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
2015-12-28 11:36:25	ga_s2am_ard_3-2-1_50HQK_2015-12-28_final.stac-item
2016-04-02 11:49:05	ga_s2am_ard_3-2-1_50JQT_2016-04-02_final.stac-item
2016-06-12 11:22:42	ga_s2am_ard_3-2-1_51JYG_2016-06-12_final.stac-item
2016-07-02 11:22:40	ga_s2am_ard_3-2-1_51JYG_2016-07-02_final.stac-item
2016-08-11 11:22:31	ga_s2am_ard_3-2-1_51JYG_2016-08-11_final.stac-item
2016-11-30 10:50:09	ga_s2am_ard_3-2-1_53LPD_2016-11-30_final.stac-item
2016-12-28 11:45:05	ga_s2am_ard_3-2-1_50JQT_2016-12-28_final.stac-item
2017-02-23 10:06:24	ga_s2am_ard_3-2-1_55HBV_2017-02-23_final.stac-item
2017-03-16 11:12:06	ga_s2am_ard_3-2-1_51JZN_2017-03-16_final.stac-item
2017-06-06 11:51:13	ga_s2am_ard_3-2-1_50JQT_2017-06-06_final.stac-item
2017-06-07 11:23:45	ga_s2am_ard_3-2-1_51JYG_2017-06-07_final.stac-item
2017-06-27 11:20:55	ga_s2am_ard_3-2-1_51JYG_2017-06-27_final.stac-item
2017-07-16 11:49:46	ga_s2am_ard_3-2-1_50JQT_2017-07-16_final.stac-item
2017-07-17 11:20:58	ga_s2am_ard_3-2-1_51JYG_2017-07-17_final.stac-item
2017-08-05 11:51:57	ga_s2am_ard_3-2-1_50JQT_2017-08-05_final.stac-item
2017-09-21 10:05:47	ga_s2am_ard_3-2-1_54HVH_2017-09-21_final.stac-item
2018-05-09 11:34:47	ga_s2am_ard_3-2-1_51JTL_2018-05-09_final.stac-item
2018-05-09 11:34:47	ga_s2am_ard_3-2-1_51JUL_2018-05-09_final.stac-item
2018-05-13 11:20:24	ga_s2am_ard_3-2-1_51JYG_2018-05-13_final.stac-item
2018-05-23 11:25:37	ga_s2am_ard_3-2-1_51JYG_2018-05-23_final.stac-item
2018-06-02 11:23:55	ga_s2am_ard_3-2-1_51JYG_2018-06-02_final.stac-item
2018-08-01 11:23:55	ga_s2am_ard_3-2-1_51JYG_2018-08-01_final.stac-item
2018-08-10 11:51:15	ga_s2am_ard_3-2-1_50JQT_2018-08-10_final.stac-item
2018-09-27 11:12:40	ga_s2am_ard_3-2-1_51JWF_2018-09-27_final.stac-item
2018-10-19 11:52:28	ga_s2am_ard_3-2-1_50JQT_2018-10-19_final.stac-item
2018-12-18 11:54:14	ga_s2am_ard_3-2-1_50JQT_2018-12-18_final.stac-item
2019-01-25 11:15:59	ga_s2am_ard_3-2-1_51JXF_2019-01-25_final.stac-item
2019-02-13 10:06:52	ga_s2am_ard_3-2-1_55HBV_2019-02-13_final.stac-item
2019-02-26 11:54:29	ga_s2am_ard_3-2-1_50KLU_2019-02-26_final.stac-item
2019-03-11 10:22:09	ga_s2am_ard_3-2-1_54KYD_2019-03-11_final.stac-item
2019-03-18 11:54:30	ga_s2am_ard_3-2-1_50KLU_2019-03-18_final.stac-item
2019-03-28 11:54:23	ga_s2am_ard_3-2-1_50JQT_2019-03-28_final.stac-item
2019-04-07 11:54:24	ga_s2am_ard_3-2-1_50JQT_2019-04-07_final.stac-item
2019-04-27 11:54:27	ga_s2am_ard_3-2-1_50JQT_2019-04-27_final.stac-item
2019-05-28 11:25:48	ga_s2am_ard_3-2-1_51JYG_2019-05-28_final.stac-item
2019-06-06 11:54:25	ga_s2am_ard_3-2-1_50JQT_2019-06-06_final.stac-item
2019-06-17 11:25:49	ga_s2am_ard_3-2-1_51JYG_2019-06-17_final.stac-item
2019-07-07 11:25:50	ga_s2am_ard_3-2-1_51JYG_2019-07-07_final.stac-item
2019-07-17 11:25:50	ga_s2am_ard_3-2-1_51JYG_2019-07-17_final.stac-item
2019-07-23 11:41:23	ga_s2am_ard_3-2-1_51LUF_2019-07-23_final.stac-item
2019-09-04 11:54:23	ga_s2am_ard_3-2-1_50JQT_2019-09-04_final.stac-item
2019-10-14 11:54:26	ga_s2am_ard_3-2-1_50JQT_2019-10-14_final.stac-item
2019-11-03 11:54:26	ga_s2am_ard_3-2-1_50JQT_2019-11-03_final.stac-item
2020-02-08 10:06:48	ga_s2am_ard_3-2-1_55HBV_2020-02-08_final.stac-item
2020-02-27 12:14:26	ga_s2am_ard_3-2-1_49JHN_2020-02-27_final.stac-item
2020-04-01 11:54:19	ga_s2am_ard_3-2-1_50KQU_2020-04-01_final.stac-item
2020-04-01 11:54:19	ga_s2am_ard_3-2-1_50JQT_2020-04-01_final.stac-item
2020-04-01 11:54:19	ga_s2am_ard_3-2-1_50JQT_2020-04-01_final.stac-item
2020-04-11 11:54:32	ga_s2am_ard_3-2-1_50KLU_2020-04-11_final.stac-item
2020-05-22 11:25:50	ga_s2am_ard_3-2-1_51JYG_2020-05-22_final.stac-item
2020-07-11 11:25:49	ga_s2am_ard_3-2-1_51JYG_2020-07-11_final.stac-item
2020-07-21 11:25:50	ga_s2am_ard_3-2-1_51JYG_2020-07-21_final.stac-item
2020-07-31 11:25:51	ga_s2am_ard_3-2-1_51JYG_2020-07-31_final.stac-item
2020-08-19 11:54:39	ga_s2am_ard_3-2-1_50KLU_2020-08-19_final.stac-item
2020-08-29 11:54:38	ga_s2am_ard_3-2-1_50KLU_2020-08-29_final.stac-item
2020-09-09 09:48:27	ga_s2am_ard_3-2-1_54GYV_2020-09-09_final
2020-09-18 11:54:28	ga_s2am_ard_3-2-1_50JQT_2020-09-18_final.stac-item
2020-10-08 11:54:29	ga_s2am_ard_3-2-1_50JQT_2020-10-08_final.stac-item
2020-10-18 11:52:25	ga_s2am_ard_3-2-1_50KQG_2020-10-18_final
2020-10-18 11:54:29	ga_s2am_ard_3-2-1_50JQT_2020-10-18_final.stac-item
2020-11-07 11:54:27	ga_s2am_ard_3-2-1_50JQT_2020-11-07_final.stac-item
2020-12-27 11:54:23	ga_s2am_ard_3-2-1_50JQT_2020-12-27_final.stac-item
2021-02-14 10:45:40	ga_s2am_ard_3-2-1_53JNF_2021-02-14_final.stac-item
2021-02-23 11:14:07	ga_s2am_ard_3-2-1_52JET_2021-02-23_final.stac-item
2021-03-07 11:54:23	ga_s2am_ard_3-2-1_50JQT_2021-03-07_final.stac-item
2021-03-21 09:58:18	ga_s2am_ard_3-2-1_54GYV_2021-03-21_final
2021-04-13 10:05:34	ga_s2am_ard_3-2-1_55HCE_2021-04-13_final.stac-item
2021-04-16 11:54:17	ga_s2am_ard_3-2-1_50JQT_2021-04-16_final.stac-item
2021-04-26 11:54:20	ga_s2am_ard_3-2-1_50JQT_2021-04-26_final.stac-item
2021-05-31 11:01:18	ga_s2am_ard_3-2-1_53LKD_2021-05-31_final.stac-item
2021-06-04 10:41:06	ga_s2am_ard_3-2-1_53LQE_2021-06-04_final
2021-06-06 11:25:46	ga_s2am_ard_3-2-1_51JYG_2021-06-06_final.stac-item
2021-06-26 11:25:46	ga_s2am_ard_3-2-1_51JYG_2021-06-26_final.stac-item
2021-07-06 11:25:47	ga_s2am_ard_3-2-1_51JYG_2021-07-06_final.stac-item
2021-07-16 11:25:48	ga_s2am_ard_3-2-1_51JYG_2021-07-16_final.stac-item
2021-07-26 11:25:48	ga_s2am_ard_3-2-1_51JYG_2021-07-26_final.stac-item
2021-08-04 11:54:26	ga_s2am_ard_3-2-1_50JQT_2021-08-04_final.stac-item
2021-08-15 11:25:47	ga_s2am_ard_3-2-1_51JYG_2021-08-15_final.stac-item
2021-09-23 11:54:26	ga_s2am_ard_3-2-1_50JQT_2021-09-23_final.stac-item
2022-01-01 11:54:25	ga_s2am_ard_3-2-1_50JQT_2022-01-01_final.stac-item
2022-03-21 10:41:27	ga_s2am_ard_3-2-1_53LPD_2022-03-21_final.stac-item
2022-05-11 11:54:27	ga_s2am_ard_3-2-1_50JQT_2022-05-11_final.stac-item
2022-12-08 09:46:18	ga_s2am_ard_3-2-1_55HGB_2022-12-08_final.stac-item
2023-01-11 11:05:48	ga_s2am_ard_3-2-1_52JEL_2023-01-11_final.stac-item
2023-01-18 10:56:04	ga_s2am_ard_3-2-1_53HKE_2023-01-18_final
2023-01-29 10:26:38	ga_s2am_ard_3-2-1_53HNC_2023-01-29_final.stac-item
2023-06-06 11:25:48	ga_s2am_ard_3-2-1_51JYG_2023-06-06_final
2023-07-15 10:16:05	ga_s2am_ard_3-2-1_54HXJ_2023-07-15_final
2023-09-17 09:58:23	ga_s2am_ard_3-2-1_55GBQ_2023-09-17_final
2023-09-22 10:45:43	ga_s2am_ard_3-2-1_53JNF_2023-09-22_final
2023-10-02 10:45:44	ga_s2am_ard_3-2-1_53JNF_2023-10-02_final
2023-10-13 10:14:55	ga_s2am_ard_3-2-1_54JYN_2023-10-13_final
2023-10-13 11:54:21	ga_s2am_ard_3-2-1_50JQT_2023-10-13_final
2023-12-25 12:04:55	ga_s2am_ard_3-2-1_50JMR_2023-12-25_final
2024-03-28 11:44:49	ga_s2am_ard_3-2-1_51JUL_2024-03-28_final
2024-03-31 11:54:32	ga_s2am_ard_3-2-1_50KLU_2024-03-31_final
2024-04-09 10:46:12	ga_s2am_ard_3-2-1_53HKE_2024-04-09_final
2024-04-11 09:46:18	ga_s2am_ard_3-2-1_55HGB_2024-04-11_final
2024-05-04 11:33:41	ga_s2am_ard_3-2-1_51KUR_2024-05-04_final
2024-05-09 10:45:44	ga_s2am_ard_3-2-1_53JNF_2024-05-09_final

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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