_ard_3-2-1_52JGN_2019-02-08_final.stac-item
2019-02-08 10:55:28	ga_s2am_ard_3-2-1_52JFN_2019-02-08_final.stac-item
2019-02-08 10:55:31	ga_s2am_ard_3-2-1_52JEN_2019-02-08_final.stac-item
2019-02-11 09:24:38	ga_s2am_ard_3-2-1_56JMP_2019-02-10_final.stac-item
2019-02-20 09:54:36	ga_s2am_ard_3-2-1_55JFJ_2019-02-20_final.stac-item
2019-02-20 09:54:41	ga_s2am_ard_3-2-1_55JEJ_2019-02-20_final.stac-item
2019-02-20 09:54:45	ga_s2am_ard_3-2-1_55JDJ_2019-02-20_final.stac-item
2019-02-20 09:54:47	ga_s2am_ard_3-2-1_55JFH_2019-02-20_final.stac-item
2019-02-20 09:54:48	ga_s2am_ard_3-2-1_55JCJ_2019-02-20_final.stac-item
2019-02-20 09:54:56	ga_s2am_ard_3-2-1_55JEH_2019-02-20_final.stac-item
2019-02-20 09:55:00	ga_s2am_ard_3-2-1_55JDH_2019-02-20_final.stac-item
2019-02-20 09:55:03	ga_s2am_ard_3-2-1_55JCH_2019-02-20_final.stac-item
2019-02-20 09:55:07	ga_s2am_ard_3-2-1_55JBH_2019-02-20_final.stac-item
2019-02-21 09:24:37	ga_s2am_ard_3-2-1_56JMP_2019-02-20_final.stac-item
2019-02-21 09:24:49	ga_s2am_ard_3-2-1_56JNN_2019-02-20_final.stac-item
2019-02-21 11:05:08	ga_s2am_ard_3-2-1_52JFP_2019-02-21_final.stac-item
2019-02-21 11:05:12	ga_s2am_ard_3-2-1_52JEP_2019-02-21_final.stac-item
2019-02-21 11:05:15	ga_s2am_ard_3-2-1_52JDP_2019-02-21_final.stac-item
2019-02-21 11:05:18	ga_s2am_ard_3-2-1_52JCP_2019-02-21_final.stac-item
2019-02-21 11:05:22	ga_s2am_ard_3-2-1_52JFN_2019-02-21_final.stac-item
2019-02-21 11:05:27	ga_s2am_ard_3-2-1_52JEN_2019-02-21_final.stac-item
2019-02-21 11:05:30	ga_s2am_ard_3-2-1_52JDN_2019-02-21_final.stac-item
2019-02-21 11:05:33	ga_s2am_ard_3-2-1_52JCN_2019-02-21_final.stac-item
2019-06-29 10:25:01	ga_s2am_ard_3-2-1_54JVP_2019-06-29_final.stac-item
2019-06-29 10:25:04	ga_s2am_ard_3-2-1_54JUP_2019-06-29_final.stac-item
2019-06-29 10:25:07	ga_s2am_ard_3-2-1_54JTP_2019-06-29_final.stac-item
2019-06-29 10:25:10	ga_s2am_ard_3-2-1_53JQJ_2019-06-29_final.stac-item
2019-06-29 10:25:15	ga_s2am_ard_3-2-1_54JVN_2019-06-29_final.stac-item
2019-06-29 10:25:19	ga_s2am_ard_3-2-1_54JUN_2019-06-29_final.stac-item
2019-06-29 10:25:22	ga_s2am_ard_3-2-1_54JTN_2019-06-29_final.stac-item
2019-06-29 10:25:25	ga_s2am_ard_3-2-1_53JQH_2019-06-29_final.stac-item
2019-07-04 11:15:23	ga_s2am_ard_3-2-1_52JCP_2019-07-04_final.stac-item
2019-07-04 11:15:27	ga_s2am_ard_3-2-1_52JBP_2019-07-04_final.stac-item
2019-07-04 11:15:30	ga_s2am_ard_3-2-1_51JYJ_2019-07-04_final.stac-item
2019-07-04 11:15:34	ga_s2am_ard_3-2-1_51JXJ_2019-07-04_final.stac-item
2019-07-04 11:15:38	ga_s2am_ard_3-2-1_52JCN_2019-07-04_final.stac-item
2019-07-04 11:15:41	ga_s2am_ard_3-2-1_52JBN_2019-07-04_final.stac-item
2019-07-04 11:15:44	ga_s2am_ard_3-2-1_51JYH_2019-07-04_final.stac-item
2019-07-04 11:15:47	ga_s2am_ard_3-2-1_51JXH_2019-07-04_final.stac-item
2019-07-09 10:25:01	ga_s2am_ard_3-2-1_54JVP_2019-07-09_final.stac-item
2019-07-09 10:25:05	ga_s2am_ard_3-2-1_54JUP_2019-07-09_final.stac-item
2019-07-09 10:25:08	ga_s2am_ard_3-2-1_54JTP_2019-07-09_final.stac-item
2019-07-09 10:25:10	ga_s2am_ard_3-2-1_53JQJ_2019-07-09_final.stac-item
2019-07-09 10:25:16	ga_s2am_ard_3-2-1_54JVN_2019-07-09_final.stac-item
2019-07-09 10:25:19	ga_s2am_ard_3-2-1_54JUN_2019-07-09_final.stac-item
2019-07-09 10:25:22	ga_s2am_ard_3-2-1_54JTN_2019-07-09_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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