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
2018-09-03 09:50:52	ga_s2am_ard_3-2-1_55JCK_2018-09-03_final.stac-item
2018-09-03 09:50:52	ga_s2am_ard_3-2-1_55JDK_2018-09-03_final.stac-item
2018-09-03 09:50:52	ga_s2am_ard_3-2-1_55JEK_2018-09-03_final.stac-item
2018-09-03 09:50:52	ga_s2am_ard_3-2-1_55JFK_2018-09-03_final.stac-item
2018-09-03 09:50:52	ga_s2am_ard_3-2-1_55JCJ_2018-09-03_final.stac-item
2018-09-03 09:50:52	ga_s2am_ard_3-2-1_55JEJ_2018-09-03_final.stac-item
2018-09-03 09:50:52	ga_s2am_ard_3-2-1_55JFJ_2018-09-03_final.stac-item
2018-09-04 09:22:42	ga_s2am_ard_3-2-1_56JMQ_2018-09-03_final.stac-item
2018-09-04 10:57:14	ga_s2am_ard_3-2-1_52JCP_2018-09-04_final.stac-item
2018-09-13 09:50:51	ga_s2am_ard_3-2-1_55JCJ_2018-09-13_final.stac-item
2018-09-13 09:50:51	ga_s2am_ard_3-2-1_55JEJ_2018-09-13_final.stac-item
2018-09-13 09:50:51	ga_s2am_ard_3-2-1_55JFJ_2018-09-13_final.stac-item
2018-09-13 09:50:51	ga_s2am_ard_3-2-1_55JCK_2018-09-13_final.stac-item
2018-09-13 09:50:51	ga_s2am_ard_3-2-1_55JDK_2018-09-13_final.stac-item
2018-09-13 09:50:51	ga_s2am_ard_3-2-1_55JEK_2018-09-13_final.stac-item
2018-09-13 09:50:51	ga_s2am_ard_3-2-1_55JFK_2018-09-13_final.stac-item
2018-09-14 09:22:41	ga_s2am_ard_3-2-1_56JMQ_2018-09-13_final.stac-item
2018-09-14 10:57:12	ga_s2am_ard_3-2-1_52JCP_2018-09-14_final.stac-item
2018-09-14 10:57:12	ga_s2am_ard_3-2-1_52JCQ_2018-09-14_final.stac-item
2018-09-14 10:57:12	ga_s2am_ard_3-2-1_52JDQ_2018-09-14_final.stac-item
2018-09-14 10:57:12	ga_s2am_ard_3-2-1_52JEP_2018-09-14_final.stac-item
2018-09-14 10:57:12	ga_s2am_ard_3-2-1_52JEQ_2018-09-14_final.stac-item
2018-09-14 10:57:12	ga_s2am_ard_3-2-1_52JFP_2018-09-14_final.stac-item
2018-09-14 10:57:12	ga_s2am_ard_3-2-1_52JFQ_2018-09-14_final.stac-item
2018-09-19 10:07:00	ga_s2am_ard_3-2-1_54JVQ_2018-09-19_final.stac-item
2018-09-19 10:07:00	ga_s2am_ard_3-2-1_54JWP_2018-09-19_final.stac-item
2018-09-19 10:07:00	ga_s2am_ard_3-2-1_54JWQ_2018-09-19_final.stac-item
2018-09-19 10:07:00	ga_s2am_ard_3-2-1_54JXP_2018-09-19_final.stac-item
2018-09-19 10:07:00	ga_s2am_ard_3-2-1_54JXQ_2018-09-19_final.stac-item
2018-09-19 10:07:00	ga_s2am_ard_3-2-1_54JYP_2018-09-19_final.stac-item
2018-09-19 10:07:00	ga_s2am_ard_3-2-1_54JYQ_2018-09-19_final.stac-item
2018-10-04 10:57:12	ga_s2am_ard_3-2-1_52JCP_2018-10-04_final.stac-item
2018-10-04 10:57:12	ga_s2am_ard_3-2-1_52JCQ_2018-10-04_final.stac-item
2018-10-04 10:57:12	ga_s2am_ard_3-2-1_52JDQ_2018-10-04_final.stac-item
2018-10-04 10:57:12	ga_s2am_ard_3-2-1_52JEP_2018-10-04_final.stac-item
2018-10-04 10:57:12	ga_s2am_ard_3-2-1_52JEQ_2018-10-04_final.stac-item
2018-10-04 10:57:12	ga_s2am_ard_3-2-1_52JFP_2018-10-04_final.stac-item
2018-10-04 10:57:12	ga_s2am_ard_3-2-1_52JFQ_2018-10-04_final.stac-item
2018-10-11 10:47:22	ga_s2am_ard_3-2-1_53JKJ_2018-10-11_final.stac-item
2018-10-11 10:47:22	ga_s2am_ard_3-2-1_53JKK_2018-10-11_final.stac-item
2018-10-11 10:47:22	ga_s2am_ard_3-2-1_52JEP_2018-10-11_final.stac-item
2018-10-11 10:47:22	ga_s2am_ard_3-2-1_53JLJ_2018-10-11_final.stac-item
2018-10-11 10:47:22	ga_s2am_ard_3-2-1_53JLK_2018-10-11_final.stac-item
2018-10-11 10:47:22	ga_s2am_ard_3-2-1_52JFP_2018-10-11_final.stac-item
2018-10-11 10:47:22	ga_s2am_ard_3-2-1_52JFQ_2018-10-11_final.stac-item
2018-10-11 10:47:22	ga_s2am_ard_3-2-1_52JGP_2018-10-11_final.stac-item
2018-10-11 10:47:22	ga_s2am_ard_3-2-1_52JGQ_2018-10-11_final.stac-item
2018-10-13 09:50:51	ga_s2am_ard_3-2-1_55JCK_2018-10-13_final.stac-item
2018-10-13 09:50:51	ga_s2am_ard_3-2-1_55JDK_2018-10-13_final.stac-item
2018-10-13 09:50:51	ga_s2am_ard_3-2-1_55JEK_2018-10-13_final.stac-item
2018-10-13 09:50:51	ga_s2am_ard_3-2-1_55JFK_2018-10-13_final.stac-item
2018-10-13 09:50:51	ga_s2am_ard_3-2-1_55JCJ_2018-10-13_final.stac-item
2018-10-13 09:50:51	ga_s2am_ard_3-2-1_55JEJ_2018-10-13_final.stac-item
2018-10-13 09:50:51	ga_s2am_ard_3-2-1_55JFJ_2018-10-13_final.stac-item
2019-04-14 10:04:35	ga_s2am_ard_3-2-1_55JCK_2019-04-14_final.stac-item
2019-04-14 10:04:39	ga_s2am_ard_3-2-1_55JBK_2019-04-14_final.stac-item
2019-04-14 10:04:42	ga_s2am_ard_3-2-1_54JYQ_2019-04-14_final.stac-item
2019-04-14 10:04:46	ga_s2am_ard_3-2-1_54JXQ_2019-04-14_final.stac-item
2019-04-14 10:04:50	ga_s2am_ard_3-2-1_55JCJ_2019-04-14_final.stac-item
2019-04-14 10:04:53	ga_s2am_ard_3-2-1_55JBJ_2019-04-14_final.stac-item
2019-04-14 10:04:56	ga_s2am_ard_3-2-1_54JYP_2019-04-14_final.stac-item
2019-04-14 10:05:00	ga_s2am_ard_3-2-1_54JXP_2019-04-14_final.stac-item
2019-04-16 10:45:16	ga_s2am_ard_3-2-1_53JKJ_2019-04-16_final.stac-item
2019-04-19 10:54:55	ga_s2am_ard_3-2-1_53JLK_2019-04-19_final.stac-item
2019-04-19 10:54:58	ga_s2am_ard_3-2-1_53JKK_2019-04-19_final.stac-item
2019-04-19 10:55:01	ga_s2am_ard_3-2-1_52JGQ_2019-04-19_final.stac-item
2019-04-19 10:55:05	ga_s2am_ard_3-2-1_52JFQ_2019-04-19_final.stac-item
2019-04-19 10:55:08	ga_s2am_ard_3-2-1_53JLJ_2019-04-19_final.stac-item
2019-04-19 10:55:13	ga_s2am_ard_3-2-1_53JKJ_2019-04-19_final.stac-item
2019-04-19 10:55:16	ga_s2am_ard_3-2-1_52JGP_2019-04-19_final.stac-item
2019-04-19 10:55:19	ga_s2am_ard_3-2-1_52JFP_2019-04-19_final.stac-item
2019-04-22 09:24:31	ga_s2am_ard_3-2-1_56JMQ_2019-04-21_final.stac-item
2019-04-26 10:44:53	ga_s2am_ard_3-2-1_53JNK_2019-04-26_final.stac-item
2019-04-26 10:44:57	ga_s2am_ard_3-2-1_53JMK_2019-04-26_final.stac-item
2019-04-26 10:45:00	ga_s2am_ard_3-2-1_53JLK_2019-04-26_final.stac-item
2019-04-26 10:45:03	ga_s2am_ard_3-2-1_53JKK_2019-04-26_final.stac-item
2019-04-26 10:45:14	ga_s2am_ard_3-2-1_53JLJ_2019-04-26_final.stac-item
2019-04-26 10:45:17	ga_s2am_ard_3-2-1_53JKJ_2019-04-26_final.stac-item
2019-05-02 09:24:32	ga_s2am_ard_3-2-1_56JMQ_2019-05-01_final.stac-item
2019-09-18 11:35:11	ga_s2am_ard_3-2-1_51JWK_2019-09-18_final.stac-item
2019-09-18 11:35:14	ga_s2am_ard_3-2-1_51JVK_2019-09-18_final.stac-item
2019-09-18 11:35:15	ga_s2am_ard_3-2-1_51JUK_2019-09-18_final.stac-item
2019-09-18 11:35:18	ga_s2am_ard_3-2-1_51JTK_2019-09-18_final.stac-item
2019-09-18 11:35:30	ga_s2am_ard_3-2-1_51JUJ_2019-09-18_final.stac-item
2019-09-18 11:35:33	ga_s2am_ard_3-2-1_51JTJ_2019-09-18_final.stac-item
2019-09-18 11:35:36	ga_s2am_ard_3-2-1_50JQP_2019-09-18_final.stac-item
2019-09-28 11:35:09	ga_s2am_ard_3-2-1_51JWK_2019-09-28_final.stac-item
2019-09-28 11:35:13	ga_s2am_ard_3-2-1_51JVK_2019-09-28_final.stac-item
2019-09-28 11:35:17	ga_s2am_ard_3-2-1_51JUK_2019-09-28_final.stac-item
2019-09-28 11:35:20	ga_s2am_ard_3-2-1_51JTK_2019-09-28_final.stac-item
2019-09-28 11:35:31	ga_s2am_ard_3-2-1_51JUJ_2019-09-28_final.stac-item
2019-09-28 11:35:35	ga_s2am_ard_3-2-1_51JTJ_2019-09-28_final.stac-item
2019-09-28 11:35:38	ga_s2am_ard_3-2-1_50JQP_2019-09-28_final.stac-item
2019-10-01 11:45:16	ga_s2am_ard_3-2-1_51JTK_2019-10-01_final.stac-item
2019-10-01 11:45:19	ga_s2am_ard_3-2-1_50JQQ_2019-10-01_final.stac-item
2019-10-01 11:45:23	ga_s2am_ard_3-2-1_50JPQ_2019-10-01_final.stac-item
2019-10-01 11:45:26	ga_s2am_ard_3-2-1_50JNQ_2019-10-01_final.stac-item
2019-10-01 11:45:31	ga_s2am_ard_3-2-1_51JTJ_2019-10-01_final.stac-item
2019-10-01 11:45:34	ga_s2am_ard_3-2-1_50JQP_2019-10-01_final.stac-item
2019-10-01 11:45:37	ga_s2am_ard_3-2-1_50JPP_2019-10-01_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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