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
2015-12-07 12:04:41	ga_s2am_ard_3-2-1_50JKT_2015-12-07_final.stac-item
2015-12-27 12:04:06	ga_s2am_ard_3-2-1_49KHQ_2015-12-27_final.stac-item
2016-01-16 12:07:17	ga_s2am_ard_3-2-1_49KGP_2016-01-16_final.stac-item
2016-02-02 11:48:17	ga_s2am_ard_3-2-1_50JKN_2016-02-02_final.stac-item
2016-05-15 12:02:55	ga_s2am_ard_3-2-1_49KHQ_2016-05-15_final.stac-item
2016-06-05 11:32:15	ga_s2am_ard_3-2-1_50HPH_2016-06-05_final.stac-item
2016-07-28 11:40:17	ga_s2am_ard_3-2-1_50HPG_2016-07-28_final
2016-10-02 12:02:45	ga_s2am_ard_3-2-1_50JKS_2016-10-02_final.stac-item
2016-10-03 11:32:06	ga_s2am_ard_3-2-1_50HPK_2016-10-03_final.stac-item
2016-10-13 11:35:59	ga_s2am_ard_3-2-1_50HQK_2016-10-13_final.stac-item
2016-10-26 11:39:44	ga_s2am_ard_3-2-1_50HMH_2016-10-26_final.stac-item
2016-10-26 11:39:44	ga_s2am_ard_3-2-1_50HNK_2016-10-26_final.stac-item
2016-11-05 11:39:53	ga_s2am_ard_3-2-1_50HMJ_2016-11-05_final.stac-item
2016-11-05 11:39:53	ga_s2am_ard_3-2-1_50HPG_2016-11-05_final
2016-12-05 11:46:51	ga_s2am_ard_3-2-1_50HMH_2016-12-05_final.stac-item
2016-12-18 11:56:02	ga_s2am_ard_3-2-1_50HMJ_2016-12-18_final.stac-item
2016-12-22 11:29:07	ga_s2am_ard_3-2-1_50HNG_2016-12-22_final
2017-02-16 11:52:25	ga_s2am_ard_3-2-1_50HLH_2017-02-16_final.stac-item
2017-07-09 12:02:49	ga_s2am_ard_3-2-1_49JGN_2017-07-09_final.stac-item
2017-07-09 12:02:49	ga_s2am_ard_3-2-1_50JKT_2017-07-09_final.stac-item
2017-12-19 12:13:16	ga_s2am_ard_3-2-1_49KHR_2017-12-19_final.stac-item
2018-01-02 11:56:01	ga_s2am_ard_3-2-1_50HMJ_2018-01-02_final.stac-item
2018-03-03 11:52:20	ga_s2am_ard_3-2-1_50HMH_2018-03-03_final.stac-item
2018-03-06 12:02:46	ga_s2am_ard_3-2-1_49JGN_2018-03-06_final.stac-item
2018-03-09 12:13:17	ga_s2am_ard_3-2-1_49JGN_2018-03-09_final.stac-item
2018-04-02 11:53:50	ga_s2am_ard_3-2-1_50HMJ_2018-04-02_final.stac-item
2018-04-25 12:02:51	ga_s2am_ard_3-2-1_50JKR_2018-04-25_final.stac-item
2018-04-29 11:45:33	ga_s2am_ard_3-2-1_50HLH_2018-04-29_final.stac-item
2018-04-29 11:45:33	ga_s2am_ard_3-2-1_50HMH_2018-04-29_final.stac-item
2018-05-05 12:03:39	ga_s2am_ard_3-2-1_50JKP_2018-05-05_final.stac-item
2018-05-15 12:03:35	ga_s2am_ard_3-2-1_50JKP_2018-05-15_final.stac-item
2018-05-25 12:03:34	ga_s2am_ard_3-2-1_49JGK_2018-05-25_final.stac-item
2018-05-25 12:03:34	ga_s2am_ard_3-2-1_50JKQ_2018-05-25_final.stac-item
2018-06-15 11:32:57	ga_s2am_ard_3-2-1_50HPK_2018-06-15_final.stac-item
2018-06-24 12:03:32	ga_s2am_ard_3-2-1_50JKQ_2018-06-24_final.stac-item
2018-06-24 12:03:32	ga_s2am_ard_3-2-1_50JKS_2018-06-24_final.stac-item
2018-07-01 11:52:21	ga_s2am_ard_3-2-1_50JKN_2018-07-01_final.stac-item
2018-07-24 12:02:50	ga_s2am_ard_3-2-1_49JGL_2018-07-24_final.stac-item
2018-07-24 12:02:50	ga_s2am_ard_3-2-1_49JGM_2018-07-24_final.stac-item
2018-08-06 12:13:21	ga_s2am_ard_3-2-1_49JGN_2018-08-06_final.stac-item
2018-08-06 12:13:21	ga_s2am_ard_3-2-1_49KHQ_2018-08-06_final.stac-item
2018-08-23 12:02:48	ga_s2am_ard_3-2-1_49JGL_2018-08-23_final.stac-item
2018-08-23 12:02:48	ga_s2am_ard_3-2-1_49KGP_2018-08-23_final.stac-item
2018-08-23 12:02:48	ga_s2am_ard_3-2-1_50JKP_2018-08-23_final.stac-item
2018-09-06 11:45:53	ga_s2am_ard_3-2-1_50HMJ_2018-09-06_final.stac-item
2018-09-13 11:33:05	ga_s2am_ard_3-2-1_50HQJ_2018-09-13_final.stac-item
2018-10-16 11:45:53	ga_s2am_ard_3-2-1_50HPK_2018-10-16_final.stac-item
2018-10-26 11:41:08	ga_s2am_ard_3-2-1_50HMK_2018-10-26_final.stac-item
2018-10-29 11:54:48	ga_s2am_ard_3-2-1_50JKN_2018-10-29_final.stac-item
2018-11-15 11:46:32	ga_s2am_ard_3-2-1_50HNK_2018-11-15_final.stac-item
2018-12-01 12:06:01	ga_s2am_ard_3-2-1_50JKM_2018-12-01_final.stac-item
2018-12-21 12:04:05	ga_s2am_ard_3-2-1_49KHQ_2018-12-21_final.stac-item
2018-12-21 12:04:19	ga_s2am_ard_3-2-1_49KHP_2018-12-21_final.stac-item
2018-12-21 12:04:49	ga_s2am_ard_3-2-1_50JKS_2018-12-21_final.stac-item
2018-12-21 12:05:32	ga_s2am_ard_3-2-1_50JKP_2018-12-21_final.stac-item
2019-01-04 11:46:32	ga_s2am_ard_3-2-1_50HNK_2019-01-04_final.stac-item
2019-02-13 11:47:03	ga_s2am_ard_3-2-1_50HMH_2019-02-13_final.stac-item
2019-05-23 12:15:14	ga_s2am_ard_3-2-1_49JGL_2019-05-23_final.stac-item
2020-02-01 11:56:48	ga_s2am_ard_3-2-1_50HLJ_2020-02-01_final.stac-item
2020-03-28 12:15:06	ga_s2am_ard_3-2-1_49JGL_2020-03-28_final.stac-item
2020-04-08 11:47:07	ga_s2am_ard_3-2-1_50HMH_2020-04-08_final.stac-item
2020-06-13 12:05:47	ga_s2am_ard_3-2-1_50JKP_2020-06-13_final.stac-item
2020-12-17 11:56:52	ga_s2am_ard_3-2-1_50HLJ_2020-12-17_final.stac-item
2021-01-03 11:46:56	ga_s2am_ard_3-2-1_50HMJ_2021-01-03_final.stac-item
2021-01-06 11:55:47	ga_s2am_ard_3-2-1_50JKP_2021-01-06_final.stac-item
2021-01-10 11:37:18	ga_s2am_ard_3-2-1_50HQG_2021-01-10_final
2021-03-10 12:04:46	ga_s2am_ard_3-2-1_49JGN_2021-03-10_final.stac-item
2021-03-20 12:03:43	ga_s2am_ard_3-2-1_49KHS_2021-03-20_final
2021-03-30 12:04:55	ga_s2am_ard_3-2-1_50JKS_2021-03-30_final.stac-item
2021-04-06 11:56:46	ga_s2am_ard_3-2-1_50HMJ_2021-04-06_final.stac-item
2021-04-13 11:47:11	ga_s2am_ard_3-2-1_50HPG_2021-04-13_final
2021-05-26 11:57:21	ga_s2am_ard_3-2-1_50HMG_2021-05-26_final
2021-06-05 11:57:21	ga_s2am_ard_3-2-1_50HMG_2021-06-05_final
2021-06-15 11:56:11	ga_s2am_ard_3-2-1_50JLM_2021-06-15_final.stac-item
2021-06-19 11:37:21	ga_s2am_ard_3-2-1_50HPG_2021-06-19_final
2021-06-21 12:14:42	ga_s2am_ard_3-2-1_49JGN_2021-06-21_final.stac-item
2021-06-28 12:05:13	ga_s2am_ard_3-2-1_50JKR_2021-06-28_final.stac-item
2021-07-02 11:47:19	ga_s2am_ard_3-2-1_50HPG_2021-07-02_final
2021-07-05 11:55:59	ga_s2am_ard_3-2-1_50JLN_2021-07-05_final.stac-item
2021-07-05 11:56:09	ga_s2am_ard_3-2-1_50JLM_2021-07-05_final.stac-item
2021-07-25 11:56:58	ga_s2am_ard_3-2-1_50HLJ_2021-07-25_final.stac-item
2021-07-28 12:05:18	ga_s2am_ard_3-2-1_49JGL_2021-07-28_final.stac-item
2021-08-07 12:04:34	ga_s2am_ard_3-2-1_49KGP_2021-08-07_final.stac-item
2021-08-11 11:47:27	ga_s2am_ard_3-2-1_50HMG_2021-08-11_final
2021-08-17 12:04:34	ga_s2am_ard_3-2-1_49KGP_2021-08-17_final.stac-item
2021-08-17 12:04:45	ga_s2am_ard_3-2-1_50JKT_2021-08-17_final.stac-item
2021-08-17 12:05:19	ga_s2am_ard_3-2-1_49JGL_2021-08-17_final.stac-item
2021-09-06 12:06:10	ga_s2am_ard_3-2-1_50JKM_2021-09-06_final.stac-item
2021-09-10 11:46:48	ga_s2am_ard_3-2-1_50HPJ_2021-09-10_final.stac-item
2021-10-23 11:57:28	ga_s2am_ard_3-2-1_50HLG_2021-10-23_final
2022-01-18 11:47:10	ga_s2am_ard_3-2-1_50HMH_2022-01-18_final.stac-item
2022-03-12 11:57:22	ga_s2am_ard_3-2-1_50HLH_2022-03-12_final.stac-item
2022-10-08 11:57:12	ga_s2am_ard_3-2-1_50HMH_2022-10-08_final.stac-item
2022-10-18 11:57:09	ga_s2am_ard_3-2-1_50HMH_2022-10-18_final.stac-item
2023-01-03 11:47:13	ga_s2am_ard_3-2-1_50HLH_2023-01-03_final.stac-item
2023-02-05 11:57:08	ga_s2am_ard_3-2-1_50HLH_2023-02-05_final
2023-04-19 12:03:43	ga_s2am_ard_3-2-1_49KHS_2023-04-19_final
2023-06-08 12:03:48	ga_s2am_ard_3-2-1_49KHS_2023-06-08_final
2023-07-08 12:03:50	ga_s2am_ard_3-2-1_49KHS_2023-07-08_final
2023-09-06 12:03:50	ga_s2am_ard_3-2-1_49KHS_2023-09-06_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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