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
2017-05-30 12:02:52	ga_s2am_ard_3-2-1_50JKQ_2017-05-30_final.stac-item
2017-05-30 12:02:52	ga_s2am_ard_3-2-1_50JLQ_2017-05-30_final.stac-item
2017-05-30 12:02:52	ga_s2am_ard_3-2-1_49JGJ_2017-05-30_final.stac-item
2017-05-30 12:02:52	ga_s2am_ard_3-2-1_49JGK_2017-05-30_final.stac-item
2017-06-13 11:43:06	ga_s2am_ard_3-2-1_50JNQ_2017-06-13_final.stac-item
2017-06-13 11:43:06	ga_s2am_ard_3-2-1_50JPQ_2017-06-13_final.stac-item
2017-06-13 11:43:06	ga_s2am_ard_3-2-1_50JQP_2017-06-13_final.stac-item
2017-06-13 11:43:06	ga_s2am_ard_3-2-1_50JQQ_2017-06-13_final.stac-item
2017-06-13 11:43:06	ga_s2am_ard_3-2-1_51JTK_2017-06-13_final.stac-item
2018-02-06 09:23:03	ga_s2am_ard_3-2-1_56JMQ_2018-02-05_final.stac-item
2018-02-08 09:57:03	ga_s2am_ard_3-2-1_54JXQ_2018-02-08_final.stac-item
2018-02-08 09:57:03	ga_s2am_ard_3-2-1_54JYP_2018-02-08_final.stac-item
2018-02-08 09:57:03	ga_s2am_ard_3-2-1_54JYQ_2018-02-08_final.stac-item
2018-02-08 09:57:03	ga_s2am_ard_3-2-1_55JBK_2018-02-08_final.stac-item
2018-02-08 09:57:03	ga_s2am_ard_3-2-1_55JCK_2018-02-08_final.stac-item
2018-02-08 11:40:45	ga_s2am_ard_3-2-1_50JNQ_2018-02-08_final.stac-item
2018-02-08 11:40:45	ga_s2am_ard_3-2-1_50JPQ_2018-02-08_final.stac-item
2018-02-08 11:40:45	ga_s2am_ard_3-2-1_50JQP_2018-02-08_final.stac-item
2018-02-08 11:40:45	ga_s2am_ard_3-2-1_50JQQ_2018-02-08_final.stac-item
2018-02-08 11:40:45	ga_s2am_ard_3-2-1_51JTK_2018-02-08_final.stac-item
2018-02-12 09:41:05	ga_s2am_ard_3-2-1_56JKQ_2018-02-12_final.stac-item
2018-02-12 09:41:05	ga_s2am_ard_3-2-1_55JEK_2018-02-12_final.stac-item
2018-02-12 09:41:05	ga_s2am_ard_3-2-1_55JFK_2018-02-12_final.stac-item
2018-02-12 09:41:05	ga_s2am_ard_3-2-1_55JGJ_2018-02-12_final.stac-item
2018-02-12 09:41:05	ga_s2am_ard_3-2-1_55JGK_2018-02-12_final.stac-item
2018-02-12 11:16:56	ga_s2am_ard_3-2-1_51JVK_2018-02-12_final.stac-item
2018-02-12 11:16:56	ga_s2am_ard_3-2-1_51JWK_2018-02-12_final.stac-item
2018-02-12 11:16:56	ga_s2am_ard_3-2-1_51JXK_2018-02-12_final.stac-item
2018-02-12 11:16:56	ga_s2am_ard_3-2-1_51JYK_2018-02-12_final.stac-item
2018-02-16 09:23:21	ga_s2am_ard_3-2-1_56JMQ_2018-02-15_final.stac-item
2018-02-16 11:04:36	ga_s2am_ard_3-2-1_52JCQ_2018-02-16_final.stac-item
2018-02-16 11:04:36	ga_s2am_ard_3-2-1_52JDQ_2018-02-16_final.stac-item
2018-02-16 11:04:36	ga_s2am_ard_3-2-1_52JEQ_2018-02-16_final.stac-item
2018-02-16 11:04:36	ga_s2am_ard_3-2-1_52JFQ_2018-02-16_final.stac-item
2018-02-18 10:01:27	ga_s2am_ard_3-2-1_54JXQ_2018-02-18_final.stac-item
2018-02-18 10:01:27	ga_s2am_ard_3-2-1_54JYP_2018-02-18_final.stac-item
2018-02-18 10:01:27	ga_s2am_ard_3-2-1_54JYQ_2018-02-18_final.stac-item
2018-02-18 10:01:27	ga_s2am_ard_3-2-1_55JBK_2018-02-18_final.stac-item
2018-02-18 10:01:27	ga_s2am_ard_3-2-1_55JCK_2018-02-18_final.stac-item
2019-04-22 09:24:31	ga_s2am_ard_3-2-1_56JMQ_2019-04-21_final.stac-item
2019-05-02 09:24:32	ga_s2am_ard_3-2-1_56JMQ_2019-05-01_final.stac-item
2019-05-09 10:54:56	ga_s2am_ard_3-2-1_53JLK_2019-05-09_final.stac-item
2019-05-09 10:54:59	ga_s2am_ard_3-2-1_53JKK_2019-05-09_final.stac-item
2019-05-09 10:55:02	ga_s2am_ard_3-2-1_52JGQ_2019-05-09_final.stac-item
2019-05-09 10:55:06	ga_s2am_ard_3-2-1_52JFQ_2019-05-09_final.stac-item
2019-05-09 10:55:17	ga_s2am_ard_3-2-1_52JGP_2019-05-09_final.stac-item
2019-05-19 10:54:55	ga_s2am_ard_3-2-1_53JLK_2019-05-19_final.stac-item
2019-05-19 10:54:59	ga_s2am_ard_3-2-1_53JKK_2019-05-19_final.stac-item
2019-05-19 10:55:02	ga_s2am_ard_3-2-1_52JGQ_2019-05-19_final.stac-item
2019-05-19 10:55:06	ga_s2am_ard_3-2-1_52JFQ_2019-05-19_final.stac-item
2019-05-19 10:55:17	ga_s2am_ard_3-2-1_52JGP_2019-05-19_final.stac-item
2019-05-21 09:54:31	ga_s2am_ard_3-2-1_55JFK_2019-05-21_final.stac-item
2019-05-21 09:54:34	ga_s2am_ard_3-2-1_55JEK_2019-05-21_final.stac-item
2019-05-21 09:54:38	ga_s2am_ard_3-2-1_55JDK_2019-05-21_final.stac-item
2019-05-21 09:54:41	ga_s2am_ard_3-2-1_55JCK_2019-05-21_final.stac-item
2019-05-24 10:04:36	ga_s2am_ard_3-2-1_55JCK_2019-05-24_final.stac-item
2019-05-24 10:04:40	ga_s2am_ard_3-2-1_55JBK_2019-05-24_final.stac-item
2019-05-24 10:04:43	ga_s2am_ard_3-2-1_54JYQ_2019-05-24_final.stac-item
2019-05-24 10:04:47	ga_s2am_ard_3-2-1_54JXQ_2019-05-24_final.stac-item
2019-05-24 10:04:57	ga_s2am_ard_3-2-1_54JYP_2019-05-24_final.stac-item
2019-06-01 09:24:30	ga_s2am_ard_3-2-1_56JMQ_2019-05-31_final.stac-item
2019-06-03 10:04:46	ga_s2am_ard_3-2-1_54JXQ_2019-06-03_final.stac-item
2019-06-06 10:14:37	ga_s2am_ard_3-2-1_54JYQ_2019-06-06_final.stac-item
2019-06-06 10:14:41	ga_s2am_ard_3-2-1_54JXQ_2019-06-06_final.stac-item
2019-06-06 10:14:45	ga_s2am_ard_3-2-1_54JWQ_2019-06-06_final.stac-item
2019-06-06 10:14:48	ga_s2am_ard_3-2-1_54JVQ_2019-06-06_final.stac-item
2019-06-09 12:05:25	ga_s2am_ard_3-2-1_50JLQ_2019-06-09_final.stac-item
2019-06-09 12:05:29	ga_s2am_ard_3-2-1_50JKQ_2019-06-09_final.stac-item
2019-06-09 12:05:32	ga_s2am_ard_3-2-1_49JGK_2019-06-09_final.stac-item
2019-06-10 09:54:30	ga_s2am_ard_3-2-1_55JFK_2019-06-10_final.stac-item
2019-06-10 09:54:34	ga_s2am_ard_3-2-1_55JEK_2019-06-10_final.stac-item
2019-06-10 09:54:37	ga_s2am_ard_3-2-1_55JDK_2019-06-10_final.stac-item
2019-06-10 09:54:40	ga_s2am_ard_3-2-1_55JCK_2019-06-10_final.stac-item
2019-06-11 09:24:31	ga_s2am_ard_3-2-1_56JMQ_2019-06-10_final.stac-item
2019-06-14 11:15:03	ga_s2am_ard_3-2-1_52JDQ_2019-06-14_final.stac-item
2019-06-14 11:15:07	ga_s2am_ard_3-2-1_52JCQ_2019-06-14_final.stac-item
2019-06-14 11:15:10	ga_s2am_ard_3-2-1_52JBQ_2019-06-14_final.stac-item
2019-06-14 11:15:13	ga_s2am_ard_3-2-1_51JYK_2019-06-14_final.stac-item
2019-06-14 11:15:28	ga_s2am_ard_3-2-1_51JYJ_2019-06-14_final.stac-item
2019-06-15 10:44:53	ga_s2am_ard_3-2-1_53JNK_2019-06-15_final.stac-item
2019-06-15 10:44:57	ga_s2am_ard_3-2-1_53JMK_2019-06-15_final.stac-item
2019-06-15 10:45:00	ga_s2am_ard_3-2-1_53JLK_2019-06-15_final.stac-item
2019-06-15 10:45:03	ga_s2am_ard_3-2-1_53JKK_2019-06-15_final.stac-item
2019-06-16 10:14:38	ga_s2am_ard_3-2-1_54JYQ_2019-06-16_final.stac-item
2019-06-16 10:14:42	ga_s2am_ard_3-2-1_54JXQ_2019-06-16_final.stac-item
2019-06-16 10:14:46	ga_s2am_ard_3-2-1_54JWQ_2019-06-16_final.stac-item
2019-06-16 10:14:49	ga_s2am_ard_3-2-1_54JVQ_2019-06-16_final.stac-item
2019-06-18 10:54:55	ga_s2am_ard_3-2-1_53JLK_2019-06-18_final.stac-item
2019-06-18 10:54:59	ga_s2am_ard_3-2-1_53JKK_2019-06-18_final.stac-item
2019-06-18 10:55:02	ga_s2am_ard_3-2-1_52JGQ_2019-06-18_final.stac-item
2019-06-18 10:55:06	ga_s2am_ard_3-2-1_52JFQ_2019-06-18_final.stac-item
2019-06-18 10:55:17	ga_s2am_ard_3-2-1_52JGP_2019-06-18_final.stac-item
2019-06-20 09:54:31	ga_s2am_ard_3-2-1_55JFK_2019-06-20_final.stac-item
2019-06-20 09:54:35	ga_s2am_ard_3-2-1_55JEK_2019-06-20_final.stac-item
2019-06-20 09:54:38	ga_s2am_ard_3-2-1_55JDK_2019-06-20_final.stac-item
2019-06-20 09:54:41	ga_s2am_ard_3-2-1_55JCK_2019-06-20_final.stac-item
2019-06-21 09:24:32	ga_s2am_ard_3-2-1_56JMQ_2019-06-20_final.stac-item
2019-06-21 11:05:02	ga_s2am_ard_3-2-1_52JFQ_2019-06-21_final.stac-item
2019-06-21 11:05:05	ga_s2am_ard_3-2-1_52JEQ_2019-06-21_final.stac-item
2019-06-21 11:05:09	ga_s2am_ard_3-2-1_52JDQ_2019-06-21_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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